langchain_evaluation.ipynb

{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Evalute LLM output\n",
    "\n",
    "This notebook presents LangChain criteria evaluators which help to evaluate generated output with other LLM using defined categories."
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### Built-in evaluators"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-14T10:10:20.658561Z",
     "start_time": "2024-09-14T10:10:20.533656Z"
    }
   },
   "cell_type": "code",
   "source": [
    "### Evaluate LLM by LLM\n",
    "# before start fill env variables .env file:\n",
    "# LANGCHAIN_API_KEY=\"put_here_your_langchain(langsmith)_api_token\"\n",
    "# OPENAI_API_KEY=\"put_here_your_openai_token\"\n",
    "# HUGGINGFACE_API_TOKEN=\"put_here_your_huggingface_token\"\n",
    "# to use OpenAI API you need to add billing details https://platform.openai.com/settings/organization/billing/overview\n",
    "# for langchain token remember to add read permissions associated with token\n",
    "from dotenv import load_dotenv\n",
    "from langchain.chains import LLMChain\n",
    "from langchain.prompts.prompt import PromptTemplate\n",
    "from langchain.llms import OpenAI\n",
    "from langchain_openai import ChatOpenAI\n",
    "from langchain.evaluation import load_evaluator\n",
    "\n",
    "#load dotenv (API key from .env)\n",
    "load_dotenv()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-14T10:10:24.858611Z",
     "start_time": "2024-09-14T10:10:22.107916Z"
    }
   },
   "cell_type": "code",
   "source": [
    "llm = ChatOpenAI(model_name=\"gpt-4o\")\n",
    "template = \"\"\"\n",
    "You are base of knowledge about star wars. Respond to question below with only name without any additional text.\n",
    "{input}\n",
    "\"\"\"\n",
    "prompt_template = PromptTemplate.from_template(template=template)\n",
    "chain = LLMChain(llm=llm, prompt=prompt_template)\n",
    "prediction = chain.predict(input=\"What is the capital of star wars Sith Empire?\")\n",
    "\n",
    "evaluator = load_evaluator(\"labeled_score_string\", llm=ChatOpenAI(model=\"gpt-4o\"))\n",
    "eval_result = evaluator.evaluate_strings(\n",
    "    prediction=prediction,\n",
    "    reference=\"Dromund Kaas\",\n",
    "    input=\"What is the capital of star wars Sith Empire?\",\n",
    ")\n",
    "print(eval_result)\n",
    "\n"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'reasoning': 'The response provided by the AI assistant is \"Dromund Kaas,\" which is indeed the correct answer to the user\\'s question about the capital of the Sith Empire in the Star Wars universe. \\n\\n- **Helpfulness**: The response is helpful as it directly answers the user\\'s question.\\n- **Relevance**: The response is relevant because it correctly identifies the capital of the Sith Empire.\\n- **Correctness**: The information is accurate and factual.\\n- **Depth**: While the response is correct, it is very brief and lacks additional context or details that could provide more depth, such as mentioning its importance or role in the Star Wars lore.\\n\\nGiven these considerations, the response is accurate but lacks depth. Therefore, it merits a good but not perfect score.\\n\\nRating: [[8]]', 'score': 8}\n"
     ]
    }
   ],
   "execution_count": 12
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### Evaluate LLM by LLM"
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:15:56.040264Z",
     "start_time": "2024-09-02T14:15:55.554488Z"
    }
   },
   "source": [
    "model = OpenAI(temperature=0)\n",
    "template = \"\"\"You are an expert in grading answers.\n",
    "You are grading the following question:\n",
    "{query}\n",
    "Here is the correct expected answer:\n",
    "{answer}\n",
    "You are grading the following predicted answer:\n",
    "{result}\n",
    "What grade do you give from 0 to 5, where 0 is the lowest for low similarity and 5 is for the high similarity?\n",
    "\"\"\"\n",
    "\n",
    "prompt = PromptTemplate(\n",
    "    input_variables=[\"query\", \"answer\", \"result\"], template=template\n",
    ")"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/michal/anaconda3/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:119: LangChainDeprecationWarning: The class `OpenAI` was deprecated in LangChain 0.0.10 and will be removed in 0.3.0. An updated version of the class exists in the langchain-openai package and should be used instead. To use it run `pip install -U langchain-openai` and import as `from langchain_openai import OpenAI`.\n",
      "  warn_deprecated(\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:15:57.483480Z",
     "start_time": "2024-09-02T14:15:56.089329Z"
    }
   },
   "source": [
    "context_examples = [\n",
    "    {\n",
    "        \"question\": \"Why people don't brief underwater?\",\n",
    "        \"context\": \"Because people don't have gills\",\n",
    "    },\n",
    "    {\n",
    "        \"question\": \"Why the sky is blue?\",\n",
    "        \"context\": \"Sky isn't blue. Its just optical effect related to sun rays coming to eye through atmosphere and interpretation in our mind.\",\n",
    "    },\n",
    "    {\n",
    "        \"question\": \"What is in my pocket?\",\n",
    "        \"context\": \"\",\n",
    "    },\n",
    "]\n",
    "prompt_qa = \"Answer the question based on the  context\\nContext:{context}\\nQuestion:{question}\\nAnswer:\"\n",
    "template = PromptTemplate(input_variables=[\"context\", \"question\"], template=prompt_qa)\n",
    "qa_chain = LLMChain(llm=model, prompt=template)\n",
    "predictions = qa_chain.apply(context_examples)\n",
    "predictions"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'text': \" People don't breathe underwater because they do not have gills, which are necessary for extracting oxygen from water.\"},\n",
       " {'text': \" The sky appears blue due to an optical effect caused by the sun's rays passing through the Earth's atmosphere and our brain's interpretation of this phenomenon. In reality, the sky does not have a color.\"},\n",
       " {'text': ' I am not able to answer that question as I do not have access to your pocket.'}]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:15:58.325074Z",
     "start_time": "2024-09-02T14:15:57.495271Z"
    }
   },
   "source": [
    "from langchain.evaluation.qa import ContextQAEvalChain\n",
    "\n",
    "eval_chain = ContextQAEvalChain.from_llm(model)\n",
    "graded_outputs = eval_chain.evaluate(\n",
    "    context_examples, predictions, question_key=\"question\", prediction_key=\"text\"\n",
    ")\n",
    "print(graded_outputs)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'text': ' CORRECT'}, {'text': ' CORRECT'}, {'text': ' CORRECT'}]\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "### Evaluation criteria"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:15:58.407397Z",
     "start_time": "2024-09-02T14:15:58.339544Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import os\n",
    "from langsmith import Client\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
    "os.environ[\"LANGCHAIN_ENDPOINT\"] = \"https://api.smith.langchain.com\"\n",
    "os.environ[\"LANGCHAIN_PROJECT\"] = \"GEMMA EVALUATIONs\"\n",
    "os.environ[\"LANGCHAIN_API_KEY\"] = \"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\""
   ],
   "outputs": [],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:15:58.456311Z",
     "start_time": "2024-09-02T14:15:58.416392Z"
    }
   },
   "cell_type": "code",
   "source": [
    "client = Client()\n",
    "# Inputs are provided to your model, so it know what to generate\n",
    "dataset_inputs = [\n",
    "    \"Why people don't have 3 legs?\",\n",
    "    \"Why people are not flying?\",\n",
    "]\n",
    "\n",
    "#use 1st LLM for generating texts\n",
    "llm_test= ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0.1,max_tokens=256)\n",
    "# llm_gen = ChatOpenAI(base_url=\"https://api-inference.huggingface.com/v1\", model=\"google/gemma-2b-it\",temperature=0.1,max_tokens=256)\n",
    "# and 2nd to evaluate different criteria of response generated with 1st LLM\n",
    "llm_gen = ChatOpenAI(model=\"gpt-4o\", temperature=0.1,max_tokens=256)"
   ],
   "outputs": [],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:16:04.851912Z",
     "start_time": "2024-09-02T14:15:58.465755Z"
    }
   },
   "cell_type": "code",
   "source": [
    "\n",
    "dataset_outputs = [\n",
    "    {\"result\": llm_test.invoke(50*dataset_inputs[0])},\n",
    "    {\"result\": llm_test.invoke(50*dataset_inputs[1])},\n",
    "]\n",
    "print(dataset_outputs)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'result': AIMessage(content='Humans do not have three legs because we are bipedal creatures, meaning we walk on two legs. Our bodies have evolved over millions of years to be efficient at walking and running on two legs, and having a third leg would not provide any significant advantage. Additionally, having three legs would likely be cumbersome and hinder our ability to move effectively.', response_metadata={'token_usage': {'completion_tokens': 69, 'prompt_tokens': 457, 'total_tokens': 526}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-b6b2fad6-73d5-45ec-8c9b-ae7f16445b90-0')}, {'result': AIMessage(content='There could be several reasons why people are not flying:\\n\\n1. Fear of COVID-19: Many people are hesitant to fly due to concerns about contracting the virus while traveling.\\n\\n2. Travel restrictions: Some countries have implemented travel restrictions or quarantine requirements, making it difficult for people to fly.\\n\\n3. Economic uncertainty: The pandemic has caused financial strain for many individuals, making it difficult for them to afford air travel.\\n\\n4. Reduced flight options: Airlines have cut back on routes and flights, leading to limited options for travelers.\\n\\n5. Health concerns: Some individuals may have underlying health conditions that make them more vulnerable to COVID-19, leading them to avoid flying.\\n\\n6. Work from home policies: With many companies implementing remote work policies, there may be less need for business travel, reducing the demand for flights.\\n\\n7. Environmental concerns: Some people are choosing to avoid flying due to the environmental impact of air travel.\\n\\n8. Alternative modes of transportation: With advancements in technology, some people may be opting for alternative modes of transportation such as trains or electric vehicles.\\n\\n9. Personal preferences: Some individuals may simply prefer not to fly for personal reasons, such as a fear of flying or a preference for road trips.', response_metadata={'token_usage': {'completion_tokens': 243, 'prompt_tokens': 307, 'total_tokens': 550}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-dfa23f98-d8ce-4dec-a694-f692400a35ed-0')}]\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:16:06.684550Z",
     "start_time": "2024-09-02T14:16:04.863071Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import uuid\n",
    "\n",
    "dataset_name = \"existential questions run:\" + uuid.uuid4().__str__() #need to modify this value on every run of notebook\n",
    "\n",
    "# Storing inputs in a dataset lets us\n",
    "# run chains and LLMs over a shared set of examples.\n",
    "dataset = client.create_dataset(\n",
    "    dataset_name=dataset_name,\n",
    "    description=\"evaluate LLM output\",\n",
    ")\n",
    "client.create_examples(\n",
    "    inputs=[{\"question\": q} for q in dataset_inputs],\n",
    "    outputs=dataset_outputs,\n",
    "    dataset_id=dataset.id,\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 8
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:16:06.742139Z",
     "start_time": "2024-09-02T14:16:06.706520Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from langchain.smith import RunEvalConfig\n",
    "from langsmith.evaluation import EvaluationResult, run_evaluator\n",
    "\n",
    "@run_evaluator\n",
    "def custom_evaluator(run, example) -> EvaluationResult:\n",
    "    \"\"\"\n",
    "    checks if output contains specific word\n",
    "    :param run: \n",
    "    :param example: \n",
    "    :return: int\n",
    "    \"\"\"\n",
    "    generated = run.outputs[\"generations\"][0][0][\"text\"]\n",
    "    if 'human' in generated:\n",
    "        score = 1\n",
    "    else:\n",
    "        score = 0\n",
    "    return EvaluationResult(key=\"result\", score=score)"
   ],
   "outputs": [],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:16:06.785379Z",
     "start_time": "2024-09-02T14:16:06.777989Z"
    }
   },
   "cell_type": "code",
   "source": [
    "eval_config = RunEvalConfig(\n",
    "    custom_evaluators=[custom_evaluator],\n",
    "    evaluators=[\n",
    "        \"criteria\",\n",
    "        \"qa\",         #directly grade a response as \"correct\" or \"incorrect\" based on the reference answer\n",
    "        \"context_qa\", #use the provided reference context in determining correctness\n",
    "        \"cot_qa\",     #use chain of thought \"reasoning\" before determining a final verdict. This tends to lead to responses that better correlate with human labels\n",
    "        RunEvalConfig.Criteria(\"insensitivity\"),\n",
    "        RunEvalConfig.Criteria(\"relevance\"),\n",
    "        RunEvalConfig.Criteria(\"helpfulness\"),\n",
    "        RunEvalConfig.Criteria(\"maliciousness\"),\n",
    "        RunEvalConfig.Criteria(\"harmfulness\"),\n",
    "        RunEvalConfig.Criteria(\"coherence\"),\n",
    "        RunEvalConfig.Criteria(\"conciseness\"),\n",
    "        RunEvalConfig.Criteria(\"misogyny\"),\n",
    "        RunEvalConfig.Criteria(\"criminality\"),\n",
    "        RunEvalConfig.Criteria(\"controversiality\"),\n",
    "        RunEvalConfig.Criteria( #custom defined criteria related to specific problem we want to solve and problems detected in output\n",
    "            {\n",
    "                \"valuation\": \"Do texts contain valuation of subject, like glorifying some characteristic or judging someone?\"\n",
    "                \" Respond Y if they do, N if they're entirely objective and stick to the facts without additions.\"\n",
    "            }\n",
    "        )\n",
    "    ],\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-02T14:18:24.519851Z",
     "start_time": "2024-09-02T14:16:06.845413Z"
    }
   },
   "cell_type": "code",
   "source": [
    "#in case of error ‘model is currently loading;’, wait couple of minutes and run notebook again\n",
    "scores = client.run_on_dataset(\n",
    "    dataset_name=dataset_name,\n",
    "    llm_or_chain_factory=llm_gen,\n",
    "    evaluation=eval_config,\n",
    "    verbose=True,\n",
    "    project_name=dataset_name,\n",
    ")\n",
    "print(scores)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "View the evaluation results for project 'existential questions run:99803b99-df87-43b5-8305-22f37b26547d' at:\n",
      "https://smith.langchain.com/o/3e1f981e-76ef-5491-9a42-e33f3bdfeba4/datasets/e6a6c9c0-db5c-4bc8-a94f-069b21023138/compare?selectedSessions=3328bc53-19b2-4846-91b6-968bce63f2a4\n",
      "\n",
      "View all tests for Dataset existential questions run:99803b99-df87-43b5-8305-22f37b26547d at:\n",
      "https://smith.langchain.com/o/3e1f981e-76ef-5491-9a42-e33f3bdfeba4/datasets/e6a6c9c0-db5c-4bc8-a94f-069b21023138\n",
      "[------------------------------------------------->] 2/2"
     ]
    },
    {
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      "text/html": [
       "<h3>Experiment Results:</h3>"
      ]
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     "data": {
      "text/plain": [
       "        feedback.helpfulness  feedback.correctness  \\\n",
       "count                    2.0                   2.0   \n",
       "unique                   NaN                   NaN   \n",
       "top                      NaN                   NaN   \n",
       "freq                     NaN                   NaN   \n",
       "mean                     1.0                   1.0   \n",
       "std                      0.0                   0.0   \n",
       "min                      1.0                   1.0   \n",
       "25%                      1.0                   1.0   \n",
       "50%                      1.0                   1.0   \n",
       "75%                      1.0                   1.0   \n",
       "max                      1.0                   1.0   \n",
       "\n",
       "        feedback.Contextual Accuracy  feedback.COT Contextual Accuracy  \\\n",
       "count                            2.0                               2.0   \n",
       "unique                           NaN                               NaN   \n",
       "top                              NaN                               NaN   \n",
       "freq                             NaN                               NaN   \n",
       "mean                             1.0                               1.0   \n",
       "std                              0.0                               0.0   \n",
       "min                              1.0                               1.0   \n",
       "25%                              1.0                               1.0   \n",
       "50%                              1.0                               1.0   \n",
       "75%                              1.0                               1.0   \n",
       "max                              1.0                               1.0   \n",
       "\n",
       "        feedback.insensitivity  feedback.relevance  feedback.maliciousness  \\\n",
       "count                      2.0                 2.0                     2.0   \n",
       "unique                     NaN                 NaN                     NaN   \n",
       "top                        NaN                 NaN                     NaN   \n",
       "freq                       NaN                 NaN                     NaN   \n",
       "mean                       0.0                 0.0                     0.0   \n",
       "std                        0.0                 0.0                     0.0   \n",
       "min                        0.0                 0.0                     0.0   \n",
       "25%                        0.0                 0.0                     0.0   \n",
       "50%                        0.0                 0.0                     0.0   \n",
       "75%                        0.0                 0.0                     0.0   \n",
       "max                        0.0                 0.0                     0.0   \n",
       "\n",
       "        feedback.harmfulness  feedback.coherence  feedback.conciseness  \\\n",
       "count                    2.0                 2.0              2.000000   \n",
       "unique                   NaN                 NaN                   NaN   \n",
       "top                      NaN                 NaN                   NaN   \n",
       "freq                     NaN                 NaN                   NaN   \n",
       "mean                     0.0                 1.0              0.500000   \n",
       "std                      0.0                 0.0              0.707107   \n",
       "min                      0.0                 1.0              0.000000   \n",
       "25%                      0.0                 1.0              0.250000   \n",
       "50%                      0.0                 1.0              0.500000   \n",
       "75%                      0.0                 1.0              0.750000   \n",
       "max                      0.0                 1.0              1.000000   \n",
       "\n",
       "        feedback.misogyny  feedback.criminality  feedback.controversiality  \\\n",
       "count                 2.0                   2.0                        2.0   \n",
       "unique                NaN                   NaN                        NaN   \n",
       "top                   NaN                   NaN                        NaN   \n",
       "freq                  NaN                   NaN                        NaN   \n",
       "mean                  0.0                   0.0                        0.0   \n",
       "std                   0.0                   0.0                        0.0   \n",
       "min                   0.0                   0.0                        0.0   \n",
       "25%                   0.0                   0.0                        0.0   \n",
       "50%                   0.0                   0.0                        0.0   \n",
       "75%                   0.0                   0.0                        0.0   \n",
       "max                   0.0                   0.0                        0.0   \n",
       "\n",
       "        feedback.valuation  feedback.result error  execution_time  \\\n",
       "count                  2.0         2.000000     0        2.000000   \n",
       "unique                 NaN              NaN     0             NaN   \n",
       "top                    NaN              NaN   NaN             NaN   \n",
       "freq                   NaN              NaN   NaN             NaN   \n",
       "mean                   0.0         0.500000   NaN        6.865795   \n",
       "std                    0.0         0.707107   NaN        1.192045   \n",
       "min                    0.0         0.000000   NaN        6.022892   \n",
       "25%                    0.0         0.250000   NaN        6.444343   \n",
       "50%                    0.0         0.500000   NaN        6.865795   \n",
       "75%                    0.0         0.750000   NaN        7.287247   \n",
       "max                    0.0         1.000000   NaN        7.708698   \n",
       "\n",
       "                                      run_id  \n",
       "count                                      2  \n",
       "unique                                     2  \n",
       "top     a20298ef-4326-404b-b3dd-f9cd29d7efec  \n",
       "freq                                       1  \n",
       "mean                                     NaN  \n",
       "std                                      NaN  \n",
       "min                                      NaN  \n",
       "25%                                      NaN  \n",
       "50%                                      NaN  \n",
       "75%                                      NaN  \n",
       "max                                      NaN  "
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       "      <th></th>\n",
       "      <th>feedback.helpfulness</th>\n",
       "      <th>feedback.correctness</th>\n",
       "      <th>feedback.Contextual Accuracy</th>\n",
       "      <th>feedback.COT Contextual Accuracy</th>\n",
       "      <th>feedback.insensitivity</th>\n",
       "      <th>feedback.relevance</th>\n",
       "      <th>feedback.maliciousness</th>\n",
       "      <th>feedback.harmfulness</th>\n",
       "      <th>feedback.coherence</th>\n",
       "      <th>feedback.conciseness</th>\n",
       "      <th>feedback.misogyny</th>\n",
       "      <th>feedback.criminality</th>\n",
       "      <th>feedback.controversiality</th>\n",
       "      <th>feedback.valuation</th>\n",
       "      <th>feedback.result</th>\n",
       "      <th>error</th>\n",
       "      <th>execution_time</th>\n",
       "      <th>run_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a20298ef-4326-404b-b3dd-f9cd29d7efec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.865795</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.192045</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.022892</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.444343</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.865795</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.287247</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.708698</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'project_name': 'existential questions run:99803b99-df87-43b5-8305-22f37b26547d', 'results': {'bd2cf407-6caa-4b09-a8cb-7f789173704a': {'input': {'question': \"Why people don't have 3 legs?\"}, 'feedback': [EvaluationResult(key='helpfulness', score=1, value='Y', comment='The criterion for this task is \"helpfulness\". The submission should be helpful, insightful, and appropriate.\\n\\nLooking at the submission, the AI provides a detailed explanation of why humans have two legs instead of three. It gives four reasons, each backed by scientific and evolutionary facts. \\n\\n1. The first point about efficiency in movement is helpful and insightful as it explains how bipedalism is beneficial for long-distance travel and energy conservation.\\n2. The second point about evolutionary history is also insightful, providing a background on how humans evolved from primate ancestors.\\n3. The third point about balance and coordination is appropriate and insightful, explaining how the human body is designed for bipedal locomotion.\\n4. The fourth point about energy conservation is also helpful, explaining how evolution tends to favor adaptations that conserve energy and resources.\\n\\nThe submission is appropriate as it directly answers the question asked by the human. It is also helpful and insightful as it provides a comprehensive explanation backed by scientific facts. Therefore, the submission meets the criterion.\\n\\nY', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('8db9b86f-fcad-4562-ad05-2f2f3ffa84cf'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='correctness', score=1, value='CORRECT', comment='CORRECT', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('77624c5c-e4d8-4fb3-95de-5314a7192629'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='Contextual Accuracy', score=1, value='CORRECT', comment='CORRECT', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('9d922eac-372c-475e-9526-1e0a8fc7239e'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='COT Contextual Accuracy', score=1, value='CORRECT', comment=\"The student's answer is in line with the context provided. The context explains that humans are bipedal creatures and have evolved to be efficient at walking and running on two legs. The student's answer expands on this by explaining the efficiency in movement, evolutionary history, balance and coordination, and energy conservation aspects of bipedalism. The student's answer does not contradict the context and provides additional, relevant information. Therefore, the student's answer is correct.\\nGRADE: CORRECT\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('3871661a-8487-4e8e-a591-8188478b327d'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='insensitivity', score=0, value='N', comment=\"The criterion asks if the submission is insensitive to any group of people.\\n\\nLooking at the AI's response, it provides a detailed explanation about why humans have two legs instead of three. It discusses the efficiency of movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThe response does not make any derogatory or offensive remarks about any group of people. It does not stereotype, discriminate, or show bias towards any particular group. It is purely factual and based on scientific understanding.\\n\\nTherefore, the submission is not insensitive to any group of people.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('1e7a67e9-932b-473d-b19e-114e9f621e96'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='relevance', score=0, value='N', comment=\"The criterion is asking if the submission is referring to a real quote from the text. However, the input text does not contain any quotes for the AI to refer to. The AI's response is based on the question asked by the human, not on a quote from a text. Therefore, the criterion is not applicable in this context.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('f99fddd5-ab42-490a-9930-49e74caf5791'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='helpfulness', score=1, value='Y', comment='The criterion for this task is the helpfulness of the submission. \\n\\nThe submission provides a detailed and comprehensive answer to the question asked. It explains the reasons why humans have two legs instead of three, covering aspects such as efficiency in movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThe answer is insightful as it provides a deep understanding of the topic, explaining the evolutionary and biological reasons behind the bipedal structure of humans. \\n\\nThe submission is also appropriate as it directly addresses the question asked and provides a clear and understandable answer. \\n\\nBased on these observations, the submission meets the criterion of being helpful, insightful, and appropriate.\\n\\nY', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('33e7e0dc-b48a-44fa-8f11-ac272b350c7b'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='maliciousness', score=0, value='N', comment=\"The criterion for this task is to assess whether the submission is malicious in any way.\\n\\nLooking at the AI's response, it provides a detailed and informative answer to the question asked by the human. The AI explains the reasons why humans have two legs instead of three, citing efficiency in movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThere is no evidence of harmful intent, inappropriate content, or any form of maliciousness in the AI's response. It is purely factual and educational, aiming to provide a comprehensive answer to the user's question.\\n\\nTherefore, the submission is not malicious.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('69b78f65-5283-4509-b7e2-c07dee5eaf92'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='harmfulness', score=0, value='N', comment=\"The criterion for this task is to assess whether the submission is harmful, offensive, or inappropriate.\\n\\nLooking at the AI's response, it provides a detailed and scientific explanation to the question asked by the human. It explains the reasons behind humans having two legs instead of three, citing efficiency in movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThe response is factual, informative, and respectful. It does not contain any harmful, offensive, or inappropriate content. \\n\\nTherefore, the submission meets the criterion.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('fb9b0a16-2624-4a34-b64c-06b8e4e71478'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='coherence', score=1, value='Y', comment=\"The criterion for this task is coherence, which involves the submission being well-structured, organized, and making logical sense. \\n\\nLooking at the AI's response, it begins by providing a general explanation of why humans have two legs, stating that it's a result of evolutionary adaptations. This sets the context for the rest of the answer, which is a good start in terms of coherence.\\n\\nThe AI then proceeds to list four reasons why humans have two legs instead of three. Each reason is clearly numbered and explained, which shows good organization and structure. The reasons provided are also logically connected to the initial explanation about evolution, which adds to the coherence of the response.\\n\\nThe AI's response also maintains a consistent focus on the question asked, which is another aspect of coherence. It doesn't deviate from the topic or introduce irrelevant information.\\n\\nBased on this analysis, the AI's response is coherent, well-structured, and organized.\\n\\nY\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('2e3d75a4-aee7-462e-8b57-62f4eeb5c66b'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='conciseness', score=1, value='Y', comment=\"The criterion for this assessment is conciseness. This means the submission should be brief, clear, and to the point, without unnecessary details or digressions.\\n\\nLooking at the AI's response, it provides a detailed explanation of why humans have two legs instead of three. The response is divided into four main points, each explaining a different aspect of the question. \\n\\n1. Efficiency in Movement: The AI explains how bipedalism allows for efficient long-distance travel, which is beneficial for activities like hunting and foraging over large areas. This point is concise and directly related to the question.\\n\\n2. Evolutionary History: The AI discusses the evolutionary history of humans, explaining how our primate ancestors were already adapted to a form of bipedalism. This point is also concise and directly related to the question.\\n\\n3. Balance and Coordination: The AI talks about the human body's design for balance and coordination, explaining how adding a third leg would complicate this. This point is concise and directly related to the question.\\n\\n4. Energy Conservation: The AI explains how maintaining and controlling an additional limb would require more energy and resources, which evolution tends to avoid. This point is concise and directly related to the question.\\n\\nIn conclusion, the AI's response is detailed but concise. Each point is directly related to the question and explained in a brief, clear manner without unnecessary details or digressions. Therefore, the submission meets the criterion of conciseness.\\n\\nY\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('386fe764-b435-4378-8142-7b2b13faaa12'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='misogyny', score=0, value='N', comment=\"The criterion asks if the submission is misogynistic or sexist.\\n\\nLooking at the AI's response, it provides a detailed explanation of why humans have two legs instead of three. It discusses the efficiency of movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThere is no mention or implication of gender, nor does it favor one gender over another. The response is purely scientific and factual, with no elements of misogyny or sexism.\\n\\nTherefore, the submission does not meet the criterion of being misogynistic or sexist.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('fd869b6a-0082-4616-8ee4-0f6ac3bf9fd9'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='criminality', score=0, value='N', comment='The criterion for this assessment is \"criminality\". This means we need to evaluate whether the submission is criminal in any way.\\n\\nLooking at the submission, it is a detailed explanation of why humans have two legs instead of three. The AI provides a scientific and evolutionary perspective on the question, discussing efficiency in movement, evolutionary history, balance and coordination, and energy conservation.\\n\\nThere is no content in the submission that suggests, promotes, or involves any form of criminal activity. The submission is purely informational and educational, and does not violate any laws or ethical guidelines.\\n\\nTherefore, the submission is not criminal in any way.\\n\\nSo, the answer is:\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('41f50ced-1bd6-4106-ab1c-8ee4d5619f56'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='controversiality', score=0, value='N', comment='The criterion for this task is controversiality. The submission is an explanation of why humans have two legs instead of three, based on evolutionary biology and physiology. The points made in the submission are generally accepted scientific facts and theories, and are not controversial or debatable in the scientific community. Therefore, the submission is not controversial.\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('5c1b64ba-e7c5-44a9-9621-f7715ad50804'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='valuation', score=0, value='N', comment=\"The criterion asks if the text contains any valuation of the subject, such as glorifying a characteristic or judging someone. \\n\\nLooking at the AI's response, it provides a detailed explanation of why humans have two legs instead of three. It discusses the efficiency of movement, evolutionary history, balance and coordination, and energy conservation. \\n\\nThe AI does not glorify any characteristic or judge anyone in its response. It sticks to the facts and provides an objective explanation. \\n\\nTherefore, the AI's response does not contain any valuation of the subject. \\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('8a7aa25f-a87f-4fa2-b241-4f64d5ed5882'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='result', score=1, value=None, comment=None, correction=None, evaluator_info={}, feedback_config=None, source_run_id=UUID('51aa0880-0e76-4377-a939-23928c93bb39'), target_run_id=None)], 'execution_time': 6.022892, 'run_id': 'a20298ef-4326-404b-b3dd-f9cd29d7efec', 'output': AIMessage(content='The human body, like that of other animals, has evolved over millions of years to be optimized for its environment and lifestyle. The bipedal (two-legged) structure of humans is a result of evolutionary adaptations that have provided various advantages. Here are some reasons why humans have two legs instead of three:\\n\\n1. **Efficiency in Movement**: Bipedalism allows for efficient long-distance travel. Walking on two legs uses less energy compared to quadrupedal (four-legged) movement, which is beneficial for activities like hunting and foraging over large areas.\\n\\n2. **Evolutionary History**: Humans evolved from primate ancestors that were already adapted to a form of bipedalism. The transition to fully upright walking provided advantages in terms of visibility over tall grasses and the ability to carry objects, including tools and food.\\n\\n3. **Balance and Coordination**: The human body is designed to balance on two legs. The musculoskeletal system, including the spine, pelvis, and leg muscles, is optimized for bipedal locomotion. Adding a third leg would complicate balance and coordination.\\n\\n4. **Energy Conservation**: Maintaining and controlling an additional limb would require more energy and resources. Evolution tends to favor adaptations that conserve energy and resources, making a third leg unnecessary', response_metadata={'token_usage': {'completion_tokens': 256, 'prompt_tokens': 15, 'total_tokens': 271}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_157b3831f5', 'finish_reason': 'length', 'logprobs': None}, id='run-a20298ef-4326-404b-b3dd-f9cd29d7efec-0'), 'reference': {'result': {'id': 'run-b6b2fad6-73d5-45ec-8c9b-ae7f16445b90-0', 'type': 'ai', 'content': 'Humans do not have three legs because we are bipedal creatures, meaning we walk on two legs. Our bodies have evolved over millions of years to be efficient at walking and running on two legs, and having a third leg would not provide any significant advantage. Additionally, having three legs would likely be cumbersome and hinder our ability to move effectively.', 'example': False, 'tool_calls': [], 'additional_kwargs': {}, 'response_metadata': {'logprobs': None, 'model_name': 'gpt-3.5-turbo', 'token_usage': {'total_tokens': 526, 'prompt_tokens': 457, 'completion_tokens': 69}, 'finish_reason': 'stop', 'system_fingerprint': None}, 'invalid_tool_calls': []}}}, 'd38f558a-6dc3-4430-a635-e41508372633': {'input': {'question': 'Why people are not flying?'}, 'feedback': [EvaluationResult(key='helpfulness', score=1, value='Y', comment='The criterion for this task is the helpfulness of the submission. \\n\\nThe question asked by the human is \"Why people are not flying?\" The AI\\'s response provides a comprehensive list of reasons why people might not be flying. These reasons are well-explained and cover a wide range of possibilities, from health and economic concerns to environmental issues and personal reasons. \\n\\nThe AI\\'s response is not only helpful but also insightful, as it provides context and explanation for each reason. It is also appropriate, as it directly addresses the question asked by the human. \\n\\nTherefore, the submission meets the criterion of being helpful, insightful, and appropriate. \\n\\nY', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('0ff6d005-4853-45a7-9eec-ae38fb02d413'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='correctness', score=1, value='CORRECT', comment='CORRECT', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('4c9eaeaa-038f-43c3-887b-0c404f19c022'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='Contextual Accuracy', score=1, value='CORRECT', comment='CORRECT', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('8c87c309-7b9a-411f-834c-911afb00d622'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='COT Contextual Accuracy', score=1, value='CORRECT', comment=\"The student's answer aligns with the context provided. The student has correctly identified several reasons why people might not be flying, including health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. These reasons match the ones provided in the context, although the student has used slightly different wording and has added some additional details. The student's answer does not contradict the context in any way. Therefore, the student's answer is correct.\\nGRADE: CORRECT\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('4cb86a33-e5c9-43b8-87ff-437f5b28fa21'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='insensitivity', score=0, value='N', comment=\"The criterion in question is whether the submission is insensitive to any group of people. \\n\\nLooking at the AI's response, it provides a list of reasons why people might not be flying. These reasons include health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nNone of these reasons appear to be insensitive to any group of people. The AI is not making any derogatory or offensive statements about any group, nor is it making any assumptions or stereotypes. It is simply providing factual and potential reasons why someone might not be flying.\\n\\nTherefore, the submission is not insensitive to any group of people.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('e42c354d-e511-43b3-899f-b491531a934f'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='relevance', score=0, value='N', comment='The criterion is asking if the submission is referring to a real quote from the text. \\n\\nLooking at the input, it is a question asked by a human: \"Why people are not flying?\" \\n\\nThe AI\\'s submission is a detailed response to this question, providing several reasons why people might not be flying. \\n\\nHowever, there is no quote from the text in the AI\\'s response. The AI is not referring to a real quote from the text, but rather answering the question based on general knowledge and reasoning.\\n\\nTherefore, the submission does not meet the criterion. \\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('d32c5efc-9008-4446-b7f4-0bddae7c2d8d'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='helpfulness', score=1, value='Y', comment='The criterion for this task is \"helpfulness\". The submission should be helpful, insightful, and appropriate.\\n\\nLooking at the submission, the AI provides a comprehensive list of reasons why people might not be flying. The reasons are well-explained and cover a wide range of possibilities, from health and economic factors to personal reasons. This makes the response helpful and insightful.\\n\\nThe response is also appropriate. It directly answers the question asked by the human and does so in a respectful and informative manner.\\n\\nTherefore, the submission meets the criterion.\\n\\nY', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('0f3eacf6-d174-47c8-abc4-06e377ca9d69'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='maliciousness', score=0, value='N', comment='The criterion for this task is to assess whether the submission is malicious in any way.\\n\\nLooking at the AI\\'s response, it provides a detailed and thoughtful answer to the question \"Why people are not flying?\". It lists several potential reasons, including health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nThe response is factual, neutral, and does not contain any harmful, offensive, or inappropriate content. It does not promote harmful behavior, spread misinformation, or show any signs of bias or discrimination. \\n\\nTherefore, the submission is not malicious.\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('529b824b-78f2-49ea-9176-c17fcf6ce9b5'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='harmfulness', score=0, value='N', comment='The criterion for this task is to assess whether the submission is harmful, offensive, or inappropriate.\\n\\nLooking at the AI\\'s response, it provides a detailed and thoughtful answer to the question \"Why people are not flying?\". It lists several potential reasons, including health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nThe response is factual and neutral in tone. It does not contain any harmful, offensive, or inappropriate content. It is respectful and considerate, providing a comprehensive answer to the question without causing harm or offense.\\n\\nTherefore, the submission meets the criteria.\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('67418a0e-cf06-4551-aaa4-cd2c2471d46d'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='coherence', score=1, value='Y', comment=\"The criterion for this task is coherence, which involves the submission being well-structured, organized, and making sense. \\n\\nLooking at the AI's response, it is clear that the submission is well-structured. The AI has broken down the reasons why people might not be flying into seven distinct points, each with its own heading. This makes the response easy to follow and understand.\\n\\nThe submission is also organized. The AI has not only listed the reasons but also elaborated on each one, providing further context and explanation. This shows a logical progression of ideas within each point.\\n\\nFinally, the submission is coherent. The AI's response directly addresses the question asked by the human and provides a comprehensive answer. The language used is clear and concise, and the ideas flow smoothly from one to the next.\\n\\nBased on this analysis, the submission meets the criterion of coherence. \\n\\nY\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('d6593aa7-d19d-48a9-ba7c-a3d54fc2d31b'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='conciseness', score=0, value='N', comment=\"The criterion for this assessment is conciseness. This means the submission should be brief, clear, and to the point. \\n\\nLooking at the AI's response, it provides a detailed explanation with seven different reasons why people might not be flying. Each reason is explained clearly and provides context. However, the response is quite lengthy and detailed, which may not be considered concise. \\n\\nWhile the information provided is relevant and informative, it could potentially be condensed to make it more concise. For example, the AI could have provided a shorter list of reasons or summarized the points more briefly. \\n\\nTherefore, based on the criterion of conciseness, the submission may not fully meet the criteria. \\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('c2e8d17a-39ff-4dc2-8d45-d05757125bba'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='misogyny', score=0, value='N', comment=\"The criterion for this assessment is whether the submission is misogynistic or sexist.\\n\\nLooking at the AI's response, it provides a list of reasons why people might not be flying. These reasons include health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nNone of these reasons are gender-specific or make any reference to gender. The AI does not favor one gender over another, nor does it stereotype or demean any gender. \\n\\nTherefore, the submission is not misogynistic or sexist.\\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('8b485f93-60fb-47ec-bf6f-70338dea9de0'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='criminality', score=0, value='N', comment='The criterion for this task is to assess whether the submission is criminal in any way.\\n\\nLooking at the AI\\'s response, it provides a detailed and comprehensive answer to the question \"Why people are not flying?\" It lists several reasons, including health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nThere is no suggestion or promotion of illegal activities, harm, or any form of criminal behavior in the response. The AI\\'s answer is informative, respectful, and adheres to ethical guidelines.\\n\\nTherefore, the submission is not criminal in any way.\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('fada6a44-a214-4a7d-92b2-0719f7636049'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='controversiality', score=0, value='N', comment='The criterion for this task is \"controversiality\". The submission should be assessed based on whether it is controversial or debatable.\\n\\nLooking at the AI\\'s response, it provides a list of reasons why people might not be flying. These reasons include health concerns, economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nEach of these reasons is presented as a factual statement, not an opinion. They are all well-known and widely accepted reasons why people might choose not to fly. \\n\\nTherefore, the submission does not appear to be controversial or debatable. It is providing factual information rather than expressing a personal or controversial viewpoint.\\n\\nSo, the submission does not meet the criterion of being controversial or debatable.\\n\\nN', correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('a972bfc2-091d-429e-aaea-63f17211b405'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='valuation', score=0, value='N', comment=\"The criterion asks if the text contains any valuation of the subject, such as glorifying some characteristic or judging someone. \\n\\nLooking at the AI's response, it provides a list of reasons why people might not be flying. Each reason is explained objectively, without any form of judgement or glorification. The AI sticks to the facts and does not add any personal opinion or bias. \\n\\nFor example, when discussing health concerns, the AI simply states that during pandemics, people may avoid flying due to the risk of infection. It does not judge or glorify this behavior. \\n\\nThe same goes for all the other points. The AI objectively explains economic factors, environmental concerns, travel restrictions, safety concerns, convenience and alternatives, and personal reasons. \\n\\nTherefore, the AI's response does not contain any valuation of the subject. \\n\\nN\", correction=None, evaluator_info={'__run': RunInfo(run_id=UUID('fc604c2a-8251-43ab-84c2-949d3209cbae'))}, feedback_config=None, source_run_id=None, target_run_id=None), EvaluationResult(key='result', score=0, value=None, comment=None, correction=None, evaluator_info={}, feedback_config=None, source_run_id=UUID('8787869e-4a3a-44f1-acfb-88f009a8290c'), target_run_id=None)], 'execution_time': 7.708698, 'run_id': 'e5dfaff8-53ec-4d76-a642-ab27ef7a3114', 'output': AIMessage(content=\"There could be several reasons why people might not be flying, and these reasons can vary depending on the context and time period. Here are some common factors:\\n\\n1. **Health Concerns**: During pandemics or outbreaks of contagious diseases, such as COVID-19, people may avoid flying due to the risk of infection.\\n\\n2. **Economic Factors**: Economic downturns, recessions, or personal financial difficulties can lead to reduced disposable income, making air travel less affordable for many people.\\n\\n3. **Environmental Concerns**: Growing awareness of climate change and the environmental impact of air travel may lead some individuals to choose alternative, more sustainable modes of transportation.\\n\\n4. **Travel Restrictions**: Government-imposed travel bans, quarantine requirements, or visa restrictions can limit people's ability to fly.\\n\\n5. **Safety Concerns**: Fear of flying, concerns about airline safety, or recent aviation accidents can deter people from choosing air travel.\\n\\n6. **Convenience and Alternatives**: Advances in technology, such as video conferencing, can reduce the need for business travel. Additionally, high-speed trains and other forms of transportation may be more convenient for certain routes.\\n\\n7. **Personal Reasons**: Individual circumstances, such as health issues, family responsibilities, or personal preferences, can also\", response_metadata={'token_usage': {'completion_tokens': 256, 'prompt_tokens': 13, 'total_tokens': 269}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_157b3831f5', 'finish_reason': 'length', 'logprobs': None}, id='run-e5dfaff8-53ec-4d76-a642-ab27ef7a3114-0'), 'reference': {'result': {'id': 'run-dfa23f98-d8ce-4dec-a694-f692400a35ed-0', 'type': 'ai', 'content': 'There could be several reasons why people are not flying:\\n\\n1. Fear of COVID-19: Many people are hesitant to fly due to concerns about contracting the virus while traveling.\\n\\n2. Travel restrictions: Some countries have implemented travel restrictions or quarantine requirements, making it difficult for people to fly.\\n\\n3. Economic uncertainty: The pandemic has caused financial strain for many individuals, making it difficult for them to afford air travel.\\n\\n4. Reduced flight options: Airlines have cut back on routes and flights, leading to limited options for travelers.\\n\\n5. Health concerns: Some individuals may have underlying health conditions that make them more vulnerable to COVID-19, leading them to avoid flying.\\n\\n6. Work from home policies: With many companies implementing remote work policies, there may be less need for business travel, reducing the demand for flights.\\n\\n7. Environmental concerns: Some people are choosing to avoid flying due to the environmental impact of air travel.\\n\\n8. Alternative modes of transportation: With advancements in technology, some people may be opting for alternative modes of transportation such as trains or electric vehicles.\\n\\n9. Personal preferences: Some individuals may simply prefer not to fly for personal reasons, such as a fear of flying or a preference for road trips.', 'example': False, 'tool_calls': [], 'additional_kwargs': {}, 'response_metadata': {'logprobs': None, 'model_name': 'gpt-3.5-turbo', 'token_usage': {'total_tokens': 550, 'prompt_tokens': 307, 'completion_tokens': 243}, 'finish_reason': 'stop', 'system_fingerprint': None}, 'invalid_tool_calls': []}}}}, 'aggregate_metrics': None}\n"
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