diff --git a/.env.example b/.env.example index e4767a97..fdee9af0 100644 --- a/.env.example +++ b/.env.example @@ -1,8 +1,11 @@ # Copy this file to a new file named .env and replace the placeholders with your actual keys. +# REMOVE "pragma: allowlist secret" when you replace with actual keys. # DO NOT fill your keys directly into this file. # OpenAI API Key OPENAI_API_KEY=YOUR_OPENAI_API_KEY_GOES_HERE # pragma: allowlist secret -# Serp API key -SERP_API_KEY=YOUR_SERP_API_KEY_GOES_HERE # pragma: allowlist secret +# PQA API Key to use LiteratureSearch tool (optional) -- it also requires OpenAI key +PQA_API_KEY=YOUR_PQA_API_KEY_GOES_HERE # pragma: allowlist secret + +# Optional: add TogetherAI, Fireworks, or Anthropic API key here to use their models diff --git a/README.md b/README.md index 12a9964f..f520c334 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,17 @@ -MD-Agent is a LLM-agent based toolset for Molecular Dynamics. +MDAgent is a LLM-agent based toolset for Molecular Dynamics. It's built using Langchain and uses a collection of tools to set up and execute molecular dynamics simulations, particularly in OpenMM. ## Environment Setup To use the OpenMM features in the agent, please set up a conda environment, following these steps. -- Create conda environment: `conda env create -n mdagent -f environment.yaml` -- Activate your environment: `conda activate mdagent` +``` +conda env create -n mdagent -f environment.yaml +conda activate mdagent +``` + +If you already have a conda environment, you can install dependencies before you activate it with the following step. +- Install the necessary conda dependencies: `conda env update -n -f environment.yaml` -If you already have a conda environment, you can install dependencies with the following step. -- Install the necessary conda dependencies: `conda install -c conda-forge openmm pdbfixer mdtraj` ## Installation @@ -16,23 +19,30 @@ If you already have a conda environment, you can install dependencies with the f pip install git+https://github.com/ur-whitelab/md-agent.git ``` - ## Usage -The first step is to set up your API keys in your environment. An OpenAI key is necessary for this project. +The next step is to set up your API keys in your environment. An API key for LLM provider is necessary for this project. Supported LLM providers are OpenAI, TogetherAI, Fireworks, and Anthropic. Other tools require API keys, such as paper-qa for literature searches. We recommend setting up the keys in a .env file. You can use the provided .env.example file as a template. 1. Copy the `.env.example` file and rename it to `.env`: `cp .env.example .env` 2. Replace the placeholder values in `.env` with your actual keys - +## LLM Providers +By default, we support LLMs through OpenAI API. However, feel free to use other LLM providers. Make sure to install the necessary package for it. Here's list of packages required for alternative LLM providers we support: +- `pip install langchain-together` to use models from TogetherAI +- `pip install langchain-anthropic` to use models from Anthropic +- `pip install langchain-fireworks` to use models from Fireworks ## Contributing -We welcome contributions to MD-Agent! If you're interested in contributing to the project, please check out our [Contributor's Guide](CONTRIBUTING.md) for detailed instructions on getting started, feature development, and the pull request process. +We welcome contributions to MDAgent! If you're interested in contributing to the project, please check out our [Contributor's Guide](CONTRIBUTING.md) for detailed instructions on getting started, feature development, and the pull request process. -We value and appreciate all contributions to MD-Agent. +We value and appreciate all contributions to MDAgent. diff --git a/environment.yaml b/environment.yaml index 812f6a46..d18f9312 100644 --- a/environment.yaml +++ b/environment.yaml @@ -5,6 +5,8 @@ dependencies: - openmm >= 7.6 - pdbfixer >= 1.5 - mdtraj + - openff-toolkit + - openmmforcefields - pip - pip: - flake8 diff --git a/mdagent/agent/agent.py b/mdagent/agent/agent.py index 760e8a8c..2adc7330 100644 --- a/mdagent/agent/agent.py +++ b/mdagent/agent/agent.py @@ -3,13 +3,11 @@ from dotenv import load_dotenv from langchain.agents import AgentExecutor, OpenAIFunctionsAgent from langchain.agents.structured_chat.base import StructuredChatAgent -from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler -from langchain.chat_models import ChatOpenAI -from ..tools import get_tools, make_all_tools +from ..tools import get_relevant_tools, make_all_tools from ..utils import PathRegistry, SetCheckpoint, _make_llm from .memory import MemoryManager -from .query_filter import make_prompt +from .prompt import openaifxn_prompt, structured_prompt load_dotenv() @@ -38,20 +36,26 @@ def __init__( tools=None, agent_type="OpenAIFunctionsAgent", # this can also be structured_chat model="gpt-4-1106-preview", # current name for gpt-4 turbo - tools_model="gpt-4-1106-preview", + tools_model=None, temp=0.1, - verbose=True, + streaming=True, + verbose=False, ckpt_dir="ckpt", top_k_tools=20, # set "all" if you want to use all tools use_human_tool=False, uploaded_files=[], # user input files to add to path registry run_id="", - use_memory=True, + use_memory=False, ): + self.llm = _make_llm(model, temp, streaming) + if tools_model is None: + tools_model = model + self.tools_llm = _make_llm(tools_model, temp, streaming) + self.use_memory = use_memory self.path_registry = PathRegistry.get_instance(ckpt_dir=ckpt_dir) self.ckpt_dir = self.path_registry.ckpt_dir - self.memory = MemoryManager(self.path_registry, run_id=run_id) + self.memory = MemoryManager(self.path_registry, self.tools_llm, run_id=run_id) self.run_id = self.memory.run_id self.uploaded_files = uploaded_files @@ -60,18 +64,10 @@ def __init__( self.agent = None self.agent_type = agent_type - self.user_tools = tools - self.tools_llm = _make_llm(tools_model, temp, verbose) self.top_k_tools = top_k_tools self.use_human_tool = use_human_tool - - self.llm = ChatOpenAI( - temperature=temp, - model=model, - client=None, - streaming=True, - callbacks=[StreamingStdOutCallbackHandler()], - ) + self.user_tools = tools + self.verbose = verbose def _initialize_tools_and_agent(self, user_input=None): """Retrieve tools and initialize the agent.""" @@ -80,9 +76,10 @@ def _initialize_tools_and_agent(self, user_input=None): else: if self.top_k_tools != "all" and user_input is not None: # retrieve only tools relevant to user input - self.tools = get_tools( + self.tools = get_relevant_tools( query=user_input, llm=self.tools_llm, + top_k_tools=self.top_k_tools, human=self.use_human_tool, ) else: @@ -97,29 +94,38 @@ def _initialize_tools_and_agent(self, user_input=None): self.llm, self.tools, ), + verbose=self.verbose, handle_parsing_errors=True, ) def run(self, user_input, callbacks=None): run_memory = self.memory.run_id_mem if self.use_memory else None - self.prompt = make_prompt( - user_input, self.agent_type, model="gpt-3.5-turbo", run_memory=run_memory - ) + if self.agent_type == "Structured": + self.prompt = structured_prompt.format(input=user_input, context=run_memory) + elif self.agent_type == "OpenAIFunctionsAgent": + self.prompt = openaifxn_prompt.format(input=user_input, context=run_memory) self.agent = self._initialize_tools_and_agent(user_input) - model_output = self.agent.run(self.prompt, callbacks=callbacks) + model_output = self.agent.invoke(self.prompt, callbacks=callbacks) if self.use_memory: self.memory.generate_agent_summary(model_output) print("Your run id is: ", self.run_id) return model_output, self.run_id def iter(self, user_input, include_run_info=True): + run_memory = self.memory.run_id_mem if self.use_memory else None + if self.agent is None: - self.prompt = make_prompt( - user_input, self.agent_type, model="gpt-3.5-turbo" - ) - self.agent = self._initialize_tools_and_agent(user_input) - for step in self.agent.iter(self.prompt, include_run_info=include_run_info): - yield step + if self.agent_type == "Structured": + self.prompt = structured_prompt.format( + input=user_input, context=run_memory + ) + elif self.agent_type == "OpenAIFunctionsAgent": + self.prompt = openaifxn_prompt.format( + input=user_input, context=run_memory + ) + self.agent = self._initialize_tools_and_agent(user_input) + for step in self.agent.iter(self.prompt, include_run_info=include_run_info): + yield step def force_clear_mem(self, all=False) -> str: if all: diff --git a/mdagent/agent/memory.py b/mdagent/agent/memory.py index 06b98c53..f450e47c 100644 --- a/mdagent/agent/memory.py +++ b/mdagent/agent/memory.py @@ -3,10 +3,8 @@ import random import string -from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler -from langchain.chains import LLMChain -from langchain.chat_models import ChatOpenAI from langchain.prompts import PromptTemplate +from langchain_core.output_parsers import StrOutputParser from mdagent.utils import PathRegistry @@ -32,8 +30,7 @@ class MemoryManager: def __init__( self, path_registry: PathRegistry, - model="gpt-3.5-turbo", - temp=0.1, + llm, run_id="", ): self.path_registry = path_registry @@ -46,14 +43,7 @@ def __init__( else: pull_mem = True - llm = ChatOpenAI( - temperature=temp, - model=model, - client=None, - streaming=True, - callbacks=[StreamingStdOutCallbackHandler()], - ) - self.llm_agent_trace = LLMChain(llm=llm, prompt=agent_summary_template) + self.llm_agent_trace = agent_summary_template | llm | StrOutputParser() self._make_all_dirs() if pull_mem: @@ -138,7 +128,7 @@ def generate_agent_summary(self, agent_trace): Returns: - None """ - llm_out = self.llm_agent_trace({"agent_trace": agent_trace})["text"] + llm_out = self.llm_agent_trace.invoke({"agent_trace": agent_trace}) key_str = f"{self.run_id}.{self.get_summary_number()}" run_summary = {key_str: llm_out} self._write_to_json(run_summary, self.agent_trace_summary) diff --git a/mdagent/agent/prompt.py b/mdagent/agent/prompt.py index 2eca04c2..dbfbd669 100644 --- a/mdagent/agent/prompt.py +++ b/mdagent/agent/prompt.py @@ -3,116 +3,53 @@ structured_prompt = PromptTemplate( input_variables=["input, context"], template=""" - You are an expert molecular dynamics scientist and - your task is to respond to the question or - solve the problem to the best of your ability using - the provided tools. - - You can only respond with a single complete - 'Thought, Action, Action Input' format - OR a single 'Final Answer' format. - - Complete format: - Thought: (reflect on your progress and decide what " "to do next) - Action: (the action name, should be the name of a tool) - Action Input: (the input string to the action) - - OR - - Final Answer: (the final answer to the original input - question) - - Use the tools provided, using the most specific tool - available for each action. - Your final answer should contain all information - necessary to answer the question and subquestions. - Your thought process should be clean and clear, - and you must explicitly state the actions you are taking. - - If you are asked to continue - or reference previous runs, - the context will be provided to you. - If context is provided, you should assume - you are continuing a chat. - - Here is the input: - Previous Context: {context} - Question: {input} """, -) -modular_analysis_prompt = PromptTemplate( - input_variables=[ - "Main_Task", - "Subtask_types", - "Proteins", - "Parameters", - "UserProposedPlan", - "context", - ], - template=""" - Approach the molecular dynamics inquiry by dissecting it into its modular - components: - Main Task: {Main_Task} - Subtasks: {Subtask_types} - Target Proteins: {Proteins} - Parameters: {Parameters} - Initial Plan Proposed by User: {UserProposedPlan} - - The Main Task is the user's request. - - The Subtasks are (some of/all) the individual steps that may need to be taken - to complete the Main Task; Preprocessing/Preparation usually involves - cleaning the initial pdb file (adding hydrogens, removing/adding water, etc.) - or making the required box for the simulation, Simulation involves running the - simulation and/or modifying the simulation script, Postprocessing involves - analyzing the results of the simulation (either using provided tools or figuring - it out on your own). Finally, Question is used if the user query is more - of a question than a request for a specific task. - - the Target Proteins are the protein(s) that the user wants to focus on, - the Parameters are the 'special' conditions that the user wants to set and use - for the simulation, preprocessing and or analysis. - - Sometimes users already have an idea of what is needed to be done. - Initial Plan Proposed by User is the user's initial plan for the simulation. You - can use this as a guide to understand what the user wants to do. You can also - modify it if you think is necessary. - - You can only respond with a single complete - 'Thought, Action, Action Input' format - OR a single 'Final Answer' format. - - Complete format: - Thought: (reflect on your progress and decide what " "to do next) - Action: (the action name, should be the name of a tool) - Action Input: (the input string to the action) - - OR - - Final Answer: (the final answer to the original input - question) - - Use the tools provided, using the most specific tool - available for each action. - Your final answer should contain all information - necessary to answer the question and subquestions. - Your thought process should be clean and clear, - and you must explicitly state the actions you are taking. - - If you are asked to continue - or reference previous runs, - the context will be provided to you. - If context is provided, you should assume - you are continuing a chat. + You are an expert molecular dynamics scientist, and + your task is to respond to the question or + solve the problem to the best of your ability using + the provided tools. + + You can only respond with a single complete + 'Thought, Action, Action Input' format + OR a single 'Final Answer' format. + + Complete format: + Thought: (reflect on your progress and decide what to do next) + Action: + ``` + {{ + "action": (the action name, it should be the name of a tool), + "action_input": (the input string for the action) + }} + ''' + + OR + + Final Answer: (the final response to the original input + question, once all steps are complete) + + You are required to use the tools provided, + using the most specific tool + available for each action. + Your final answer should contain all information + necessary to answer the question and its subquestions. + Before you finish, reflect on your progress and make + sure you have addressed the question in its entirety. + + If you are asked to continue + or reference previous runs, + the context will be provided to you. + If context is provided, you should assume + you are continuing a chat. - Here is the input: - Previous Context: {context} - """, + Here is the input: + Previous Context: {context} + Question: {input} """, ) openaifxn_prompt = PromptTemplate( input_variables=["input", "context"], template=""" - You are an expert molecular dynamics scientist and your + You are an expert molecular dynamics scientist, and your task is to respond to the question or solve the problem to the best of your ability using the provided tools. Once you map a path to a short name, diff --git a/mdagent/agent/query_filter.py b/mdagent/agent/query_filter.py deleted file mode 100644 index 35c546ce..00000000 --- a/mdagent/agent/query_filter.py +++ /dev/null @@ -1,341 +0,0 @@ -import json -from dataclasses import dataclass -from enum import Enum -from typing import List, Optional - -import outlines -from outlines import generate, models -from pydantic import BaseModel - -from .prompt import modular_analysis_prompt, openaifxn_prompt, structured_prompt - -################################################################ - -""" -The following is based on outlines documentations and examples -https://outlines-dev.github.io/outlines/welcome/ - -Classes and functions described in this file: -- Parameters -- Task_type -- FilteredQuery -- Example -- query_filter -- create_filtered_query - - -query_filter: A function that takes a raw query and a list of -examples (Example classes) and returns a "prompt for filtering" -that include the examples (similar to -Few-shot prompting). - -create_filtered_query: A function that uses (so far an openai model) and the -query_filter function to create a filtered query - -Parameters: A dataclass that represents the parameters of a molecular dynamics. I've -included Temperature, Pressure, Time, ForceField, WaterModel, SaltConcentration, pH, -Solvate, Ensemble, and Other_Parameters. All parameters are optional, depending on what -the user includes in its input. -it has two main methods: 1) to parse a string into a Parameters object. -and a __repr__ method to print the object as a string (useful for making a -pretty prompt) - - -Task_type: An Enum class that represents the different types of tasks that a user can -ask for, or that the model used in create_filtered_query assumes it needs. - It has a __repr__ method to print the object as a string (useful for making a -pretty prompt) and a parse_task_type_string method to parse a string into a -Task_type object. - -FilteredQuery: A pydantic BaseModel class that represents the final structure that will -summarize the info from the users request. It uses the two classes defined above. - -Example: A dataclass that represents an example of a raw query and its filtered query. -""" - - -################################################################ -@dataclass -class Parameters: - Temperature: Optional[str] - Pressure: Optional[str] - Time: Optional[str] - ForceField: Optional[str] - WaterModel: Optional[str] - SaltConcentration: Optional[str] - pH: Optional[str] - Solvate: Optional[bool] - Ensemble: Optional[str] - Other_Parameters: Optional[str] - - def __repr__(self) -> str: - return ( - f"Parameters(Temperature = '{self.Temperature}'," - f"Pressure = '{self.Pressure}'," - f"Time = '{self.Time}'," - f"ForceField = '{self.ForceField}'," - f"WaterModel = '{self.WaterModel}'," - f"SaltConcentration = '{self.SaltConcentration}'," - f"pH = '{self.pH}'," - f"Solvate = '{self.Solvate}'," - f"Ensemble = '{self.Ensemble}'," - f"Other_Parameters = '{self.Other_Parameters}'" - ")" - ) - - @staticmethod - def parse_parameters_string(param_str): - # Remove the 'Parameters' prefix and parentheses - param_str = param_str.replace("Parameters(", "").replace(")", "") - # Split the string into key-value pairs - pairs = param_str.split(",") - param_dict = {} - for pair in pairs: - key, value = pair.split("=") - key = key.strip() - value = value.strip().strip("'") - # Convert 'True' and 'False' strings to boolean values - if value == "True": - value = True - elif value == "False": - value = False - param_dict[key] = value - return Parameters(**param_dict) - - def items(self): - return self.__dict__.items() - - -class Task_type(str, Enum): - question = "Question" - preprocessing = "Preprocessing" - preparation = "Preparation" - simulation = "Simulation" - postnalysis = "Postanalysis" - - def __repr__(self): - return f"{self.value}" - - @staticmethod - def parse_task_type_string(task_type_str): - if type(task_type_str) == str: - if task_type_str.startswith("["): - task_type_str = task_type_str.replace("[", "").replace("]", "") - task_type_str = task_type_str.split(",") - return [Task_type(task_type.strip()) for task_type in task_type_str] - return Task_type(task_type_str.strip()) - elif type(task_type_str) == list: - return [Task_type(task_type) for task_type in task_type_str] - elif type(task_type_str) == Task_type: - return task_type_str - - def __str__(self): - return self.value - - -class FilteredQuery(BaseModel): - Main_Task: str - Subtask_types: List[Task_type] # conlist(Task_type, min_length=1) - ProteinS: List[str] - Parameters: Parameters - UserProposedPlan: List[str] # conlist(str, min_length=0] - - -@dataclass -class Example: - Raw_query: str - Filtered_Query: FilteredQuery - - -@outlines.prompt -def query_filter(raw_query, examples: list[Example]): - """You are about to organize an user query. User will - ask for a specific Molecular Dynamics related task, from wich you will - extract: - 1. The main task of the query - 2. A list of subtasks that are part of the main task - 3. The protein of interest mentioned in the raw query (as a PDB ID, - UniProt ID, name, or sequence) - 4. Parameters or conditions specified by the user for the simulation - 5. The plan proposed by the user for the simulation (if any) - - - {% for example in examples %} - Raw Query: "{{ example.Raw_query }}" - RESULT: { - "Main_Task": "{{ example.Filtered_Query.Main_Task }}", - "Subtask_types": "{{ example.Filtered_Query.Subtask_types }}", - "ProteinS": "{{ example.Filtered_Query.ProteinS }}", - "Parameters": "{{ example.Filtered_Query.Parameters }}", - "UserProposedPlan": "{{ example.Filtered_Query.UserProposedPlan }}"} - {% endfor %} - - Here is the new raw query that you need to filter: - Raw Query: {{raw_query}} - RESULT: - """ - - -examples = [ - Example( - Raw_query="I want a simulation of 1A3N at 280K", - Filtered_Query=FilteredQuery( - Main_Task="Simulate 1A3N at 280K", - Subtask_types=["Simulation"], - ProteinS=["1A3N"], - Parameters=Parameters( - Temperature="280K", - Pressure=None, - Time=None, - ForceField=None, - WaterModel=None, - SaltConcentration=None, - pH=None, - Solvate=None, - Ensemble=None, - Other_Parameters=None, - ), - UserProposedPlan=[], - ), - ), - Example( - Raw_query="What is the best force field for 1A3N?", - Filtered_Query=FilteredQuery( - Main_Task="Answer the question: best force field for 1A3N?", - Subtask_types=["Question"], - ProteinS=["1A3N"], - Parameters=Parameters( - Temperature=None, - Pressure=None, - Time=None, - ForceField=None, - WaterModel=None, - SaltConcentration=None, - pH=None, - Solvate=None, - Ensemble=None, - Other_Parameters=None, - ), - UserProposedPlan=[], - ), - ), - Example( - Raw_query="""Calculate the Radial Distribution Function of 1A3N with - water. Youll have to download the PDB file, clean it, and solvate it - for the simulation. The trajectory and - topology files can be used to calculate the RDF.""", - Filtered_Query=FilteredQuery( - Main_Task="Calculate the Radial Distribution Function of 1A3N with water.", - Subtask_types=["Preprocessing", "Simulation", "Postanalysis"], - ProteinS=["1A3N"], - Parameters=Parameters( - Temperature=None, - Pressure=None, - Time=None, - ForceField=None, - WaterModel=None, - SaltConcentration=None, - pH=None, - Solvate=True, - Ensemble=None, - Other_Parameters=None, - ), - UserProposedPlan=[ - "Downlaod PDB file for 1A3N", - "Clean/Pre-process the PDB file", - "Calculate the Radial Distribution Function with water.", - "With the trajectory and topology files, calculate the RDF.", - ], - ), - ), -] - - -def create_filtered_query(raw_query, model="gpt-3.5-turbo", examples=examples): - filter_model = models.openai(model) - generator = generate.text(filter_model) - return generator(query_filter(raw_query, examples=examples)) - - -def make_prompt(user_input, agent_type, model="gpt-3.5-turbo", run_memory=None): - if agent_type == "Structured": - tries = 1 - - while tries <= 3: - try: - structured_query = create_filtered_query(user_input, model=model) - structured_query = json.loads(structured_query) - parameters = Parameters.parse_parameters_string( - structured_query["Parameters"] - ) - _parameters = "" - for key, value in parameters.items(): - if value == "None": - continue - else: - _parameters += f"{key}: {value}, " - _plan = "" - if structured_query["UserProposedPlan"] == "[]": - _plan += "None" - else: - if type(structured_query["UserProposedPlan"]) == str: - for plan in structured_query["UserProposedPlan"].split(","): - _plan += f"{plan}," - elif type(structured_query["UserProposedPlan"]) == list: - for plan in structured_query["UserProposedPlan"]: - _plan += f"{plan}," - _proteins = "" - if structured_query["ProteinS"] == "['None']": - _proteins += "None" - elif structured_query["ProteinS"] == "[]": - _proteins += "None" - else: - for protein in eval(structured_query["ProteinS"]): - _proteins += f"{protein}, " - _subtasks = "" - if structured_query["Subtask_types"] == "['None']": - _subtasks += "None" - elif structured_query["Subtask_types"] == "[]": - _subtasks += "None" - elif structured_query["Subtask_types"] == ["None"]: - _subtasks += "None" - else: - if type(structured_query["Subtask_types"]) == str: - for subtask in Task_type.parse_task_type_string( - structured_query["Subtask_types"] - ): - _subtasks += f"{subtask}, " - elif type(structured_query["Subtask_types"]) == list: - for subtask in structured_query["Subtask_types"]: - _str = Task_type.parse_task_type_string(subtask) - _subtasks += f"{_str}, " - prompt = modular_analysis_prompt.format( - Main_Task=structured_query["Main_Task"], - Subtask_types=_subtasks, - Proteins=_proteins, - Parameters=_parameters, - UserProposedPlan=_plan, - context=run_memory, - ) - break - except ValueError as e: - print(f"Failed to structure query, attempt {tries}/3. Retrying...") - print(e, e.args) - tries += 1 - continue - except Exception as e: - print(f"Failed to structure query, attempt {tries}/3. Retrying...") - print(e, e.args) - tries += 1 - continue - - if tries > 3: - print( - "Failed to structure query after 3 attempts." - "Input will be used as is." - ) - return structured_prompt.format(input=user_input, context=run_memory) - else: - return prompt - elif agent_type == "OpenAIFunctionsAgent": - return openaifxn_prompt.format(input=user_input, context=run_memory) diff --git a/mdagent/tools/__init__.py b/mdagent/tools/__init__.py index 79c851ff..bf02a575 100644 --- a/mdagent/tools/__init__.py +++ b/mdagent/tools/__init__.py @@ -1,3 +1,3 @@ -from .maketools import get_tools, make_all_tools +from .maketools import get_relevant_tools, make_all_tools -__all__ = ["get_tools", "make_all_tools"] +__all__ = ["get_relevant_tools", "make_all_tools"] diff --git a/mdagent/tools/base_tools/__init__.py b/mdagent/tools/base_tools/__init__.py index 197b2a75..0698b54a 100644 --- a/mdagent/tools/base_tools/__init__.py +++ b/mdagent/tools/base_tools/__init__.py @@ -12,6 +12,14 @@ ) from .analysis_tools.rmsd_tools import ComputeLPRMSD, ComputeRMSD, ComputeRMSF from .analysis_tools.sasa import SolventAccessibleSurfaceArea +from .analysis_tools.secondary_structure import ( + ComputeAcylindricity, + ComputeAsphericity, + ComputeDSSP, + ComputeGyrationTensor, + ComputeRelativeShapeAntisotropy, + SummarizeProteinStructure, +) from .analysis_tools.vis_tools import VisFunctions, VisualizeProtein from .preprocess_tools.clean_tools import CleaningToolFunction from .preprocess_tools.packing import PackMolTool @@ -37,12 +45,7 @@ UniprotID2Name, ) from .simulation_tools.create_simulation import ModifyBaseSimulationScriptTool -from .simulation_tools.setup_and_run import ( - SetUpandRunFunction, - SetUpAndRunTool, - SimulationFunctions, -) -from .util_tools.git_issues_tool import SerpGitTool +from .simulation_tools.setup_and_run import SetUpandRunFunction from .util_tools.registry_tools import ListRegistryPaths, MapPath2Name from .util_tools.search_tools import Scholar2ResultLLM @@ -86,10 +89,7 @@ "RDFTool", "RMSDCalculator", "Scholar2ResultLLM", - "SerpGitTool", - "SetUpAndRunTool", "SetUpandRunFunction", - "SimulationFunctions", "SimulationOutputFigures", "SmallMolPDB", "UniprotID2Name", @@ -97,4 +97,14 @@ "VisFunctions", "VisualizeProtein", "get_pdb", + "CleaningToolFunction", + "SetUpandRunFunction", + "ModifyBaseSimulationScriptTool", + "RDFTool", + "ComputeDSSP", + "ComputeGyrationTensor", + "ComputeAsphericity", + "ComputeAcylindricity", + "ComputeRelativeShapeAntisotropy", + "SummarizeProteinStructure", ] diff --git a/mdagent/tools/base_tools/analysis_tools/rdf_tool.py b/mdagent/tools/base_tools/analysis_tools/rdf_tool.py index 6bdc16cf..2e6fd5d4 100644 --- a/mdagent/tools/base_tools/analysis_tools/rdf_tool.py +++ b/mdagent/tools/base_tools/analysis_tools/rdf_tool.py @@ -26,7 +26,8 @@ class RDFTool(BaseTool): name = "RDFTool" description = ( "Calculate the radial distribution function (RDF) of a trajectory " - "of a protein with respect to water molecules." + "of a protein with respect to water molecules using the trajectory file ID " + "(trajectory_fileid) and optionally the topology file ID (topology_fileid). " ) args_schema = RDFToolInput path_registry: Optional[PathRegistry] @@ -45,6 +46,9 @@ def _run(self, **input): elif "Invalid file extension" in str(e): print("File Extension Not Supported in RDF tool: ", str(e)) return ("Failed. File Extension Not Supported", str(e)) + elif "not in path registry" in str(e): + print("File ID not in Path Registry in RDF tool: ", str(e)) + return ("Failed. File ID not in Path Registry", str(e)) else: raise ValueError(f"Error during inputs in RDF tool {e}") @@ -92,11 +96,11 @@ def _run(self, **input): Log_id=trajectory_id, ) fig_id = self.path_registry.get_fileid(plot_name, type=FileType.FIGURE) - - plt.savefig(f"{self.path_registry.ckpt_figures}/rdf_{trajectory_id}.png") + file_path = f"{self.path_registry.ckpt_figures}/rdf_{trajectory_id}.png" + plt.savefig(file_path) self.path_registry.map_path( fig_id, - plot_name, + file_path, description=f"RDF plot for the trajectory file with id: {trajectory_id}", ) plt.close() @@ -106,6 +110,10 @@ def _arun(self, input): pass def validate_input(self, input): + input = input.get("input", input) + + input = input.get("action_input", input) + trajectory_id = input.get("trajectory_fileid", None) topology_id = input.get("topology_fileid", None) @@ -115,7 +123,9 @@ def validate_input(self, input): atom_indices = input.get("atom_indices", None) if not trajectory_id: - raise ValueError("Incorrect Inputs: Trajectory file ID is required") + raise ValueError( + "Incorrect Inputs: Trajectory file ID ('trajectory_fileid')is required" + ) # check if trajectory id is valid fileids = self.path_registry.list_path_names() @@ -131,7 +141,7 @@ def validate_input(self, input): if not topology_id: raise ValueError( "Incorrect Inputs: " - "Topology file is required for trajectory " + "Topology file (topology_fileid) is required for trajectory " "file with extension {}".format(ending) ) if topology_id not in fileids: diff --git a/mdagent/tools/base_tools/analysis_tools/rgy.py b/mdagent/tools/base_tools/analysis_tools/rgy.py index ffeba6a6..71f58b40 100644 --- a/mdagent/tools/base_tools/analysis_tools/rgy.py +++ b/mdagent/tools/base_tools/analysis_tools/rgy.py @@ -5,101 +5,91 @@ import numpy as np from langchain.tools import BaseTool -from mdagent.utils import FileType, PathRegistry +from mdagent.utils import FileType, PathRegistry, load_single_traj class RadiusofGyration: def __init__(self, path_registry): self.path_registry = path_registry - self.includes_top = [".h5", ".lh5", ".pdb"] - - def _grab_files(self, pdb_id: str) -> None: - if "_" in pdb_id: - pdb_id = pdb_id.split("_")[0] - self.pdb_id = pdb_id - all_names = self.path_registry._list_all_paths() - try: - self.pdb_path = [ - name - for name in all_names - if pdb_id in name and ".pdb" in name and "records" in name - ][0] - except IndexError: - raise ValueError(f"No pdb file found for {pdb_id}") - try: - self.dcd_path = [ - name - for name in all_names - if pdb_id in name and ".dcd" in name and "records" in name - ][0] - except IndexError: - self.dcd_path = None - pass - return None - - def _load_traj(self, pdb_id: str) -> None: - self._grab_files(pdb_id) - if self.dcd_path: - self.traj = md.load(self.dcd_path, top=self.pdb_path) - else: - self.traj = md.load(self.pdb_path) - return None + self.top_file = "" + self.traj_file = "" + self.traj = None + + def _load_traj(self, top_file: str, traj_file: str): + self.traj_file = traj_file + self.top_file = top_file + self.traj = load_single_traj( + path_registry=self.path_registry, + top_fileid=top_file, + traj_fileid=traj_file, + traj_required=True, + ) - def rad_gyration_per_frame(self, pdb_id: str) -> str: - self._load_traj(pdb_id) + def rgy_per_frame(self, force_recompute: bool = False) -> str: rg_per_frame = md.compute_rg(self.traj) - self.rgy_file = ( - f"{self.path_registry.ckpt_figures}/radii_of_gyration_{self.pdb_id}.csv" - ) - - np.savetxt( - self.rgy_file, rg_per_frame, delimiter=",", header="Radius of Gyration (nm)" - ) - self.path_registry.map_path( - f"{self.path_registry.ckpt_figures}/radii_of_gyration_{self.pdb_id}.csv", - self.rgy_file, - description=f"Radii of gyration per frame for {self.pdb_id}", + f"{self.path_registry.ckpt_figures}/radii_of_gyration_{self.traj_file}.csv" ) - return f"Radii of gyration saved to {self.rgy_file}" - - def rad_gyration_average(self, pdb_id: str) -> str: - _ = self.rad_gyration_per_frame(pdb_id) + rgy_id = f"rgy_{self.traj_file}" + if rgy_id in self.path_registry.list_path_names() and force_recompute is False: + print("RGY already computed, skipping re-compute") + # todo -> maybe allow re-compute & save under different id/path + else: + np.savetxt( + self.rgy_file, + rg_per_frame, + delimiter=",", + header="Radius of Gyration (nm)", + ) + self.path_registry.map_path( + f"rgy_{self.traj_file}", + self.rgy_file, + description=f"Radii of gyration per frame for {self.traj_file}", + ) + return f"Radii of gyration saved to {self.rgy_file} with id {rgy_id}." + + def rgy_average(self) -> str: + _ = self.rgy_per_frame() rg_per_frame = np.loadtxt(self.rgy_file, delimiter=",", skiprows=1) avg_rg = rg_per_frame.mean() return f"Average radius of gyration: {avg_rg:.2f} nm" - def plot_rad_gyration(self, pdb_id: str) -> str: - _ = self.rad_gyration_per_frame(pdb_id) + def plot_rgy(self) -> str: + _ = self.rgy_per_frame() rg_per_frame = np.loadtxt(self.rgy_file, delimiter=",", skiprows=1) - fig_analysis = f"rgy_{self.pdb_id}" + fig_analysis = f"rgy_{self.traj_file}" plot_name = self.path_registry.write_file_name( type=FileType.FIGURE, fig_analysis=fig_analysis, file_format="png" ) + print("plot_name: ", plot_name) plot_id = self.path_registry.get_fileid( file_name=plot_name, type=FileType.FIGURE ) - + if plot_name.endswith(".png"): + plot_name = plot_name.split(".png")[0] + plot_path = f"{self.path_registry.ckpt_figures}/{plot_name}" plt.plot(rg_per_frame) plt.xlabel("Frame") plt.ylabel("Radius of Gyration (nm)") - plt.title(f"{pdb_id} - Radius of Gyration Over Time") + plt.title(f"{self.traj_file} - Radius of Gyration Over Time") - plt.savefig(f"{self.path_registry.ckpt_figures}/{plot_name}") + plt.savefig(f"{plot_path}") self.path_registry.map_path( plot_id, - f"{self.path_registry.ckpt_figures}/{plot_name}", - description=f"Plot of radii of gyration over time for {self.pdb_id}", + plot_path, + description=f"Plot of radii of gyration over time for {self.traj_file}", ) + plt.close() + plt.clf() return "Plot saved as: " + f"{plot_name}.png with plot ID {plot_id}" class RadiusofGyrationAverage(BaseTool): name = "RadiusofGyrationAverage" description = """This tool calculates the average radius of gyration - for the given trajectory file. Give this tool the - protein ID (PDB ID) only. The tool will automatically find the necessary files.""" + for a trajectory. Give this tool BOTH the trajectory file ID and the + topology file ID.""" path_registry: Optional[PathRegistry] @@ -107,11 +97,15 @@ def __init__(self, path_registry): super().__init__() self.path_registry = path_registry - def _run(self, pdb_id: str) -> str: + def _run(self, traj_file: str, top_file: str) -> str: """use the tool.""" + RGY = RadiusofGyration(self.path_registry) + try: + RGY._load_traj(top_file=top_file, traj_file=traj_file) + except Exception as e: + return f"Error loading traj: {e}" try: - RGY = RadiusofGyration(self.path_registry) - return "Succeeded. " + RGY.rad_gyration_average(pdb_id) + return "Succeeded. " + RGY.rgy_average() except ValueError as e: return f"Failed. ValueError: {e}" except Exception as e: @@ -125,8 +119,9 @@ async def _arun(self, query: str) -> str: class RadiusofGyrationPerFrame(BaseTool): name = "RadiusofGyrationPerFrame" description = """This tool calculates the radius of gyration - at each frame of a given trajectory file. Give this tool the - protein ID (PDB ID) only. The tool will automatically find the necessary files. + at each frame of a given trajectory. + Give this tool BOTH the trajectory file ID and the + topology file ID. The tool will save the radii of gyration to a csv file and map it to the registry.""" @@ -136,11 +131,15 @@ def __init__(self, path_registry): super().__init__() self.path_registry = path_registry - def _run(self, pdb_id: str) -> str: + def _run(self, traj_file: str, top_file: str) -> str: """use the tool.""" + RGY = RadiusofGyration(self.path_registry) try: - RGY = RadiusofGyration(self.path_registry) - return "Succeeded. " + RGY.rad_gyration_per_frame(pdb_id) + RGY._load_traj(top_file=top_file, traj_file=traj_file) + except Exception as e: + return f"Error loading traj: {e}" + try: + return "Succeeded. " + RGY.rgy_per_frame() except ValueError as e: return f"Failed. ValueError: {e}" except Exception as e: @@ -155,8 +154,8 @@ class RadiusofGyrationPlot(BaseTool): name = "RadiusofGyrationPlot" description = """This tool calculates the radius of gyration at each frame of a given trajectory file and plots it. - Give this tool the protein ID (PDB ID) only. - The tool will automatically find the necessary files. + Give this tool BOTH the trajectory file ID and the + topology file ID. The tool will save the plot to a png file and map it to the registry.""" path_registry: Optional[PathRegistry] @@ -165,11 +164,15 @@ def __init__(self, path_registry): super().__init__() self.path_registry = path_registry - def _run(self, pdb_id: str) -> str: + def _run(self, traj_file: str, top_file: str) -> str: """use the tool.""" + RGY = RadiusofGyration(self.path_registry) + try: + RGY._load_traj(top_file=top_file, traj_file=traj_file) + except Exception as e: + return f"Error loading traj: {e}" try: - RGY = RadiusofGyration(self.path_registry) - return "Succeeded. " + RGY.plot_rad_gyration(pdb_id) + return "Succeeded. " + RGY.plot_rgy() except ValueError as e: return f"Failed. ValueError: {e}" except Exception as e: diff --git a/mdagent/tools/base_tools/analysis_tools/secondary_structure.py b/mdagent/tools/base_tools/analysis_tools/secondary_structure.py new file mode 100644 index 00000000..f00decb4 --- /dev/null +++ b/mdagent/tools/base_tools/analysis_tools/secondary_structure.py @@ -0,0 +1,598 @@ +from typing import Optional + +import matplotlib.pyplot as plt +import mdtraj as md +import numpy as np +from langchain.tools import BaseTool + +from mdagent.utils import FileType, PathRegistry, load_single_traj + + +def write_raw_x( + x: str, values: np.ndarray, traj_id: str, path_registry: PathRegistry +) -> str: + """ + Writes raw x values to a file and saves the file to the path registry. + + Args: + x: The name of the analysis tool that produced the values (e.g., "dssp") + values: The x values to save. + traj_id: The id of the trajectory the values are associated with. + path_registry: The path registry to save the file to. + + Returns: + The file id of the saved file. + """ + file_name = path_registry.write_file_name( + FileType.RECORD, record_type=x, file_format="npy" + ) + file_id = path_registry.get_fileid(file_name, FileType.RECORD) + + file_path = f"{path_registry.ckpt_records}/{file_name}" + np.save(file_path, values) + + path_registry.map_path( + file_id, + file_path, + description=f"{x} values for trajectory with id: {traj_id}", + ) + return file_id + + +class ComputeDSSP(BaseTool): + name = "ComputeDSSP" + description = """Compute the DSSP (secondary structure) assignment + for a protein trajectory. Input is a trajectory file ID and + a target_frames, which can be "first", "last", or "all", + and an optional topology file ID. + Input "first" to get DSSP of only the first frame. + Input "last" to get DSSP of only the last frame. + Input "all" to get DSSP of all frames in trajectory, combined. + The output is an array with the DSSP code for each + residue at each time point.""" + path_registry: PathRegistry = PathRegistry.get_instance() + simplified: bool = True + + def __init__(self, path_registry: PathRegistry, simplified: bool = True): + super().__init__() + self.path_registry = path_registry + self.simplified = simplified + + def _dssp_codes(self) -> list[str]: + """ + Returns the DSSP codes used by MDTraj. If simplified is True, only + the codes H, E, and C are used. Otherwise, the full set of codes is + used.""" + if self.simplified: + return ["H", "E", "C", "NA"] + return ["H", "B", "E", "G", "I", "T", "S", " ", "NA"] + + def _dssp_natural_language(self) -> dict[str, str]: + """ + Returns a dictionary mapping DSSP codes to their natural language + descriptions. If simplified is True, only the codes H, E, and C are + used. Otherwise, the full set of codes is used.""" + if self.simplified: + return { + "H": "residues in helix", + "E": "residues in strand", + "C": "residues in coil", + "NA": "residues not assigned, not a protein residue", + } + return { + "H": "residues in alpha helix", + "B": "residues in beta bridge", + "E": "residues in extended strand", + "G": "residues in three helix", + "I": "residues in five helix", + "T": "residues in hydrogen bonded turn", + "S": "residues in bend", + " ": "residues in loop or irregular", + "NA": "residues not assigned, not a protein residue", + } + + def _convert_dssp_counts(self, dssp_counts: dict) -> dict: + """ + Converts a dictionary of DSSP codes to their counts into a dictionary + of natural language descriptions to their counts. + is used. + + Args: + dssp_counts: A dictionary mapping DSSP codes to their counts. + + Returns: + A dictionary mapping natural language descriptions to their counts. + """ + code_to_description = self._dssp_natural_language() + + descriptive_counts = { + code_to_description[code]: count for code, count in dssp_counts.items() + } + return descriptive_counts + + def _summarize_dssp(self, dssp_array: np.ndarray) -> dict[str, int]: + """ + Summarizes the DSSP assignments for a trajectory. Returns a dictionary + mapping DSSP codes to their counts. + + Args: + dssp_array: An array of DSSP codes for each residue at each time point. + + Returns: + A dictionary mapping natural language descriptions to their counts. + """ + dssp_codes = self._dssp_codes() + dssp_dict = {code: 0 for code in dssp_codes} + for frame in dssp_array: + for code in frame: + if code in dssp_dict.keys(): + dssp_dict[code] += 1 + else: + dssp_dict[code] = 1 + return self._convert_dssp_counts(dssp_dict) + + def _compute_dssp(self, traj: md.Trajectory) -> np.ndarray: + """ + Computes the DSSP assignments for a trajectory. + + Args: + traj: The trajectory to compute DSSP assignments for. + + Returns: + An array of DSSP codes for each residue at each time point. + """ + return md.compute_dssp(traj, simplified=self.simplified) + + def _get_frame(self, traj, target_frames): + """ + Retrieves the target frame(s) of the trajectory for DSSP. + + Args: + traj: the trajectory + target_frames: the target frames to select. can be first, last, or all + + Returns: + the trajectory with only target frames""" + + if target_frames.lower().strip() == "all": + return traj + if target_frames.lower().strip() == "first": + return traj[0] + if target_frames.lower().strip() == "last": + return traj[-1] + else: + raise ValueError("Target Frames must be 'all', 'first', or 'last'.") + + def _run( + self, + traj_file: str, + top_file: Optional[str] = None, + target_frames: str = "last", + ) -> str: + """ + Computes the DSSP assignments for a trajectory and saves the results + to a file. + + Args: + traj_file: The file id of the trajectory to compute DSSP assignments for. + top_file: The file id of the topology file to use. + + Returns: + A summary of the DSSP assignments. + """ + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + traj = self._get_frame(traj, target_frames) + except Exception as e: + print("Error loading trajectory: ", e) + return str(e) + + dssp_array = self._compute_dssp(traj) + write_raw_x("dssp", dssp_array, traj_file, self.path_registry) + summary = self._summarize_dssp(dssp_array) + return str(summary) + + async def _arun(self, traj_file, top_file): + """Runs the tool asynchronously.""" + raise NotImplementedError("Async version not implemented") + + +class ComputeGyrationTensor(BaseTool): + name = "ComputeGyrationTensor" + description = """Compute the gyration tensor for each frame in a + molecular dynamics trajectory. + Input is a trajectory file ID and an optional topology file ID. + The output is an array of gyration tensors for each frame of the + trajectory.""" + path_registry: PathRegistry = PathRegistry.get_instance() + + def __init__(self, path_registry: PathRegistry): + super().__init__() + self.path_registry = path_registry + + def _compute_gyration_tensor(self, traj: md.Trajectory) -> np.ndarray: + """ + Computes the gyration tensor for a trajectory. + + Args: + traj: The trajectory to compute the gyration tensor for. + + Returns: + An array of gyration tensors for each frame of the trajectory. + """ + return md.compute_gyration_tensor(traj) + + def _run(self, traj_file: str, top_file: Optional[str] = None) -> str: + """ + Computes the gyration tensor for a trajectory and saves the results + to a file. + + Args: + traj_file: The file id of the trajectory to compute the gyration tensor for. + top_file: The file id of the topology file to use. + + Returns: + A message indicating the success of the computation + """ + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + except Exception as e: + return str(e) + + gyration_tensors = self._compute_gyration_tensor(traj) + if traj.n_frames == 1: + return ( + "Gyration tensor computed for " + "a single frame, no file saved." + f"Gyrations tensor: {gyration_tensors}" + ) + + file_id = write_raw_x( + "gyration_tensor", gyration_tensors, traj_file, self.path_registry + ) + return f"Gyration tensor computed successfully, saved to {file_id}" + + async def _arun(self, traj_file, top_file=None): + """Runs the tool asynchronously.""" + raise NotImplementedError("Async version not implemented") + + +def plot_x_over_time( + x: str, values: np.ndarray, traj_id: str, path_registry: PathRegistry +) -> str: + """ + Plots the values of x over time and saves the plot to a file. + + Args: + x: The name of the analysis tool that produced the values (e.g., "dssp") + values: The x values to plot. + traj_id: The id of the trajectory the values are associated with. + path_registry: The path registry to save the file to. + + Returns: + The file id of the saved file. + """ + plt.figure(figsize=(10, 6)) + plt.plot(values) + plt.xlabel("Frame") + plt.ylabel(x) + plt.title(f"{x} Over Time") + plt.grid(True) + + file_name = path_registry.write_file_name( + FileType.FIGURE, + file_format="png", + ) + file_id = path_registry.get_fileid(file_name, FileType.RECORD) + + file_path = f"{path_registry.ckpt_figures}/{x}_over_time_{traj_id}.png" + plt.savefig(file_path, format="png", dpi=300, bbox_inches="tight") + plt.close() + + path_registry.map_path( + file_id, + file_name, + description=(f"{x} plot for trajectory " f"with id: {traj_id}"), + ) + return file_id + + +class ComputeAsphericity(BaseTool): + name = "ComputeAsphericity" + description = """Compute the asphericity for each frame in a + molecular dynamics trajectory. + Input is a trajectory file ID and an optional topology file ID. + The output is asphericity values for each frame of the + trajectory.""" + path_registry: PathRegistry = PathRegistry.get_instance() + + def __init__(self, path_registry: PathRegistry): + super().__init__() + self.path_registry = path_registry + + def _compute_asphericity(self, traj: md.Trajectory) -> np.ndarray: + """ + Computes the asphericity for a trajectory. + + Args: + traj: The trajectory to compute the asphericity for. + + Returns: + An array of asphericity values for each frame of the trajectory.""" + return md.asphericity(traj) + + def _run(self, traj_file: str, top_file: Optional[str] = None) -> str: + """ + Computes the asphericity for a trajectory and saves the results + to a file. + + Args: + traj_file: The file id of the trajectory to compute the asphericity for. + top_file: The file id of the topology file to use. + + Returns: + A message indicating the success of the computation. + """ + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + except Exception as e: + return str(e) + asphericity_values = self._compute_asphericity(traj) + if traj.n_frames == 1: + return ( + "Asphericity computed for " + "a single frame, no file saved." + f"Asphericity: {asphericity_values}" + ) + raw_file_id = write_raw_x( + "asphericity", asphericity_values, traj_file, self.path_registry + ) + plot_file_id = plot_x_over_time( + "Asphericity", asphericity_values, traj_file, self.path_registry + ) + return ( + "asphericity_values saved to " + f"{raw_file_id}, plot saved to " + f"{plot_file_id}" + ) + + async def _arun(self, traj_file, top_file): + """Runs the tool asynchronously.""" + raise NotImplementedError("Async version not implemented") + + +class ComputeAcylindricity(BaseTool): + name = "ComputeAcylindricity" + description = """Compute the acylindricity for each frame in a + molecular dynamics trajectory. + Input is a trajectory file ID and an optional topology file ID. + The output is an array of acylindricity values for + each frame of the trajectory.""" + path_registry: PathRegistry = PathRegistry.get_instance() + + def __init__(self, path_registry: PathRegistry): + super().__init__() + self.path_registry = path_registry + + def _compute_acylindricity(self, traj: md.Trajectory) -> np.ndarray: + """ + Computes the acylindricity for a trajectory. + + Args: + traj: The trajectory to compute the acylindricity for. + + Returns: + An array of acylindricity values for each frame of the trajectory. + """ + return md.acylindricity(traj) + + def _run(self, traj_file: str, top_file: Optional[str] = None) -> str: + """ + Computes the acylindricity for a trajectory and saves the results + to a file. + + Args: + traj_file: The file id of the trajectory to compute the acylindricity for. + top_file: The file id of the topology file to use. + + Returns: + A message indicating the success of the computation. + """ + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + except Exception as e: + return str(e) + acylindricity_values = self._compute_acylindricity(traj) + if traj.n_frames == 1: + return ( + "Acylindricity computed for " + "a single frame, no file saved." + f"Acylindricity: {acylindricity_values}" + ) + raw_file_id = write_raw_x( + "acylindricity", acylindricity_values, traj_file, self.path_registry + ) + plot_file_id = plot_x_over_time( + "acylindricity", acylindricity_values, traj_file, self.path_registry + ) + return ( + "acylindricity_values saved to " + f"{raw_file_id}, plot saved to " + f"{plot_file_id}" + ) + + async def _arun(self, traj_file, top_file): + """Runs the tool asynchronously.""" + raise NotImplementedError("Async version not implemented") + + +class ComputeRelativeShapeAntisotropy(BaseTool): + name = "ComputeRelativeShapeAntisotropy" + description = """Compute the relative shape antisotropy for each + frame in a molecular dynamics trajectory. Input is a trajectory + file ID and an optional topology file ID. + The output is an array of relative shape antisotropy values + for each frame of the trajectory.""" + path_registry: PathRegistry = PathRegistry.get_instance() + + def __init__(self, path_registry: PathRegistry): + super().__init__() + self.path_registry = path_registry + + def _compute_relative_shape_antisotropy(self, traj: md.Trajectory) -> np.ndarray: + """ + Computes the relative shape antisotropy for a trajectory. + + Args: + traj: The trajectory to compute the relative shape antisotropy for. + + Returns: + An array of relative shape antisotropy + values for each frame of the trajectory. + """ + return md.relative_shape_antisotropy(traj) + + def _run(self, traj_file: str, top_file: Optional[str] = None) -> str: + """ + Computes the relative shape antisotropy for a trajectory and saves the results + to a file. + + Args: + traj_file: The file id of the trajectory to + compute the relative shape antisotropy for. + top_file: The file id of the topology file to use. + + Returns: + A message indicating the success of the computation. + """ + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + except Exception as e: + return str(e) + relative_shape_antisotropy_values = self._compute_relative_shape_antisotropy( + traj + ) + if traj.n_frames == 1: + return ( + "Relative shape antisotropy computed for " + "a single frame, no file saved." + f"Relative shape antisotropy: {relative_shape_antisotropy_values}" + ) + + raw_file_id = write_raw_x( + "relative_shape_antisotropy", + relative_shape_antisotropy_values, + traj_file, + self.path_registry, + ) + plot_file_id = plot_x_over_time( + "relative_shape_antisotropy", + relative_shape_antisotropy_values, + traj_file, + self.path_registry, + ) + return ( + "relative_shape_antisotropy_values saved to " + f"{raw_file_id}, plot saved to " + f"{plot_file_id}" + ) + + async def _arun(self, traj_file, top_file): + """Runs the tool asynchronously.""" + raise NotImplementedError("Async version not implemented") + + +class SummarizeProteinStructure(BaseTool): + name = "SummarizeProteinStructure" + description = ( + "Get the number of atoms, residues, chains, " + "frames, and bonds in a protein trajectory. " + "Input is a trajectory file ID" + "and an optional topology file ID. " + "The output is a dictionary " + "containing the analyses." + ) + path_registry: PathRegistry = PathRegistry.get_instance() + + def __init__(self, path_registry: PathRegistry): + super().__init__() + self.path_registry = path_registry + + def summarize_protein_structure( + self, traj, requested_analyses: list | None = None + ) -> dict[str, int]: + """ + Summarizes the structure of a protein trajectory. + + Args: + traj: The trajectory to summarize the + structure of. + requested_analyses: A list of the analyses + to include in the summary. + + Returns: + A dictionary containing the requested analyses. + """ + if not traj.topology: + raise ValueError("Topolgy is required for this analysis to be meaningful.") + if not requested_analyses: + requested_analyses = ["atoms", "residues", "chains", "frames", "bonds"] + result = {} + if "atoms" in requested_analyses: + result["n_atoms"] = traj.n_atoms + if "residues" in requested_analyses: + result["n_residues"] = traj.n_residues + if "chains" in requested_analyses: + result["n_chains"] = traj.n_chains + if "frames" in requested_analyses: + result["n_frames"] = traj.n_frames + if "bonds" in requested_analyses: + result["n_bonds"] = len([bond for bond in traj.topology.bonds]) + return result + + def _run(self, traj_file: str, top_file: Optional[str] = None) -> str: + try: + traj = load_single_traj( + path_registry=self.path_registry, + traj_fileid=traj_file, + top_fileid=top_file, + ) + if not traj: + raise Exception("Trajectory could not be loaded.") + except Exception as e: + return str(e) + try: + result = self.summarize_protein_structure(traj) + except Exception as e: + return str(e) + return str(result) diff --git a/mdagent/tools/base_tools/preprocess_tools/clean_tools.py b/mdagent/tools/base_tools/preprocess_tools/clean_tools.py index 821295b9..1be094f3 100644 --- a/mdagent/tools/base_tools/preprocess_tools/clean_tools.py +++ b/mdagent/tools/base_tools/preprocess_tools/clean_tools.py @@ -30,7 +30,7 @@ class CleaningToolFunctionInput(BaseModel): add_hydrogens: bool = Field( True, description="Whether to add hydrogens to the file." ) - add_hydrogens_ph: int = Field(7.0, description="pH at which hydrogens are added.") + add_hydrogens_ph: float = Field(7.0, description="pH at which hydrogens are added.") class CleaningToolFunction(BaseTool): diff --git a/mdagent/tools/base_tools/preprocess_tools/pdb_get.py b/mdagent/tools/base_tools/preprocess_tools/pdb_get.py index eac925ec..6212a6c9 100644 --- a/mdagent/tools/base_tools/preprocess_tools/pdb_get.py +++ b/mdagent/tools/base_tools/preprocess_tools/pdb_get.py @@ -1,7 +1,6 @@ from typing import Optional import requests -import streamlit as st from langchain.tools import BaseTool from rdkit import Chem from rdkit.Chem import AllChem @@ -27,7 +26,7 @@ def get_pdb(query_string: str, path_registry: PathRegistry): } r = requests.post(url, json=query) if r.status_code == 204: - return None + return None, None if "cif" in query_string or "CIF" in query_string: filetype = "cif" else: @@ -36,7 +35,6 @@ def get_pdb(query_string: str, path_registry: PathRegistry): results = r.json()["result_set"] pdbid = max(results, key=lambda x: x["score"])["identifier"] print(f"PDB file found with this ID: {pdbid}") - st.markdown(f"PDB file found with this ID: {pdbid}", unsafe_allow_html=True) url = f"https://files.rcsb.org/download/{pdbid}.{filetype}" pdb = requests.get(url) filename = path_registry.write_file_name( @@ -57,7 +55,7 @@ def get_pdb(query_string: str, path_registry: PathRegistry): ) return filename, file_id - return None + return None, None class ProteinName2PDBTool(BaseTool): @@ -165,6 +163,68 @@ def smiles2name(self, smi: str) -> str: return "Unknown Molecule" return name + def get_pubchem_cid(self, smiles): + _url = "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/smiles/" + url = _url + f"{smiles}/cids/JSON" + response = requests.get(url) + if response.status_code == 200: + data = response.json() + return data["IdentifierList"]["CID"][0] + return None + + def get_hetcode_from_cid(self, cid): + print(cid) + url = f"https://pubchem.ncbi.nlm.nih.gov/rest/pug_view/data/compound/{cid}/JSON" + response = requests.get(url) + header_1 = "Interactions and Pathways" + header_2 = "Protein Bound 3D Structures" + header_3 = "Ligands from Protein Bound 3D Structures" + header_4 = "PDBe Ligand Code" + if response.status_code == 200: + data = response.json() + for section in data["Record"]["Section"]: + if section["TOCHeading"] == header_1: + for subsection in section["Section"]: + if subsection["TOCHeading"] == header_2: + for subsubsection in subsection["Section"]: + if subsubsection["TOCHeading"] == header_3: + for s in subsubsection["Section"]: + if s["TOCHeading"] == header_4: + return s["Information"][0]["Value"][ + "StringWithMarkup" + ][0]["String"] + return None + + def get_hetcode(self, smiles): + cid = self.get_pubchem_cid(smiles) + if cid is not None: + return self.get_hetcode_from_cid(cid) + return None + + def _add_res_info(self, m, code, name=None): + """This code is unnecesarilly big considering i only want to add + the HET code to the molecule, but there is a bug in RDKIT that screws the + PDB file if all the other attributes are not added. + Updating residue Name from UNL to the HET code present in pubchem + Everythin else (number, is heteroatom, etc) is kept the same but needs to be + added to avoid the bug. + See: https://github.com/rdkit/rdkit/pull/7286#issue-2200600916""" + block = AllChem.MolToPDBBlock(m) + for line in block.split("\n"): + if line.startswith("HETATM"): # avoiding CONECT, COMPND, etc. + atom_number = line[6:11] + atom_name = line[12:16] + res_number = line[22:26] + atom = m.GetAtomWithIdx(int(atom_number) - 1) + res_inf = Chem.AtomPDBResidueInfo() + res_inf.SetName(f"{atom_name}") + res_inf.SetResidueName(f"{code}") + res_inf.SetResidueNumber(int(res_number)) + res_inf.SetIsHeteroAtom(True) + atom.SetPDBResidueInfo(res_inf) + if name: + m.SetProp("_Name", name) + def small_molecule_pdb(self, mol_str: str) -> str: # takes in molecule name or smiles (converts to smiles if name) # writes pdb file name.pdb (gets name from smiles if possible) @@ -175,16 +235,30 @@ def small_molecule_pdb(self, mol_str: str) -> str: if self.is_smiles(mol_str): m = Chem.MolFromSmiles(mol_str) mol_name = self.smiles2name(mol_str) + HET_code = self.get_hetcode(mol_str) + if not HET_code: + HET_code = "UNK" else: # if input is not smiles, try getting smiles smi = self.molname2smiles(mol_str) m = Chem.MolFromSmiles(smi) mol_name = mol_str + HET_code = self.get_hetcode(smi) + if not HET_code: + HET_code = "UNL" + try: # only if needed m = Chem.AddHs(m) + except Exception: pass + AllChem.EmbedMolecule(m) + # add HET code to molecule + file_name = f"{self.path_registry.ckpt_pdb}/{mol_name}.pdb" + if HET_code != "UNL": # if HET code is UNL no need for this... + self._add_res_info(m, HET_code, mol_name) + Chem.MolToPDBFile(m, file_name) print("finished writing pdb file") self.path_registry.map_path( diff --git a/mdagent/tools/base_tools/preprocess_tools/uniprot.py b/mdagent/tools/base_tools/preprocess_tools/uniprot.py index 03b939d0..28dfae69 100644 --- a/mdagent/tools/base_tools/preprocess_tools/uniprot.py +++ b/mdagent/tools/base_tools/preprocess_tools/uniprot.py @@ -697,7 +697,7 @@ def get_ids( entry["primaryAccession"] for entry in accession ] if accession else [] if single_id: - return all_ids.pop() + return [all_ids[0]] if all_ids else [] return list(set(all_ids)) def get_gene_names(self, query: str, primary_accession: str | None = None) -> list: diff --git a/mdagent/tools/base_tools/simulation_tools/__init__.py b/mdagent/tools/base_tools/simulation_tools/__init__.py index 56933956..0022cf88 100644 --- a/mdagent/tools/base_tools/simulation_tools/__init__.py +++ b/mdagent/tools/base_tools/simulation_tools/__init__.py @@ -1,9 +1,7 @@ from .create_simulation import ModifyBaseSimulationScriptTool -from .setup_and_run import SetUpandRunFunction, SetUpAndRunTool, SimulationFunctions +from .setup_and_run import SetUpandRunFunction __all__ = [ "ModifyBaseSimulationScriptTool", "SetUpandRunFunction", - "SetUpAndRunTool", - "SimulationFunctions", ] diff --git a/mdagent/tools/base_tools/simulation_tools/create_simulation.py b/mdagent/tools/base_tools/simulation_tools/create_simulation.py index 8fdaf918..51ce6e36 100644 --- a/mdagent/tools/base_tools/simulation_tools/create_simulation.py +++ b/mdagent/tools/base_tools/simulation_tools/create_simulation.py @@ -2,9 +2,9 @@ from typing import Optional from langchain.base_language import BaseLanguageModel -from langchain.chains import LLMChain from langchain.prompts import PromptTemplate from langchain.tools import BaseTool +from langchain_core.output_parsers import StrOutputParser from pydantic import BaseModel, Field from mdagent.utils import FileType, PathRegistry @@ -48,7 +48,7 @@ def _prompt_summary(self, query: str): prompt = PromptTemplate( template=prompt_template, input_variables=["base_script", "query"] ) - llm_chain = LLMChain(prompt=prompt, llm=self.llm) + llm_chain = prompt | self.llm | StrOutputParser() return llm_chain.invoke(query) diff --git a/mdagent/tools/base_tools/simulation_tools/setup_and_run.py b/mdagent/tools/base_tools/simulation_tools/setup_and_run.py index d0391d1f..d6dfe023 100644 --- a/mdagent/tools/base_tools/simulation_tools/setup_and_run.py +++ b/mdagent/tools/base_tools/simulation_tools/setup_and_run.py @@ -1,6 +1,4 @@ # Standard Library Imports -import ast -import json import os import re @@ -8,13 +6,10 @@ import textwrap from typing import Any, Dict, List, Optional, Type -import langchain -import streamlit as st -from langchain.chains import LLMChain -from langchain.prompts import PromptTemplate +import requests from langchain.tools import BaseTool +from openff.toolkit.topology import Molecule from openmm import ( - AndersenThermostat, BrownianIntegrator, LangevinIntegrator, LangevinMiddleIntegrator, @@ -22,7 +17,6 @@ OpenMMException, Platform, VerletIntegrator, - app, unit, ) from openmm.app import ( @@ -43,8 +37,10 @@ Simulation, StateDataReporter, ) -from openmm.unit import bar, femtoseconds, kelvin, nanometers, picosecond, picoseconds +from openmm.unit import bar, kelvin, nanometers, picoseconds +from openmmforcefields.generators import SMIRNOFFTemplateGenerator from pydantic import BaseModel, Field +from rdkit import Chem # Local Library/Application Imports from mdagent.utils import FileType, PathRegistry @@ -106,430 +102,6 @@ ] -class SimulationFunctions: - def __init__( - self, - path_registry, - temperature: float = 0.05, - model_name: str = "gpt-4", - request_timeout: int = 1000, - max_tokens: int = 2000, - ): - self.path_registry = path_registry - self.temperature = temperature - self.model_name = model_name - self.request_timeout = request_timeout - self.max_tokens = max_tokens - - self.llm = langchain.chat_models.ChatOpenAI( - temperature=self.temperature, - model_name=self.model_name, - request_timeout=self.request_timeout, - max_tokens=self.request_timeout, - ) - - #######==================System Congifuration==================######## - # System Configuration initialization. - - def _create_system( - pdb, - forcefield, - nonbondedMethod="NoCutoff", - nonbondedCutoff=None, - ewaldErrorTolerance=None, - constraints="None", - rigidWater=False, - constraintTolerance=None, - **kwargs, - ): - # Create a dictionary to hold system parameters - system_params = { - "nonbondedMethod": nonbondedMethod, - "constraints": constraints, - "rigidWater": rigidWater, - } - - # Set nonbondedCutoff if applicable - if ( - nonbondedMethod in ["PME", "CutoffNonPeriodic", "CutoffPeriodic"] - and nonbondedCutoff is not None - ): - system_params["nonbondedCutoff"] = nonbondedCutoff - - # Set ewaldErrorTolerance if PME is used - if nonbondedMethod == "PME" and ewaldErrorTolerance is not None: - system_params["ewaldErrorTolerance"] = ewaldErrorTolerance - - # Set constraintTolerance if constraints are used - if constraints in ["HBonds", " AllBonds"] and constraintTolerance is not None: - system_params["constraintTolerance"] = constraintTolerance - elif system_params["rigidWater"] and constraintTolerance is not None: - system_params["constraintTolerance"] = constraintTolerance - - # Update system_params with any additional parameters provided - system_params.update(kwargs) - system = forcefield.createSystem(pdb.topology, **system_params) - return system - - ########==================Integrator==================######## - # Integrator - def _define_integrator( - integrator_type="LangevinMiddle", - temperature=300 * kelvin, - friction=1.0 / picoseconds, - timestep=0.004 * picoseconds, - **kwargs, - ): - # Create a dictionary to hold integrator parameters - integrator_params = { - "temperature": temperature, - "friction": friction, - "timestep": timestep, - } - - # Update integrator_params with any additional parameters provided - integrator_params.update(kwargs) - - # Create the integrator - if integrator_type == "LangevinMiddle": - integrator = LangevinMiddleIntegrator(**integrator_params) - elif integrator_type == "Verlet": - integrator = VerletIntegrator(**integrator_params) - elif integrator_type == "Brownian": - integrator = BrownianIntegrator(**integrator_params) - else: - raise Exception("Integrator type not recognized") - - return integrator - - def _prompt_summary(self, query: str): - prompt_template = """Your input is the original query. Your - task is to parse through the user query. - and provide a summary of the file path input, - the type of preprocessing needed (this is the - same as cleaning the file), the forcefield - used for the simulation, - the ensemble of the simulation, the integrator needed, - the number of steps, the timestep, the temperature, - and other instructions. - and follow the format "name: description. - - File Path: what is the file path of the file - you are using? it must include a .cif or .pdb extension. - Preprocessing: what preprocessing is needed? - you can choose from the following: standard cleaning, - remove water, add hydrogens, add hydrogens and remove - water. The default is add hydrogens and remove water. - Forcefield: what forcefields are you using? - you can choose from the following: AMBER, CHARMM, - OPLS, GROMACS. Default --> "amber14-all.xml, tip3p.xml". - Ensemble: what ensemble are you using? - you can choose from the following: - NPT, NVT, NVE. Default --> "NVT". - Integrator: what integrator are you using? - you can choose from the following: - Langevin, Verlet, Brownian. - The default depends on the ensemble - (NPT -> Langevin, NVT -> Langevin, NVE -> Verlet). - Number of Steps: how many steps - are you using? The default is 10000. - Timestep: what is the timestep? - Default --> "1 fs". - Temperature: what is the temperature? - Default --> "300 K". - Pressure: What is the pressure? - If NPT ensemble, the default is 1.0 bar, otherwise None. - Friction: what is the friction coefficient? - Default --> "1.0" - record_params: what parameters do you want to record? - you can choose from the following: - step, time, potentialEnergy, kineticEnergy, - totalEnergy, temperature, volume, density, - progress, remainingTime, speed, elapsedTime, - separator, systemMass, totalSteps, append. - Default --> ["step", "potentialEnergy", "temperature"]. - Other Instructions: what other instructions do you have? - The default is none. - Example of the final output: - File Path: 1a1p.pdb - Preprocessing: standard cleaning - Forcefield: amber14-all.xml, tip3p.xml - Ensemble: NPT - Integrator: Langevin - Number of Steps: 10000 - Timestep: 1 fs - Temperature: 300 K - Pressure: 1.0 bar - Friction: 1.0 - record_params: ["step", "potentialEnergy", "temperature"] - Other Instructions: none - If there is not enough information in a category, - you may fill in with the default, but explicitly state so. - Here is the information:{query}""" - prompt = PromptTemplate(template=prompt_template, input_variables=["query"]) - llm_chain = LLMChain(prompt=prompt, llm=self.llm) - - return llm_chain.run(" ".join(query)) - - def _save_to_file(self, summary: str, filename: str): - """Parse the summary string and - save it to a file in JSON format.""" - # Split the summary into lines - lines = summary.strip().split("\n") - - # Parse each line into a key and a value - summary_dict = {} - for line in lines: - key, value = line.split(":") - summary_dict[key.strip()] = value.strip() - - # Save the dictionary to a file - with open(filename, "w") as f: - json.dump(summary_dict, f) - - # add filename to registry - file_description = "Simulation Parameters" - self.path_registry.map_path(filename, filename, file_description) - - def _instruction_summary(self, query: str): - summary = self._prompt_summary(query) - self._save_to_file( - summary, f"{self.path_registry.ckpt_files}/simulation_parameters.json" - ) - return summary - - def _setup_simulation_from_json(self, file_name): - # Open the json file and load the parameters - with open(file_name, "r") as f: - params = json.load(f) - return params - - def _setup_and_run_simulation(self, query): - # Load the force field - # ask for inputs from the user - params = self._setup_simulation_from_json(query) - - # forcefield key can be forcefield_files or Forcefield - if "forcefield_files" in params: - params["forcefield_files"] = ( - params["forcefield_files"] - .replace("(default)", "") - .replace(" and ", ",") - .strip() - ) - Forcefield_files = [ - file.strip() for file in params["forcefield_files"].split(",") - ] - Forcefield = Forcefield_files[0] - Water_model = Forcefield_files[1] - else: - params["Forcefield"] = ( - params["Forcefield"] - .replace("(default)", "") - .replace(" and ", ",") - .strip() - ) - Forcefield_files = [ - file.strip() for file in params["Forcefield"].split(",") - ] - Forcefield = Forcefield_files[0] - Water_model = Forcefield_files[1] - print("Setting up forcefields :", Forcefield, Water_model) - st.markdown("Setting up forcefields", unsafe_allow_html=True) - # check if forcefields end in .xml - if Forcefield.endswith(".xml") and Water_model.endswith(".xml"): - forcefield = ForceField(Forcefield, Water_model) - # adding forcefield to registry - - # Load the PDB file - pdbfile = self.path_registry.get_mapped_path(params["File Path"]) - name = pdbfile.split(".")[0] - end = pdbfile.split(".")[1] - if end == "pdb": - pdb = PDBFile(pdbfile) - elif end == "cif": - pdb = PDBxFile(pdbfile) - - modeller = Modeller(pdb.topology, pdb.positions) - system = forcefield.createSystem( - modeller.topology, - nonbondedMethod=app.PME, - nonbondedCutoff=1.0 * nanometers, - constraints=app.PME, - ) - - _integrator = params["Integrator"].split(" ")[0].strip() - _temp = params["Temperature"].split(" ")[0].strip() - _friction_coef = params["Friction"].split(" ")[0].strip() - _timestep = params["Timestep"].split(" ")[0].strip() - - if _integrator == "Langevin": - print( - "Setting up Langevin integrator with Parameters:", - _temp, - "K", - _friction_coef, - "1/ps", - _timestep, - "fs", - ) - st.markdown("Setting up Langevin integrator", unsafe_allow_html=True) - if params["Ensemble"] == "NPT": - _pressure = params["Pressure"].split(" ")[0].strip() - system.addForce(MonteCarloBarostat(_pressure * bar, _temp * kelvin)) - integrator = LangevinIntegrator( - float(_temp) * kelvin, - float(_friction_coef) / picosecond, - float(_timestep) * femtoseconds, - ) - elif _integrator == "Verlet": - if params["Ensemble"] == "NPT": - _pressure = params["Pressure"].split(" ")[0].strip() - system.addForce(AndersenThermostat(_temp * kelvin, 1 / picosecond)) - system.addForce(MonteCarloBarostat(_pressure * bar, _temp * kelvin)) - print( - "Setting up Verlet integrator with Parameters:", - _timestep, - "fs", - _temp, - "K", - _pressure, - "bar", - ) - print("Setting up Verlet integrator with Parameters:", _timestep, "fs") - st.markdown("Setting up Verlet integrator", unsafe_allow_html=True) - integrator = VerletIntegrator(float(_timestep) * picoseconds) - - simulation = Simulation(modeller.topology, system, integrator) - simulation.context.setPositions(modeller.positions) - simulation.minimizeEnergy() - # save initial positions to registry - file_name = "initial_positions.pdb" - with open(file_name, "w") as f: - PDBFile.writeFile( - simulation.topology, - simulation.context.getState(getPositions=True).getPositions(), - f, - ) - print("Initial Positions saved to initial_positions.pdb") - simulation.reporters.append(PDBReporter(f"{name}.pdb", 1000)) - # reporter_args = {"reportInterval": 1000} - reporter_args = {} - params["record_params"] = ast.literal_eval(params["record_params"]) - for param in params["record_params"]: - if param in [ - "step", - "time", - "potentialEnergy", - "kineticEnergy", - "totalEnergy", - "temperature", - "volume", - "density", - "progress", - "remainingTime", - "speed", - "elapsedTime", - "separator", - "systemMass", - "totalSteps", - "append", - ]: - # The params from the json file should be booleans - reporter_args[param] = True - simulation.reporters.append( - StateDataReporter(f"{name}.csv", 1000, **reporter_args) - ) - - simulation.step(int(params["Number of Steps"].split(" ")[0].strip())) - - # add filenames to registry - file_name1 = "simulation_trajectory.pdb" - file_description1 = "Simulation PDB, containing the simulation trajectory" - self.path_registry.map_path(file_name1, f"{name}.pdb", file_description1) - file_name2 = "simulation_data.csv" - file_description2 = ( - "Simulation Data, containing step, potential energy, and temperature" - ) - self.path_registry.map_path(file_name2, f"{name}.csv", file_description2) - - return simulation - - def _extract_parameters_path(self): - """Check directory for parameters.json file.""" - # Check if there is a parameters.json file in the directory. - if os.path.exists("simulation_parameters_summary.json"): - return "simulation_parameters_summary.json" - # If there's no exact match, check for - # any JSON file that contains 'parameters' in its name. - else: - for file in os.listdir("."): - if "parameters" in file and file.endswith(".json"): - return file - # If no matching file is found, raise an exception. - raise ValueError("No parameters.json file found in directory.") - - -class SetUpAndRunTool(BaseTool): - name = "SetUpAndRunTool" - description = """This tool will set up the simulation objects - and run the simulation. - It will ask for the parameters path. - input: json file - """ - path_registry: Optional[PathRegistry] - - def __init__( - self, - path_registry: Optional[PathRegistry], - ): - super().__init__() - self.path_registry = path_registry - - def _run(self, query: str) -> str: - """Use the tool""" - # find the parameters in the directory - try: - if self.path_registry is None: # this should not happen - return "Registry not initialized" - sim_fxns = SimulationFunctions(path_registry=self.path_registry) - parameters = sim_fxns._extract_parameters_path() - - except ValueError as e: - return ( - str(e) - + """\nPlease use the Instruction summary tool with the - to create a parameters.json file in the directory.""" - ) - self.log("This are the parameters:") - self.log(parameters) - # print the parameters in json file - with open(parameters) as f: - params = json.load(f) - for key, value in params.items(): - print(key, ":", value) - - self.log("Are you sure you want to run the simulation? (y/n)") - response = input("yes or no: ") - if response.lower() in ["yes", "y"]: - sim_fxns._setup_and_run_simulation(parameters) - else: - return "Simulation interrupted due to human input" - return "Simulation Completed, simulation trajectory and data files saved." - - def log(self, text, color="blue"): - if color == "blue": - print("\033[1;34m\t{}\033[00m".format(text)) - if color == "red": - print("\033[31m\t{}\033[00m".format(text)) - - async def _arun(self, query: str) -> str: - """Use the tool asynchronously.""" - raise NotImplementedError("custom_search does not support async") - - -#######==================System Configuration==================######## -# System Configuration class SetUpandRunFunctionInput(BaseModel): pdb_id: str forcefield_files: List[str] @@ -678,12 +250,23 @@ def __init__( def setup_system(self): print("Building system...") - st.markdown("Building system", unsafe_allow_html=True) self.pdb_id = self.params["pdb_id"] self.pdb_path = self.path_registry.get_mapped_path(self.pdb_id) self.pdb = PDBFile(self.pdb_path) self.forcefield = ForceField(*self.params["forcefield_files"]) - self.system = self._create_system(self.pdb, self.forcefield, **self.sys_params) + try: + self.system = self._create_system( + self.pdb, self.forcefield, **self.sys_params + ) + print("System built successfully") + print(self.system) + except ValueError as e: + if "No template found for" in str(e): + raise ValueError(str(e)) + else: + raise ValueError( + f"Error building system. Please check the forcefield files {str(e)}" + ) if self.sys_params.get("nonbondedMethod", None) in [ CutoffPeriodic, @@ -700,7 +283,6 @@ def setup_system(self): def setup_integrator(self): print("Setting up integrator...") - st.markdown("Setting up integrator", unsafe_allow_html=True) int_params = self.int_params integrator_type = int_params.get("integrator_type", "LangevinMiddle") @@ -725,7 +307,6 @@ def setup_integrator(self): def create_simulation(self): print("Creating simulation...") - st.markdown("Creating simulation", unsafe_allow_html=True) self.simulation = Simulation( self.modeller.topology, self.system, @@ -873,40 +454,125 @@ def _create_system( # if use_constraint_tolerance: # constraintTolerance = system_params.pop('constraintTolerance') + print("About to create system...") self.modeller = Modeller(pdb.topology, pdb.positions) - if solvate: - try: - self.modeller.addSolvent(forcefield) - except ValueError as e: - print("Error adding solvent", type(e).__name__, "–", e) - if "No Template for" in str(e): - raise ValueError(str(e)) - except AttributeError as e: - print("Error adding solvent: ", type(e).__name__, "–", e) - print("Trying to add solvent with 1 nm padding") - if "NoneType" and "value_in_unit" in str(e): - try: - self.modeller.addSolvent(forcefield, padding=1 * nanometers) - except Exception as e: - print("Error adding solvent", type(e).__name__, "–", e) - raise (e) - except Exception as e: - if "Cannot neutralize the system because the" in str(e): - try: - self.modeller.addSolvent(forcefield, padding=1 * nanometers) - except Exception as e: - print("Error adding solvent", type(e).__name__, "–", e) + attempts = 0 + solvent_list = ["MOH", "EOH", "HOH", "ACN", "URE", "DMS", "DMF", "GOL", "BNZ"] + while attempts < 3: + print(f"Attempts at creating system: {attempts}/3") + if solvate: + try: + self.modeller.addSolvent(forcefield) + except ValueError as e: + print("Error adding solvent", type(e).__name__, "–", e) + if "No template found for" in str(e): + smiles = self._error_to_smiles(e, solvent_list) + + molecule = Molecule.from_smiles(smiles) + smirnoff = SMIRNOFFTemplateGenerator(molecules=molecule) + forcefield.registerTemplateGenerator(smirnoff.generator) + attempts += 1 + print( + f"Attempt {attempts} to add small \ + molecules to forcefield." + ) + continue + else: + raise ValueError(str(e)) + + except AttributeError as e: + print("Error adding solvent: ", type(e).__name__, "–", e) + print("Trying to add solvent with 1 nm padding") + if "NoneType" and "value_in_unit" in str(e): + try: + self.modeller.addSolvent(forcefield, padding=1 * nanometers) + except Exception as e: + print("Error adding solvent", type(e).__name__, "–", e) + raise (e) + except Exception as e: + if "Cannot neutralize the system because the" in str(e): + try: + self.modeller.addSolvent(forcefield, padding=1 * nanometers) + except Exception as e: + print("Error adding solvent", type(e).__name__, "–", e) + raise (e) + else: + print("Exception: ", str(e)) raise (e) - else: - print("Exception: ", str(e)) - raise (e) - system = forcefield.createSystem(self.modeller.topology, **system_params) - else: - system = forcefield.createSystem(self.modeller.topology, **system_params) + system = forcefield.createSystem( + self.modeller.topology, **system_params + ) + break + else: + try: + print("adding system without solvent") + system = forcefield.createSystem( + self.modeller.topology, **system_params + ) + break + except ValueError as e: + if "No template found for" in str(e): + print("Trying to add component to Forcefield...") + smiles = self._error_to_smiles(e, solvent_list) + + molecule = Molecule.from_smiles(smiles) + smirnoff = SMIRNOFFTemplateGenerator(molecules=molecule) + forcefield.registerTemplateGenerator(smirnoff.generator) + attempts += 1 + print( + f"Attempt {attempts} to add small \ + molecules to forcefield." + ) + continue + else: + raise ValueError(str(e)) + if attempts == 3: + raise ValueError("Could not create system after 3 attemps.") return system + def _code_to_smiles( + self, query: str + ) -> ( + str | None + ): # from https://github.com/ur-whitelab/chemcrow-public/blob/main/chemcrow/tools/databases.py + url = " https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{}/{}" + r = requests.get(url.format(query, "property/IsomericSMILES/JSON")) + # convert the response to a json object + data = r.json() + # return the SMILES string + try: + smi = data["PropertyTable"]["Properties"][0]["IsomericSMILES"] + except KeyError: + return None + return smi + + def _error_to_smiles(self, e, solvent_list): + pattern = r"residue \d+ \((\w+)\)" + # Search for the pattern in the error message + match = re.search(pattern, str(e)) + if not match: + print("No residue code found in the error message.") + raise ValueError(str(e)) + residue_code = match.group(1) + print(f"Residue code: {residue_code}") + if residue_code not in solvent_list: + print( + "Residue code not in solvent list. Adding forcefield \ + not supported." + ) + raise ValueError(str(e)) + + print("Trying to add missing component to Forcefield...") + smiles = self._code_to_smiles(residue_code) + if not smiles: + print("No SMILES found for HET code.") + raise ValueError(str(e)) + + print(f"Found SMILES from HET code: {smiles}") + return smiles + def unit_to_string(self, unit): """Needed to convert units to strings for the script Otherwise internal __str()__ method makes the script @@ -1084,6 +750,20 @@ def _construct_script_content( """ return script_content + def het_to_smiles(het_code): + try: + # Fetch the molecule using RDKit's PDB parser + molecule = Chem.MolFromPDBCode(het_code) + + if molecule: + # Convert the molecule to SMILES + smiles = Chem.MolToSmiles(molecule) + return smiles + else: + return "Invalid HET code or molecule not found." + except Exception as e: + return str(e) + def write_standalone_script(self, filename="reproduce_simulation.py"): """Extracting parameters from the class instance Inspired by the code snippet provided from openmm-setup @@ -1154,12 +834,10 @@ def remove_leading_spaces(text): file.write(script_content) print(f"Standalone simulation script written to {directory}/{filename}") - st.markdown("Standalone simulation script written", unsafe_allow_html=True) def run(self): # Minimize and Equilibrate print("Performing energy minimization...") - st.markdown("Performing energy minimization", unsafe_allow_html=True) self.simulation.minimizeEnergy() print("Minimization complete!") @@ -1173,7 +851,6 @@ def run(self): ) self.path_registry.map_path(f"top_{self.sim_id}", top_name, top_description) print("Initial Positions saved to initial_positions.pdb") - st.markdown("Minimization complete! Equilibrating...", unsafe_allow_html=True) print("Equilibrating...") _temp = self.int_params["Temperature"] self.simulation.context.setVelocitiesToTemperature(_temp) @@ -1181,11 +858,9 @@ def run(self): self.simulation.step(_eq_steps) # Simulate print("Simulating...") - st.markdown("Simulating...", unsafe_allow_html=True) self.simulation.currentStep = 0 self.simulation.step(self.sim_params["Number of Steps"]) print("Done!") - st.markdown("Done!", unsafe_allow_html=True) if not self.save: if os.path.exists("temp_trajectory.dcd"): os.remove("temp_trajectory.dcd") @@ -1266,7 +941,6 @@ def _run(self, **input_args): openmmsim.create_simulation() print("simulation set!") - st.markdown("simulation set!", unsafe_allow_html=True) except ValueError as e: msg = str(e) + f"This were the inputs {input_args}" if "No template for" in msg: @@ -1808,11 +1482,9 @@ def check_system_params(cls, values): forcefield_files = values.get("forcefield_files") if forcefield_files is None or forcefield_files is []: print("Setting default forcefields") - st.markdown("Setting default forcefields", unsafe_allow_html=True) forcefield_files = ["amber14-all.xml", "amber14/tip3pfb.xml"] elif len(forcefield_files) == 0: print("Setting default forcefields v2") - st.markdown("Setting default forcefields", unsafe_allow_html=True) forcefield_files = ["amber14-all.xml", "amber14/tip3pfb.xml"] else: for file in forcefield_files: diff --git a/mdagent/tools/base_tools/util_tools/__init__.py b/mdagent/tools/base_tools/util_tools/__init__.py index 079e5904..87f60934 100644 --- a/mdagent/tools/base_tools/util_tools/__init__.py +++ b/mdagent/tools/base_tools/util_tools/__init__.py @@ -1,4 +1,3 @@ -from .git_issues_tool import SerpGitTool from .registry_tools import ListRegistryPaths, MapPath2Name from .search_tools import Scholar2ResultLLM @@ -6,5 +5,4 @@ "ListRegistryPaths", "MapPath2Name", "Scholar2ResultLLM", - "SerpGitTool", ] diff --git a/mdagent/tools/base_tools/util_tools/git_issues_tool.py b/mdagent/tools/base_tools/util_tools/git_issues_tool.py deleted file mode 100644 index 8ce86f1d..00000000 --- a/mdagent/tools/base_tools/util_tools/git_issues_tool.py +++ /dev/null @@ -1,177 +0,0 @@ -from typing import List, Optional - -import requests -import tiktoken -from langchain.chains import LLMChain -from langchain.prompts import PromptTemplate -from langchain.tools import BaseTool -from serpapi import GoogleSearch - -from mdagent.utils import _make_llm - - -class GitToolFunctions: - """Class to store the functions of the tool.""" - - def __init__( - self, - model: str = "gpt-3.5-turbo-16k", - temp: float = 0.05, - verbose: bool = False, - ): - self.model = model - self.temp = temp - self.verbose = verbose - self.llm = _make_llm(model=self.model, temp=self.temp, verbose=self.verbose) - - def _prompt_summary(self, query: str, output: str): - prompt_template = """You're receiving the following github issues and comments. - They come after looking for issues - in the openmm repo for the query: {query}. - The responses have the following format: - Issue: body of the issue - Comment: comments in response to the issue. - There are up to 5 comments per issue. - Some of the comments do not address the issue. - You job is to decide: - 1) if the issue is relevant to the query. - 2) if the comments are relevant to the issue. - Then, make a summary of the issue and comments. - Only keeping the relevant information. - If there are PDB files shared, - just add a few lines from them, not all of it. - If a comment is not relevant, - do not include it in the summary. - And if the issue is not relevant, - do not include it in the summary. - Keep in the summary all possible solutions given - in the comments if they are appropiate. - The summary should have at most 2.5k tokens. - The answer you have to summarize is: - {output} - - you:""" - prompt = PromptTemplate( - template=prompt_template, input_variables=["query", "output"] - ) - llm_chain = LLMChain(prompt=prompt, llm=self.llm) - - return llm_chain.run({"query": query, "output": output}) - - """Function to get the number of requests remaining for the Github API """ - - def get_requests_remaining(self): - url = "https://api.github.com/rate_limit" - response = requests.get(url) - return response.json()["rate"]["remaining"] - - def make_encoding(self): - return tiktoken.encoding_for_model("gpt-4") - - -class SerpGitTool(BaseTool): - name = "Openmm_Github_Issues_Search" - description = """ Tool that searches inside - github issues in openmm. Make - your query as if you were googling something. - Input: Trying to run a simulation with a - custom forcefield error: error_code. - Output: Relevant issues with your query. - Input: """ - serp_key: Optional[str] - - def __init__(self, serp_key): - super().__init__() - self.serp_key = serp_key - - def _run(self, query: str): - fxns = GitToolFunctions() - # print("this is the key", self.serp_key) - params = { - "engine": "google", - "q": "site:github.com/openmm/openmm/issues " + query, - "api_key": self.serp_key, - } - encoding = fxns.make_encoding() - search = GoogleSearch(params) - results = search.get_dict() - organic_results = results.get("organic_results") - if organic_results is None: - if results.get("error"): - return "Failed. Error: " + results.get("error") - else: - return "Failed. Error: No 'organic_results' found" - issues_numbers: List = ( - [] - ) # list that will contain issue id numbers retrieved from the google search - number_of_results = ( - 3 # number of results to be retrieved from the google search - ) - print(len(organic_results), "results found with SERP API") - for result in organic_results: - if ( - len(issues_numbers) == number_of_results - ): # break if we have enough results - break - link = result["link"] - number = int(link.split("/")[-1]) - # check if number is integer - if isinstance(number, int): - issues_numbers.append(number) - - # search for issues - - number_of_requests = len(issues_numbers) * 2 # 1 for comments, 1 for issues - remaining_requests = fxns.get_requests_remaining() - print("remaining requests", remaining_requests) - if remaining_requests > number_of_requests: - issues_dict = {} - print("number of issues", len(issues_numbers)) - for number in issues_numbers: - url_comments = f"https://api.github.com/repos/openmm/openmm/issues/{number}/comments" - url_issues = ( - f"https://api.github.com/repos/openmm/openmm/issues/{number}" - ) - response_issues = requests.get(url_issues) - response_comments = requests.get(url_comments) - - if ( - response_issues.status_code == 200 - and response_comments.status_code == 200 - ): - issues = response_issues.json() - issue = issues["title"] - body = issues["body"] - comments = response_comments.json() - body += f"\n\n Comments for issue {number}: \n" - for i, comment in enumerate(comments): - body += f"Answer#{i}:{comment['body']} \n" - if i > 5: # up to 5 comments per issue should be enough, - # some issues have more than 100 comments - break # TODO definitely summarize comments - # if there are more than x amount of comments. - issues_dict[f"{number}"] = [issue, body] - else: - print(f"Error: {response_comments.status_code} for issue {number}") - continue - - # prepare the output - output = "" - for key in issues_dict.keys(): - output += f"Issue {key}: {issues_dict[key][0]} \n" - output += f"Body: {issues_dict[key][1]} \n" - - num_tokens = len(encoding.encode(str(output))) - if num_tokens > 4000: - # summarize output - output = fxns._prompt_summary(query, output) - return "Succeeded. " + output - else: - return ( - "Failed. Not enough requests remaining for Github API. " - "Try again later" - ) - - def _arun(self, query) -> str: - """Use the tool asynchronously.""" - raise NotImplementedError("Name2PDB does not support async") diff --git a/mdagent/tools/base_tools/util_tools/search_tools.py b/mdagent/tools/base_tools/util_tools/search_tools.py index 9d687343..1015d69d 100644 --- a/mdagent/tools/base_tools/util_tools/search_tools.py +++ b/mdagent/tools/base_tools/util_tools/search_tools.py @@ -1,17 +1,30 @@ +import logging import os import re from typing import Optional import langchain +import nest_asyncio import paperqa import paperscraper from langchain.base_language import BaseLanguageModel from langchain.tools import BaseTool +from langchain_core.output_parsers import StrOutputParser from pypdf.errors import PdfReadError from mdagent.utils import PathRegistry +def configure_logging(path): + # to log all runtime errors from paperscraper, which can be VERY noisy + log_file = os.path.join(path, "scraping_errors.log") + logging.basicConfig( + filename=log_file, + level=logging.ERROR, + format="%(asctime)s:%(levelname)s:%(message)s", + ) + + def paper_scraper(search: str, pdir: str = "query") -> dict: try: return paperscraper.search_papers(search, pdir=pdir) @@ -31,10 +44,11 @@ def paper_search(llm, query, path_registry): ) path = f"{path_registry.ckpt_files}/query" - query_chain = langchain.chains.llm.LLMChain(llm=llm, prompt=prompt) + query_chain = prompt | llm | StrOutputParser() if not os.path.isdir(path): os.mkdir(path) - search = query_chain.run(query) + configure_logging(path) + search = query_chain.invoke(query) print("\nSearch:", search) papers = paper_scraper(search, pdir=f"{path}/{re.sub(' ', '', search)}") return papers @@ -43,10 +57,14 @@ def paper_search(llm, query, path_registry): def scholar2result_llm(llm, query, path_registry, k=5, max_sources=2): """Useful to answer questions that require technical knowledge. Ask a specific question.""" + if llm.model_name.startswith("gpt"): + docs = paperqa.Docs(llm=llm.model_name) + else: + docs = paperqa.Docs() # uses default gpt model in paperqa + papers = paper_search(llm, query, path_registry) if len(papers) == 0: return "Failed. Not enough papers found" - docs = paperqa.Docs(llm=llm.model_name) not_loaded = 0 for path, data in papers.items(): try: @@ -77,6 +95,7 @@ def __init__(self, llm, path_registry): self.path_registry = path_registry def _run(self, query) -> str: + nest_asyncio.apply() return scholar2result_llm(self.llm, query, self.path_registry) async def _arun(self, query) -> str: diff --git a/mdagent/tools/maketools.py b/mdagent/tools/maketools.py index 6add628f..d19129ac 100644 --- a/mdagent/tools/maketools.py +++ b/mdagent/tools/maketools.py @@ -1,15 +1,23 @@ -import streamlit as st +import os + +import numpy as np from dotenv import load_dotenv from langchain import agents from langchain.base_language import BaseLanguageModel -from langchain.embeddings.openai import OpenAIEmbeddings -from langchain.vectorstores import Chroma +from langchain_openai import OpenAIEmbeddings +from sklearn.feature_extraction.text import TfidfVectorizer +from sklearn.metrics.pairwise import cosine_similarity from mdagent.utils import PathRegistry from .base_tools import ( CleaningToolFunction, + ComputeAcylindricity, + ComputeAsphericity, + ComputeDSSP, + ComputeGyrationTensor, ComputeLPRMSD, + ComputeRelativeShapeAntisotropy, ComputeRMSD, ComputeRMSF, ContactsTool, @@ -49,6 +57,7 @@ SimulationOutputFigures, SmallMolPDB, SolventAccessibleSurfaceArea, + SummarizeProteinStructure, UniprotID2Name, VisualizeProtein, ) @@ -66,13 +75,20 @@ def make_all_tools( # all_tools += [PythonREPLTool()] all_tools += [ ModifyBaseSimulationScriptTool(path_registry=path_instance, llm=llm), - Scholar2ResultLLM(llm=llm, path_registry=path_instance), ] + if "OPENAI_API_KEY" in os.environ and "PQA_API_KEY" in os.environ: + all_tools += [Scholar2ResultLLM(llm=llm, path_registry=path_instance)] if human: all_tools += [agents.load_tools(["human"], llm)[0]] # add base tools base_tools = [ + SummarizeProteinStructure(path_registry=path_instance), + ComputeAcylindricity(path_registry=path_instance), + ComputeAsphericity(path_registry=path_instance), + ComputeDSSP(path_registry=path_instance), + ComputeGyrationTensor(path_registry=path_instance), + ComputeRelativeShapeAntisotropy(path_registry=path_instance), CleaningToolFunction(path_registry=path_instance), ComputeLPRMSD(path_registry=path_instance), ComputeRMSD(path_registry=path_instance), @@ -120,47 +136,44 @@ def make_all_tools( return all_tools -def get_tools( - query, - llm: BaseLanguageModel, - top_k_tools=15, - human=False, -): - ckpt_dir = PathRegistry.get_instance().ckpt_dir +def get_relevant_tools(query, llm: BaseLanguageModel, top_k_tools=15, human=False): + """ + Get most relevant tools for the query using vector similarity search. + Query and tools are vectorized using either OpenAI embeddings or TF-IDF. + + If an OpenAI API key is available, it uses embeddings for a more + sophisticated search. Otherwise, it falls back to using TF-IDF for + simpler, term-based matching. + + Returns: + - A list of the most relevant tools, or None if no tools are found. + """ all_tools = make_all_tools(llm, human=human) + if not all_tools: + return None + + tool_texts = [f"{tool.name} {tool.description}" for tool in all_tools] - # set vector DB for all tools - vectordb = Chroma( - collection_name="all_tools_vectordb", - embedding_function=OpenAIEmbeddings(), - persist_directory=f"{ckpt_dir}/all_tools_vectordb", - ) - # vectordb.delete_collection() #<--- to clear previous vectordb directory - for i, tool in enumerate(all_tools): - vectordb.add_texts( - texts=[tool.description], - ids=[tool.name], - metadatas=[{"tool_name": tool.name, "index": i}], - ) - vectordb.persist() - - # retrieve 'k' tools - k = min(top_k_tools, vectordb._collection.count()) + # convert texts to vectors + if "OPENAI_API_KEY" in os.environ: + embeddings = OpenAIEmbeddings(model="text-embedding-3-small") + try: + tool_vectors = np.array(embeddings.embed_documents(tool_texts)) + query_vector = np.array(embeddings.embed_query(query)).reshape(1, -1) + except Exception as e: + print(f"Error generating embeddings for tool retrieval: {e}") + return None + else: + vectorizer = TfidfVectorizer() + tool_vectors = vectorizer.fit_transform(tool_texts) + query_vector = vectorizer.transform([query]) + + similarities = cosine_similarity(query_vector, tool_vectors).flatten() + k = min(max(top_k_tools, 1), len(all_tools)) if k == 0: return None - docs = vectordb.similarity_search(query, k=k) - retrieved_tools = [] - for d in docs: - index = d.metadata.get("index") - if index is not None and 0 <= index < len(all_tools): - retrieved_tools.append(all_tools[index]) - else: - print(f"Invalid index {index}.") - print("Some tools may be duplicated.") - print(f"Try to delete vector DB at {ckpt_dir}/all_tools_vectordb.") - st.markdown( - "Invalid index. Some tools may be duplicated Try to delete VDB.", - unsafe_allow_html=True, - ) + top_k_indices = np.argsort(similarities)[-k:][::-1] + retrieved_tools = [all_tools[i] for i in top_k_indices] + return retrieved_tools diff --git a/mdagent/utils/data_handling.py b/mdagent/utils/data_handling.py index 4fab9fdf..4a9dc4f7 100644 --- a/mdagent/utils/data_handling.py +++ b/mdagent/utils/data_handling.py @@ -10,7 +10,7 @@ def load_single_traj( path_registry, - top_fileid, + top_fileid=None, traj_fileid=None, traj_required=False, ignore_warnings=False, @@ -20,7 +20,7 @@ def load_single_traj( Parameters: path_registry (PathRegistry): mapping file IDs to file paths. - top_fileid (str): File ID for the topology file. + top_fileid (str, optional): File ID for the topology file. traj_fileid (str, optional): File ID for the trajectory file. traj_required (bool, optional): Whether the traj file is required. Default is False. @@ -30,9 +30,18 @@ def load_single_traj( if not isinstance(path_registry, PathRegistry): raise ValueError("path_registry must be an instance of PathRegistry.") all_fileids = path_registry.list_path_names() - if top_fileid not in all_fileids: - raise ValueError(f"Topology File ID '{top_fileid}' not found in PathRegistry") - top_path = path_registry.get_mapped_path(top_fileid) + + if top_fileid is None: + # check for traj_fileid + if traj_fileid is None: + raise ValueError("Trajectory File ID is required, and it's not provided.") + else: + if top_fileid not in all_fileids: + raise ValueError( + f"Topology File ID '{top_fileid}' not found in PathRegistry" + ) + else: + top_path = path_registry.get_mapped_path(top_fileid) if traj_fileid is None: if not traj_required: @@ -48,12 +57,17 @@ def load_single_traj( return md.load(top_path) else: raise ValueError("Trajectory File ID is required, and it's not provided.") - - if traj_fileid not in all_fileids: - raise ValueError( - f"Trajectory File ID '{traj_fileid}' not found in PathRegistry." - ) - traj_path = path_registry.get_mapped_path(traj_fileid) + else: + if traj_fileid not in all_fileids: + raise ValueError( + f"Trajectory File ID '{traj_fileid}' not found in PathRegistry." + ) + else: + traj_path = path_registry.get_mapped_path(traj_fileid) + if top_fileid is None: + return md.load(traj_path) + elif traj_fileid is None: + return md.load(top_path) return md.load(traj_path, top=top_path) diff --git a/mdagent/utils/makellm.py b/mdagent/utils/makellm.py index 82bd4803..d9f0b70f 100644 --- a/mdagent/utils/makellm.py +++ b/mdagent/utils/makellm.py @@ -1,23 +1,59 @@ -import langchain +import importlib.util + from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler -def _make_llm(model, temp, verbose): +def check_package_exists(package_name, model): + if not importlib.util.find_spec(package_name): + raise ImportError( + f"The package required to run model '{model}' is missing: '{package_name}'." + ) + + +def _make_llm(model, temp, streaming): if model.startswith("gpt-3.5-turbo") or model.startswith("gpt-4"): - llm = langchain.chat_models.ChatOpenAI( + from langchain_openai import ChatOpenAI + + llm = ChatOpenAI( temperature=temp, model_name=model, request_timeout=1000, - streaming=True if verbose else False, - callbacks=[StreamingStdOutCallbackHandler()] if verbose else None, + streaming=streaming, + callbacks=[StreamingStdOutCallbackHandler()] if streaming else None, ) - elif model.startswith("text-"): - llm = langchain.OpenAI( + elif model.startswith("accounts/fireworks"): + check_package_exists("langchain_fireworks", model) + from langchain_fireworks import ChatFireworks + + llm = ChatFireworks( + temperature=temp, + model_name=model, + request_timeout=1000, + streaming=streaming, + callbacks=[StreamingStdOutCallbackHandler()] if streaming else None, + ) + elif model.startswith("together/"): + # user needs to add 'together/' prefix to use TogetherAI provider + check_package_exists("langchain_together", model) + from langchain_together import ChatTogether + + llm = ChatTogether( + temperature=temp, + model=model.replace("together/", ""), + request_timeout=1000, + streaming=streaming, + callbacks=[StreamingStdOutCallbackHandler()] if streaming else None, + ) + elif model.startswith("claude"): + check_package_exists("langchain_anthropic", model) + from langchain_anthropic import ChatAnthropic + + llm = ChatAnthropic( temperature=temp, model_name=model, - streaming=True if verbose else False, - callbacks=[StreamingStdOutCallbackHandler()] if verbose else None, + streaming=streaming, + callbacks=[StreamingStdOutCallbackHandler()] if streaming else None, ) else: - raise ValueError(f"Invalid model name: {model}") + raise ValueError(f"Unrecognized or unsupported model name: {model}") return llm diff --git a/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181241.json b/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181241.json deleted file mode 100644 index 79e61998..00000000 --- a/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181241.json +++ /dev/null @@ -1,69 +0,0 @@ -{ - "agent_settings": { - "llm": "gpt-4-1106-preview", - "agent_type": "Structured", - "tools_llm": "gpt-4-1106-preview", - "subagents_llm": "gpt-4-1106-preview", - "resume": false, - "learn": false, - "curriculum": true - }, - "user_prompt": "Download and clean 1A3N.", - "prompt_success": true, - "total_steps": 3, - "failed_steps": 0, - "total_time_seconds": "42.115", - "total_time_minutes": "0.702", - "final_answer": "The fibronectin PDB file has been successfully downloaded and cleaned. It is now ready for further analysis or simulation steps.", - "tools_used": { - "PDBFileDownloader": 1, - "CleaningToolFunction": 2 - }, - "num_skills_before": 0, - "num_skills_after": 0, - "tools_details": { - "Step 1": { - "tool": "PDBFileDownloader", - "tool_input": { - "query": "fibronectin" - }, - "observation": "Succeeded. Downloaded the PDB file:5TFY_181207", - "status_complete": true, - "step_elapsed_time (sec)": "7.614", - "timestamp_from_start (sec)": "7.614" - }, - "Step 2": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'", - "status_complete": false, - "step_elapsed_time (sec)": "9.472", - "timestamp_from_start (sec)": "17.086" - }, - "Step 3": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY_181207", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Succeeded. File cleaned!\nFile ID:{file_id}\nPath:{directory}/{file_name}", - "status_complete": true, - "step_elapsed_time (sec)": "19.394", - "timestamp_from_start (sec)": "36.481" - } - }, - "run_id": "31fef58f-1863-4a7e-b694-71d129cb8bfa" -} diff --git a/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181533.json b/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181533.json deleted file mode 100644 index 9e11a6d8..00000000 --- a/notebooks/eval_demo/ckpt_eval/individual_eval_20240422-181533.json +++ /dev/null @@ -1,69 +0,0 @@ -{ - "agent_settings": { - "llm": "gpt-4-1106-preview", - "agent_type": "Structured", - "tools_llm": "gpt-4-1106-preview", - "subagents_llm": "gpt-4-1106-preview", - "resume": false, - "learn": false, - "curriculum": true - }, - "user_prompt": "Download and clean 1A3N.", - "prompt_success": true, - "total_steps": 3, - "failed_steps": 0, - "total_time_seconds": "40.278", - "total_time_minutes": "0.671", - "final_answer": "The fibronectin PDB file has been successfully downloaded and cleaned. The file is ready for further use.", - "tools_used": { - "PDBFileDownloader": 1, - "CleaningToolFunction": 2 - }, - "num_skills_before": 0, - "num_skills_after": 0, - "tools_details": { - "Step 1": { - "tool": "PDBFileDownloader", - "tool_input": { - "query": "fibronectin" - }, - "observation": "Succeeded. Downloaded the PDB file:5TFY_181459", - "status_complete": true, - "step_elapsed_time (sec)": "5.994", - "timestamp_from_start (sec)": "5.994" - }, - "Step 2": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'", - "status_complete": false, - "step_elapsed_time (sec)": "11.529", - "timestamp_from_start (sec)": "17.522" - }, - "Step 3": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY_181459", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Succeeded. File cleaned!\nFile ID:{file_id}\nPath:{directory}/{file_name}", - "status_complete": true, - "step_elapsed_time (sec)": "16.831", - "timestamp_from_start (sec)": "34.353" - } - }, - "run_id": "866c3c27-c5ff-4e21-bf5a-3bd02672f399" -} diff --git a/notebooks/eval_demo/eval_demo.ipynb b/notebooks/eval_demo/eval_demo.ipynb deleted file mode 100644 index b69b8876..00000000 --- a/notebooks/eval_demo/eval_demo.ipynb +++ /dev/null @@ -1,951 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# this is slightly old - the latest evaluator now has memory info and correct run_id" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Evaluating prompt: Download and clean fibronectin.\n", - "Thought: The user's main task is to download and clean the fibronectin protein structure. The first subtask is to download the fibronectin PDB file. I will use the PDBFileDownloader tool to download the PDB file for fibronectin.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"fibronectin\"\n", - " }\n", - "}\n", - "```" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-22 18:11:21.984 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "PDB file found with this ID: 5TFY\n", - "No names found. The JSON file is empty or does not contain name mappings.\n", - "The next subtask is to clean and preprocess the downloaded fibronectin PDB file. This typically involves removing heterogens, adding missing atoms and hydrogens, replacing nonstandard residues, and/or removing water. I will use the CleaningToolFunction to perform these tasks on the downloaded PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: Name not found in path registry.\n", - "The previous attempt to clean the fibronectin PDB file failed because the file was not found in the path registry. It seems there was a misunderstanding with the PDB ID used in the CleaningToolFunction. The PDB ID should be the one that was downloaded, which is '5TFY_181122'. I will correct the PDB ID and attempt to clean the file again using the CleaningToolFunction.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY_181122\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: /Users/quinny/repos/md-agent_eval/ckpt/ckpt_9/pdb/5TFY_raw_20240422_181122.pdb\n", - "Names found in registry: 5TFY_181122\n", - "The fibronectin PDB file has been successfully downloaded and cleaned. The next steps in the user's initial plan are not specified, but typically after cleaning, the file would be prepared for molecular dynamics simulation. This could include setting up the simulation environment, selecting a force field, and solvating the protein if necessary. However, without further instructions from the user, I cannot proceed with these steps.\n", - "\n", - "Since the main task and the subtasks outlined by the user have been completed, I will provide the final answer with the details of the cleaned PDB file for fibronectin.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The fibronectin PDB file has been successfully downloaded and cleaned. The cleaned file is available and can be used for further molecular dynamics simulation steps.\"\n", - "}\n", - "```\n", - "----- Evaluation Summary -----\n", - "Run ID: 670ff44b-48a1-41ea-aaa8-30bf701a34dd\n", - "Total Steps: 4\n", - "Total Time: 49.63 seconds (0.83 minutes)\n", - "Evaluating prompt: Download and clean 1A3N.\n", - "Thought: The user's main task is to download and clean the fibronectin protein structure. The first subtask is to download the fibronectin PDB file. I will use the PDBFileDownloader tool to download the PDB file for fibronectin.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"fibronectin\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 5TFY\n", - "Names found in registry: 5TFY_181122, 5TFY_181149\n", - "The PDB file for fibronectin has been successfully downloaded. The next subtask is to clean and preprocess the fibronectin PDB file. This involves removing heterogens, adding missing atoms and hydrogens, replacing nonstandard residues, and removing water if necessary. I will use the CleaningToolFunction to perform these tasks on the downloaded PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: Name not found in path registry.\n", - "The attempt to clean the fibronectin PDB file failed because the file was not found in the path registry. This could be due to an incorrect PDB ID or an issue with the file path. Since the PDB file was successfully downloaded with the ID \"5TFY_181207\", I need to use the correct ID that includes the date suffix to ensure the file is found in the path registry. I will retry the CleaningToolFunction with the full PDB ID including the date suffix.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY_181207\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: /Users/quinny/repos/md-agent_eval/ckpt/ckpt_9/pdb/5TFY_raw_20240422_181207.pdb\n", - "Names found in registry: 5TFY_181122, 5TFY_181149, 5TFY_181207\n", - "The fibronectin PDB file has been successfully cleaned and preprocessed. This completes the subtasks outlined in the user's initial plan. The cleaned PDB file is now ready for further molecular dynamics simulations or analysis as required by the user.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The fibronectin PDB file has been successfully downloaded and cleaned. It is now ready for further analysis or simulation steps.\"\n", - "}\n", - "```\n", - "----- Evaluation Summary -----\n", - "Run ID: 31fef58f-1863-4a7e-b694-71d129cb8bfa\n", - "Total Steps: 4\n", - "Total Time: 42.12 seconds (0.70 minutes)\n", - "All evaluations saved to evaluation_results/mega_eval_20240422-181241.json.\n" - ] - } - ], - "source": [ - "from mdagent import Evaluator\n", - "\n", - "evaluator = Evaluator(eval_dir=\"evaluation_results\") # that's the default - change base_dir if desired\n", - "\n", - "# to do it manually\n", - "agent_params = {\n", - " \"agent_type\": \"Structured\",\n", - " \"learn\": False,\n", - " 'model': 'gpt-3.5-turbo',\n", - " 'tools_model': 'gpt-3.5-turbo',\n", - "}\n", - "prompts = [\n", - " 'Download and clean fibronectin.',\n", - " 'Download and clean 1A3N.',\n", - "]\n", - "evaluator.run_and_evaluate(prompts, agent_params=agent_params)\n", - "evaluator.save()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[{'agent_settings': {'llm': 'gpt-4-1106-preview',\n", - " 'agent_type': 'Structured',\n", - " 'tools_llm': 'gpt-4-1106-preview',\n", - " 'subagents_llm': 'gpt-4-1106-preview',\n", - " 'resume': False,\n", - " 'learn': False,\n", - " 'curriculum': True},\n", - " 'user_prompt': 'Download and clean fibronectin.',\n", - " 'prompt_success': True,\n", - " 'total_steps': 3,\n", - " 'failed_steps': 0,\n", - " 'total_time_seconds': '49.630',\n", - " 'total_time_minutes': '0.827',\n", - " 'final_answer': 'The fibronectin PDB file has been successfully downloaded and cleaned. The cleaned file is available and can be used for further molecular dynamics simulation steps.',\n", - " 'tools_used': {'PDBFileDownloader': 1, 'CleaningToolFunction': 2},\n", - " 'num_skills_before': 0,\n", - " 'num_skills_after': 0,\n", - " 'tools_details': {'Step 1': {'tool': 'PDBFileDownloader',\n", - " 'tool_input': {'query': 'fibronectin'},\n", - " 'observation': 'Succeeded. Downloaded the PDB file:5TFY_181122',\n", - " 'status_complete': True,\n", - " 'step_elapsed_time (sec)': '12.319',\n", - " 'timestamp_from_start (sec)': '12.319'},\n", - " 'Step 2': {'tool': 'CleaningToolFunction',\n", - " 'tool_input': {'pdb_id': '5TFY',\n", - " 'replace_nonstandard_residues': True,\n", - " 'add_missing_atoms': True,\n", - " 'remove_heterogens': True,\n", - " 'remove_water': True,\n", - " 'add_hydrogens': True,\n", - " 'add_hydrogens_ph': 7.0},\n", - " 'observation': \"Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'\",\n", - " 'status_complete': False,\n", - " 'step_elapsed_time (sec)': '10.498',\n", - " 'timestamp_from_start (sec)': '22.817'},\n", - " 'Step 3': {'tool': 'CleaningToolFunction',\n", - " 'tool_input': {'pdb_id': '5TFY_181122',\n", - " 'replace_nonstandard_residues': True,\n", - " 'add_missing_atoms': True,\n", - " 'remove_heterogens': True,\n", - " 'remove_water': True,\n", - " 'add_hydrogens': True,\n", - " 'add_hydrogens_ph': 7.0},\n", - " 'observation': 'Succeeded. File cleaned!\\nFile ID:{file_id}\\nPath:{directory}/{file_name}',\n", - " 'status_complete': True,\n", - " 'step_elapsed_time (sec)': '17.433',\n", - " 'timestamp_from_start (sec)': '40.250'}},\n", - " 'run_id': '670ff44b-48a1-41ea-aaa8-30bf701a34dd',\n", - " 'execution_success': True},\n", - " {'agent_settings': {'llm': 'gpt-4-1106-preview',\n", - " 'agent_type': 'Structured',\n", - " 'tools_llm': 'gpt-4-1106-preview',\n", - " 'subagents_llm': 'gpt-4-1106-preview',\n", - " 'resume': False,\n", - " 'learn': False,\n", - " 'curriculum': True},\n", - " 'user_prompt': 'Download and clean 1A3N.',\n", - " 'prompt_success': True,\n", - " 'total_steps': 3,\n", - " 'failed_steps': 0,\n", - " 'total_time_seconds': '42.115',\n", - " 'total_time_minutes': '0.702',\n", - " 'final_answer': 'The fibronectin PDB file has been successfully downloaded and cleaned. It is now ready for further analysis or simulation steps.',\n", - " 'tools_used': {'PDBFileDownloader': 1, 'CleaningToolFunction': 2},\n", - " 'num_skills_before': 0,\n", - " 'num_skills_after': 0,\n", - " 'tools_details': {'Step 1': {'tool': 'PDBFileDownloader',\n", - " 'tool_input': {'query': 'fibronectin'},\n", - " 'observation': 'Succeeded. Downloaded the PDB file:5TFY_181207',\n", - " 'status_complete': True,\n", - " 'step_elapsed_time (sec)': '7.614',\n", - " 'timestamp_from_start (sec)': '7.614'},\n", - " 'Step 2': {'tool': 'CleaningToolFunction',\n", - " 'tool_input': {'pdb_id': '5TFY',\n", - " 'replace_nonstandard_residues': True,\n", - " 'add_missing_atoms': True,\n", - " 'remove_heterogens': True,\n", - " 'remove_water': True,\n", - " 'add_hydrogens': True,\n", - " 'add_hydrogens_ph': 7.0},\n", - " 'observation': \"Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'\",\n", - " 'status_complete': False,\n", - " 'step_elapsed_time (sec)': '9.472',\n", - " 'timestamp_from_start (sec)': '17.086'},\n", - " 'Step 3': {'tool': 'CleaningToolFunction',\n", - " 'tool_input': {'pdb_id': '5TFY_181207',\n", - " 'replace_nonstandard_residues': True,\n", - " 'add_missing_atoms': True,\n", - " 'remove_heterogens': True,\n", - " 'remove_water': True,\n", - " 'add_hydrogens': True,\n", - " 'add_hydrogens_ph': 7.0},\n", - " 'observation': 'Succeeded. File cleaned!\\nFile ID:{file_id}\\nPath:{directory}/{file_name}',\n", - " 'status_complete': True,\n", - " 'step_elapsed_time (sec)': '19.394',\n", - " 'timestamp_from_start (sec)': '36.481'}},\n", - " 'run_id': '31fef58f-1863-4a7e-b694-71d129cb8bfa',\n", - " 'execution_success': True}]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "evaluator.evaluations" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "evaluator.reset() # clear evaluations" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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LLMAgent TypeUser PromptPrompt SuccessExecution SuccessError MessageTotal StepsFailed StepsTime (s)Time (min)
0gpt-4-1106-previewStructuredNoneTrueTrueNone3049.6300.827
1gpt-4-1106-previewStructuredNoneTrueTrueNone3042.1150.702
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" - ], - "text/plain": [ - " LLM Agent Type User Prompt Prompt Success \\\n", - "0 gpt-4-1106-preview Structured None True \n", - "1 gpt-4-1106-preview Structured None True \n", - "\n", - " Execution Success Error Message Total Steps Failed Steps Time (s) \\\n", - "0 True None 3 0 49.630 \n", - "1 True None 3 0 42.115 \n", - "\n", - " Time (min) \n", - "0 0.827 \n", - "1 0.702 " - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# you can load it later and create a table\n", - "from mdagent import Evaluator\n", - "\n", - "evaluator = Evaluator()\n", - "evaluator.load('evaluation_results/mega_eval_20240422-181241.json')\n", - "df = evaluator.create_table(simple=True) # this is default\n", - "\n", - "df.to_latex('evaluation_results/eval_table.tex', index=False) # you can create latex tables\n", - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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agent_settings_llmagent_settings_agent_typeagent_settings_tools_llmagent_settings_subagents_llmagent_settings_resumeagent_settings_learnagent_settings_curriculumuser_promptprompt_successtotal_stepsfailed_stepstotal_time_secondstotal_time_minutesfinal_answertools_used_PDBFileDownloadertools_used_CleaningToolFunctionnum_skills_beforenum_skills_aftertools_details_Step 1_tooltools_details_Step 1_tool_inputtools_details_Step 1_observationtools_details_Step 1_status_completetools_details_Step 1_step_elapsed_time (sec)tools_details_Step 1_timestamp_from_start (sec)tools_details_Step 2_tooltools_details_Step 2_tool_inputtools_details_Step 2_observationtools_details_Step 2_status_completetools_details_Step 2_step_elapsed_time (sec)tools_details_Step 2_timestamp_from_start (sec)tools_details_Step 3_tooltools_details_Step 3_tool_inputtools_details_Step 3_observationtools_details_Step 3_status_completetools_details_Step 3_step_elapsed_time (sec)tools_details_Step 3_timestamp_from_start (sec)run_idexecution_success
0gpt-4-1106-previewStructuredgpt-4-1106-previewgpt-4-1106-previewFalseFalseTrueDownload and clean fibronectin.True3049.6300.827The fibronectin PDB file has been successfully...1200PDBFileDownloader{'query': 'fibronectin'}Succeeded. Downloaded the PDB file:5TFY_181122True12.31912.319CleaningToolFunction{'pdb_id': '5TFY', 'replace_nonstandard_residu...Failed. Check your file path. File not found: ...False10.49822.817CleaningToolFunction{'pdb_id': '5TFY_181122', 'replace_nonstandard...Succeeded. File cleaned!\\nFile ID:{file_id}\\nP...True17.43340.250670ff44b-48a1-41ea-aaa8-30bf701a34ddTrue
1gpt-4-1106-previewStructuredgpt-4-1106-previewgpt-4-1106-previewFalseFalseTrueDownload and clean 1A3N.True3042.1150.702The fibronectin PDB file has been successfully...1200PDBFileDownloader{'query': 'fibronectin'}Succeeded. Downloaded the PDB file:5TFY_181207True7.6147.614CleaningToolFunction{'pdb_id': '5TFY', 'replace_nonstandard_residu...Failed. Check your file path. File not found: ...False9.47217.086CleaningToolFunction{'pdb_id': '5TFY_181207', 'replace_nonstandard...Succeeded. File cleaned!\\nFile ID:{file_id}\\nP...True19.39436.48131fef58f-1863-4a7e-b694-71d129cb8bfaTrue
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" - ], - "text/plain": [ - " agent_settings_llm agent_settings_agent_type agent_settings_tools_llm \\\n", - "0 gpt-4-1106-preview Structured gpt-4-1106-preview \n", - "1 gpt-4-1106-preview Structured gpt-4-1106-preview \n", - "\n", - " agent_settings_subagents_llm agent_settings_resume agent_settings_learn \\\n", - "0 gpt-4-1106-preview False False \n", - "1 gpt-4-1106-preview False False \n", - "\n", - " agent_settings_curriculum user_prompt prompt_success \\\n", - "0 True Download and clean fibronectin. True \n", - "1 True Download and clean 1A3N. True \n", - "\n", - " total_steps failed_steps total_time_seconds total_time_minutes \\\n", - "0 3 0 49.630 0.827 \n", - "1 3 0 42.115 0.702 \n", - "\n", - " final_answer \\\n", - "0 The fibronectin PDB file has been successfully... \n", - "1 The fibronectin PDB file has been successfully... \n", - "\n", - " tools_used_PDBFileDownloader tools_used_CleaningToolFunction \\\n", - "0 1 2 \n", - "1 1 2 \n", - "\n", - " num_skills_before num_skills_after tools_details_Step 1_tool \\\n", - "0 0 0 PDBFileDownloader \n", - "1 0 0 PDBFileDownloader \n", - "\n", - " tools_details_Step 1_tool_input \\\n", - "0 {'query': 'fibronectin'} \n", - "1 {'query': 'fibronectin'} \n", - "\n", - " tools_details_Step 1_observation \\\n", - "0 Succeeded. Downloaded the PDB file:5TFY_181122 \n", - "1 Succeeded. Downloaded the PDB file:5TFY_181207 \n", - "\n", - " tools_details_Step 1_status_complete \\\n", - "0 True \n", - "1 True \n", - "\n", - " tools_details_Step 1_step_elapsed_time (sec) \\\n", - "0 12.319 \n", - "1 7.614 \n", - "\n", - " tools_details_Step 1_timestamp_from_start (sec) tools_details_Step 2_tool \\\n", - "0 12.319 CleaningToolFunction \n", - "1 7.614 CleaningToolFunction \n", - "\n", - " tools_details_Step 2_tool_input \\\n", - "0 {'pdb_id': '5TFY', 'replace_nonstandard_residu... \n", - "1 {'pdb_id': '5TFY', 'replace_nonstandard_residu... \n", - "\n", - " tools_details_Step 2_observation \\\n", - "0 Failed. Check your file path. File not found: ... \n", - "1 Failed. Check your file path. File not found: ... \n", - "\n", - " tools_details_Step 2_status_complete \\\n", - "0 False \n", - "1 False \n", - "\n", - " tools_details_Step 2_step_elapsed_time (sec) \\\n", - "0 10.498 \n", - "1 9.472 \n", - "\n", - " tools_details_Step 2_timestamp_from_start (sec) tools_details_Step 3_tool \\\n", - "0 22.817 CleaningToolFunction \n", - "1 17.086 CleaningToolFunction \n", - "\n", - " tools_details_Step 3_tool_input \\\n", - "0 {'pdb_id': '5TFY_181122', 'replace_nonstandard... \n", - "1 {'pdb_id': '5TFY_181207', 'replace_nonstandard... \n", - "\n", - " tools_details_Step 3_observation \\\n", - "0 Succeeded. File cleaned!\\nFile ID:{file_id}\\nP... \n", - "1 Succeeded. File cleaned!\\nFile ID:{file_id}\\nP... \n", - "\n", - " tools_details_Step 3_status_complete \\\n", - "0 True \n", - "1 True \n", - "\n", - " tools_details_Step 3_step_elapsed_time (sec) \\\n", - "0 17.433 \n", - "1 19.394 \n", - "\n", - " tools_details_Step 3_timestamp_from_start (sec) \\\n", - "0 40.250 \n", - "1 36.481 \n", - "\n", - " run_id execution_success \n", - "0 670ff44b-48a1-41ea-aaa8-30bf701a34dd True \n", - "1 31fef58f-1863-4a7e-b694-71d129cb8bfa True " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "df_full = evaluator.create_table(simple=False) # get all info\n", - "\n", - "# show all columns (it'll be very long rows!)\n", - "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n", - " display(df_full)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Evaluating prompt: Download and clean fibronectin.\n", - "Thought: The user's main task is to download and clean the fibronectin protein structure. The first subtask is to download the fibronectin PDB file. I will use the PDBFileDownloader tool to download the PDB file for fibronectin.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"fibronectin\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 5TFY\n", - "No names found. The JSON file is empty or does not contain name mappings.\n", - "The next subtask is to clean and preprocess the downloaded fibronectin PDB file. This typically involves removing heterogens, adding missing atoms and hydrogens, replacing nonstandard residues, and/or removing water. I will use the CleaningToolFunction to perform these tasks on the downloaded PDB file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: Name not found in path registry.\n", - "The previous attempt to clean the PDB file failed because the file was not found in the path registry. This could be due to an incorrect PDB ID or a problem with the file path. Since the PDB ID '5TFY' was successfully downloaded, I will attempt to clean the file again, ensuring that the PDB ID is correctly specified.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY_181417\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: /Users/quinny/repos/md-agent_eval/ckpt/ckpt_10/pdb/5TFY_raw_20240422_181417.pdb\n", - "Names found in registry: 5TFY_181417\n", - "The fibronectin PDB file has been successfully downloaded and cleaned. The main task and subtasks requested by the user have been completed. The cleaned file is now ready for further processing or simulation as per the user's requirements.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The fibronectin PDB file has been successfully downloaded and cleaned. The cleaned file is ready for further use.\"\n", - "}\n", - "```\n", - "----- Evaluation Summary -----\n", - "Run ID: 943a58af-f062-4ab3-a55d-bf571b584d25\n", - "Total Steps: 4\n", - "Total Time: 45.95 seconds (0.77 minutes)\n", - "Evaluating prompt: Download and clean 1A3N.\n", - "Thought: The user's main task is to download and clean the fibronectin protein structure. The first subtask is to download the fibronectin PDB file. I will use the PDBFileDownloader tool to download the PDB file for fibronectin.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"fibronectin\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 5TFY\n", - "Names found in registry: 5TFY_181417, 5TFY_181445\n", - "The next subtask is to clean and preprocess the downloaded fibronectin PDB file. This involves removing heterogens, adding missing atoms and hydrogens, replacing nonstandard residues, and removing water if necessary. I will use the CleaningToolFunction to perform these tasks on the downloaded PDB file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: Name not found in path registry.\n", - "The previous attempt to clean the fibronectin PDB file failed because the file was not found in the path registry. It seems there was a misunderstanding in the PDB ID used. The PDB ID should be the one returned by the PDBFileDownloader tool, which was \"5TFY_181459\". I will correct the PDB ID and attempt to clean the file again using the CleaningToolFunction.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"5TFY_181459\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```file path: /Users/quinny/repos/md-agent_eval/ckpt/ckpt_10/pdb/5TFY_raw_20240422_181459.pdb\n", - "Names found in registry: 5TFY_181417, 5TFY_181445, 5TFY_181459\n", - "The fibronectin PDB file has been successfully downloaded and cleaned. The main task and subtasks requested by the user have been completed. The cleaned file is now ready for further processing or simulation as per the user's requirements.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The fibronectin PDB file has been successfully downloaded and cleaned. The file is ready for further use.\"\n", - "}\n", - "```\n", - "----- Evaluation Summary -----\n", - "Run ID: 866c3c27-c5ff-4e21-bf5a-3bd02672f399\n", - "Total Steps: 4\n", - "Total Time: 40.28 seconds (0.67 minutes)\n", - "All evaluations saved to evaluation_results/mega_eval_20240422-181533.json.\n" - ] - } - ], - "source": [ - "# you can use \"automate\" to automate the process of running, saving, and creating the simple table\n", - "\n", - "evaluator.reset() # empty the evaluation info\n", - "df2 = evaluator.automate(prompts, agent_params=agent_params)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "df2" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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LLMAgent TypeUser PromptPrompt SuccessExecution SuccessError MessageTotal StepsFailed StepsTime (s)Time (min)
0gpt-4-1106-previewStructuredDownload and clean fibronectin.NoneFalseTypeError: Object of type ChatOpenAI is not JS...NoneNoneNoneNone
1gpt-4-1106-previewStructuredDownload and clean 1A3N.NoneFalseTypeError: Object of type ChatOpenAI is not JS...NoneNoneNoneNone
\n", - "
" - ], - "text/plain": [ - " LLM Agent Type User Prompt \\\n", - "0 gpt-4-1106-preview Structured Download and clean fibronectin. \n", - "1 gpt-4-1106-preview Structured Download and clean 1A3N. \n", - "\n", - " Prompt Success Execution Success \\\n", - "0 None False \n", - "1 None False \n", - "\n", - " Error Message Total Steps Failed Steps \\\n", - "0 TypeError: Object of type ChatOpenAI is not JS... None None \n", - "1 TypeError: Object of type ChatOpenAI is not JS... None None \n", - "\n", - " Time (s) Time (min) \n", - "0 None None \n", - "1 None None " - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df2 # old results to show it can capture when MD-Agent throws exception errors" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/eval_demo/evaluation_results/eval_table.tex b/notebooks/eval_demo/evaluation_results/eval_table.tex deleted file mode 100644 index 77926c40..00000000 --- a/notebooks/eval_demo/evaluation_results/eval_table.tex +++ /dev/null @@ -1,8 +0,0 @@ -\begin{tabular}{lllrrlrrll} -\toprule -LLM & Agent Type & User Prompt & Prompt Success & Execution Success & Error Message & Total Steps & Failed Steps & Time (s) & Time (min) \\ -\midrule -gpt-4-1106-preview & Structured & NaN & True & True & NaN & 3 & 0 & 49.630 & 0.827 \\ -gpt-4-1106-preview & Structured & NaN & True & True & NaN & 3 & 0 & 42.115 & 0.702 \\ -\bottomrule -\end{tabular} diff --git a/notebooks/eval_demo/evaluation_results/mega_eval_20240422-181533.json b/notebooks/eval_demo/evaluation_results/mega_eval_20240422-181533.json deleted file mode 100644 index 1c30ec72..00000000 --- a/notebooks/eval_demo/evaluation_results/mega_eval_20240422-181533.json +++ /dev/null @@ -1,142 +0,0 @@ -[ - { - "agent_settings": { - "llm": "gpt-4-1106-preview", - "agent_type": "Structured", - "tools_llm": "gpt-4-1106-preview", - "subagents_llm": "gpt-4-1106-preview", - "resume": false, - "learn": false, - "curriculum": true - }, - "user_prompt": "Download and clean fibronectin.", - "prompt_success": true, - "total_steps": 3, - "failed_steps": 0, - "total_time_seconds": "45.945", - "total_time_minutes": "0.766", - "final_answer": "The fibronectin PDB file has been successfully downloaded and cleaned. The cleaned file is ready for further use.", - "tools_used": { - "PDBFileDownloader": 1, - "CleaningToolFunction": 2 - }, - "num_skills_before": 0, - "num_skills_after": 0, - "tools_details": { - "Step 1": { - "tool": "PDBFileDownloader", - "tool_input": { - "query": "fibronectin" - }, - "observation": "Succeeded. Downloaded the PDB file:5TFY_181417", - "status_complete": true, - "step_elapsed_time (sec)": "10.064", - "timestamp_from_start (sec)": "10.064" - }, - "Step 2": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'", - "status_complete": false, - "step_elapsed_time (sec)": "11.307", - "timestamp_from_start (sec)": "21.371" - }, - "Step 3": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY_181417", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Succeeded. File cleaned!\nFile ID:{file_id}\nPath:{directory}/{file_name}", - "status_complete": true, - "step_elapsed_time (sec)": "17.757", - "timestamp_from_start (sec)": "39.128" - } - }, - "run_id": "943a58af-f062-4ab3-a55d-bf571b584d25", - "execution_success": true - }, - { - "agent_settings": { - "llm": "gpt-4-1106-preview", - "agent_type": "Structured", - "tools_llm": "gpt-4-1106-preview", - "subagents_llm": "gpt-4-1106-preview", - "resume": false, - "learn": false, - "curriculum": true - }, - "user_prompt": "Download and clean 1A3N.", - "prompt_success": true, - "total_steps": 3, - "failed_steps": 0, - "total_time_seconds": "40.278", - "total_time_minutes": "0.671", - "final_answer": "The fibronectin PDB file has been successfully downloaded and cleaned. The file is ready for further use.", - "tools_used": { - "PDBFileDownloader": 1, - "CleaningToolFunction": 2 - }, - "num_skills_before": 0, - "num_skills_after": 0, - "tools_details": { - "Step 1": { - "tool": "PDBFileDownloader", - "tool_input": { - "query": "fibronectin" - }, - "observation": "Succeeded. Downloaded the PDB file:5TFY_181459", - "status_complete": true, - "step_elapsed_time (sec)": "5.994", - "timestamp_from_start (sec)": "5.994" - }, - "Step 2": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Failed. Check your file path. File not found: [Errno 2] No such file or directory: 'Name not found in path registry.'", - "status_complete": false, - "step_elapsed_time (sec)": "11.529", - "timestamp_from_start (sec)": "17.522" - }, - "Step 3": { - "tool": "CleaningToolFunction", - "tool_input": { - "pdb_id": "5TFY_181459", - "replace_nonstandard_residues": true, - "add_missing_atoms": true, - "remove_heterogens": true, - "remove_water": true, - "add_hydrogens": true, - "add_hydrogens_ph": 7.0 - }, - "observation": "Succeeded. File cleaned!\nFile ID:{file_id}\nPath:{directory}/{file_name}", - "status_complete": true, - "step_elapsed_time (sec)": "16.831", - "timestamp_from_start (sec)": "34.353" - } - }, - "run_id": "866c3c27-c5ff-4e21-bf5a-3bd02672f399", - "execution_success": true - } -] diff --git a/notebooks/experiments/prompts.md b/notebooks/experiments/prompts.md new file mode 100644 index 00000000..b0185ac8 --- /dev/null +++ b/notebooks/experiments/prompts.md @@ -0,0 +1,25 @@ +Simulate pdb 1MBN at two different temperatures: 300K, 400K for 1ns seconds each. Plot RMSD of both over time, and compare the final secondary structures at the end of the simulations. +Download the pdb file for PDB ID 1LYZ. +Download the PDB file for PDB ID 1GZX. Then, analyze the secondary structure of the protein and tell me how many chains, sheets, etc. there are. +What are common parameters to simulate fibronectin? +Simulate 1XQ8 for 1ns at temperate 300K. Then tell me if the secondary structure changed from before the simulation to after. +Simulate 1A3N and 7VDE, two PDB IDs for hemoglobin with the same parameters. Find the appropriate parameters from literature. Then, plot the radius of gyration throughout the both simulations. +Simulate 1ZNI for 1ns at temp=300K. +Simulate 4RMB at 100K, 200K, and 300K. Then plot the radius of gyration over time for all three simulations. Lastly, compare the change in secondary structure for the three analyses throughout the simulation. +What are the known interractions of protein 1BDG? +Download the PDB file for 1AEE. Then, tell me how many chains and atoms are in the protein. +Simulate protein 1ZNI at 300K for 1ns and calculate RMSD. +Download the PDB files for 8PFK and 8PFQ. Then, compare the secondary structure of the two proteins, including number atoms, secondary structure, number of chains, etc. +Simulate fibronectin (PDB ID 1FNF) for 1ns. Use an appropriate temperature from literature. +Compare the RMSF of 1UBQ at high pressure and low pressure. Perform the simulation for 1 ns and vary only the pressure. +Simulate hemoglobin oxygenated (1A3N) and de-oxygenated (6BB5) +Simulate Trypsin (1TRN) for 1ns at 300K and compute SASA. +Download the pdb file for 1C3W and describe the secondary structure. Then simulate the protein at 300K for 1ns. Plot RMSD over time and radius of gyration over time. +Download the PDB file for 1XQ8. Then, save the visualization for it. +Download the PDB for 2YXF. Tell me about its stability, as found in literature. Then, simulate it for 1ns and plot its RMSD over time. +Simulate 1MBN in water and in methanol solutions. +Download Protein 1ATN +Download and clean protein 1A3N +Perform a short simulation of protein 1PQ2 +Analyze the rdf of the simulation of 1A3N solvated in water +Make an rdf analysis of both oxygenated and deoxygenated hemoglobin structures diff --git a/notebooks/radius_of_gyration/proteins.txt b/notebooks/radius_of_gyration/proteins.txt deleted file mode 100644 index a90c3071..00000000 --- a/notebooks/radius_of_gyration/proteins.txt +++ /dev/null @@ -1,10 +0,0 @@ -1A3N -1TRZ -1TUP -1BR1 -1ATN -2RH1 -1IGT -1PQ2 -2TNF -1BO9 diff --git a/notebooks/radius_of_gyration/rgy_1A3N.ipynb b/notebooks/radius_of_gyration/rgy_1A3N.ipynb deleted file mode 100644 index fcc2e38d..00000000 --- a/notebooks/radius_of_gyration/rgy_1A3N.ipynb +++ /dev/null @@ -1,280 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1A3N and calculate the average radius of gyration, I need to first set up and run a simulation for the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 22:33:25.431 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: The previous action attempted to set up and run a simulation for the protein with PDB ID 1A3N, but it failed because the PDB ID was not recognized. I need to ensure that the PDB ID is correctly inputted into the SetUpandRunFunction tool. I will correct the input and try running the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The previous action to set up and run a simulation for the protein with PDB ID 1A3N failed because the PDB ID was not recognized. It seems there might be an issue with the PDB ID input format or the tool may require the actual file rather than just the PDB ID. To resolve this, I will first attempt to download the PDB file for 1A3N using the PDBFileDownloader tool, which should provide the correct file for the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1A3N\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1A3N\n", - "Now that I have successfully downloaded the PDB file for protein 1A3N, I can proceed to set up and run the simulation using the SetUpandRunFunction tool. I will use the file ID obtained from the download in the previous step as the input for the PDB ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_223357\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 1A3N is missing hydrogen atoms, which are necessary for the forcefield to recognize the residues correctly. To fix this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. This should prepare the file for a successful simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_223357\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 1A3N has been cleaned and the necessary hydrogen atoms have been added, I can proceed to set up and run the simulation again using the SetUpandRunFunction tool with the cleaned file ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_223429\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1A3N_223429_20240222_223445.py\n", - "['LOG_sim0_223445_1A3N_223429_20240222_223445.txt', 'proteins.txt', 'ckpt', 'rgy_ 1TRZ.ipynb', 'TRAJ_sim0_223445_1A3N_223429_20240222_223445.dcd', 'paths_registry.json', 'files', 'TOP_sim0_223445_1A3N_223429_20240222_223445.pdb', 'rgy_ 1TRZ copy.ipynb', 'rgy_1A3N.ipynb']\n", - "The simulation for protein 1A3N has been successfully completed, and the necessary files have been generated. I can now use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_223429\"\n", - " }\n", - "}\n", - "```\n", - "Final Answer: The simulation for protein 1A3N was successfully completed, and the average radius of gyration calculated from the trajectory file is 2.30 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation for protein 1A3N was successfully completed, and the average radius of gyration calculated from the trajectory file is 2.30 nm.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "protein_id = \"1A3N\"\n", - "agent.run(f\"Simulate protein {protein_id} and calculate the average radius of gyration.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1ATN.ipynb b/notebooks/radius_of_gyration/rgy_1ATN.ipynb deleted file mode 100644 index 2c5676f7..00000000 --- a/notebooks/radius_of_gyration/rgy_1ATN.ipynb +++ /dev/null @@ -1,276 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1ATN and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[4].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1ATN and calculate the average radius of gyration, I will first need to set up and run a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration for the simulated trajectory.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 22:50:02.883 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The previous action attempted to run a simulation using the PDB ID \"1ATN\" but encountered an error because the PDB file was not found in the input. To proceed, I need to ensure that the PDB file for the protein 1ATN is available for the simulation. I will use the PDBFileDownloader tool to download the PDB file for protein 1ATN.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1ATN\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1ATN\n", - "Now that I have successfully downloaded the PDB file for protein 1ATN, I can proceed to set up and run a short simulation of the protein using the SetUpandRunFunction tool. I will use the downloaded PDB file ID \"1ATN_225014\" as the input for the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_225014\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 1ATN is missing hydrogen atoms, which are necessary for the forcefield to recognize the residues correctly. To resolve this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. This should prepare the file for a successful simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_225014\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 1ATN has been successfully cleaned and is now ready for simulation. I will proceed to set up and run a short simulation of the protein using the cleaned PDB file ID \"1ATN_225040\" with the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_225040\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1ATN_225040_20240222_225052.py\n", - "['proteins.txt', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'TOP_sim0_225052_1ATN_225040_20240222_225053.pdb', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'LOG_sim0_225052_1ATN_225040_20240222_225053.txt', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'TRAJ_sim0_225052_1ATN_225040_20240222_225053.dcd', 'rgy_1A3N.ipynb']\n", - "The simulation for protein 1ATN has been completed successfully, and the necessary files have been generated. Now, I will use the RadiusofGyrationAverage tool to calculate the average radius of gyration for the simulated trajectory file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_225040\"\n", - " }\n", - "}\n", - "```\n", - "The average radius of gyration for the simulated protein 1ATN has been calculated and is 3.02 nm. This completes the task.\n", - "\n", - "Final Answer: The average radius of gyration for the simulated protein 1ATN is 3.02 nm." - ] - }, - { - "data": { - "text/plain": [ - "'The average radius of gyration for the simulated protein 1ATN has been calculated and is 3.02 nm. This completes the task.\\n\\nFinal Answer: The average radius of gyration for the simulated protein 1ATN is 3.02 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1BO9.ipynb b/notebooks/radius_of_gyration/rgy_1BO9.ipynb deleted file mode 100644 index fb3c955f..00000000 --- a/notebooks/radius_of_gyration/rgy_1BO9.ipynb +++ /dev/null @@ -1,235 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1BO9 and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[9].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1BO9 and calculate the average radius of gyration, I will first need to set up and run a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration for the simulated trajectory.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BO9\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-23 00:10:51.647 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Building system...\n", - "The previous attempt to simulate protein 1BO9 failed because the file was not found. Before running a simulation, I need to ensure that the protein structure file (PDB file) for 1BO9 is available. I will use the PDBFileDownloader tool to download the PDB file for protein 1BO9.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1BO9\"\n", - " }\n", - "}\n", - "```\n", - "PDB file found with this ID: 1BO9\n", - "Now that the PDB file for protein 1BO9 has been successfully downloaded, I can proceed with setting up and running a short simulation using the SetUpandRunFunction tool. I will use the downloaded PDB file ID as the input for the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BO9_001059\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1BO9_001059_20240223_001119.py\n", - "['TOP_sim0_001031_2TNF_001016_20240223_001032.pdb', 'rgy_2TNF.ipynb', 'rgy_1PQ2.ipynb', 'proteins.txt', 'rgy_2RH1.ipynb', 'TRAJ_sim0_001119_1BO9_001059_20240223_001120.dcd', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'LOG_sim0_001119_1BO9_001059_20240223_001120.txt', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'rgy_1BO9.ipynb', 'TOP_sim0_001119_1BO9_001059_20240223_001120.pdb', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'TRAJ_sim0_001031_2TNF_001016_20240223_001032.dcd', 'LOG_sim0_001031_2TNF_001016_20240223_001032.txt', 'rgy_1A3N.ipynb', 'rgy_1IGT.ipynb']\n", - "The simulation for protein 1BO9 has been completed successfully, and the necessary files have been generated. The next step is to calculate the average radius of gyration for the simulated trajectory. I will use the RadiusofGyrationAverage tool with the protein ID that was used in the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BO9_001059\"\n", - " }\n", - "}\n", - "```\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/mdtraj/formats/pdb/pdbfile.py:200: UserWarning: Unlikely unit cell vectors detected in PDB file likely resulting from a dummy CRYST1 record. Discarding unit cell vectors.\n", - " warnings.warn('Unlikely unit cell vectors detected in PDB file likely '\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Final Answer: The simulation of protein 1BO9 was successfully completed, and the average radius of gyration calculated for the simulated trajectory is 1.12 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 1BO9 was successfully completed, and the average radius of gyration calculated for the simulated trajectory is 1.12 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1BR1.ipynb b/notebooks/radius_of_gyration/rgy_1BR1.ipynb deleted file mode 100644 index 85ab1066..00000000 --- a/notebooks/radius_of_gyration/rgy_1BR1.ipynb +++ /dev/null @@ -1,242 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1BR1 and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[3].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1BR1 and calculate the average radius of gyration, I will first need to set up and run a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 22:39:23.171 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The previous action attempted to run a simulation using the SetUpandRunFunction tool but encountered an error because the PDB ID was not recognized. To correct this, I will first download the PDB file for protein 1BR1 using the PDBFileDownloader tool. Once the file is downloaded, I can proceed with the simulation setup and execution.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1BR1\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1BR1\n", - "Now that the PDB file for protein 1BR1 has been successfully downloaded, I can proceed with setting up and running a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I will use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_223929\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 1BR1 is missing hydrogen atoms, which are necessary for the forcefield to recognize the residues correctly. To resolve this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. After cleaning the PDB file, I will attempt to run the simulation again using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_223929\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 1BR1 has been cleaned and the necessary hydrogen atoms have been added, I can proceed with setting up and running a short simulation of the protein using the SetUpandRunFunction tool with the cleaned PDB file. After the simulation is complete, I will use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_224108\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n" - ] - } - ], - "source": [ - "agent.run(prompt)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1IGT.ipynb b/notebooks/radius_of_gyration/rgy_1IGT.ipynb deleted file mode 100644 index 813c88cc..00000000 --- a/notebooks/radius_of_gyration/rgy_1IGT.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1IGT and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[6].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1IGT and calculate the average radius of gyration, I will first need to set up and run a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration for the given trajectory file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 23:21:40.181 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: The previous action attempted to use the SetUpandRunFunction tool to simulate the protein with PDB ID 1IGT, but it failed because the PDB ID was not recognized. I need to ensure that the PDB ID is correctly inputted into the tool. I will try running the SetUpandRunFunction tool again with the correct PDB ID format.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The SetUpandRunFunction tool requires a valid PDB ID to run a simulation. The error message indicates that the PDB ID provided (\"1IGT\") is not being recognized as a valid input. It's possible that the PDB file for 1IGT needs to be downloaded or retrieved from a database before it can be used for simulation. I will use the PDBFileDownloader tool to download the PDB file for protein 1IGT.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1IGT\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1IGT\n", - "Now that the PDB file for protein 1IGT has been successfully downloaded, I can proceed with setting up and running a short simulation using the SetUpandRunFunction tool. I will use the downloaded PDB file ID \"1IGT_232215\" as the input for the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_232215\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for 1IGT is missing a hydrogen atom on residue 1 (ASP). Before I can run the simulation, I need to clean the PDB file to ensure it has all the necessary atoms and is compatible with the forcefield. I will use the CleaningToolFunction to clean the PDB file by adding missing atoms, including hydrogens, and then attempt to run the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_232215\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 1IGT has been successfully cleaned, and missing atoms including hydrogens have been added. Now that the file is prepared, I can proceed with setting up and running a short simulation using the SetUpandRunFunction tool with the cleaned PDB file ID \"1IGT_232259\".\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_232259\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1IGT_232259_20240222_232314.py\n", - "['proteins.txt', 'rgy_2RH1.ipynb', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'TOP_sim0_232314_1IGT_232259_20240222_232316.pdb', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'LOG_sim0_232314_1IGT_232259_20240222_232316.txt', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'rgy_1A3N.ipynb', 'TRAJ_sim0_232314_1IGT_232259_20240222_232316.dcd', 'rgy_1IGT.ipynb']\n", - "The simulation for protein 1IGT has been completed successfully, and the necessary files have been generated. The next step is to calculate the average radius of gyration using the RadiusofGyrationAverage tool. I will use the trajectory file ID provided in the simulation summary to perform this calculation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_232259\"\n", - " }\n", - "}\n", - "```Final Answer: The simulation of protein 1IGT was successfully completed, and the average radius of gyration calculated for the simulated trajectory is 5.35 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 1IGT was successfully completed, and the average radius of gyration calculated for the simulated trajectory is 5.35 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1PQ2.ipynb b/notebooks/radius_of_gyration/rgy_1PQ2.ipynb deleted file mode 100644 index 99df096d..00000000 --- a/notebooks/radius_of_gyration/rgy_1PQ2.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1PQ2 and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[7].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein with PDB ID 1PQ2 and calculate the average radius of gyration, I will first need to set up and run a simulation for the protein. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 23:47:20.893 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: The previous attempt to run a simulation failed because the PDB ID was not recognized. I need to ensure that the PDB ID is correctly inputted and recognized by the system. I will attempt to run the simulation again with the correct PDB ID for protein 1PQ2.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The system is not recognizing the PDB ID \"1PQ2\" as a valid input for the simulation setup. It's possible that the PDB file for 1PQ2 needs to be downloaded before running the simulation. I will use the PDBFileDownloader tool to download the PDB file for protein 1PQ2.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1PQ2\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1PQ2\n", - "Now that the PDB file for protein 1PQ2 has been successfully downloaded, I can proceed to set up and run the simulation using the SetUpandRunFunction tool with the downloaded file ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_234745\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because there is an issue with the template for residue 1 (LYS) in the PDB file. It seems that the PDB file contains a residue that does not match the standard template for lysine (LYS) and is missing atoms. Before attempting another simulation, I need to clean the PDB file to ensure that all residues match the standard templates and that any missing atoms are added. I will use the CleaningToolFunction to clean the PDB file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_234745\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 1PQ2 has been successfully cleaned, and I now have a file ID for the cleaned file. I can proceed to set up and run the simulation using the SetUpandRunFunction tool with the cleaned file ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_234824\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1PQ2_234824_20240222_234836.py\n", - "['LOG_sim0_234836_1PQ2_234824_20240222_234837.txt', 'rgy_1PQ2.ipynb', 'proteins.txt', 'rgy_2RH1.ipynb', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'TRAJ_sim0_234836_1PQ2_234824_20240222_234837.dcd', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'TOP_sim0_234836_1PQ2_234824_20240222_234837.pdb', 'rgy_1A3N.ipynb', 'rgy_1IGT.ipynb']\n", - "The simulation for protein 1PQ2 has been completed successfully, and the necessary files have been generated. I can now use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_234824\"\n", - " }\n", - "}\n", - "```Final Answer: The simulation of protein 1PQ2 was successfully completed, and the average radius of gyration calculated from the trajectory is 3.25 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 1PQ2 was successfully completed, and the average radius of gyration calculated from the trajectory is 3.25 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1TRZ.ipynb b/notebooks/radius_of_gyration/rgy_1TRZ.ipynb deleted file mode 100644 index 052af9cd..00000000 --- a/notebooks/radius_of_gyration/rgy_1TRZ.ipynb +++ /dev/null @@ -1,275 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1TRZ and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[1].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1TRZ and calculate the average radius of gyration, I will first need to set up and run a simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 22:29:51.742 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Setting default forcefields v2\n", - "Thought: The previous action attempted to run a simulation using the SetUpandRunFunction tool but failed because the PDB ID was not recognized. It seems that the tool requires a file ID from the path registry rather than the PDB ID directly. To resolve this, I will first download the PDB file for protein 1TRZ using the PDBFileDownloader tool. Once I have the file, I can proceed with setting up and running the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1TRZ\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1TRZ\n", - "Now that I have successfully downloaded the PDB file for protein 1TRZ, I can proceed with setting up and running the simulation using the SetUpandRunFunction tool. I will use the file ID obtained from the download in the simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_223000\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 1TRZ is missing hydrogen atoms, which are necessary for the forcefield to recognize the residues correctly. To resolve this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. This should prepare the file for a successful simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_223000\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 1TRZ has been cleaned and the necessary hydrogen atoms have been added, I can proceed with setting up and running the simulation using the SetUpandRunFunction tool. I will use the new file ID obtained from the cleaning process in the simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_223027\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1TRZ_223027_20240222_223035.py\n", - "['proteins.txt', 'ckpt', 'rgy_ 1TRZ.ipynb', 'TOP_sim0_223035_1TRZ_223027_20240222_223035.pdb', 'paths_registry.json', 'LOG_sim0_223035_1TRZ_223027_20240222_223035.txt', 'files', 'rgy_1A3N.ipynb', 'TRAJ_sim0_223035_1TRZ_223027_20240222_223035.dcd']\n", - "The simulation has been successfully completed, and the necessary files have been generated. Now, I will use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_223027\"\n", - " }\n", - "}\n", - "```\n", - "Final Answer: The simulation of protein 1TRZ was successfully completed, and the average radius of gyration calculated from the trajectory file is 1.33 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 1TRZ was successfully completed, and the average radius of gyration calculated from the trajectory file is 1.33 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_1TUP.ipynb b/notebooks/radius_of_gyration/rgy_1TUP.ipynb deleted file mode 100644 index c6a34b9c..00000000 --- a/notebooks/radius_of_gyration/rgy_1TUP.ipynb +++ /dev/null @@ -1,305 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 1TUP and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[2].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1TUP and calculate the average radius of gyration, I will first need to set up and run a simulation for the protein using the SetUpandRunFunction tool. After the simulation is complete, I can then use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 22:37:26.694 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Setting default forcefields v2\n", - "The previous action attempted to run a simulation for the protein with PDB ID 1TUP, but it failed because the PDB ID was not recognized. I need to ensure that the PDB ID is correctly inputted into the SetUpandRunFunction tool. I will retry the simulation setup and execution with the correct PDB ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The previous action failed because the PDB ID was not recognized. It seems there might be a misunderstanding about the PDB ID or the file ID required for the simulation. To resolve this, I will first download the PDB file for the protein with PDB ID 1TUP using the PDBFileDownloader tool. Once I have the PDB file, I can proceed with setting up and running the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1TUP\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1TUP\n", - "Now that I have successfully downloaded the PDB file for protein 1TUP, I can proceed with setting up and running the simulation using the SetUpandRunFunction tool. I will use the file ID obtained from the download in the previous step as the input for the PDB ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_223753\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 1TUP contains a residue (DT) that is not recognized by the default forcefield, likely due to missing hydrogen atoms. To address this, I will use the CleaningToolFunction to clean the PDB file by adding missing atoms, including hydrogens, and then attempt to run the simulation again with the cleaned file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_223753\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 1TUP has been successfully cleaned, which should resolve the issue with the unrecognized residue and missing hydrogen atoms. I can now proceed to set up and run the simulation again using the cleaned PDB file ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_223827\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false,\n", - " \"solvate\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1TUP_223827_20240222_223844.py\n", - "['TOP_sim0_223844_1TUP_223827_20240222_223844.pdb', 'proteins.txt', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_ 1TRZ.ipynb', 'rgy_1BR1.ipynb', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'TRAJ_sim0_223844_1TUP_223827_20240222_223844.dcd', 'files', 'LOG_sim0_223844_1TUP_223827_20240222_223844.txt', 'rgy_ 1TRZ copy.ipynb', 'rgy_1A3N.ipynb']\n", - "The simulation for protein 1TUP has been successfully completed, and the necessary files have been generated. I can now use the RadiusofGyrationAverage tool to calculate the average radius of gyration from the trajectory file generated by the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_223827\"\n", - " }\n", - "}\n", - "```Final Answer: The simulation of protein 1TUP was successfully completed, and the average radius of gyration calculated from the trajectory is 3.63 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 1TUP was successfully completed, and the average radius of gyration calculated from the trajectory is 3.63 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_2RH1.ipynb b/notebooks/radius_of_gyration/rgy_2RH1.ipynb deleted file mode 100644 index a7d03770..00000000 --- a/notebooks/radius_of_gyration/rgy_2RH1.ipynb +++ /dev/null @@ -1,355 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 2RH1 and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[5].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 2RH1 and calculate its average radius of gyration, I need to perform two main tasks. First, I need to set up and run a simulation for the protein 2RH1. After the simulation is complete, I can then calculate the average radius of gyration from the trajectory file generated. I will start by setting up and running the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-22 23:00:02.998 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To correct the error from the previous attempt, I need to include the `ewaldErrorTolerance` parameter in the `system_params` since the `nonbondedMethod` is set to PME. I will set a typical value for `ewaldErrorTolerance` and then rerun the simulation setup using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The previous action failed because the PDB ID was not recognized correctly. I need to ensure that the PDB ID is provided in a format that the SetUpandRunFunction tool can recognize. I will correct this by providing the PDB ID \"2RH1\" again, ensuring it is in the correct format for the tool to recognize and process.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The SetUpandRunFunction tool is not recognizing the PDB ID \"2RH1\" as a valid input. It's possible that the PDB file needs to be downloaded or retrieved from a database before it can be used in the simulation. I will use the PDBFileDownloader tool to download the PDB file for protein 2RH1, which should provide me with a file ID that can be used for the simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"2RH1\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 2RH1\n", - "Now that I have successfully downloaded the PDB file for protein 2RH1 with the file ID \"2RH1_230057\", I can proceed to set up and run the simulation using the SetUpandRunFunction tool. This time, I will use the file ID instead of the PDB ID in the input to ensure the tool recognizes the file correctly.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_230057\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (ASP). The set of atoms is similar to ALA, but it is missing 5 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file for protein 2RH1 is missing hydrogen atoms for residue ASP (aspartic acid). This is a common issue when working with PDB files, as they often lack hydrogen atoms since X-ray crystallography does not always resolve them. To proceed, I need to add the missing hydrogen atoms to the PDB file. I will use the CleaningToolFunction to clean the PDB file by adding the missing hydrogen atoms and then attempt to rerun the simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_230057\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 2RH1 has been successfully cleaned, and missing hydrogen atoms have been added. The file ID for the cleaned file is \"2RH1_230123\". I can now proceed to set up and run the simulation using the cleaned PDB file. I will use the SetUpandRunFunction tool again with the new file ID.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_230123\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2RH1_230123_20240222_230143.py\n", - "['proteins.txt', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'TOP_sim0_230143_2RH1_230123_20240222_230153.pdb', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'TRAJ_sim0_230143_2RH1_230123_20240222_230153.dcd', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'rgy_ 2RH1.ipynb', 'rgy_1A3N.ipynb', 'LOG_sim0_230143_2RH1_230123_20240222_230153.txt']\n", - "The simulation for protein 2RH1 has been successfully completed, and the necessary files have been generated. The next step is to calculate the average radius of gyration from the trajectory file. I will use the RadiusofGyrationAverage tool to calculate this value using the trajectory file ID provided in the simulation summary.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_230123\"\n", - " }\n", - "}\n", - "```Final Answer: The simulation of protein 2RH1 was successfully completed, and the average radius of gyration calculated from the trajectory is 5.87 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation of protein 2RH1 was successfully completed, and the average radius of gyration calculated from the trajectory is 5.87 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/radius_of_gyration/rgy_2TNF.ipynb b/notebooks/radius_of_gyration/rgy_2TNF.ipynb deleted file mode 100644 index 5e7c10e1..00000000 --- a/notebooks/radius_of_gyration/rgy_2TNF.ipynb +++ /dev/null @@ -1,264 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "agent = MDAgent(resume=False, learn=False, agent_type=\"Structured\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'Simulate protein 2TNF and calculate the average radius of gyration.'" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#get the second line from proteins.txt\n", - "with open('proteins.txt') as f:\n", - " proteins = f.readlines()\n", - " protein = proteins[8].strip()\n", - "\n", - "prompt = f\"Simulate protein {protein} and calculate the average radius of gyration.\"\n", - "prompt" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 2TNF and calculate the average radius of gyration, I need to perform two main tasks. First, I need to set up and run a simulation for the protein 2TNF. After the simulation is complete, I can then calculate the average radius of gyration using the trajectory file generated from the simulation. I will start by setting up and running the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-23 00:09:38.472 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /Users/samcox/anaconda3/envs/mda_feb21/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: The previous action attempted to run a simulation using the SetUpandRunFunction tool but failed because the PDB ID was not recognized. It seems that the tool requires a file ID rather than the PDB ID. To resolve this, I will first download the PDB file for protein 2TNF using the PDBFileDownloader tool. Once I have the file, I can proceed with the simulation setup and run.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"2TNF\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 2TNF\n", - "Now that I have successfully downloaded the PDB file for protein 2TNF, I can proceed with setting up and running the simulation using the SetUpandRunFunction tool. I will use the file ID obtained from the download in the previous step to ensure the tool recognizes the input.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_000944\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "The simulation setup failed because the PDB file for protein 2TNF is missing hydrogen atoms, which are necessary for the forcefield to recognize the residues correctly. To fix this issue, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. This should prepare the file for a successful simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_000944\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 2TNF has been cleaned and the missing hydrogen atoms have been added, I can proceed with setting up and running the simulation again using the SetUpandRunFunction tool. This time, I will use the cleaned file ID to ensure the simulation can be set up correctly.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_001016\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"NoCutoff\",\n", - " \"constraints\": \"None\",\n", - " \"rigidWater\": false\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2TNF_001016_20240223_001031.py\n", - "['TOP_sim0_001031_2TNF_001016_20240223_001032.pdb', 'rgy_2TNF.ipynb', 'rgy_1PQ2.ipynb', 'proteins.txt', 'rgy_2RH1.ipynb', 'TRAJ_sim0_224125_1BR1_224108_20240222_224129.dcd', 'LOG_sim0_224125_1BR1_224108_20240222_224129.txt', 'ckpt', 'rgy_1ATN.ipynb', 'rgy_1BR1.ipynb', 'rgy_1BO9.ipynb', 'TOP_sim0_224125_1BR1_224108_20240222_224129.pdb', 'paths_registry.json', 'rgy_1TUP.ipynb', 'files', 'rgy_1TRZ.ipynb', 'TRAJ_sim0_001031_2TNF_001016_20240223_001032.dcd', 'LOG_sim0_001031_2TNF_001016_20240223_001032.txt', 'rgy_1A3N.ipynb', 'rgy_1IGT.ipynb']\n", - "The simulation for protein 2TNF has been successfully completed, and the necessary files have been generated. Now, I need to calculate the average radius of gyration using the trajectory file from the simulation. I will use the RadiusofGyrationAverage tool to perform this calculation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RadiusofGyrationAverage\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_001016\"\n", - " }\n", - "}\n", - "```\n", - "Final Answer: The simulation for protein 2TNF was successfully completed, and the average radius of gyration was calculated to be 2.10 nm." - ] - }, - { - "data": { - "text/plain": [ - "'Final Answer: The simulation for protein 2TNF was successfully completed, and the average radius of gyration was calculated to be 2.10 nm.'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "agent.run(prompt)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rdf/rdf.ipynb b/notebooks/rdf/rdf.ipynb deleted file mode 100644 index 79258b92..00000000 --- a/notebooks/rdf/rdf.ipynb +++ /dev/null @@ -1,107 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from mdagent import MDAgent\n", - "agent = MDAgent(agent_type=\"Structured\",learn = False)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#Multi Prompt tasks\n", - "\n", - "proteins = [\n", - " '1A3N', \n", - " '1TRZ',\n", - " '1TUP',\n", - " '1BR1',\n", - " '1ATN',\n", - " '2RH1',\n", - " '1IGT',\n", - " '1PQ2',\n", - " '2TNF',\n", - " '1BO9',]\n", - "\n", - "prompt_template_1 = \"Simulate {protein} in water at 280K. Dont forget to clean the protein first\"\n", - "\n", - "prompt_template_2 = (\"You already have a simulation of {protein} in water at 280K. Please use the dcd records and topology\"\n", - " \" files of the simulation to get the rdf between water and the protein.\" \n", - " \"The records and topology are inside the files directory. The path registry has descriptions and ids of the files too.\")\n", - "prompt_template = \"Calculate the radial distribution function of {protein} at 280K with water\"\n", - "prompts_1 = [prompt_template_1.format(protein=protein) for protein in proteins]\n", - "prompts_2 = [prompt_template_2.format(protein=protein) for protein in proteins]\n", - "prompts = [prompt_template.format(protein=protein) for protein in proteins]\n", - "print(prompts_1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import traceback\n", - "import sys\n", - "import io\n", - "# A context manager to capture stdout\n", - "attempt = 1 #change this depending on the attempt\n", - "class CaptureStdout:\n", - " def __enter__(self):\n", - " self._stdout = sys.stdout\n", - " sys.stdout = self._stringio = io.StringIO()\n", - " return self\n", - "\n", - " def __exit__(self, *args):\n", - " sys.stdout = self._stdout\n", - "\n", - " def get_value(self):\n", - " return self._stringio.getvalue()\n", - "\n", - "for i, (prompt,protein) in enumerate(zip(prompts_1,proteins)):\n", - " with CaptureStdout() as capture:\n", - " try:\n", - " agent.run(prompt)\n", - " except Exception as e:\n", - " print(e)\n", - " traceback.print_exc()\n", - " finally:\n", - " with open(f'Attempt_{attempt}_{protein}_MP1.txt', 'w') as f: #change this depending on the attempt or test\n", - " #write the prompt in the first line\n", - " f.write(\"Taking out subagents\\n\\n\")\n", - " f.write(\"Query from the user: \")\n", - " f.write(prompt+\"\\n\\n\")\n", - " #write the output of the cell in the second line\n", - " f.write(capture.get_value())" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "TestingEnv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/13AN_gpt4.ipynb b/notebooks/rmsd/13AN_gpt4.ipynb deleted file mode 100644 index 7d5e5886..00000000 --- a/notebooks/rmsd/13AN_gpt4.ipynb +++ /dev/null @@ -1,261 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: The task involves multiple steps: downloading a PDB file for the protein with the identifier 13AN, cleaning the PDB file, running a simulation, and then calculating the RMSD. I will start by downloading the PDB file for the protein 13AN.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"13AN\"\n", - " }\n", - "}\n", - "```\n", - "\n", - "The previous attempt to download the PDB file for the protein with the identifier 13AN failed. It's possible that the identifier is incorrect or the file is not available in the PDB database. I will attempt to download the file again to confirm if the issue persists.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"13AN\"\n", - " }\n", - "}\n", - "```The repeated failure to download the PDB file for the protein with the identifier 13AN suggests that there may be an issue with the identifier itself. It is possible that 13AN is not a valid PDB identifier or the file does not exist in the database. To proceed, I will attempt to verify the validity of the PDB identifier 13AN.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1A3N\"\n", - " }\n", - "}\n", - "```\n", - "PDB file found with this ID: 1A3N\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 11:58:45.944 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The PDB file for the protein with the identifier 1A3N has been successfully downloaded. The next step is to clean the PDB file to prepare it for simulation. This involves removing heterogens, adding missing atoms and hydrogens, replacing nonstandard residues, and removing water if necessary. After cleaning, I will set up and run a simulation for the protein.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_115846\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for the protein with the identifier 1A3N has been cleaned successfully. The next step is to set up and run a simulation for the cleaned protein. After the simulation, I will calculate the RMSD to assess the structural deviation over the course of the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_115907\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": 1.0,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The simulation setup failed because the `ewaldErrorTolerance` parameter was not specified, which is required when the `nonbondedMethod` is set to PME (Particle Mesh Ewald). I will correct this by adding the `ewaldErrorTolerance` parameter and then reattempt the simulation setup.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1A3N_115907\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": 1.0,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1A3N_115907_20240219_115954.py\n", - "['TRAJ_sim_115954_1A3N_115907_20240219_115959.dcd', 'ckpt', '13AN_gpt3.5.ipynb', 'LOG_sim_115954_1A3N_115907_20240219_115959.txt', 'paths_registry.json', 'files']\n", - "The simulation for the protein with the identifier 1A3N has been completed successfully. The next step is to calculate the RMSD to assess the structural deviation over the course of the simulation. To do this, I will use the RMSDCalculator tool with the appropriate files and parameters.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1A3N_Clean_20240219_115907.pdb\",\n", - " \"trajectory\": \"files/dcd/1A3N_Simulation_20240219_115907.dcd\",\n", - " \"ref_file\": \"files/pdb/1A3N_Clean_20240219_115907.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for the protein with the identifier 1A3N has been completed successfully, and the RMSD value is 1.0070107981652348e-06. This value indicates the average deviation of the protein's backbone atoms from their initial positions throughout the simulation, which is a very small value suggesting minimal deviation.\n", - "\n", - "Final Answer: The PDB file for the protein with the identifier 1A3N was successfully downloaded, cleaned, and simulated. The RMSD of the protein's backbone atoms over the course of the simulation was calculated to be 1.0070107981652348e-06, indicating minimal structural deviation." - ] - }, - { - "data": { - "text/plain": [ - "\"The RMSD calculation for the protein with the identifier 1A3N has been completed successfully, and the RMSD value is 1.0070107981652348e-06. This value indicates the average deviation of the protein's backbone atoms from their initial positions throughout the simulation, which is a very small value suggesting minimal deviation.\\n\\nFinal Answer: The PDB file for the protein with the identifier 1A3N was successfully downloaded, cleaned, and simulated. The RMSD of the protein's backbone atoms over the course of the simulation was calculated to be 1.0070107981652348e-06, indicating minimal structural deviation.\"" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from mdagent import MDAgent\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "myagent.run(\"Download PDB file for 13AN. Clean the PDB file then Simulate protein 13AN. calculate RMSD.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SmallMoleculePDB\n", - "PDBFileDownloader\n", - "SetUpandRunFunction\n", - "ppi_distance\n", - "RMSDCalculator\n", - "ModifyScriptTool\n", - "packmol_tool\n", - "CleaningToolFunction\n", - "PostSimulationFigures\n", - "Calculator\n", - "PDBVisualization\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1ATN_gpt4.ipynb b/notebooks/rmsd/1ATN_gpt4.ipynb deleted file mode 100644 index e29e882c..00000000 --- a/notebooks/rmsd/1ATN_gpt4.ipynb +++ /dev/null @@ -1,288 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1ATN and calculate RMSD, I will need to perform several steps. First, I will download the PDB file for protein 1ATN. Then, I will set up and run a short simulation of the protein using the SetUpandRunFunction tool. After the simulation is complete, I will use the RMSDCalculator tool to calculate the RMSD from the output files of the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1ATN\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1ATN\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 14:07:55.815 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the PDB file for protein 1ATN, the next step is to set up and run a short simulation of the protein. I will use the SetUpandRunFunction tool to perform this task. After the simulation, I will use the RMSDCalculator tool to calculate the RMSD from the output files.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_140756\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To proceed with the simulation, I need to correct the system parameters by specifying the `ewaldErrorTolerance` since the `nonbondedMethod` is set to PME. I will then re-run the SetUpandRunFunction tool with the corrected parameters.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_140756\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (ACE). The set of atoms is similar to ACE, but it is missing 3 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file for protein 1ATN contains a residue (ACE) that is missing hydrogen atoms, which is not recognized by the default forcefield. To resolve this, I will use the CleaningToolFunction to clean the PDB file by adding missing atoms, including hydrogens, and then attempt to run the simulation again with the cleaned PDB file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_140756\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 1ATN has been cleaned and prepared, I can proceed with the simulation setup again. I will use the SetUpandRunFunction tool with the cleaned PDB file and the previously defined parameters, ensuring that the simulation is correctly configured this time.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1ATN_140840\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1ATN_140840_20240219_140858.py\n", - "['1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', 'LOG_sim_140858_1ATN_140840_20240219_140911.txt', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', 'TRAJ_sim_140858_1ATN_140840_20240219_140911.dcd', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb']\n", - "The simulation of protein 1ATN has been successfully completed. The next step is to calculate the RMSD using the RMSDCalculator tool. I will use the output files from the simulation to perform this calculation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1ATN_140840\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"1ATN_140840\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation failed because the tool did not recognize the file format provided. It seems that the output files from the simulation were not specified correctly. To correct this, I need to ensure that the file paths for the PDB file and the trajectory are valid and in a format that the RMSDCalculator tool can recognize. I will adjust the input to include the correct file paths and formats, then attempt the RMSD calculation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1ATN_Clean_20240219_140840.pdb\",\n", - " \"trajectory\": \"files/dcd/1ATN_Simulation_20240219_140840.dcd\",\n", - " \"ref_file\": \"files/pdb/1ATN_Clean_20240219_140840.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for the simulation of protein 1ATN has been successfully completed. The calculated RMSD value is 1.358283396385289e-06, which indicates the average deviation of the protein's backbone atoms from their initial positions throughout the simulation.\n", - "\n", - "Final Answer: The RMSD value calculated for the simulation of protein 1ATN is approximately 1.36 x 10^-6. This value represents the root mean square deviation of the protein's backbone atoms from their initial positions over the course of the simulation.Time taken (s): 1341.2940640449524\n", - "Time taken (min): 22.354901067415874\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 1ATN and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "ppi_distance\n", - "RMSDCalculator\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "PostSimulationFigures\n", - "packmol_tool\n", - "CleaningToolFunction\n", - "Python_REPL\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1B09_gpt4.ipynb b/notebooks/rmsd/1B09_gpt4.ipynb deleted file mode 100644 index 6e9edabd..00000000 --- a/notebooks/rmsd/1B09_gpt4.ipynb +++ /dev/null @@ -1,342 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Mon Feb 19\n", - "- before: 3.80\n", - "- during: 4.13\n", - "- after: 4.13 (plus .20?)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein with PDB ID 1B09 and calculate the RMSD, I will first need to set up and run a molecular dynamics simulation. After the simulation is complete, I can then use the RMSDCalculator tool to calculate the RMSD using the output files from the simulation. I will start by setting up and running the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1B09\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To correct the error and proceed with the simulation, I need to specify the `ewaldErrorTolerance` parameter since the `nonbondedMethod` is set to PME. I will update the `system_params` with this parameter and re-execute the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1B09\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```The error indicates that the PDB ID provided is not recognized in the format expected by the tool. I need to download the PDB file for protein 1B09 using the PDBFileDownloader tool to obtain the correct file id to use in the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1B09\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1B09\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 17:24:31.778 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the correct PDB file id for protein 1B09, I can proceed with the molecular dynamics simulation setup using the SetUpandRunFunction tool. I will use the file id \"1B09_172432\" in place of the PDB ID and re-execute the SetUpandRunFunction tool with the corrected parameters.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1B09_172432\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (GLN). The set of atoms is similar to GLN, but it is missing 8 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The error message indicates that the PDB file for protein 1B09 is missing hydrogen atoms for residue 1 (GLN). To resolve this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. This will prepare the file for the simulation by ensuring that all necessary atoms are present.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1B09_172432\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```With the PDB file now cleaned and prepared, I can proceed with the molecular dynamics simulation setup using the SetUpandRunFunction tool. I will use the new file id \"1B09_172514\" for the cleaned PDB file and re-execute the SetUpandRunFunction tool with the corrected parameters.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1B09_172514\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1B09_172514_20240219_172526.py\n", - "['TRAJ_sim_172526_1B09_172514_20240219_172642.dcd', 'TRAJ_sim_170546_1BR1_161323_20240219_170622.dcd', '1BR1_gpt4_fail.ipynb', '1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'Visualization.ipynb', 'ckpt', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', 'LOG_sim_172526_1B09_172514_20240219_172642.txt', '2RH1_gpt4.ipynb', 'LOG_sim_170546_1BR1_161323_20240219_170622.txt']\n", - "The simulation for protein 1B09 has been completed successfully. The next step is to calculate the RMSD using the RMSDCalculator tool. I will use the output files from the simulation to perform this calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1B09_172514\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"1B09_172514\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the RMSDCalculator tool requires a valid PDB file format and a proper selection syntax for the calculation. The trajectory file format provided (\"output.dcd\") is not recognized as a valid input for the topology. I need to ensure that the PDB file path and the trajectory file path are correctly specified and that the selection syntax is valid for MDAnalysis. Since the simulation was successful, there should be valid output files to use. I will adjust the input to the RMSDCalculator tool to include the correct file paths and re-execute the tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1B09_Clean_20240219_172514.pdb\",\n", - " \"trajectory\": \"files/dcd/output_20240219_172514.dcd\",\n", - " \"ref_file\": \"files/pdb/1B09_Clean_20240219_172514.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for protein 1B09 has been completed successfully, and the value obtained is 2.7723044082971227e-06. This value indicates the average deviation of the backbone atoms from their initial positions throughout the simulation.\n", - "\n", - "Final Answer:\n", - "```\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The RMSD for protein 1B09 after simulation is 2.7723044082971227e-06.\"\n", - "}\n", - "```\n", - "\n", - "\n", - "Time taken (s): 9890.472062826157\n", - "Time taken (min): 164.8412010471026\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 1B09 and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SmallMoleculePDB\n", - "SetUpandRunFunction\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "packmol_tool\n", - "PostSimulationFigures\n", - "CleaningToolFunction\n", - "Python_REPL\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1BR1_gpt4_fail.ipynb b/notebooks/rmsd/1BR1_gpt4_fail.ipynb deleted file mode 100644 index 14b5402e..00000000 --- a/notebooks/rmsd/1BR1_gpt4_fail.ipynb +++ /dev/null @@ -1,358 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Mon Feb 19\n", - "- before: 3.13/3.14\n", - "- after: 3.80 (interrupted after 70 min, when it failed RMSD and started simulation again)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein with PDB ID 1BR1 and calculate the RMSD, I will first need to set up and run a molecular dynamics simulation. After the simulation is complete, I can then use the RMSDCalculator tool to calculate the RMSD from the simulation output files.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To correct the error and proceed with the simulation, I need to add the `ewaldErrorTolerance` parameter to the `system_params` since the `nonbondedMethod` is set to PME (Particle Mesh Ewald). I will adjust the `system_params` accordingly and re-execute the `SetUpandRunFunction` tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```The error indicates that the PDB ID provided is not recognized in the format expected by the tool. I need to use the file ID from the path registry instead of the PDB ID directly. To resolve this, I will first download the PDB file for protein 1BR1 using the PDBFileDownloader tool and then use the file ID obtained to run the simulation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1BR1\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1BR1\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 16:10:40.652 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the PDB file ID for protein 1BR1, I can proceed with setting up and running the molecular dynamics simulation using the `SetUpandRunFunction` tool. I will use the file ID obtained in the previous step as the input for the `pdb_id` parameter.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_161041\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (ALA). The set of atoms is similar to ALA, but it is missing 5 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The error message indicates that the PDB file for protein 1BR1 is missing hydrogen atoms for residue ALA (alanine). This is a common issue with PDB files, as they often lack hydrogen atoms because X-ray crystallography does not always resolve them. To proceed, I need to use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. I will set the `add_hydrogens` parameter to true and use the file ID for 1BR1 to clean the PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_161041\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```\n", - "Now that the PDB file has been cleaned and the missing hydrogen atoms have been added, I can proceed with setting up and running the molecular dynamics simulation using the `SetUpandRunFunction` tool. I will use the new file ID obtained from the cleaning process as the input for the `pdb_id` parameter.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_161323\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1BR1_161323_20240219_161347.py\n", - "['1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'Visualization.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', 'TRAJ_sim_161347_1BR1_161323_20240219_161423.dcd', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', 'LOG_sim_161347_1BR1_161323_20240219_161423.txt', '2RH1_gpt4.ipynb']\n", - "The simulation for protein 1BR1 has been successfully completed. The next step is to calculate the RMSD using the RMSDCalculator tool. I will use the output files from the simulation to perform this calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1BR1_161323\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"1BR1_161323\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the RMSDCalculator tool requires a valid PDB file and a valid selection syntax for the calculation. The trajectory file format provided ('output.dcd') is not recognized as a valid input for the topology. To resolve this, I need to specify the correct file format for the PDB file and ensure that the selection syntax is valid. Since the trajectory file is likely named differently, I need to find the correct file name for the trajectory output from the simulation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SkillRetrieval\",\n", - " \"action_input\": {\n", - " \"query\": \"simulation output file names for SetUpandRunFunction\"\n", - " }\n", - "}\n", - "```\n", - "\u001b[43mNo skill file found at ckpt/skill_library/skills.json\u001b[0m\n", - "The SkillRetrieval tool did not return any results for the query regarding the simulation output file names. This suggests that there may not be a specific tool or skill that provides the names of output files from the `SetUpandRunFunction` tool. However, since the simulation was completed successfully, the output files should exist. Typically, the trajectory file from an OpenMM simulation is saved with the `.dcd` extension, and the initial PDB file used for the simulation can serve as the reference file for RMSD calculations. I will proceed by assuming the trajectory file is named 'output.dcd' and the reference PDB file is '1BR1_161323.pdb', and I will attempt to calculate the RMSD again using the RMSDCalculator tool with these assumptions.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1BR1_161323.pdb\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"1BR1_161323.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the file '1BR1_161323.pdb' cannot be found, which suggests that the file path or name is incorrect. Since the simulation was completed, the output files should be in the system, but they may have different names or paths. To resolve this, I need to use the correct file path for the PDB and trajectory files. The file paths are typically provided after the simulation is completed. I will use the SetUpandRunFunction tool again to check the output file paths and names.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1BR1_161323\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3p.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 1BR1 and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1IGT_gpt4.ipynb b/notebooks/rmsd/1IGT_gpt4.ipynb deleted file mode 100644 index 1f74c7e1..00000000 --- a/notebooks/rmsd/1IGT_gpt4.ipynb +++ /dev/null @@ -1,381 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Mon Feb 19\n", - "- before: 2.32\n", - "- after: 3.13" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1IGT and calculate RMSD, I will need to perform several steps. First, I need to set up and run a molecular dynamics simulation for the protein. After the simulation is complete, I can calculate the RMSD using the simulation output files. I will start by setting up and running the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 15:17:59.390 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "error found: constraintTolerance must be specified if rigidWater is True\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The previous attempt to set up and run a molecular dynamics simulation for protein 1IGT failed because the constraintTolerance parameter was not specified, which is required when rigidWater is set to True. I will correct this by adding the constraintTolerance parameter to the system_params and then reattempt the simulation setup and execution using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The previous attempt to set up and run a molecular dynamics simulation for protein 1IGT failed because the ewaldErrorTolerance parameter was not specified, which is required when the nonbondedMethod is set to PME. I will correct this by adding the ewaldErrorTolerance parameter to the system_params and then reattempt the simulation setup and execution using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The previous attempt to set up and run a molecular dynamics simulation for protein 1IGT failed because the pdb_id was not recognized. It seems that the system requires a file id rather than the PDB code. To resolve this, I will first download the PDB file for protein 1IGT using the PDBFileDownloader tool and then proceed with the simulation setup using the correct file id.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1IGT\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1IGT\n", - "Now that I have successfully downloaded the PDB file for protein 1IGT, I can proceed with setting up and running the molecular dynamics simulation using the correct file id. I will use the SetUpandRunFunction tool with the file id obtained from the previous step.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_151841\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (ASP). The set of atoms is similar to ASP, but it is missing 1 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file for protein 1IGT is missing a hydrogen atom on residue 1 (ASP). This issue can be resolved by using the CleaningToolFunction to add the missing hydrogen atoms to the protein structure. After cleaning the PDB file, I will attempt to set up and run the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_151841\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for protein 1IGT has been successfully cleaned and the missing hydrogen atoms have been added, I can proceed with setting up and running the molecular dynamics simulation using the cleaned file id. I will use the SetUpandRunFunction tool with the new file id obtained from the cleaning process.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1IGT_151916\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1IGT_151916_20240219_151926.py\n", - "['1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', 'TRAJ_sim_151926_1IGT_151916_20240219_151937.dcd', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', 'LOG_sim_151926_1IGT_151916_20240219_151937.txt', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb']\n", - "The molecular dynamics simulation for protein 1IGT has been successfully completed. The next step is to calculate the RMSD using the output files from the simulation. I will use the RMSDCalculator tool to perform this calculation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1IGT_151916\",\n", - " \"trajectory\": \"1IGT_151916.dcd\",\n", - " \"ref_file\": \"1IGT_151916\",\n", - " \"selection\": \"protein\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation failed because the file format provided was not recognized as a valid topology or coordinate format. To resolve this, I need to ensure that the PDB file used for the RMSD calculation is in the correct format and that the selection syntax for the protein is valid. I will use the PDBVisualization tool to confirm the file format and visualize the protein structure to ensure that the selection syntax is correct.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBVisualization\",\n", - " \"action_input\": {\n", - " \"query\": \"1IGT_151916\"\n", - " }\n", - "}\n", - "```\n", - "The visualization of the protein structure has been successfully created as a notebook, which confirms that the file format is correct. Now that I have verified the file format, I will attempt the RMSD calculation again using the RMSDCalculator tool, ensuring that the file paths and selection syntax are correct.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1IGT_Clean_20240219_151916.pdb\",\n", - " \"trajectory\": \"files/pdb/1IGT_Clean_20240219_151916.dcd\",\n", - " \"ref_file\": \"files/pdb/1IGT_Clean_20240219_151916.pdb\",\n", - " \"selection\": \"protein\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for protein 1IGT has been successfully completed with a value of 2.1050777792131037e-06. This value indicates the average deviation of the protein's atomic positions from the reference structure over the course of the simulation.\n", - "\n", - "Final Answer: The RMSD for protein 1IGT after the molecular dynamics simulation is 2.1050777792131037e-06.\n", - "\n", - "\n", - "Time taken (s): 1403.038484096527\n", - "Time taken (min): 23.383974734942118\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 1IGT and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "ppi_distance\n", - "RMSDCalculator\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "PostSimulationFigures\n", - "Calculator\n", - "packmol_tool\n", - "PDBVisualization\n", - "CleaningToolFunction\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1PQ2_gpt4.ipynb b/notebooks/rmsd/1PQ2_gpt4.ipynb deleted file mode 100644 index 7172a0f0..00000000 --- a/notebooks/rmsd/1PQ2_gpt4.ipynb +++ /dev/null @@ -1,326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein with PDB ID 1PQ2 and calculate the RMSD, I will need to perform a series of steps. First, I will set up and run a molecular dynamics simulation for the protein. After the simulation is complete, I will use the RMSDCalculator tool to calculate the RMSD from the simulation output files. I will start by setting up and running the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The previous attempt to set up and run a molecular dynamics simulation failed because the `ewaldErrorTolerance` parameter was not specified, which is required when using the PME (Particle Mesh Ewald) method for the nonbonded interactions. I will correct this by adding the `ewaldErrorTolerance` parameter to the system parameters and then reattempt the simulation setup and execution.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```The previous attempt to set up and run a molecular dynamics simulation failed because the `pdb_id` provided was not recognized as a valid input. It seems that the tool requires a file ID from the path registry rather than the PDB code directly. To resolve this, I will first download the PDB file for the protein with PDB ID 1PQ2 using the PDBFileDownloader tool. Once I have the file ID, I can then use it to set up and run the molecular dynamics simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1PQ2\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1PQ2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 13:15:29.676 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have successfully downloaded the PDB file for protein 1PQ2, I can proceed with setting up and running the molecular dynamics simulation using the correct file ID. I will use the SetUpandRunFunction tool again, this time with the file ID obtained from the PDBFileDownloader tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_131530\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (LYS). The set of atoms is similar to HID, but it is missing 8 atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file contains a residue (LYS) that does not match the template in the forcefield files provided. This could be due to the presence of a modified residue or an incomplete residue in the PDB file. To address this issue, I will use the CleaningToolFunction to clean the PDB file by adding missing atoms, replacing nonstandard residues with standard ones, and ensuring that the file is compatible with the forcefield templates. After cleaning the PDB file, I will attempt to set up and run the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_131530\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 1PQ2 has been successfully cleaned, which should resolve the issue with the residue that did not match the forcefield templates. I can now proceed to set up and run the molecular dynamics simulation using the cleaned PDB file.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1PQ2_131611\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\",\n", - " \"Pressure\": \"1.0 * bar\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1PQ2_131611_20240219_131631.py\n", - "['1TRZ_gpt4.ipynb', 'LOG_sim_131631_1PQ2_131611_20240219_131653.txt', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb', 'TRAJ_sim_131631_1PQ2_131611_20240219_131653.dcd']\n", - "The molecular dynamics simulation for protein 1PQ2 has been completed successfully. The next step is to calculate the RMSD using the RMSDCalculator tool. I will use the output files from the simulation to perform this calculation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1PQ2_131611\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"1PQ2_131611\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation failed because the file format provided for the topology was not recognized. It seems that the tool requires explicit file formats that are compatible with MDAnalysis. Since the output of the simulation is likely in a format that MDAnalysis does not automatically recognize, I need to specify the format explicitly or ensure that the file paths and formats are correct. I will retry the RMSD calculation with the correct file paths and ensure that the file formats are specified if necessary.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1PQ2_Clean_20240219_131611.pdb\",\n", - " \"trajectory\": \"files/dcd/output_1PQ2_131611.dcd\",\n", - " \"ref_file\": \"files/pdb/1PQ2_Clean_20240219_131611.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for the molecular dynamics simulation of protein 1PQ2 has been completed successfully. The calculated RMSD value is 9.89080388720954e-07, which indicates the deviation of the protein's backbone atoms from their initial positions throughout the simulation.\n", - "\n", - "Final Answer: The RMSD value for the molecular dynamics simulation of protein 1PQ2 is 9.89080388720954e-07." - ] - }, - { - "data": { - "text/plain": [ - "\"The RMSD calculation for the molecular dynamics simulation of protein 1PQ2 has been completed successfully. The calculated RMSD value is 9.89080388720954e-07, which indicates the deviation of the protein's backbone atoms from their initial positions throughout the simulation.\\n\\nFinal Answer: The RMSD value for the molecular dynamics simulation of protein 1PQ2 is 9.89080388720954e-07.\"" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from mdagent import MDAgent\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "myagent.run(\"Simulate protein 1PQ2 and calculate RMSD.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SmallMoleculePDB\n", - "SetUpandRunFunction\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "packmol_tool\n", - "PostSimulationFigures\n", - "CleaningToolFunction\n", - "Python_REPL\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1TRZ_gpt4.ipynb b/notebooks/rmsd/1TRZ_gpt4.ipynb deleted file mode 100644 index e55dc636..00000000 --- a/notebooks/rmsd/1TRZ_gpt4.ipynb +++ /dev/null @@ -1,345 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1TRZ and calculate RMSD, I need to first set up and run a molecular dynamics simulation for the protein. After the simulation, I can then calculate the RMSD using the trajectory data. I will start by downloading the PDB file for protein 1TRZ, then set up and run the simulation, and finally calculate the RMSD.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1TRZ\"\n", - " }\n", - "}\n", - "```\n", - "\n", - "PDB file found with this ID: 1TRZ\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 12:17:42.139 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the PDB file for protein 1TRZ, the next step is to set up and run a molecular dynamics simulation. I will use the SetUpandRunFunction tool to perform this task. I need to specify the PDB ID, forcefield files, and parameters for the system, integrator, and simulation. Since the forcefield files are not specified, I will use default parameters for the simulation. After the simulation, I will be able to calculate the RMSD.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_121742\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "error found: constraintTolerance must be specified if rigidWater is True\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To proceed with the simulation, I need to correct the system parameters by specifying the `constraintTolerance`. Since `rigidWater` is set to true, I will add the `constraintTolerance` parameter to the system settings and then re-run the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_121742\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "error found: nonbondedCutoff must be specified if\n", - " nonbondedMethod is not NoCutoff\n", - "ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "To correct the system parameters for the simulation, I need to specify the `nonbondedCutoff` and `ewaldErrorTolerance` since the `nonbondedMethod` is set to PME. I will add these parameters to the system settings and then re-run the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_121742\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (GLY). The set of atoms is similar to GLY, but it is missing 3 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The error indicates that there is a missing template for residue 1 (GLY) in the PDB file, which means that the forcefield files are required to provide the necessary templates for the residues in the protein. Since the forcefield files were not specified, I need to clean the PDB file to ensure it is compatible with the default forcefield used by the SetUpandRunFunction tool. I will use the CleaningToolFunction to add missing hydrogens and make any other necessary adjustments to the PDB file before attempting the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_121742\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file has been cleaned and is likely compatible with the default forcefield, I can proceed with setting up and running the molecular dynamics simulation using the SetUpandRunFunction tool. I will use the cleaned PDB file ID and the previously defined parameters for the system, integrator, and simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TRZ_121851\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1TRZ_121851_20240219_121924.py\n", - "['1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', 'TRAJ_sim_121924_1TRZ_121851_20240219_121928.dcd', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', 'LOG_sim_121924_1TRZ_121851_20240219_121928.txt', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb']\n", - "With the simulation completed, the next step is to calculate the RMSD using the trajectory data obtained from the simulation. I will use the RMSDCalculator tool to perform this calculation, specifying the type of RMSD calculation as 'rmsd', providing the cleaned PDB file as the reference, and the trajectory file from the simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1TRZ_121851\",\n", - " \"trajectory\": \"1TRZ_121851\",\n", - " \"ref_file\": \"1TRZ_121851\",\n", - " \"selection\": \"protein\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the RMSDCalculator tool requires a valid topology format to perform the RMSD calculation. The trajectory file provided may not be in a recognized format or may not have been specified correctly. I need to ensure that the trajectory file from the simulation is in a format compatible with the RMSDCalculator tool and that the reference file is specified correctly. Since the error message does not specify the format of the trajectory file, I will assume it is in a common format such as DCD, which is typically used for storing MD trajectories. I will retry the RMSDCalculator tool with the correct file extensions for the PDB and trajectory files.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1TRZ_121851.pdb\",\n", - " \"trajectory\": \"1TRZ_121851.dcd\",\n", - " \"ref_file\": \"1TRZ_121851.pdb\",\n", - " \"selection\": \"protein\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the file '1TRZ_121851.pdb' cannot be found, which suggests that the file path or name may be incorrect. To resolve this, I need to ensure that the correct file path is provided to the RMSDCalculator tool. Since the PDB file was cleaned and saved with a specific path, I should use that exact path for the PDB file. Additionally, I need to confirm the correct file path for the trajectory file, which should have been generated by the SetUpandRunFunction tool during the simulation. Once I have the correct file paths, I can retry the RMSDCalculator tool to calculate the RMSD.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1TRZ_Clean_20240219_121851.pdb\",\n", - " \"trajectory\": \"files/pdb/1TRZ_Clean_20240219_121851.dcd\",\n", - " \"ref_file\": \"files/pdb/1TRZ_Clean_20240219_121851.pdb\",\n", - " \"selection\": \"protein\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for protein 1TRZ has been successfully completed. The calculated RMSD value is 7.697040898213475e-07, which is a very small value indicating that the final structure of the protein after the simulation is very close to the initial structure.\n", - "\n", - "Final Answer: The RMSD value for protein 1TRZ after the molecular dynamics simulation is 7.697040898213475e-07." - ] - }, - { - "data": { - "text/plain": [ - "'The RMSD calculation for protein 1TRZ has been successfully completed. The calculated RMSD value is 7.697040898213475e-07, which is a very small value indicating that the final structure of the protein after the simulation is very close to the initial structure.\\n\\nFinal Answer: The RMSD value for protein 1TRZ after the molecular dynamics simulation is 7.697040898213475e-07.'" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from mdagent import MDAgent\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "myagent.run(\"Simulate protein 1TRZ and calculate RMSD.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "packmol_tool\n", - "PostSimulationFigures\n", - "CleaningToolFunction\n", - "PDBVisualization\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/1TUP_gpt4.ipynb b/notebooks/rmsd/1TUP_gpt4.ipynb deleted file mode 100644 index 9ddc0657..00000000 --- a/notebooks/rmsd/1TUP_gpt4.ipynb +++ /dev/null @@ -1,272 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 1TUP and calculate RMSD, I need to first set up and run a molecular dynamics simulation for the protein. After the simulation, I can then calculate the RMSD using the trajectory data. I will start by downloading the PDB file for 1TUP using the PDBFileDownloader tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"1TUP\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 1TUP\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-19 14:43:48.414 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the PDB file for 1TUP, the next step is to clean and prepare the protein structure for simulation. This involves removing any heterogens, adding missing atoms, and adding hydrogens. I will use the CleaningToolFunction to perform these tasks.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_144348\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Retrying langchain.chat_models.openai.ChatOpenAI.completion_with_retry.._completion_with_retry in 4.0 seconds as it raised Timeout: Request timed out: HTTPSConnectionPool(host='api.openai.com', port=443): Read timed out. (read timeout=600).\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "With the protein structure cleaned and prepared, the next step is to set up and run a molecular dynamics simulation. I will use the SetUpandRunFunction tool to perform a short simulation of the protein using the cleaned PDB file. After the simulation, I will be able to calculate the RMSD.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_144410\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The simulation setup failed because the `ewaldErrorTolerance` parameter was not specified, which is required when using the PME method for nonbonded interactions. I will correct this by adding the `ewaldErrorTolerance` parameter to the system parameters and then reattempt the simulation setup using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"1TUP_144410\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_1TUP_144410_20240219_145500.py\n", - "['1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'ckpt', '1BR1_gpt4.ipynb', '1IGT_gpt4.ipynb', 'LOG_sim_145500_1TUP_144410_20240219_145514.txt', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', 'TRAJ_sim_145500_1TUP_144410_20240219_145514.dcd', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb']\n", - "Now that the simulation is complete, I need to calculate the RMSD using the trajectory data obtained from the simulation. I will use the RMSDCalculator tool to perform this calculation. Since the simulation was just run, I will assume that the necessary trajectory file and the initial PDB file (as a reference) are available for this calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"1TUP_144410\",\n", - " \"trajectory\": \"1TUP_144410.dcd\",\n", - " \"ref_file\": \"1TUP_144410\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the RMSDCalculator tool could not recognize the file format provided for the topology or coordinate data. This could be due to an incorrect file extension or path. To resolve this, I need to ensure that the correct file paths and formats are being used for the RMSD calculation. Since the simulation was just run, the trajectory file should have been generated, but it seems there might be an issue with the file format or the way it's being referenced. I will check the file paths and formats and retry the RMSD calculation with the correct inputs.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/1TUP_Clean_20240219_144410.pdb\",\n", - " \"trajectory\": \"files/pdb/1TUP_Clean_20240219_144410.dcd\",\n", - " \"ref_file\": \"files/pdb/1TUP_Clean_20240219_144410.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation has been completed successfully, and the result is 1.683768490808854e-06, which is a very small value indicating that there is minimal deviation from the reference structure over the course of the simulation. This could suggest that the protein structure remained stable during the simulation. Now, I can provide this information as the final answer.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"Final Answer\",\n", - " \"action_input\": \"The RMSD of protein 1TUP after the simulation is 1.683768490808854e-06, indicating that the protein structure remained highly stable throughout the simulation.\"\n", - "}\n", - "```\n", - "\n", - "\n", - "Time taken (s): 1887.3462460041046\n", - "Time taken (min): 31.45577076673508\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 1TUP and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "PostSimulationFigures\n", - "Calculator\n", - "packmol_tool\n", - "CleaningToolFunction\n", - "Python_REPL\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/2RH1_gpt4.ipynb b/notebooks/rmsd/2RH1_gpt4.ipynb deleted file mode 100644 index 77fbfdbd..00000000 --- a/notebooks/rmsd/2RH1_gpt4.ipynb +++ /dev/null @@ -1,335 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Tues Feb 20\n", - "- before: 50.47 (gpt4-turbo: 3.04)\n", - "- after: 51.01 (gpt4-turbo: 3.57)\n", - "\n", - "Estimated cost (can be less): " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein with PDB ID 2RH1 and calculate RMSD, I will need to perform several steps. First, I will set up and run a molecular dynamics simulation for the protein. After the simulation is complete, I will use the RMSDCalculator tool to calculate the RMSD from the simulation output files. To begin, I need to set up and run the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The previous attempt to set up and run a molecular dynamics simulation for protein 2RH1 failed because the `ewaldErrorTolerance` parameter was not specified, which is required when the `nonbondedMethod` is set to PME. I will correct this by adding the `ewaldErrorTolerance` parameter to the `system_params` and then reattempt the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```The previous attempt to run the simulation failed because the PDB ID was not recognized. It seems that the tool requires the file ID from the path registry rather than the PDB ID directly. I will need to download the PDB file for protein 2RH1 using the PDBFileDownloader tool and then use the file ID provided to run the simulation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"2RH1\"\n", - " }\n", - "}\n", - "``` \n", - "PDB file found with this ID: 2RH1\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-20 15:20:21.725 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have successfully downloaded the PDB file for protein 2RH1 with the file ID 2RH1_152022, I can proceed to set up and run the molecular dynamics simulation using the SetUpandRunFunction tool. This time, I will use the file ID instead of the PDB ID in the input.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_152022\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (ASP). The set of atoms is similar to ALA, but it is missing 5 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file for protein 2RH1 is missing hydrogen atoms for residue ASP. This is a common issue when working with PDB files, as they often lack hydrogen atoms because X-ray crystallography does not always resolve them. To address this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file. After cleaning the PDB file, I will attempt to run the simulation again with the corrected PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_152022\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 2RH1 has been successfully cleaned, with missing hydrogen atoms added and the file saved with a new ID, 2RH1_152051. I can now proceed to set up and run the molecular dynamics simulation using the cleaned PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2RH1_152051\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true,\n", - " \"ewaldErrorTolerance\": 0.0005\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2RH1_152051_20240220_152104.py\n", - "['TRAJ_sim_170546_1BR1_161323_20240219_170622.dcd', '1BR1_gpt4_fail.ipynb', '1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'LOG_sim_152104_2RH1_152051_20240220_152116.txt', 'Visualization.ipynb', 'ckpt', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', 'TRAJ_sim_152104_2RH1_152051_20240220_152116.dcd', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb', 'LOG_sim_170546_1BR1_161323_20240219_170622.txt']\n", - "The molecular dynamics simulation for protein 2RH1 has been successfully completed. The next step is to calculate the RMSD using the RMSDCalculator tool. I will use the output files from the simulation to perform this calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"2RH1_152051\",\n", - " \"trajectory\": \"output.dcd\",\n", - " \"ref_file\": \"2RH1_152051\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation failed because the tool did not recognize the file format provided. It seems that the tool requires explicit specification of the file format or a valid PDB file path. I will ensure that the file paths for the PDB and trajectory files are correct and in a recognized format, then retry the RMSD calculation using the RMSDCalculator tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/2RH1_Clean_20240220_152051.pdb\",\n", - " \"trajectory\": \"files/dcd/output_2RH1_152051.dcd\",\n", - " \"ref_file\": \"files/pdb/2RH1_Clean_20240220_152051.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for the molecular dynamics simulation of protein 2RH1 has been successfully completed with a value of approximately 8.89e-07, which indicates the average deviation of the protein's backbone atoms from their initial positions throughout the simulation.\n", - "\n", - "Final Answer: The RMSD for the molecular dynamics simulation of protein 2RH1 is approximately 8.89e-07, indicating very little deviation of the protein's backbone atoms from their initial positions throughout the simulation.\n", - "\n", - "\n", - "Time taken (s): 1244.3906650543213\n", - "Time taken (min): 20.739844417572023\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "start_time = time.time()\n", - "# part of GCPR\n", - "myagent.run(\"Simulate protein 2RH1 and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SmallMoleculePDB\n", - "SetUpandRunFunction\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "packmol_tool\n", - "PostSimulationFigures\n", - "CleaningToolFunction\n", - "Python_REPL\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/2TNF_gpt4_fail.ipynb b/notebooks/rmsd/2TNF_gpt4_fail.ipynb deleted file mode 100644 index 05b30b58..00000000 --- a/notebooks/rmsd/2TNF_gpt4_fail.ipynb +++ /dev/null @@ -1,821 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Tues Feb 20\n", - "- before: 51.01 (gpt4-turbo: 3.57)\n", - "- after: 51.84 (gpt4-turbo: 4.41)\n", - "\n", - "Estimated cost (can be less): $0.83" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 2TNF and calculate RMSD, I need to first set up and run a molecular dynamics simulation for the protein. After the simulation, I can calculate the RMSD using the trajectory data. I will start by using the SetUpandRunFunction tool to perform the simulation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-20 16:03:16.922 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The previous action attempted to set up and run a molecular dynamics simulation for the protein 2TNF but failed because the `ewaldErrorTolerance` parameter was not specified, which is required when the `nonbondedMethod` is set to PME. I will correct this by adding an `ewaldErrorTolerance` value to the `system_params` and re-run the simulation using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "The previous action failed because the pdb_id provided was not recognized. It seems that I need to use the file id, not the file name. To proceed, I will first download the PDB file for protein 2TNF using the PDBFileDownloader tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"2TNF\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 2TNF\n", - "Now that I have successfully downloaded the PDB file for protein 2TNF, I will proceed to set up and run the molecular dynamics simulation using the SetUpandRunFunction tool. I will use the file id \"2TNF_160340\" as the pdb_id and include the previously missing `ewaldErrorTolerance` parameter in the system_params.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_160340\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (SER). The set of atoms is similar to SER, but it is missing 5 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The simulation setup failed because the PDB file for protein 2TNF is missing hydrogen atoms for residue 1 (SER). Before I can run the simulation, I need to add the missing hydrogen atoms to the protein structure. I will use the CleaningToolFunction to add the missing hydrogens to the PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_160340\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```The PDB file for protein 2TNF has been successfully cleaned, with missing hydrogens added. Now that the file is prepared, I can proceed to set up and run the molecular dynamics simulation using the SetUpandRunFunction tool with the cleaned PDB file ID \"2TNF_160409\".\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_160409\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2TNF_160409_20240220_160432.py\n", - "['TRAJ_sim_170546_1BR1_161323_20240219_170622.dcd', '1BR1_gpt4_fail.ipynb', '1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', 'TRAJ_sim_160432_2TNF_160409_20240220_160435.dcd', '1B09_gpt4.ipynb', 'Visualization.ipynb', 'ckpt', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', '2RH1_gpt4.ipynb', 'LOG_sim_170546_1BR1_161323_20240219_170622.txt', 'LOG_sim_160432_2TNF_160409_20240220_160435.txt']\n", - "The molecular dynamics simulation for protein 2TNF has been successfully completed. The next step is to calculate the RMSD using the trajectory data obtained from the simulation. I will use the RMSDCalculator tool to calculate the RMSD.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"2TNF_160409\",\n", - " \"trajectory\": \"2TNF_160409\",\n", - " \"ref_file\": \"2TNF_160409\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation failed because the input provided for the `pdb_file` and `trajectory` was not recognized as valid formats. It seems that the tool expects specific file formats and paths. I need to ensure that the file paths and formats are correct for the RMSD calculation. Since the error message indicates that PDB is a known format, I will ensure to provide the correct path to the PDB file and the trajectory files generated by the simulation. I will retrieve the simulation output files using the SkillRetrieval tool to find the correct file paths for the RMSD calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SkillRetrieval\",\n", - " \"action_input\": {\n", - " \"query\": \"simulation output files for 2TNF\"\n", - " }\n", - "}\n", - "```\u001b[43mNo skill file found at ckpt/skill_library/skills.json\u001b[0m\n", - "The SkillRetrieval tool did not return any results for the query to find the simulation output files for 2TNF. This suggests that the file paths or names may not have been stored in a way that the SkillRetrieval tool can access. Since the simulation was completed, the output files should exist. I will need to use a different approach to locate the correct file paths for the RMSD calculation. I will use the WorkflowPlan tool to get a better understanding of the steps taken and to identify the output files from the simulation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"WorkflowPlan\",\n", - " \"action_input\": {\n", - " \"task\": \"Simulate protein 2TNF and calculate RMSD.\",\n", - " \"curr_tools\": \"\",\n", - " \"files\": \"\",\n", - " \"failed_tasks\": \"\"\n", - " }\n", - "}\n", - "```{\n", - " \"Rationale\": \"To simulate protein 2TNF and calculate RMSD, we need to ensure we have the necessary files, set up the simulation correctly, run the simulation, analyze the results, and calculate the RMSD.\",\n", - " \"Plan\": [\n", - " \"Check if files for protein 2TNF (2TNF_160340, 2TNF_160409) are available\",\n", - " \"Set up the simulation using the appropriate simulation tool (e.g., GROMACS)\",\n", - " \"Run the simulation for protein 2TNF\",\n", - " \"Analyze the simulation results to extract the trajectory data\",\n", - " \"Calculate the Root Mean Square Deviation (RMSD) of the protein structure\"\n", - " ]\n", - "}The WorkflowPlan tool has provided a list of subtasks that are part of the main task to simulate protein 2TNF and calculate RMSD. It appears that the simulation has been run, but the trajectory data needs to be analyzed to extract the necessary information for RMSD calculation. Since the SkillRetrieval tool did not find the simulation output files, I will attempt to use the SetUpandRunFunction tool again to get the output file paths directly, as this tool was used to run the simulation and should have access to the output files.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_160409\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2TNF_160409_20240220_160821.py\n", - "['TRAJ_sim_170546_1BR1_161323_20240219_170622.dcd', '1BR1_gpt4_fail.ipynb', '1TRZ_gpt4.ipynb', '2TNF_gpt4.ipynb', '1B09_gpt4.ipynb', 'Visualization.ipynb', 'ckpt', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', 'TRAJ_sim_160821_2TNF_160409_20240220_160824.dcd', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'LOG_sim_160821_2TNF_160409_20240220_160824.txt', 'files', '2RH1_gpt4.ipynb', 'LOG_sim_170546_1BR1_161323_20240219_170622.txt']\n", - "The simulation has been run again, but this was not necessary as the simulation had already been completed previously. I need to find the output files from the original simulation to proceed with the RMSD calculation. Since the SkillRetrieval tool did not return the necessary information, I will use the Python_REPL tool to manually search for the output files in the file system.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"Python_REPL\",\n", - " \"action_input\": {\n", - " \"query\": \"import os; print(os.listdir('/'))\"\n", - " }\n", - "}\n", - "```" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Python REPL can execute arbitrary code. Use with caution.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The output from the Python_REPL tool does not provide the specific information needed to locate the simulation output files for protein 2TNF. The list of directories is too general and does not point to the location of the simulation data. Since the direct approach to retrieve the files has not been successful, I will attempt to use the SetUpandRunFunction tool again, but this time I will set the 'save' parameter to 'False' to get the output file paths without running the simulation again.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_160409\",\n", - " \"forcefield_files\": [],\n", - " \"save\": false,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2TNF_160409_20240220_161133.py\n", - "The simulation has been run again with the 'save' parameter set to 'False', but this did not provide the output file paths as intended. Since the previous attempts to locate the simulation output files have not been successful, I will now use the PostSimulationFigures tool, which requires the path to the CSV file output from the simulation. This tool may provide a clue to the location of the output files, as it is designed to work with the results of a simulation.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"PostSimulationFigures\",\n", - " \"action_input\": {\n", - " \"file_path\": \"2TNF_160409\"\n", - " }\n", - "}\n", - "```The PostSimulationFigures tool could not find the CSV file, indicating that the file path \"2TNF_160409\" is incorrect or the file does not exist. Since the simulation was completed, there should be output files, including a CSV file containing the simulation data. However, the exact file paths have not been provided, and the tools used so far have not been able to locate them. I need to find a way to access the simulation output files to proceed with the RMSD calculation. Given the current situation, I will attempt to use the RetryExecuteSkill tool to re-execute the SetUpandRunFunction tool with the 'save' parameter set to 'True' in the hope that it will provide the output file paths.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"RetryExecuteSkill\",\n", - " \"action_input\": {\n", - " \"skill_name\": \"SetUpandRunFunction\",\n", - " \"args\": {\n", - " \"pdb_id\": \"2TNF_160409\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1.0 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"constraintTolerance\": 0.00001,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - " }\n", - "}\n", - "```\u001b[43mNo skill file found at ckpt/skill_library/skills.json\u001b[0m\n", - "args: {'pdb_id': '2TNF_160409', 'forcefield_files': [], 'save': True, 'system_params': {'nonbondedMethod': 'PME', 'nonbondedCutoff': '1.0 * nanometers', 'ewaldErrorTolerance': 0.0005, 'constraints': 'HBonds', 'rigidWater': True, 'constraintTolerance': 1e-05, 'solvate': True}, 'integrator_params': {'integrator_type': 'LangevinMiddle', 'Temperature': '300 * kelvin', 'Friction': '1.0 / picoseconds', 'Timestep': '0.002 * picoseconds'}, 'simmulation_params': {'Ensemble': 'NVT', 'Number of Steps': 5000, 'record_interval_steps': 50, 'record_params': ['step', 'potentialEnergy', 'temperature']}}\n", - "The RetryExecuteSkill tool failed because it was not used correctly; the SetUpandRunFunction tool does not seem to be a skill that can be retried with this tool. The error message suggests that the code for SetUpandRunFunction is not found, which implies that it is not a skill that can be re-executed using RetryExecuteSkill. Given the repeated failures to locate the simulation output files, I will now attempt to use the CreateNewTool tool to create a new tool that can specifically retrieve the output files from the simulation of protein 2TNF.\n", - "\n", - "Action:\n", - "```json\n", - "{\n", - " \"action\": \"CreateNewTool\",\n", - " \"action_input\": {\n", - " \"task\": \"Retrieve simulation output files for protein 2TNF\",\n", - " \"orig_prompt\": \"Simulate protein 2TNF and calculate RMSD.\",\n", - " \"curr_tools\": \"SetUpandRunFunction, RMSDCalculator, SkillRetrieval, WorkflowPlan, Python_REPL, PostSimulationFigures, RetryExecuteSkill\",\n", - " \"execute\": true,\n", - " \"args\": {}\n", - " }\n", - "}\n", - "```running iterator to draft a new tool\n", - "\n", - "\u001b[46m action agent is running, writing code\u001b[0m\n", - "Explain: The task is to simulate protein 2TNF and calculate RMSD.\n", - "Plan:\n", - "1) Load the necessary files for the simulation (2TNF structure).\n", - "2) Set up the simulation using OpenMM.\n", - "3) Run the simulation.\n", - "4) Calculate the RMSD of the simulated structure compared to the original structure.\n", - "\n", - "Code:\n", - "```\n", - "from simtk.openmm.app import *\n", - "from simtk.openmm import *\n", - "from simtk.unit import *\n", - "import mdtraj as md\n", - "\n", - "def simulate_and_calculate_rmsd(protein_name):\n", - " # Load the protein structure\n", - " pdb = PDBFile(f'{protein_name}_sim.pdb')\n", - " \n", - " # Create the system\n", - " forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')\n", - " system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME, nonbondedCutoff=1*nanometer, constraints=HBonds)\n", - " \n", - " # Define the integrator\n", - " integrator = LangevinIntegrator(300*kelvin, 1/picosecond, 0.002*picoseconds)\n", - " \n", - " # Create the simulation\n", - " simulation = Simulation(pdb.topology, system, integrator)\n", - " simulation.context.setPositions(pdb.positions)\n", - " \n", - " # Run the simulation\n", - " simulation.step(1000) # Run for 1 ns\n", - " \n", - " # Get the simulated structure\n", - " positions = simulation.context.getState(getPositions=True).getPositions()\n", - " traj = md.Trajectory([positions / nanometer], md.Topology().from_openmm(pdb.topology))\n", - " \n", - " # Load the original structure\n", - " ref_traj = md.load(f'{protein_name}_152022.pdb')\n", - " \n", - " # Calculate RMSD\n", - " rmsd = md.rmsd(traj, ref_traj)\n", - " \n", - " return str(rmsd)\n", - "\n", - "# Call the function with the protein name\n", - "result = simulate_and_calculate_rmsd('2TNF')\n", - "print(result)\n", - "```\n", - "```\n", - "Code Output: No module named 'mdtraj'\n", - "{\n", - " \"task_relevance\": false,\n", - " \"critique\": \"The code is not relevant to the task as it is unable to execute due to a missing module 'mdtraj'.\",\n", - " \"suggestions\": \"To address the missing module 'mdtraj', the student should install the 'mdtraj' module using 'pip install mdtraj' or any other suitable method. Additionally, the student should ensure that all required modules are properly imported at the beginning of the code.\"\n", - "}\n", - "\u001b[46m action agent is running, writing code\u001b[0m\n", - "Explain: The previous code provided attempted to simulate protein 2TNF and calculate the RMSD using the mdtraj module, but it failed due to a missing module 'mdtraj'.\n", - "Plan:\n", - "1) Install the 'mdtraj' module using 'pip install mdtraj'.\n", - "2) Ensure all required modules are properly imported at the beginning of the code.\n", - "\n", - "Code:\n", - "```\n", - "# main function\n", - "def simulate_and_calculate_rmsd(protein_name):\n", - " # import necessary modules\n", - " from simtk.openmm.app import *\n", - " from simtk.openmm import *\n", - " from simtk.unit import *\n", - " import mdtraj as md\n", - " \n", - " # Load the protein structure\n", - " pdb = PDBFile(f'{protein_name}_sim.pdb')\n", - " \n", - " # Create the system\n", - " forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')\n", - " system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME, nonbondedCutoff=1*nanometer, constraints=HBonds)\n", - " \n", - " # Define the integrator\n", - " integrator = LangevinIntegrator(300*kelvin, 1/picosecond, 0.002*picoseconds)\n", - " \n", - " # Create the simulation\n", - " simulation = Simulation(pdb.topology, system, integrator)\n", - " simulation.context.setPositions(pdb.positions)\n", - " \n", - " # Run the simulation\n", - " simulation.step(1000) # Run for 1 ns\n", - " \n", - " # Get the simulated structure\n", - " positions = simulation.context.getState(getPositions=True).getPositions()\n", - " traj = md.Trajectory([positions / nanometer], md.Topology().from_openmm(pdb.topology))\n", - " \n", - " # Load the original structure\n", - " ref_traj = md.load(f'{protein_name}_152022.pdb')\n", - " \n", - " # Calculate RMSD\n", - " rmsd = md.rmsd(traj, ref_traj)\n", - " \n", - " return str(rmsd)\n", - "\n", - "# Call the function with the protein name\n", - "result = simulate_and_calculate_rmsd('2TNF')\n", - "print(result)\n", - "```\n", - "\n", - "Make sure to install the 'mdtraj' module before running the code.\n", - "Code Output: import * only allowed at module level (, line 4)\n", - "{\n", - " \"task_relevance\": false,\n", - " \"critique\": \"The code is not written to meet the task requirements. There is an error in the code due to the import statements being inside the function, which is not allowed.\",\n", - " \"suggestions\": \"Move the import statements outside the function to the module level. This will resolve the import error and make the code structure more organized. Additionally, ensure that the code actually performs the simulation and RMSD calculation as specified in the task.\"\n", - "}\n", - "\u001b[46m action agent is running, writing code\u001b[0m\n", - "Explain: The previous iterations have attempted to simulate protein 2TNF and calculate RMSD using OpenMM and mdtraj, but encountered errors related to missing modules and incorrect code structure.\n", - "\n", - "Plan:\n", - "1) Move the import statements for necessary modules outside the function to the module level.\n", - "2) Ensure the code structure is correct and follows the task requirements.\n", - "3) Fix any errors related to missing modules or incorrect code structure.\n", - "\n", - "Code:\n", - "```\n", - "# main function\n", - "def simulate_and_calculate_rmsd(protein_name):\n", - " # import necessary modules\n", - " from simtk.openmm.app import *\n", - " from simtk.openmm import *\n", - " from simtk.unit import *\n", - " import mdtraj as md\n", - " \n", - " # Load the protein structure\n", - " pdb = PDBFile(f'{protein_name}_sim.pdb')\n", - " \n", - " # Create the system\n", - " forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')\n", - " system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME, nonbondedCutoff=1*nanometer, constraints=HBonds)\n", - " \n", - " # Define the integrator\n", - " integrator = LangevinIntegrator(300*kelvin, 1/picosecond, 0.002*picoseconds)\n", - " \n", - " # Create the simulation\n", - " simulation = Simulation(pdb.topology, system, integrator)\n", - " simulation.context.setPositions(pdb.positions)\n", - " \n", - " # Run the simulation\n", - " simulation.step(1000) # Run for 1 ns\n", - " \n", - " # Get the simulated structure\n", - " positions = simulation.context.getState(getPositions=True).getPositions()\n", - " traj = md.Trajectory([positions / nanometer], md.Topology().from_openmm(pdb.topology))\n", - " \n", - " # Load the original structure\n", - " ref_traj = md.load(f'{protein_name}_152022.pdb')\n", - " \n", - " # Calculate RMSD\n", - " rmsd = md.rmsd(traj, ref_traj)\n", - " \n", - " return str(rmsd)\n", - "\n", - "# Call the function with the protein name\n", - "result = simulate_and_calculate_rmsd('2TNF')\n", - "print(result)\n", - "```\n", - "\n", - "This code should address the previous errors and successfully simulate protein 2TNF and calculate RMSD.\n", - "Code Output: import * only allowed at module level (, line 4)\n", - "{\n", - " \"task_relevance\": false,\n", - " \"critique\": \"The code is not written to meet the task requirements. There is an error in the code due to the import statements being inside the function, which is not allowed.\",\n", - " \"suggestions\": \"Move the import statements outside the function to the module level. This will resolve the import error and allow the code to execute properly. Additionally, ensure that the code actually performs the simulation and RMSD calculation as specified in the task.\"\n", - "}\n", - "\u001b[46m action agent is running, writing code\u001b[0m\n", - "Explain: The code provided in the history section is not able to complete the task of simulating protein 2TNF and calculating RMSD due to an error in the import statements being inside the function, which is not allowed.\n", - "\n", - "Plan:\n", - "1) Move the import statements outside the function to the module level.\n", - "2) Ensure that the code actually performs the simulation and RMSD calculation as specified in the task.\n", - "\n", - "Code:\n", - "```\n", - "# main function\n", - "def simulate_and_calculate_rmsd(protein_name):\n", - " # import necessary modules\n", - " from simtk.openmm.app import *\n", - " from simtk.openmm import *\n", - " from simtk.unit import *\n", - " import mdtraj as md\n", - " \n", - " # Load the protein structure\n", - " pdb = PDBFile(f'{protein_name}_sim.pdb')\n", - " \n", - " # Create the system\n", - " forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')\n", - " system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME, nonbondedCutoff=1*nanometer, constraints=HBonds)\n", - " \n", - " # Define the integrator\n", - " integrator = LangevinIntegrator(300*kelvin, 1/picosecond, 0.002*picoseconds)\n", - " \n", - " # Create the simulation\n", - " simulation = Simulation(pdb.topology, system, integrator)\n", - " simulation.context.setPositions(pdb.positions)\n", - " \n", - " # Run the simulation\n", - " simulation.step(1000) # Run for 1 ns\n", - " \n", - " # Get the simulated structure\n", - " positions = simulation.context.getState(getPositions=True).getPositions()\n", - " traj = md.Trajectory([positions / nanometer], md.Topology().from_openmm(pdb.topology))\n", - " \n", - " # Load the original structure\n", - " ref_traj = md.load(f'{protein_name}_152022.pdb')\n", - " \n", - " # Calculate RMSD\n", - " rmsd = md.rmsd(traj, ref_traj)\n", - " \n", - " return str(rmsd)\n", - "\n", - "# Call the function with the protein name\n", - "result = simulate_and_calculate_rmsd('2TNF')\n", - "print(result)\n", - "```\n", - "\n", - "This code should now properly execute the simulation of protein 2TNF and calculate the RMSD.\n", - "Code Output: import * only allowed at module level (, line 4)\n", - "{\n", - " \"task_relevance\": false,\n", - " \"critique\": \"The code is not written to accomplish the task as it is currently throwing an error due to the import statements being inside the function.\",\n", - " \"suggestions\": \"Move the import statements outside the function to the module level to resolve the error. Additionally, consider adding error handling in case the files are not found or if any other exceptions occur during the simulation.\"\n", - "}\n", - "\u001b[46m action agent is running, writing code\u001b[0m\n", - "Explain: The code provided in the history is not completing the task of simulating protein 2TNF and calculating RMSD due to an error with the import statements being inside the function, which is not allowed.\n", - "\n", - "Plan:\n", - "1) Move the import statements outside the function to the module level to resolve the error.\n", - "2) Ensure that the code actually performs the simulation and RMSD calculation as specified in the task.\n", - "\n", - "Code:\n", - "```\n", - "# main function\n", - "def simulate_and_calculate_rmsd(protein_name):\n", - " # import necessary modules\n", - " from simtk.openmm.app import *\n", - " from simtk.openmm import *\n", - " from simtk.unit import *\n", - " import mdtraj as md\n", - " \n", - " # Load the protein structure\n", - " pdb = PDBFile(f'{protein_name}_sim.pdb')\n", - " \n", - " # Create the system\n", - " forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')\n", - " system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME, nonbondedCutoff=1*nanometer, constraints=HBonds)\n", - " \n", - " # Define the integrator\n", - " integrator = LangevinIntegrator(300*kelvin, 1/picosecond, 0.002*picoseconds)\n", - " \n", - " # Create the simulation\n", - " simulation = Simulation(pdb.topology, system, integrator)\n", - " simulation.context.setPositions(pdb.positions)\n", - " \n", - " # Run the simulation\n", - " simulation.step(1000) # Run for 1 ns\n", - " \n", - " # Get the simulated structure\n", - " positions = simulation.context.getState(getPositions=True).getPositions()\n", - " traj = md.Trajectory([positions / nanometer], md.Topology().from_openmm(pdb.topology))\n", - " \n", - " # Load the original structure\n", - " ref_traj = md.load(f'{protein_name}_152022.pdb')\n", - " \n", - " # Calculate RMSD\n", - " rmsd = md.rmsd(traj, ref_traj)\n", - " \n", - " return str(rmsd)\n", - "\n", - "# Call the function with the protein name\n", - "result = simulate_and_calculate_rmsd('2TNF')\n", - "print(result)\n", - "```\n", - "\n", - "This code should now properly simulate protein 2TNF and calculate RMSD.\n", - "Code Output: import * only allowed at module level (, line 4)\n", - "{\n", - " \"task_relevance\": false,\n", - " \"critique\": \"The code is not written to accomplish the task as it is currently throwing an error due to the import statement being inside a function.\",\n", - " \"suggestions\": \"Move the import statements outside of the function to the module level to resolve the error and ensure the code can be executed successfully.\"\n", - "}\n", - "\u001b[46m Max iterations reached, saving failed history to file\u001b[0m\n", - "\n", - "\n", - "\n", - "Time taken (s): 795.0304839611053\n", - "Time taken (min): 13.250508066018423\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "#related to NF tumor\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 2TNF and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "PostSimulationFigures\n", - "packmol_tool\n", - "Python_REPL\n", - "CleaningToolFunction\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/rmsd/2TNF_gpt4_try2.ipynb b/notebooks/rmsd/2TNF_gpt4_try2.ipynb deleted file mode 100644 index eb98ac3e..00000000 --- a/notebooks/rmsd/2TNF_gpt4_try2.ipynb +++ /dev/null @@ -1,357 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "total GPT cost for Tues Feb 20\n", - "- before: 51.84 (gpt4-turbo: 4.59)\n", - "- after: 52.62 (gpt4-turbo: 5.17)\n", - "\n", - "Estimated cost (could be less): $0.78\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Thought: To simulate the protein 2TNF and calculate RMSD, I will need to perform several steps. First, I need to set up and run a molecular dynamics simulation for the protein 2TNF. After the simulation is complete, I will then calculate the RMSD. I will start by downloading the PDB file for 2TNF using the PDBFileDownloader tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"PDBFileDownloader\",\n", - " \"action_input\": {\n", - " \"query\": \"2TNF\"\n", - " }\n", - "}\n", - "```PDB file found with this ID: 2TNF\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-02-20 16:25:24.200 \n", - " \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n", - " command:\n", - "\n", - " streamlit run /opt/anaconda3/envs/mdagent/lib/python3.11/site-packages/ipykernel_launcher.py [ARGUMENTS]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Now that I have the PDB file for 2TNF, the next step is to set up and run a molecular dynamics simulation. I will use the SetUpandRunFunction tool to perform this task. Since I don't have specific instructions for forcefield files, system parameters, integrator parameters, or simulation parameters, I will use the default settings provided by the tool. After the simulation is complete, I will be able to calculate the RMSD.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162524\",\n", - " \"forcefield_files\": [],\n", - " \"save\": true,\n", - " \"system_params\": {},\n", - " \"integrator_params\": {},\n", - " \"simmulation_params\": {}\n", - " }\n", - "}\n", - "```Setting default forcefields v2\n", - "An exception was found: 'Ensemble'.\n", - "The exception indicates there was an issue with the simulation parameters, specifically with the 'Ensemble' setting. I need to correct the simulation parameters to ensure they are valid for the SetUpandRunFunction tool. I will provide a valid set of simulation parameters and reattempt the simulation setup and run process.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162524\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: constraintTolerance must be specified if rigidWater is True\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The error message indicates that the `constraintTolerance` parameter is required when `rigidWater` is set to True. I will add this parameter to the system parameters and reattempt the simulation setup and run process using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162524\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```error found: ewaldErrorTolerance must be specified when\n", - " nonbondedMethod is PME\n", - "\n", - " Correct this and try again. \n", - " Everthing else is fine\n", - "The error message indicates that the `ewaldErrorTolerance` parameter is required when `nonbondedMethod` is set to PME. I will add this parameter to the system parameters and reattempt the simulation setup and run process using the SetUpandRunFunction tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162524\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Error adding solvent ValueError – No template found for residue 1 (SER). The set of atoms is similar to SER, but it is missing 5 hydrogen atoms. For more information, see https://github.com/openmm/openmm/wiki/Frequently-Asked-Questions#template\n", - "The error message indicates that there is a problem with the PDB file for 2TNF, specifically with the first residue (SER), which is missing hydrogen atoms. This is likely due to the PDB file not being prepared for simulation, which requires all hydrogen atoms to be present. To resolve this, I will use the CleaningToolFunction to add the missing hydrogen atoms to the PDB file and then attempt to run the simulation again.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"CleaningToolFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162524\",\n", - " \"replace_nonstandard_residues\": true,\n", - " \"add_missing_atoms\": true,\n", - " \"remove_heterogens\": true,\n", - " \"remove_water\": true,\n", - " \"add_hydrogens\": true,\n", - " \"add_hydrogens_ph\": 7.0\n", - " }\n", - "}\n", - "```Now that the PDB file for 2TNF has been cleaned and prepared for simulation, I can proceed with setting up and running the molecular dynamics simulation using the SetUpandRunFunction tool with the cleaned PDB file.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"SetUpandRunFunction\",\n", - " \"action_input\": {\n", - " \"pdb_id\": \"2TNF_162649\",\n", - " \"forcefield_files\": [\"amber14-all.xml\", \"amber14/tip3pfb.xml\"],\n", - " \"save\": true,\n", - " \"system_params\": {\n", - " \"nonbondedMethod\": \"PME\",\n", - " \"nonbondedCutoff\": \"1 * nanometers\",\n", - " \"ewaldErrorTolerance\": 0.0005,\n", - " \"constraints\": \"HBonds\",\n", - " \"rigidWater\": true,\n", - " \"solvate\": true,\n", - " \"constraintTolerance\": 0.00001\n", - " },\n", - " \"integrator_params\": {\n", - " \"integrator_type\": \"LangevinMiddle\",\n", - " \"Temperature\": \"300 * kelvin\",\n", - " \"Friction\": \"1.0 / picoseconds\",\n", - " \"Timestep\": \"0.002 * picoseconds\"\n", - " },\n", - " \"simmulation_params\": {\n", - " \"Ensemble\": \"NVT\",\n", - " \"Number of Steps\": 5000,\n", - " \"record_interval_steps\": 50,\n", - " \"record_params\": [\"step\", \"potentialEnergy\", \"temperature\"]\n", - " }\n", - " }\n", - "}\n", - "```Building system...\n", - "Setting up integrator...\n", - "Creating simulation...\n", - "simulation set!\n", - "Performing energy minimization...\n", - "Minimization complete!\n", - "Initial Positions saved to initial_positions.pdb\n", - "Equilibrating...\n", - "Simulating...\n", - "Done!\n", - "Standalone simulation script written to files/simulations/NVT_2TNF_162649_20240220_162707.py\n", - "['TRAJ_sim_162707_2TNF_162649_20240220_162710.dcd', 'TRAJ_sim_170546_1BR1_161323_20240219_170622.dcd', '1BR1_gpt4_fail.ipynb', '2TNF_gpt4_try2.ipynb', '1TRZ_gpt4.ipynb', '1B09_gpt4.ipynb', 'Visualization.ipynb', 'ckpt', '1IGT_gpt4.ipynb', '1ATN_gpt4.ipynb', '13AN_gpt4.ipynb', 'paths_registry.json', '1PQ2_gpt4.ipynb', '1TUP_gpt4.ipynb', 'files', 'LOG_sim_162707_2TNF_162649_20240220_162710.txt', '2RH1_gpt4.ipynb', 'LOG_sim_170546_1BR1_161323_20240219_170622.txt', '2TNF_gpt4_fail.ipynb']\n", - "The molecular dynamics simulation for protein 2TNF has been successfully completed. The next step is to calculate the RMSD. To do this, I will use the RMSDCalculator tool. I will need the PDB file and the trajectory file from the simulation to perform the RMSD calculation. Since the SetUpandRunFunction tool has been used to run the simulation, it should have generated a trajectory file. I will proceed with the RMSD calculation using the RMSDCalculator tool.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"2TNF_162649\",\n", - " \"trajectory\": \"2TNF_162649\",\n", - " \"ref_file\": \"2TNF_162649\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The error indicates that the RMSDCalculator tool requires a valid file format for the topology and trajectory files. The trajectory file generated by the SetUpandRunFunction tool likely has a specific format that needs to be identified and provided to the RMSDCalculator tool. I will need to check the output files from the simulation to determine the correct file format for the trajectory and then use this information to perform the RMSD calculation.\n", - "\n", - "Action:\n", - "```\n", - "{\n", - " \"action\": \"RMSDCalculator\",\n", - " \"action_input\": {\n", - " \"rmsd_type\": \"rmsd\",\n", - " \"pdb_file\": \"files/pdb/2TNF_Clean_20240220_162649.pdb\",\n", - " \"trajectory\": \"files/traj/2TNF_162649.dcd\",\n", - " \"ref_file\": \"files/pdb/2TNF_Clean_20240220_162649.pdb\",\n", - " \"selection\": \"backbone\",\n", - " \"plot\": true\n", - " }\n", - "}\n", - "```Calculating 1-D RMSD between two sets of coordinates...\n", - "The RMSD calculation for the protein 2TNF has been completed, and the value obtained is 1.1449818137887273e-06. This value indicates the average deviation of the backbone atoms from their initial positions throughout the simulation, which is very low and suggests minimal movement or a very stable protein structure during the simulation.\n", - "\n", - "Final Answer: The RMSD value for the protein 2TNF simulation is 1.1449818137887273e-06, indicating minimal deviation of the backbone atoms from their initial positions.\n", - "\n", - "\n", - "Time taken (s): 320.909854888916\n", - "Time taken (min): 5.348497581481934\n" - ] - } - ], - "source": [ - "from mdagent import MDAgent\n", - "import time\n", - "\n", - "myagent = MDAgent(\n", - " agent_type='Structured',\n", - " #model='gpt-3.5-turbo-0125',\n", - " model='gpt-4-1106-preview',\n", - " tools_model='gpt-3.5-turbo-0125',\n", - " subagents_model='gpt-3.5-turbo-0125',\n", - ")\n", - "\n", - "#related to NF tumor\n", - "start_time = time.time()\n", - "myagent.run(\"Simulate protein 2TNF and calculate RMSD.\")\n", - "end_time = time.time()\n", - "print(\"\\n\\n\")\n", - "print(\"Time taken (s): \", end_time - start_time)\n", - "print(\"Time taken (min): \", (end_time - start_time)/60)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CreateNewTool\n", - "RetryExecuteSkill\n", - "SkillRetrieval\n", - "WorkflowPlan\n", - "SetUpandRunFunction\n", - "SmallMoleculePDB\n", - "RMSDCalculator\n", - "ppi_distance\n", - "PDBFileDownloader\n", - "ModifyScriptTool\n", - "Calculator\n", - "PostSimulationFigures\n", - "packmol_tool\n", - "Python_REPL\n", - "CleaningToolFunction\n" - ] - } - ], - "source": [ - "for tool in myagent.tools:\n", - " print(tool.name)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mdagent", - "language": "python", - "name": "mdagent" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/setup.py b/setup.py index f94b4fd6..85ae8841 100644 --- a/setup.py +++ b/setup.py @@ -17,14 +17,12 @@ license="MIT", packages=find_packages(), install_requires=[ - "chromadb==0.4.24", - "google-search-results", - "langchain==0.0.336", - "langchain_experimental", + "langchain==0.2.12", + "langchain-community", + "langchain-openai==0.1.19", "matplotlib", "nbformat", "openai", - "outlines", "paper-qa==4.0.0rc8 ", "paper-scraper @ git+https://github.com/blackadad/paper-scraper.git", "pandas", @@ -33,8 +31,6 @@ "rdkit", "requests", "seaborn", - "streamlit", - "tiktoken", "scikit-learn", "scipy==1.14.0", ], diff --git a/tests/conftest.py b/tests/conftest.py index afafc2c8..38a35ffa 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -34,6 +34,13 @@ def path_to_cif(): os.chdir(original_cwd) +@pytest.fixture +def loaded_cif_traj(): + tests_dir = os.path.dirname(os.path.abspath(__file__)) + cif_path = os.path.join(tests_dir, "3pqr.cif") + return md.load(cif_path) + + @pytest.fixture(scope="module") def raw_alanine_pdb_file(request): pdb_content = """ diff --git a/tests/test_analysis/test_inertia.py b/tests/test_analysis/test_inertia.py index 961ff477..67a7c91a 100644 --- a/tests/test_analysis/test_inertia.py +++ b/tests/test_analysis/test_inertia.py @@ -57,4 +57,4 @@ def test_plot_moi_multiple_frames(mock_close, mock_savefig, moi_functions): result = moi_functions.plot_moi() assert "Plot of moments of inertia over time saved" in result mock_savefig.assert_called_once() - mock_close.assert_called_once() + mock_close.mock_close.call_count >= 1 diff --git a/tests/test_analysis/test_rgy_tool.py b/tests/test_analysis/test_rgy_tool.py new file mode 100644 index 00000000..4e5033c2 --- /dev/null +++ b/tests/test_analysis/test_rgy_tool.py @@ -0,0 +1,28 @@ +import pytest + +from mdagent.tools.base_tools.analysis_tools.rgy import RadiusofGyration + + +@pytest.fixture +def rgy(get_registry, loaded_cif_traj): + registry = get_registry("raw", False) + rgy = RadiusofGyration(path_registry=registry) + rgy.traj = loaded_cif_traj + rgy.top_file = "test_top_dummy" + rgy.traj_file = "test_traj_dummy" + return rgy + + +def test_rgy_per_frame(rgy): + output = rgy.rgy_per_frame() + assert "Radii of gyration saved to " in output + + +def test_rgy_average(rgy): + output = rgy.rgy_average() + assert "Average radius of gyration: " in output + + +def test_plot_rgy(rgy): + output = rgy.plot_rgy() + assert "Plot saved as: " in output diff --git a/tests/test_analysis/test_secondary_structure.py b/tests/test_analysis/test_secondary_structure.py new file mode 100644 index 00000000..699e5aef --- /dev/null +++ b/tests/test_analysis/test_secondary_structure.py @@ -0,0 +1,219 @@ +import mdtraj as md +import numpy as np +import pytest + +from mdagent.tools.base_tools.analysis_tools.secondary_structure import ( + ComputeAcylindricity, + ComputeAsphericity, + ComputeDSSP, + ComputeGyrationTensor, + ComputeRelativeShapeAntisotropy, + SummarizeProteinStructure, +) + + +@pytest.fixture +def compute_dssp_simple(get_registry): + registry = get_registry("raw", True) + return ComputeDSSP(path_registry=registry, simplified=True) + + +@pytest.fixture +def compute_dssp(get_registry): + registry = get_registry("raw", True) + return ComputeDSSP(path_registry=registry, simplified=False) + + +def test_compute_dssp(loaded_cif_traj, compute_dssp_simple, compute_dssp): + dssp_simple = compute_dssp_simple._compute_dssp(loaded_cif_traj) + assert dssp_simple.shape[1] == 374 + assert np.all( + dssp_simple[0][:10] + == np.array(["C", "C", "C", "E", "E", "E", "C", "C", "E", "E"]) + ) + + dssp = compute_dssp._compute_dssp(loaded_cif_traj) + assert dssp.shape[1] == 374 + assert np.all(dssp[0][:10] == [" ", " ", " ", "E", "E", "E", "T", "T", "E", "E"]) + + +def test_get_frame(compute_dssp): + # random dummy traj with 3 frames + xyz = np.random.rand(10, 10, 3) + topology = md.Topology() + chain = topology.add_chain() + residue = topology.add_residue("ALA", chain) + for _ in range(10): + topology.add_atom("CA", md.element.carbon, residue) + traj = md.Trajectory(xyz, topology) + + # first frame + first_frame = compute_dssp._get_frame(traj, "first") + assert first_frame.n_frames == 1 + assert np.array_equal(first_frame.xyz, traj.xyz[0].reshape(1, -1, 3)) + + # last frame + last_frame = compute_dssp._get_frame(traj, "last") + assert last_frame.n_frames == 1 + assert np.array_equal(last_frame.xyz, traj.xyz[-1].reshape(1, -1, 3)) + + # all frames + all_frames = compute_dssp._get_frame(traj, "all") + assert all_frames.n_frames == traj.n_frames + assert np.array_equal(all_frames.xyz, traj.xyz) + + +def test_dssp_codes(compute_dssp_simple, compute_dssp): + dssp_codes_simple = compute_dssp_simple._dssp_codes() + assert dssp_codes_simple == ["H", "E", "C", "NA"] + + nl_simple = compute_dssp_simple._dssp_natural_language() + assert nl_simple == { + "H": "residues in helix", + "E": "residues in strand", + "C": "residues in coil", + "NA": "residues not assigned, not a protein residue", + } + + dssp_codes = compute_dssp._dssp_codes() + assert dssp_codes == ["H", "B", "E", "G", "I", "T", "S", " ", "NA"] + + nl = compute_dssp._dssp_natural_language() + assert nl == { + "H": "residues in alpha helix", + "B": "residues in beta bridge", + "E": "residues in extended strand", + "G": "residues in three helix", + "I": "residues in five helix", + "T": "residues in hydrogen bonded turn", + "S": "residues in bend", + " ": "residues in loop or irregular", + "NA": "residues not assigned, not a protein residue", + } + + +def test_convert_dssp_counts(compute_dssp_simple, compute_dssp): + dssp_counts = {"H": 0, "E": 5, "C": 5} + + descriptive_counts = compute_dssp_simple._convert_dssp_counts(dssp_counts) + assert descriptive_counts == { + "residues in helix": 0, + "residues in strand": 5, + "residues in coil": 5, + } + + dssp_counts = {"H": 0, "B": 0, "E": 5, "G": 0, "I": 0, "T": 0, "S": 0, " ": 5} + + descriptive_counts = compute_dssp._convert_dssp_counts(dssp_counts) + + assert descriptive_counts == { + "residues in alpha helix": 0, + "residues in beta bridge": 0, + "residues in extended strand": 5, + "residues in three helix": 0, + "residues in five helix": 0, + "residues in hydrogen bonded turn": 0, + "residues in bend": 0, + "residues in loop or irregular": 5, + } + + +def test_summarize_dssp(compute_dssp_simple, compute_dssp): + dssp_array = np.array([["C", "C", "C", "E", "E", "E", "C", "C", "E", "E"]]) + summary = compute_dssp_simple._summarize_dssp(dssp_array) + assert summary == { + "residues in helix": 0, + "residues in strand": 5, + "residues in coil": 5, + "residues not assigned, not a protein residue": 0, + } + + dssp_array = np.array([[" ", " ", " ", "E", "E", "E", "T", "T", "E", "E"]]) + summary = compute_dssp._summarize_dssp(dssp_array) + assert summary == { + "residues in alpha helix": 0, + "residues in beta bridge": 0, + "residues in extended strand": 5, + "residues in three helix": 0, + "residues in five helix": 0, + "residues in hydrogen bonded turn": 2, + "residues in bend": 0, + "residues in loop or irregular": 3, + "residues not assigned, not a protein residue": 0, + } + + +def test_compute_gyration_tensor(get_registry, loaded_cif_traj): + gyration_tensor = np.array( + [ + [ + [3.45897484, 0.17571401, -0.08759158], + [0.17571401, 0.944077, 0.17698189], + [-0.08759158, 0.17698189, 0.73760228], + ] + ] + ) + registry = get_registry("raw", True) + gy_tensor = ComputeGyrationTensor(path_registry=registry)._compute_gyration_tensor( + loaded_cif_traj + ) + assert np.allclose(gy_tensor, gyration_tensor) + + +def test_compute_asphericity(get_registry, loaded_cif_traj): + registry = get_registry("raw", True) + asphericity = ComputeAsphericity(path_registry=registry) + output = asphericity._compute_asphericity(loaded_cif_traj) + assert np.allclose(output, np.array([2.63956945])) + + +def test_compute_acylindricity(get_registry, loaded_cif_traj): + registry = get_registry("raw", True) + acylindricity = ComputeAcylindricity(path_registry=registry) + output = acylindricity._compute_acylindricity(loaded_cif_traj) + assert np.allclose(output, np.array([0.41455165])) + + +def test_compute_relative_shape_antisotropy(get_registry, loaded_cif_traj): + registry = get_registry("raw", True) + compute_relative_shape_antisotropy = ComputeRelativeShapeAntisotropy( + path_registry=registry + ) + output = compute_relative_shape_antisotropy._compute_relative_shape_antisotropy( + loaded_cif_traj + ) + assert np.allclose(output, np.array([0.26852832])) + + +def test_get_protein_stats(get_registry): + registry = get_registry("raw", True) + get_stats = SummarizeProteinStructure(registry) + + n_atoms = 5 + n_frames = 2 + coordinates = np.random.random((n_frames, n_atoms, 3)) + + topology = md.Topology() + + for _ in range(n_atoms): + topology.add_atom( + "C", + md.element.carbon, + topology.add_residue("methane", topology.add_chain()), + ) + + bonds = [(0, i) for i in range(1, n_atoms)] + for bond in bonds: + topology.add_bond(topology.atom(bond[0]), topology.atom(bond[1])) + + traj = md.Trajectory(coordinates, topology) + assert get_stats.summarize_protein_structure( + traj, ["atoms", "residues", "chains", "frames", "bonds"] + ) == {"n_atoms": 5, "n_residues": 5, "n_chains": 5, "n_frames": 2, "n_bonds": 4} + + # without topology + traj = md.Trajectory(coordinates, None) + with pytest.raises(ValueError): + get_stats.summarize_protein_structure( + traj, ["atoms", "residues", "chains", "frames", "bonds"] + ) diff --git a/tests/test_general_tools/test_search_tools.py b/tests/test_general_tools/test_search_tools.py index 9e28d201..e457ee6e 100644 --- a/tests/test_general_tools/test_search_tools.py +++ b/tests/test_general_tools/test_search_tools.py @@ -1,5 +1,5 @@ import pytest -from langchain.chat_models import ChatOpenAI +from langchain_openai import ChatOpenAI from mdagent.tools.base_tools import Scholar2ResultLLM diff --git a/tests/test_preprocess/test_pdb_tools.py b/tests/test_preprocess/test_pdb_tools.py index 6459bd48..7652197d 100644 --- a/tests/test_preprocess/test_pdb_tools.py +++ b/tests/test_preprocess/test_pdb_tools.py @@ -131,3 +131,38 @@ def test_packmol_download_only(packmol, small_molecule): ) assert time_before == time_after os.remove(f"{packmol.path_registry.ckpt_pdb}/{small_molecule[0]}.pdb") + + +cids = { + "CO": 887, + "CCO": 702, + "O": 962, + "CC(=O)C": 180, + "C(=O)(N)N": 1176, + "CS(=O)C": 679, + "CN(C)C=O": 6228, + "C(C(CO)O)O": 753, +} + + +def get_cid(smiles): + return cids[smiles] + + +pairs = [ + ("CO", "MOH"), + ("CCO", "EOH"), + ("O", "HOH"), + ("CC(=O)C", "ACN"), + ("C(=O)(N)N", "URE"), + ("CS(=O)C", "DMS"), + ("CN(C)C=O", "DMF"), + ("CCO", "EOH"), + ("C(C(CO)O)O", "GOL"), +] + + +@pytest.mark.parametrize("smiles, codes", pairs) +def test_get_het_codes(molpdb, smiles, codes): + cid = get_cid(smiles) # to not test the get_cid function + assert molpdb.get_hetcode_from_cid(cid) == codes diff --git a/tests/test_preprocess/test_uniprot.py b/tests/test_preprocess/test_uniprot.py index e4b118bc..370dda9b 100644 --- a/tests/test_preprocess/test_uniprot.py +++ b/tests/test_preprocess/test_uniprot.py @@ -478,7 +478,7 @@ def test_get_structure_info(query_uniprot): ) -def get_ids(query_uniprot): +def test_get_ids(query_uniprot): hg_ids = [ "P84792", "P02042", @@ -488,17 +488,14 @@ def get_ids(query_uniprot): "P02089", "P02070", "O13163", - "Q10733", "P02008", "B3EWR7", - "Q90487", "P04244", "P02094", "P83479", "P01966", "O93349", "P68872", - "P02110", "P69905", "P02088", "P02100", @@ -507,8 +504,10 @@ def get_ids(query_uniprot): "P02091", ] all_ids = query_uniprot.get_ids("hemoglobin") + print(all_ids) single_id = query_uniprot.get_ids("hemoglobin", single_id=True) - assert single_id in hg_ids + assert single_id[0] in hg_ids + assert len(single_id) == 1 assert all(i in all_ids for i in hg_ids) diff --git a/tests/test_sim/test_simulation_tools.py b/tests/test_sim/test_simulation_tools.py deleted file mode 100644 index 5b8a7cc6..00000000 --- a/tests/test_sim/test_simulation_tools.py +++ /dev/null @@ -1,46 +0,0 @@ -from unittest.mock import mock_open, patch - -import pytest - -from mdagent.tools.base_tools import SimulationFunctions - - -@pytest.fixture -def sim_fxns(get_registry): - return SimulationFunctions(get_registry("raw", False)) - - -@patch("os.path.exists") -@patch("os.listdir") -def test_extract_parameters_path(mock_listdir, mock_exists, sim_fxns): - # Test when parameters.json exists - mock_exists.return_value = True - assert sim_fxns._extract_parameters_path() == "simulation_parameters_summary.json" - mock_exists.assert_called_once_with("simulation_parameters_summary.json") - mock_exists.reset_mock() # Reset the mock for the next scenario - - # Test when parameters.json does not exist, but some_parameters.json does - mock_exists.return_value = False - mock_listdir.return_value = ["some_parameters.json", "other_file.txt"] - assert sim_fxns._extract_parameters_path() == "some_parameters.json" - - # Test when no appropriate file exists - mock_listdir.return_value = ["other_file.json", "other_file.txt"] - with pytest.raises(ValueError) as e: - sim_fxns._extract_parameters_path() - assert str(e.value) == "No parameters.json file found in directory." - - -@patch( - "builtins.open", - new_callable=mock_open, - read_data='{"param1": "value1", "param2": "value2"}', -) -@patch("json.load") -def test_setup_simulation_from_json(mock_json_load, mock_file_open, sim_fxns): - # Define the mock behavior for json.load - mock_json_load.return_value = {"param1": "value1", "param2": "value2"} - params = sim_fxns._setup_simulation_from_json("test_file.json") - mock_file_open.assert_called_once_with("test_file.json", "r") - mock_json_load.assert_called_once() - assert params == {"param1": "value1", "param2": "value2"} diff --git a/tests/test_utils/test_memory.py b/tests/test_utils/test_memory.py index 0f7d7199..1f233000 100644 --- a/tests/test_utils/test_memory.py +++ b/tests/test_utils/test_memory.py @@ -2,6 +2,7 @@ import os import pytest +from langchain_openai import ChatOpenAI from mdagent.agent.agent import MDAgent from mdagent.agent.memory import MemoryManager @@ -9,7 +10,8 @@ @pytest.fixture def memory_manager(get_registry): - return MemoryManager(get_registry("raw", False)) + llm = ChatOpenAI() + return MemoryManager(get_registry("raw", False), llm) def test_mdagent_memory(): @@ -26,11 +28,13 @@ def test_mdagent_memory(): def test_memory_init(memory_manager, get_registry): + llm = ChatOpenAI() + assert memory_manager is not None assert memory_manager.run_id is not None assert len(memory_manager.run_id) == 8 - mm_path_id = MemoryManager(get_registry("raw", False), run_id="TESTRUNN") + mm_path_id = MemoryManager(get_registry("raw", False), llm, run_id="TESTRUNN") assert mm_path_id.run_id == "TESTRUNN" diff --git a/tests/test_utils/test_query_filter.py b/tests/test_utils/test_query_filter.py deleted file mode 100644 index 381f7e40..00000000 --- a/tests/test_utils/test_query_filter.py +++ /dev/null @@ -1,89 +0,0 @@ -# test_query_filter.py -from mdagent.agent.query_filter import Example, FilteredQuery, Parameters, query_filter - - -def test_parameters_repr(): - params = Parameters( - Temperature=300, - Pressure=1.0, - Time=None, - ForceField="AMBER", - WaterModel=None, - SaltConcentration=None, - pH=7.0, - Solvate=None, - Ensemble="NVT", - Other_Parameters=None, - ) - expected_repr = ( - "Parameters(Temperature = '300'," - "Pressure = '1.0'," - "Time = 'None'," - "ForceField = 'AMBER'," - "WaterModel = 'None'," - "SaltConcentration = 'None'," - "pH = '7.0'," - "Solvate = 'None'," - "Ensemble = 'NVT'," - "Other_Parameters = 'None')" - ) - assert repr(params) == expected_repr - - -def test_query_filter_simple(): - raw_query = "Find the melting point of NaCl" - example = Example( - Raw_query="Find the melting point of NaCl", - Filtered_Query=FilteredQuery( - Main_Task="Find the melting point of NaCl", - Subtask_types=["Question"], - ProteinS=["None"], - Parameters=Parameters( - Temperature=None, - Pressure=None, - Time=None, - ForceField=None, - WaterModel=None, - SaltConcentration=None, - pH=None, - Solvate=None, - Ensemble=None, - Other_Parameters=None, - ), - UserProposedPlan=[], - ), - ) - examples = [example] - expected_output = """You are about to organize an user query. User will -ask for a specific Molecular Dynamics related task, from wich you will -extract: -1. The main task of the query -2. A list of subtasks that are part of the main task -3. The protein of interest mentioned in the raw query (as a PDB ID, - UniProt ID, name, or sequence) -4. Parameters or conditions specified by the user for the simulation -5. The plan proposed by the user for the simulation (if any) - - -Raw Query: "Find the melting point of NaCl" -RESULT: { - "Main_Task": "Find the melting point of NaCl", - "Subtask_types": "[Question]", - "ProteinS": "['None']", - "Parameters": "Parameters(Temperature = 'None',\ -Pressure = 'None',\ -Time = 'None',\ -ForceField = 'None',\ -WaterModel = 'None',\ -SaltConcentration = 'None',\ -pH = 'None',\ -Solvate = 'None',\ -Ensemble = 'None',\ -Other_Parameters = 'None')", - "UserProposedPlan": "[]"} - -Here is the new raw query that you need to filter: -Raw Query: Find the melting point of NaCl -RESULT:""" - # Assuming the function query_filter returns a string for simplicity - assert query_filter(raw_query, examples=examples) == expected_output diff --git a/tests/test_utils/test_top_k_tools.py b/tests/test_utils/test_top_k_tools.py new file mode 100644 index 00000000..2f3dda3b --- /dev/null +++ b/tests/test_utils/test_top_k_tools.py @@ -0,0 +1,96 @@ +import os +from unittest.mock import MagicMock, patch + +import numpy as np +import pytest + +from mdagent.tools.maketools import get_relevant_tools + + +@pytest.fixture +def mock_llm(): + return MagicMock() + + +@pytest.fixture +def mock_tools(): + Tool = MagicMock() + tool1 = Tool(name="Tool1", description="This is the first tool") + tool2 = Tool(name="Tool2", description="This is the second tool") + tool3 = Tool(name="Tool3", description="This is the third tool") + return [tool1, tool2, tool3] + + +@patch("mdagent.tools.maketools.make_all_tools") +@patch("mdagent.tools.maketools.OpenAIEmbeddings") +def test_get_relevant_tools_with_openai_embeddings( + mock_openai_embeddings, mock_make_all_tools, mock_llm, mock_tools +): + mock_make_all_tools.return_value = mock_tools + mock_embed_documents = mock_openai_embeddings.return_value.embed_documents + mock_embed_query = mock_openai_embeddings.return_value.embed_query + mock_embed_documents.return_value = np.random.rand(3, 512) + mock_embed_query.return_value = np.random.rand(512) + + with patch.dict( + os.environ, {"OPENAI_API_KEY": "test_key"} # pragma: allowlist secret + ): + relevant_tools = get_relevant_tools("test query", mock_llm, top_k_tools=2) + assert len(relevant_tools) == 2 + assert relevant_tools[0] in mock_tools + assert relevant_tools[1] in mock_tools + + +@patch("mdagent.tools.maketools.make_all_tools") +@patch("mdagent.tools.maketools.TfidfVectorizer") +def test_get_relevant_tools_with_tfidf( + mock_tfidf_vectorizer, mock_make_all_tools, mock_llm, mock_tools +): + mock_make_all_tools.return_value = mock_tools + mock_vectorizer = mock_tfidf_vectorizer.return_value + mock_vectorizer.fit_transform.return_value = np.random.rand(3, 10) + mock_vectorizer.transform.return_value = np.random.rand(1, 10) + + with patch.dict(os.environ, {}, clear=True): # ensure OPENAI_API_KEY is not set + relevant_tools = get_relevant_tools("test query", mock_llm, top_k_tools=2) + assert len(relevant_tools) == 2 + assert relevant_tools[0] in mock_tools + assert relevant_tools[1] in mock_tools + + +@patch("mdagent.tools.maketools.make_all_tools") +def test_get_relevant_tools_with_no_tools(mock_make_all_tools, mock_llm): + mock_make_all_tools.return_value = [] + + with patch.dict(os.environ, {}, clear=True): + relevant_tools = get_relevant_tools("test query", mock_llm) + assert relevant_tools is None + + +@patch("mdagent.tools.maketools.make_all_tools") +@patch("mdagent.tools.maketools.OpenAIEmbeddings") +def test_get_relevant_tools_with_openai_exception( + mock_openai_embeddings, mock_make_all_tools, mock_llm, mock_tools +): + mock_make_all_tools.return_value = mock_tools + mock_embed_documents = mock_openai_embeddings.return_value.embed_documents + mock_embed_documents.side_effect = Exception("Embedding error") + + with patch.dict( + os.environ, {"OPENAI_API_KEY": "test_key"} # pragma: allowlist secret + ): + relevant_tools = get_relevant_tools("test query", mock_llm) + assert relevant_tools is None + + +@patch("mdagent.tools.maketools.make_all_tools") +def test_get_relevant_tools_top_k(mock_make_all_tools, mock_llm, mock_tools): + mock_make_all_tools.return_value = mock_tools + + with patch.dict(os.environ, {}, clear=True): + relevant_tools = get_relevant_tools("test query", mock_llm, top_k_tools=1) + assert len(relevant_tools) == 1 + assert relevant_tools[0] in mock_tools + + relevant_tools = get_relevant_tools("test query", mock_llm, top_k_tools=5) + assert len(relevant_tools) == len(mock_tools)