Pre-pylint refactoring, part I, issues #3, #5 and #7

GeminiAgentsToolkit · Sep 16, 2024 · 51cd14b · 51cd14b
1 parent 6686537
commit 51cd14b
Show file tree

Hide file tree

Showing 13 changed files with 308 additions and 166 deletions.
diff --git a/README.md b/README.md
@@ -75,7 +75,7 @@ This project uses Gemini via Google Cloud API. To use the project you must first
 
 ### Allow requesting LLM models via APIs
 1. The project uses [Vertex AI API](https://cloud.google.com/vertex-ai/) to request Gemini models, Vertex AI API should be allowed in your Google cloud account. You need to allow it from the [Google Cloud Vertex AI API product page](https://console.cloud.google.com/apis/library/aiplatform.googleapis.com).
-2. [Optional] With this [instructions](https://cloud.google.com/apis/docs/capping-api-usage) you can limit or increase your API requests quota.
+2. [Optional] With these [instructions](https://cloud.google.com/apis/docs/capping-api-usage) you can limit or increase your API requests quota.
 
 ### Set up gcloud tool in your environment
 Follow the Google instructions to [install](https://cloud.google.com/sdk/docs/install) gcloud and to [initialize](https://cloud.google.com/sdk/docs/initializing) it.
@@ -125,21 +125,21 @@ In this example, you have created a custom function and gave Gemini ability to u
 <summary>See code</summary>
 
 ```python
-import config.config as config
-from gemini_agents_toolkit import agent
-
 import vertexai
+from config import (PROJECT_ID, REGION, SIMPLE_MODEL)
+from gemini_agents_toolkit import agent
 
 
 def say_to_duck(say: str):
     """say something to a duck"""
     return f"duck answer is: duck duck {say} duck duck duck"
 
 
-vertexai.init(project=config.project_id, location=config.region)
+vertexai.init(project=PROJECT_ID, location=REGION)
 
 all_functions = [say_to_duck]
-duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions, model_name=config.simple_model)
+duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions,
+                                                          model_name=SIMPLE_MODEL)
 
 print(duck_comms_agent.send_message("say to the duck message: I am hungry"))
 ```
@@ -156,40 +156,47 @@ python examples/multi_agent_example.py
 <summary>See code</summary>
 
 ```python
-import config.config as config
-from gemini_agents_toolkit import agent
-
+import datetime
 import vertexai
+from config import (PROJECT_ID, REGION, SIMPLE_MODEL)
+from gemini_agents_toolkit import agent
 
-
-vertexai.init(project=config.project_id, location=config.region)
+vertexai.init(project=PROJECT_ID, location=REGION)
 
 
 def generate_duck_comms_agent():
+    """create an agent to say to a duck"""
+
     def say_to_duck(say: str):
         """say something to a duck"""
         return f"duck answer is: duck duck {say} duck duck duck"
+
     return agent.create_agent_from_functions_list(
-        functions=[say_to_duck], 
-        delegation_function_prompt="Agent can communicat to ducks and can say something to them. And provides the answer from the duck.", 
-        model_name=config.simple_model)
+        functions=[say_to_duck],
+        delegation_function_prompt=("""Agent can communicat to ducks and can say something to them.
+                                    And provides the answer from the duck."""),
+        model_name=SIMPLE_MODEL)
 
 
 def generate_time_checker_agent():
+    """create an agent to get the time"""
+
     def get_local_time():
         """get the current local time"""
-        import datetime
         return datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
     return agent.create_agent_from_functions_list(
-        functions=[get_local_time], 
-        delegation_function_prompt="Agent can provide the current local time.", 
-        model_name=config.simple_model)
+        functions=[get_local_time],
+        delegation_function_prompt="Agent can provide the current local time.",
+        model_name=SIMPLE_MODEL)
 
 
 duck_comms_agent = generate_duck_comms_agent()
 time_checker_agent = generate_time_checker_agent()
 
-main_agent = agent.create_agent_from_functions_list(delegates=[time_checker_agent, duck_comms_agent], model_name=config.simple_model)
+main_agent = agent.create_agent_from_functions_list(
+    delegates=[time_checker_agent, duck_comms_agent],
+    model_name=SIMPLE_MODEL)
 
 print(main_agent.send_message("say to the duck message: I am hungry"))
 print(main_agent.send_message("can you tell me what time it is?"))
@@ -208,11 +215,10 @@ python examples/simple_scheduler_example.py
 <summary>See code</summary>
 
 ```python
-import config.config as config
-from gemini_agents_toolkit import agent
 import time
-
 import vertexai
+from config import (PROJECT_ID, REGION, SIMPLE_MODEL)
+from gemini_agents_toolkit import agent
 
 
 def say_to_duck(say: str):
@@ -221,13 +227,17 @@ def say_to_duck(say: str):
 
 
 def print_msg_from_agent(msg: str):
+    """print message in console"""
     print(msg)
 
 
-vertexai.init(project=config.project_id, location=config.region)
+vertexai.init(project=PROJECT_ID, location=REGION)
 
 all_functions = [say_to_duck]
-duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions, model_name=config.simple_model, add_scheduling_functions=True, on_message=print_msg_from_agent)
+duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions,
+                                                          model_name=SIMPLE_MODEL,
+                                                          add_scheduling_functions=True,
+                                                          on_message=print_msg_from_agent)
 
 # no need to print result directly since we passed to agent on_message
 duck_comms_agent.send_message("can you be saying, each minute, to the duck that I am hungry")
@@ -247,28 +257,46 @@ python examples/pipeline_example.py
 <summary>See code</summary>
 
 ```python
-import config.config as config
+import vertexai
+from config import (PROJECT_ID, REGION, DEFAULT_MODEL, SIMPLE_MODEL)
 from gemini_agents_toolkit import agent
 from gemini_agents_toolkit.pipeline.basic_step import BasicStep
 
-import vertexai
-
 
 def say_to_duck(say: str):
     """say something to a duck"""
     return f"duck answer is: duck duck {say} duck duck duck"
 
 
-vertexai.init(project=config.project_id, location=config.region)
+vertexai.init(project=PROJECT_ID, location=REGION)
 
 all_functions = [say_to_duck]
-duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions, model_name=config.simple_model)
-computation_agent = agent.create_agent_from_functions_list(model_name=config.default_model, system_instruction="you are agent design to do computation")
-printing_agent = agent.create_agent_from_functions_list(model_name=config.default_model, system_instruction="you are agent design to do nice prints in the shell. You do not have to be producing BASH commands your output will be printed by other developer in the bush you are ONLY in charge of the formattin ASCII characters that will be printed. No need to even use characters like ``` before/after you response")
-
-pipeline = (BasicStep(duck_comms_agent, "say to duck: I am hungry") | 
-            BasicStep(computation_agent, "calculate how many times word duck was used in the response") | 
-            BasicStep(printing_agent, "print number in a nice format, go nuts with how you want it to look"))
+duck_comms_agent = agent.create_agent_from_functions_list(functions=all_functions,
+                                                          model_name=SIMPLE_MODEL)
+computation_agent = agent.create_agent_from_functions_list(
+    model_name=DEFAULT_MODEL,
+    system_instruction="you are agent design to do computation"
+)
+
+PRINTING_AGENT_PROMPT = """
+You are agent design to do nice prints in the shell.
+You do not have to be producing BASH commands,
+your output will be printed by other developer in the bash.
+You are ONLY in charge of the formatting ASCII characters  that will be printed.
+No need to even use characters like ``` before/after you response.
+"""
+printing_agent = agent.create_agent_from_functions_list(model_name=DEFAULT_MODEL,
+                                                        system_instruction=PRINTING_AGENT_PROMPT)
+
+pipeline = (BasicStep(duck_comms_agent, "say to duck: I am hungry") |
+            BasicStep(
+                computation_agent,
+                "calculate how many times word duck was used in the response"
+            ) |
+            BasicStep(
+                printing_agent,
+                "print number in a nice format, go nuts with how you want it to look"
+            ))
 print(pipeline.execute())
 ```
 </details>

diff --git a/config/__init__.py b/config/__init__.py
@@ -0,0 +1,12 @@
+"""The module to provide configuration values."""
+
+import os
+
+# ***** Google Cloud project settings *****
+PROJECT_ID =  os.getenv('GOOGLE_PROJECT')
+API_KEY =  os.getenv('GOOGLE_API_KEY')
+REGION = os.environ.get('GOOGLE_REGION', 'us-west1')
+
+DEFAULT_MODEL = 'gemini-1.5-pro'
+# simple model is used for demo examples as a cost optimization
+SIMPLE_MODEL = 'gemini-1.5-flash'
diff --git a/config/config.py b/config/config.py
diff --git a/examples/investing_pipeline_example.py b/examples/investing_pipeline_example.py
@@ -1,33 +1,38 @@
-import config.config as config
-from gemini_agents_toolkit import agent
-from gemini_agents_toolkit.pipeline.eager_pipeline import EagerPipeline
+"""This example illustrates creating an advanced pipeline with different step types."""
 
-import vertexai
 import random
+import vertexai
+from config import (PROJECT_ID, REGION, DEFAULT_MODEL)
+from gemini_agents_toolkit import agent
+from gemini_agents_toolkit.pipeline.eager_pipeline import EagerPipeline
 
-
+# pylint: disable-next=invalid-name
 current_limit_buy_price = None
+# pylint: disable-next=invalid-name
 current_limit_sell_price = None
 
 
 def check_if_limit_sell_order_exists():
     """Check if limit sell order exists"""
-    global current_limit_sell_price
     return current_limit_sell_price is not None
 
 
 def cancel_limit_sell_order():
     """Cancel limit sell order"""
+    # pylint: disable-next=global-statement
     global current_limit_sell_price
     current_limit_sell_price = None
     return "Limit sell order canceled"
 
 
 def set_limit_sell_order(price: float):
-    """Set limit sell order. Price is float and it can not be a formula or logic that prints formula, input HAS to be fully computed price.
+    """Set limit sell order.
+    Price is float, and it can not be a formula or logic that prints formula,
+    input HAS to be fully computed price.
     
     Args:
         price: Price to set limit sell order"""
+    # pylint: disable-next=global-statement
     global current_limit_sell_price
     current_limit_sell_price = price
     return f"Limit sell order set at {price}"
@@ -37,32 +42,34 @@ def check_current_tqqq_price():
     """Current price of TQQQ"""
     # return 125.3 + random number in the range [-100, 100]
     return 125.3 + random.randint(-100, 100)
-    
+
 
 def get_current_limit_buy_price():
     """Current limit buy price of TQQQ"""
-    global current_limit_buy_price
     return current_limit_buy_price
 
 
 def check_if_limit_buy_order_exists():
     """Check if limit buy order exists"""
-    global current_limit_buy_price
     return current_limit_buy_price is not None
 
 
 def cancel_limit_buy_order():
     """Cancel limit buy order"""
+    # pylint: disable-next=global-statement
     global current_limit_buy_price
     current_limit_buy_price = None
     return "Limit buy order canceled"
 
 
 def set_limit_buy_order(price: float):
-    """Set limit buy order. Price is float and it can not be a formula or logic that prints formula, input HAS to be fully computed price.
+    """Set limit buy order.
+    Price is float, and it can not be a formula or logic that prints formula,
+    input HAS to be fully computed price.
     
     Args:
         price: Price to set limit buy order"""
+    # pylint: disable-next=global-statement
     global current_limit_buy_price
     current_limit_buy_price = price
     return f"Limit buy order set at {price}"
@@ -73,10 +80,21 @@ def check_how_many_shares_i_own():
     return 30 + random.randint(-20, 1)
 
 
-vertexai.init(project=config.project_id, location=config.region)
+vertexai.init(project=PROJECT_ID, location=REGION)
 
-all_functions = [check_if_limit_sell_order_exists, cancel_limit_sell_order, set_limit_sell_order, check_current_tqqq_price, check_if_limit_buy_order_exists, get_current_limit_buy_price, cancel_limit_buy_order, set_limit_buy_order, check_how_many_shares_i_own]
-investor_agent = agent.create_agent_from_functions_list(functions=all_functions, model_name=config.default_model)
+all_functions = [
+    check_if_limit_sell_order_exists,
+    cancel_limit_sell_order,
+    set_limit_sell_order,
+    check_current_tqqq_price,
+    check_if_limit_buy_order_exists,
+    get_current_limit_buy_price,
+    cancel_limit_buy_order,
+    set_limit_buy_order,
+    check_how_many_shares_i_own
+]
+investor_agent = agent.create_agent_from_functions_list(functions=all_functions,
+                                                        model_name=DEFAULT_MODEL)
 
 pipeline = EagerPipeline(default_agent=investor_agent)
 if not pipeline.boolean_step("check if I own more than 30 shares of TQQQ"):
@@ -86,11 +104,15 @@ def check_how_many_shares_i_own():
     else:
         print("everywhere")
         if pipeline.boolean_step("is there a limit buy exists already?"):
-            if not pipeline.boolean_step("is there current limit buy price lower than curent price of TQQQ -5%?"):
+            if not pipeline.boolean_step(
+                    "is there current limit buy price lower than current price of TQQQ -5%?"):
                 pipeline.step("cancel limit buy order")
-                pipeline.step("""set limit buy order for TQQQ for price 3 precent below the current price. 
-                              Do not return compute formula, do compute of the price yourself in your head""")
+                pipeline.step(
+                    """set limit buy order for TQQQ for price 3 percent below the current price. 
+                    Do not return compute formula,
+                    do compute of the price yourself in your head""")
         else:
-            pipeline.step("""set limit buy order for TQQQ for price 3 precent below the current price. 
-                          Do not return compute formula, do compute of the price yourself in your head""")
+            pipeline.step(
+                """set limit buy order for TQQQ for price 3 percent below the current price. 
+                Do not return compute formula, do compute of the price yourself in your head""")
 print(pipeline.summary())