{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can download the `requirements.txt` for this course from the workspace of this lab. `File --> Open...`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# L2: Create Agents to Research and Write an Article\n",
    "\n",
    "In this lesson, you will be introduced to the foundational concepts of multi-agent systems and get an overview of the crewAI framework."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The libraries are already installed in the classroom. If you're running this notebook on your own machine, you can install the following:\n",
    "```Python\n",
    "!pip install crewai==0.28.8 crewai_tools==0.1.6 langchain_community==0.0.29\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "height": 64
   },
   "outputs": [],
   "source": [
    "# Warning control\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Import from the crewAI libray."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "height": 166
   },
   "outputs": [],
   "source": [
    "from crewai import Agent, Task, Crew\n",
    "from crewai_tools import (\n",
    "    #DirectoryReadTool,\n",
    "    #FileReadTool,\n",
    "    #SerperDevTool,\n",
    "    #WebsiteSearchTool,\n",
    "    #DOCXSearchTool,\n",
    "    #RagTool,\n",
    "    TXTSearchTool\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- As a LLM for your agents, you'll be using OpenAI's `gpt-3.5-turbo`.\n",
    "\n",
    "**Optional Note:** crewAI also allow other popular models to be used as a LLM for your Agents. You can see some of the examples at the [bottom of the notebook](#1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "height": 149
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from utils import get_openai_api_key\n",
    "\n",
    "# Set up API keys\n",
    "\n",
    "openai_api_key = get_openai_api_key()\n",
    "\n",
    "os.environ[\"OPENAI_MODEL_NAME\"] = 'gpt-3.5-turbo'\n",
    "os.environ[\"OPENAI_API_KEY\"] = \"sk-proj-h6HzpeR29C5zZHqleyLMT3BlbkFJLJCKDOrG3ZzYHE03EQHH\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "height": 132
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Inserting batches in chromadb:   0%|          | 0/1 [00:04<?, ?it/s]\n",
      "Inserting batches in chromadb:   0%|          | 0/1 [00:03<?, ?it/s]\n"
     ]
    }
   ],
   "source": [
    "# Instantiate tools\n",
    "#meeting_trans_docs_tool = DirectoryReadTool(directory='./meeting-transcription')\n",
    "#brd_temp_docs_tool = DirectoryReadTool(directory='./brd-template')\n",
    "#file_tool = FileReadTool()\n",
    "#web_rag_tool = WebsiteSearchTool()\n",
    "#docx_search_tool = DOCXSearchTool()\n",
    "#rag_tool = RagTool()\n",
    "mt_tool = TXTSearchTool(txt='./meeting-transcription/meeting-transcript.txt')\n",
    "brd_tool = TXTSearchTool(txt='./brd-template/brd-template.txt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating Agents\n",
    "\n",
    "- Define your Agents, and provide them a `role`, `goal` and `backstory`.\n",
    "- It has been seen that LLMs perform better when they are role playing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agent: Planner\n",
    "\n",
    "**Note**: The benefit of using _multiple strings_ :\n",
    "```Python\n",
    "varname = \"line 1 of text\"\n",
    "          \"line 2 of text\"\n",
    "```\n",
    "\n",
    "versus the _triple quote docstring_:\n",
    "```Python\n",
    "varname = \"\"\"line 1 of text\n",
    "             line 2 of text\n",
    "          \"\"\"\n",
    "```\n",
    "is that it can avoid adding those whitespaces and newline characters, making it better formatted to be passed to the LLM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "height": 200
   },
   "outputs": [],
   "source": [
    "text_parsing_agent = Agent(\n",
    "    role=\"Text Interpreter\",\n",
    "    goal=\"Parse and interpret the raw text input, structuring it into manageable sections\"\n",
    "         \"or data points that are relevant for analysis and processing.\",\n",
    "    backstory=\"You excel at deciphering complex textual data. You act as the first line of analysis,\"\n",
    "         \"turning unstructured text into organized segments. You should enhance efficiency in data\"\n",
    "         \"handling and support subsequent stages of data processing.\",\n",
    "    tools=[mt_tool],\n",
    "    allow_delegation=True,\n",
    "\tverbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agent: Writer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "height": 217
   },
   "outputs": [],
   "source": [
    "data_extraction_agent = Agent(\n",
    "    role=\"Data Extraction Agent\",\n",
    "    goal=\"Identify and extract essential data points, statistics,\"\n",
    "         \"and specific information from the parsed text that are crucial\"\n",
    "         \"for drafting a Business Requirements Document.\",\n",
    "    backstory=\"You should tackle the challenge of sifting through detailed textual data to\"\n",
    "         \"find relevant information. You should be doing it with precision and speed, equipped\"\n",
    "         \"with capabilities to recognize and categorize data efficiently, making it invaluable\"\n",
    "         \"for projects requiring quick turnaround and accurate data handling.\",\n",
    "    tools=[mt_tool, brd_tool],\n",
    "    allow_delegation=True,\n",
    "    verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agent: Editor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "height": 251
   },
   "outputs": [],
   "source": [
    "brd_compiler_agent = Agent(\n",
    "    role=\"BRD Compiler\",\n",
    "    goal=\"Assemble the extracted data into a well-structured Business Requirements Document,\"\n",
    "         \"ensuring that it is clear, coherent, and formatted according to standards.\",\n",
    "    backstory=\"You are a meticulous Business Requirement Document compiler, You should alleviate\"\n",
    "         \"the burdens of manual document assembly. Ensure that all documents are crafted with\"\n",
    "         \"precision, adhering to organizational standards, and ready for stakeholder review. You\"\n",
    "         \"should be automating routine documentation tasks, thus allowing human team members to focus\"\n",
    "         \"on more strategic activities.\",\n",
    "    tools=[brd_tool],\n",
    "    output_file='generated-brd/brd.md',  # The final blog post will be saved here\n",
    "    allow_delegation=True,\n",
    "    verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating Tasks\n",
    "\n",
    "- Define your Tasks, and provide them a `description`, `expected_output` and `agent`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task: Plan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "height": 217
   },
   "outputs": [],
   "source": [
    "text_parsing = Task(\n",
    "    description=(\n",
    "        \"1. Open and read the contents of the input text file.\\n\"\n",
    "        \"2. Analyze the document structure to identify headings, subheadings, and key paragraphs.\\n\"\n",
    "        \"3. Extract text under each identified section, ensuring context is preserved.\\n\"\n",
    "        \"4. Format the extracted text into a JSON structure with labels indicating the type\"\n",
    "            \"of content (e.g., heading, detail).\"\n",
    "    ),\n",
    "    expected_output=\"Structured JSON object containing separated sections of\"\n",
    "                    \"text with labels based on their content type.\",\n",
    "    agent=text_parsing_agent,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task: Write"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "height": 234
   },
   "outputs": [],
   "source": [
    "data_extraction = Task(\n",
    "    description=(\n",
    "        \"1. Take the JSON structured data from the Text Parsing Agent.\\n\"\n",
    "        \"2. Identify and extract specific data points like project goals, technical requirements,\"\n",
    "            \"and stakeholder information.\\n\"\n",
    "\t\t\"3. Organize the extracted data into relevant categories for easy access and use.\\n\"\n",
    "        \"4. Format all extracted data into a structured form suitable for document generation,\"\n",
    "            \"ensuring it's ready for template insertion.\\n\"\n",
    "    ),\n",
    "    expected_output=\"A comprehensive list of key data points organized by category, ready for use in document generation.\",\n",
    "    agent=data_extraction_agent,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task: Edit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "height": 200
   },
   "outputs": [],
   "source": [
    "compile_brd = Task(\n",
    "    description=(\n",
    "        \"1. Accept the structured and categorized data from the Data Extraction Agent.\\n\"\n",
    "        \"2. Open and read the BRD template for data insertion.\\n\"\n",
    "        \"3. Insert the received data into the respective sections of the BRD template.\\n\"\n",
    "        \"4. Apply formatting rules to ensure the document is professional and adheres to standards.\\n\"\n",
    "        \"5. Save the populated and formatted document as a new markdown file, marking the task as complete.\\n\"\n",
    "    ),\n",
    "    expected_output=\"A complete Business Requirements Document in markdown format, ready for review and distribution.\",\n",
    "    agent=brd_compiler_agent\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating the Crew\n",
    "\n",
    "- Create your crew of Agents\n",
    "- Pass the tasks to be performed by those agents.\n",
    "    - **Note**: *For this simple example*, the tasks will be performed sequentially (i.e they are dependent on each other), so the _order_ of the task in the list _matters_.\n",
    "- `verbose=2` allows you to see all the logs of the execution. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "height": 98
   },
   "outputs": [],
   "source": [
    "crew = Crew(\n",
    "    agents=[text_parsing_agent, data_extraction_agent, brd_compiler_agent],\n",
    "    tasks=[text_parsing, data_extraction, compile_brd],\n",
    "    verbose=2\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the Crew"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**: LLMs can provide different outputs for they same input, so what you get might be different than what you see in the video."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[95m [DEBUG]: == Working Agent: Text Interpreter\u001b[00m\n",
      "\u001b[1m\u001b[95m [INFO]: == Starting Task: 1. Open and read the contents of the input text file.\n",
      "2. Analyze the document structure to identify headings, subheadings, and key paragraphs.\n",
      "3. Extract text under each identified section, ensuring context is preserved.\n",
      "4. Format the extracted text into a JSON structure with labels indicating the typeof content (e.g., heading, detail).\u001b[00m\n",
      "\n",
      "\n",
      "\u001b[1m> Entering new CrewAgentExecutor chain...\u001b[0m\n"
     ]
    },
    {
     "ename": "AuthenticationError",
     "evalue": "Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************EQHH. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAuthenticationError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[12], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mcrew\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkickoff\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\crew.py:252\u001b[0m, in \u001b[0;36mCrew.kickoff\u001b[1;34m(self, inputs)\u001b[0m\n\u001b[0;32m    249\u001b[0m metrics \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m    251\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprocess \u001b[38;5;241m==\u001b[39m Process\u001b[38;5;241m.\u001b[39msequential:\n\u001b[1;32m--> 252\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run_sequential_process\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    253\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprocess \u001b[38;5;241m==\u001b[39m Process\u001b[38;5;241m.\u001b[39mhierarchical:\n\u001b[0;32m    254\u001b[0m     result, manager_metrics \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_run_hierarchical_process()\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\crew.py:293\u001b[0m, in \u001b[0;36mCrew._run_sequential_process\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    288\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moutput_log_file:\n\u001b[0;32m    289\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_file_handler\u001b[38;5;241m.\u001b[39mlog(\n\u001b[0;32m    290\u001b[0m         agent\u001b[38;5;241m=\u001b[39mrole, task\u001b[38;5;241m=\u001b[39mtask\u001b[38;5;241m.\u001b[39mdescription, status\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstarted\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    291\u001b[0m     )\n\u001b[1;32m--> 293\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcontext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtask_output\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    294\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m task\u001b[38;5;241m.\u001b[39masync_execution:\n\u001b[0;32m    295\u001b[0m     task_output \u001b[38;5;241m=\u001b[39m output\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\task.py:173\u001b[0m, in \u001b[0;36mTask.execute\u001b[1;34m(self, agent, context, tools)\u001b[0m\n\u001b[0;32m    171\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mthread\u001b[38;5;241m.\u001b[39mstart()\n\u001b[0;32m    172\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 173\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    174\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    175\u001b[0m \u001b[43m        \u001b[49m\u001b[43magent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43magent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    176\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcontext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    177\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtools\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtools\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    178\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    179\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\task.py:182\u001b[0m, in \u001b[0;36mTask._execute\u001b[1;34m(self, agent, task, context, tools)\u001b[0m\n\u001b[0;32m    181\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_execute\u001b[39m(\u001b[38;5;28mself\u001b[39m, agent, task, context, tools):\n\u001b[1;32m--> 182\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute_task\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    183\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    184\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcontext\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    185\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtools\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtools\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    186\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    188\u001b[0m     exported_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_export_output(result)\n\u001b[0;32m    190\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moutput \u001b[38;5;241m=\u001b[39m TaskOutput(\n\u001b[0;32m    191\u001b[0m         description\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdescription,\n\u001b[0;32m    192\u001b[0m         exported_output\u001b[38;5;241m=\u001b[39mexported_output,\n\u001b[0;32m    193\u001b[0m         raw_output\u001b[38;5;241m=\u001b[39mresult,\n\u001b[0;32m    194\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\agent.py:221\u001b[0m, in \u001b[0;36mAgent.execute_task\u001b[1;34m(self, task, context, tools)\u001b[0m\n\u001b[0;32m    218\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39magent_executor\u001b[38;5;241m.\u001b[39mtools_description \u001b[38;5;241m=\u001b[39m render_text_description(parsed_tools)\n\u001b[0;32m    219\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39magent_executor\u001b[38;5;241m.\u001b[39mtools_names \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__tools_names(parsed_tools)\n\u001b[1;32m--> 221\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    222\u001b[0m \u001b[43m    \u001b[49m\u001b[43m{\u001b[49m\n\u001b[0;32m    223\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minput\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtask_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    224\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtool_names\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtools_names\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    225\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtools\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtools_description\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    226\u001b[0m \u001b[43m    \u001b[49m\u001b[43m}\u001b[49m\n\u001b[0;32m    227\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutput\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m    229\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_rpm:\n\u001b[0;32m    230\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_rpm_controller\u001b[38;5;241m.\u001b[39mstop_rpm_counter()\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain\\chains\\base.py:163\u001b[0m, in \u001b[0;36mChain.invoke\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    162\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_chain_error(e)\n\u001b[1;32m--> 163\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m    164\u001b[0m run_manager\u001b[38;5;241m.\u001b[39mon_chain_end(outputs)\n\u001b[0;32m    166\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m include_run_info:\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain\\chains\\base.py:153\u001b[0m, in \u001b[0;36mChain.invoke\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m    150\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    151\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_inputs(inputs)\n\u001b[0;32m    152\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m--> 153\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    154\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m new_arg_supported\n\u001b[0;32m    155\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call(inputs)\n\u001b[0;32m    156\u001b[0m     )\n\u001b[0;32m    158\u001b[0m     final_outputs: Dict[\u001b[38;5;28mstr\u001b[39m, Any] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprep_outputs(\n\u001b[0;32m    159\u001b[0m         inputs, outputs, return_only_outputs\n\u001b[0;32m    160\u001b[0m     )\n\u001b[0;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\agents\\executor.py:124\u001b[0m, in \u001b[0;36mCrewAgentExecutor._call\u001b[1;34m(self, inputs, run_manager)\u001b[0m\n\u001b[0;32m    122\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_continue(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miterations, time_elapsed):\n\u001b[0;32m    123\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest_within_rpm_limit \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest_within_rpm_limit():\n\u001b[1;32m--> 124\u001b[0m         next_step_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_take_next_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    125\u001b[0m \u001b[43m            \u001b[49m\u001b[43mname_to_tool_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    126\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcolor_mapping\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    127\u001b[0m \u001b[43m            \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    128\u001b[0m \u001b[43m            \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    129\u001b[0m \u001b[43m            \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    130\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    131\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstep_callback:\n\u001b[0;32m    132\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstep_callback(next_step_output)\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain\\agents\\agent.py:1138\u001b[0m, in \u001b[0;36mAgentExecutor._take_next_step\u001b[1;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[0;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[0;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[0;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[1;32m-> 1138\u001b[0m         \u001b[43m[\u001b[49m\n\u001b[0;32m   1139\u001b[0m \u001b[43m            \u001b[49m\u001b[43ma\u001b[49m\n\u001b[0;32m   1140\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_iter_next_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   1141\u001b[0m \u001b[43m                \u001b[49m\u001b[43mname_to_tool_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1142\u001b[0m \u001b[43m                \u001b[49m\u001b[43mcolor_mapping\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1143\u001b[0m \u001b[43m                \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1144\u001b[0m \u001b[43m                \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1145\u001b[0m \u001b[43m                \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1146\u001b[0m \u001b[43m            \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1147\u001b[0m \u001b[43m        \u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m   1148\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain\\agents\\agent.py:1138\u001b[0m, in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[0;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[0;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[1;32m-> 1138\u001b[0m         \u001b[43m[\u001b[49m\n\u001b[0;32m   1139\u001b[0m \u001b[43m            \u001b[49m\u001b[43ma\u001b[49m\n\u001b[0;32m   1140\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ma\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_iter_next_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   1141\u001b[0m \u001b[43m                \u001b[49m\u001b[43mname_to_tool_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1142\u001b[0m \u001b[43m                \u001b[49m\u001b[43mcolor_mapping\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1143\u001b[0m \u001b[43m                \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1144\u001b[0m \u001b[43m                \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1145\u001b[0m \u001b[43m                \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   1146\u001b[0m \u001b[43m            \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1147\u001b[0m \u001b[43m        \u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m   1148\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\crewai\\agents\\executor.py:186\u001b[0m, in \u001b[0;36mCrewAgentExecutor._iter_next_step\u001b[1;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[0;32m    183\u001b[0m     intermediate_steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_intermediate_steps(intermediate_steps)\n\u001b[0;32m    185\u001b[0m     \u001b[38;5;66;03m# Call the LLM to see what to do.\u001b[39;00m\n\u001b[1;32m--> 186\u001b[0m     output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplan\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    187\u001b[0m \u001b[43m        \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    188\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    189\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    190\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    192\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m OutputParserException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    193\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_parsing_errors, \u001b[38;5;28mbool\u001b[39m):\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain\\agents\\agent.py:397\u001b[0m, in \u001b[0;36mRunnableAgent.plan\u001b[1;34m(self, intermediate_steps, callbacks, **kwargs)\u001b[0m\n\u001b[0;32m    389\u001b[0m final_output: Any \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    390\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream_runnable:\n\u001b[0;32m    391\u001b[0m     \u001b[38;5;66;03m# Use streaming to make sure that the underlying LLM is invoked in a\u001b[39;00m\n\u001b[0;32m    392\u001b[0m     \u001b[38;5;66;03m# streaming\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    395\u001b[0m     \u001b[38;5;66;03m# Because the response from the plan is not a generator, we need to\u001b[39;00m\n\u001b[0;32m    396\u001b[0m     \u001b[38;5;66;03m# accumulate the output into final output and return that.\u001b[39;00m\n\u001b[1;32m--> 397\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrunnable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcallbacks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m    398\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mfinal_output\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m:\u001b[49m\n\u001b[0;32m    399\u001b[0m \u001b[43m            \u001b[49m\u001b[43mfinal_output\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:2875\u001b[0m, in \u001b[0;36mRunnableSequence.stream\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m   2869\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstream\u001b[39m(\n\u001b[0;32m   2870\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   2871\u001b[0m     \u001b[38;5;28minput\u001b[39m: Input,\n\u001b[0;32m   2872\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   2873\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[0;32m   2874\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[1;32m-> 2875\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtransform(\u001b[38;5;28miter\u001b[39m([\u001b[38;5;28minput\u001b[39m]), config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:2862\u001b[0m, in \u001b[0;36mRunnableSequence.transform\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m   2856\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[0;32m   2857\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   2858\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[0;32m   2859\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   2860\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[0;32m   2861\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[1;32m-> 2862\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_stream_with_config(\n\u001b[0;32m   2863\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[0;32m   2864\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform,\n\u001b[0;32m   2865\u001b[0m         patch_config(config, run_name\u001b[38;5;241m=\u001b[39m(config \u001b[38;5;129;01mor\u001b[39;00m {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_name\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname),\n\u001b[0;32m   2866\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[0;32m   2867\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:1881\u001b[0m, in \u001b[0;36mRunnable._transform_stream_with_config\u001b[1;34m(self, input, transformer, config, run_type, **kwargs)\u001b[0m\n\u001b[0;32m   1879\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m   1880\u001b[0m     \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m-> 1881\u001b[0m         chunk: Output \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[0;32m   1882\u001b[0m         \u001b[38;5;28;01myield\u001b[39;00m chunk\n\u001b[0;32m   1883\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m final_output_supported:\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:2826\u001b[0m, in \u001b[0;36mRunnableSequence._transform\u001b[1;34m(self, input, run_manager, config)\u001b[0m\n\u001b[0;32m   2817\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step \u001b[38;5;129;01min\u001b[39;00m steps:\n\u001b[0;32m   2818\u001b[0m     final_pipeline \u001b[38;5;241m=\u001b[39m step\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[0;32m   2819\u001b[0m         final_pipeline,\n\u001b[0;32m   2820\u001b[0m         patch_config(\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   2823\u001b[0m         ),\n\u001b[0;32m   2824\u001b[0m     )\n\u001b[1;32m-> 2826\u001b[0m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43moutput\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mfinal_pipeline\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m   2827\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43moutput\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:1282\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m   1279\u001b[0m final: Input\n\u001b[0;32m   1280\u001b[0m got_first_val \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m-> 1282\u001b[0m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43michunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m:\u001b[49m\n\u001b[0;32m   1283\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# The default implementation of transform is to buffer input and\u001b[39;49;00m\n\u001b[0;32m   1284\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# then call stream.\u001b[39;49;00m\n\u001b[0;32m   1285\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# It'll attempt to gather all input into a single chunk using\u001b[39;49;00m\n\u001b[0;32m   1286\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# the `+` operator.\u001b[39;49;00m\n\u001b[0;32m   1287\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# If the input is not addable, then we'll assume that we can\u001b[39;49;00m\n\u001b[0;32m   1288\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# only operate on the last chunk,\u001b[39;49;00m\n\u001b[0;32m   1289\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# and we'll iterate until we get to the last chunk.\u001b[39;49;00m\n\u001b[0;32m   1290\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mgot_first_val\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m   1291\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfinal\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43michunk\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:4736\u001b[0m, in \u001b[0;36mRunnableBindingBase.transform\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m   4730\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[0;32m   4731\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   4732\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[0;32m   4733\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   4734\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[0;32m   4735\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[1;32m-> 4736\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbound\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[0;32m   4737\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[0;32m   4738\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_merge_configs(config),\n\u001b[0;32m   4739\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs},\n\u001b[0;32m   4740\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\runnables\\base.py:1300\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[1;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[0;32m   1297\u001b[0m             final \u001b[38;5;241m=\u001b[39m ichunk\n\u001b[0;32m   1299\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m got_first_val:\n\u001b[1;32m-> 1300\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream(final, config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\language_models\\chat_models.py:249\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[1;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[0;32m    242\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    243\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_error(\n\u001b[0;32m    244\u001b[0m         e,\n\u001b[0;32m    245\u001b[0m         response\u001b[38;5;241m=\u001b[39mLLMResult(\n\u001b[0;32m    246\u001b[0m             generations\u001b[38;5;241m=\u001b[39m[[generation]] \u001b[38;5;28;01mif\u001b[39;00m generation \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[0;32m    247\u001b[0m         ),\n\u001b[0;32m    248\u001b[0m     )\n\u001b[1;32m--> 249\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m    250\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    251\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_end(LLMResult(generations\u001b[38;5;241m=\u001b[39m[[generation]]))\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_core\\language_models\\chat_models.py:229\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[1;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[0;32m    227\u001b[0m generation: Optional[ChatGenerationChunk] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    228\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 229\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_stream\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m    230\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m:\u001b[49m\n\u001b[0;32m    231\u001b[0m \u001b[43m            \u001b[49m\u001b[43mchunk\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrun-\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_id\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\langchain_openai\\chat_models\\base.py:408\u001b[0m, in \u001b[0;36mChatOpenAI._stream\u001b[1;34m(self, messages, stop, run_manager, **kwargs)\u001b[0m\n\u001b[0;32m    405\u001b[0m params \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mTrue\u001b[39;00m}\n\u001b[0;32m    407\u001b[0m default_chunk_class \u001b[38;5;241m=\u001b[39m AIMessageChunk\n\u001b[1;32m--> 408\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessage_dicts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[0;32m    409\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(chunk, \u001b[38;5;28mdict\u001b[39m):\n\u001b[0;32m    410\u001b[0m         chunk \u001b[38;5;241m=\u001b[39m chunk\u001b[38;5;241m.\u001b[39mdict()\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\openai\\_utils\\_utils.py:277\u001b[0m, in \u001b[0;36mrequired_args.<locals>.inner.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    275\u001b[0m             msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[38;5;241m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    276\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[1;32m--> 277\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\openai\\resources\\chat\\completions.py:606\u001b[0m, in \u001b[0;36mCompletions.create\u001b[1;34m(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, parallel_tool_calls, presence_penalty, response_format, seed, stop, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[0;32m    573\u001b[0m \u001b[38;5;129m@required_args\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m], [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m    574\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[0;32m    575\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    604\u001b[0m     timeout: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m|\u001b[39m httpx\u001b[38;5;241m.\u001b[39mTimeout \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m|\u001b[39m NotGiven \u001b[38;5;241m=\u001b[39m NOT_GIVEN,\n\u001b[0;32m    605\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ChatCompletion \u001b[38;5;241m|\u001b[39m Stream[ChatCompletionChunk]:\n\u001b[1;32m--> 606\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    607\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/chat/completions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    608\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    609\u001b[0m \u001b[43m            \u001b[49m\u001b[43m{\u001b[49m\n\u001b[0;32m    610\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmessages\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    611\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmodel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    612\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfrequency_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    613\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunction_call\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunction_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    614\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunctions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunctions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    615\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogit_bias\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogit_bias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    616\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogprobs\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogprobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    617\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmax_tokens\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    618\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mn\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    619\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mparallel_tool_calls\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mparallel_tool_calls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    620\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpresence_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    621\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mresponse_format\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mresponse_format\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    622\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mseed\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m 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\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtemperature\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    627\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtool_choice\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtool_choice\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    628\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtools\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtools\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    629\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtop_logprobs\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_logprobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    630\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtop_p\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    631\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43muser\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43muser\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    632\u001b[0m \u001b[43m            \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    633\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcompletion_create_params\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCompletionCreateParams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    634\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    635\u001b[0m \u001b[43m        \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    636\u001b[0m \u001b[43m            \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\n\u001b[0;32m    637\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    638\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mChatCompletion\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    639\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    640\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mStream\u001b[49m\u001b[43m[\u001b[49m\u001b[43mChatCompletionChunk\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    641\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\openai\\_base_client.py:1240\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[1;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[0;32m   1226\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[0;32m   1227\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   1228\u001b[0m     path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1235\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m   1236\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[0;32m   1237\u001b[0m     opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[0;32m   1238\u001b[0m         method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, json_data\u001b[38;5;241m=\u001b[39mbody, files\u001b[38;5;241m=\u001b[39mto_httpx_files(files), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions\n\u001b[0;32m   1239\u001b[0m     )\n\u001b[1;32m-> 1240\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\openai\\_base_client.py:921\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m    912\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\n\u001b[0;32m    913\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m    914\u001b[0m     cast_to: Type[ResponseT],\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    919\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m    920\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[1;32m--> 921\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    922\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    923\u001b[0m \u001b[43m        \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    924\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    925\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    926\u001b[0m \u001b[43m        \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    927\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\Fozan\\Downloads\\OneDrive_2024-06-09\\.venv\\Lib\\site-packages\\openai\\_base_client.py:1020\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m   1017\u001b[0m         err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[0;32m   1019\u001b[0m     log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRe-raising status error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m-> 1020\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_status_error_from_response(err\u001b[38;5;241m.\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m   1022\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_response(\n\u001b[0;32m   1023\u001b[0m     cast_to\u001b[38;5;241m=\u001b[39mcast_to,\n\u001b[0;32m   1024\u001b[0m     options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1027\u001b[0m     stream_cls\u001b[38;5;241m=\u001b[39mstream_cls,\n\u001b[0;32m   1028\u001b[0m )\n",
      "\u001b[1;31mAuthenticationError\u001b[0m: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************EQHH. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "result = crew.kickoff(inputs={})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Display the results of your execution as markdown in the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "height": 47
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "# Business Requirements Document\n",
       "\n",
       "## Project Goals:\n",
       "1. **Increase customer engagement by 20% within the next quarter**\n",
       "2. **Implement a new CRM system to streamline communication**\n",
       "\n",
       "## Technical Requirements:\n",
       "1. **Integration with existing database systems**\n",
       "2. **Mobile responsiveness for all user interfaces**\n",
       "\n",
       "## Stakeholder Information:\n",
       "1. **Stakeholder 1:**\n",
       "   - **Name:** John Smith\n",
       "   - **Role:** Project Manager\n",
       "   - **Contact:** jsmith@email.com\n",
       "\n",
       "2. **Stakeholder 2:**\n",
       "   - **Name:** Emily Johnson\n",
       "   - **Role:** Lead Developer\n",
       "   - **Contact:** ejohnson@email.com"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Markdown\n",
    "Markdown(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python 3.11.9\n"
     ]
    }
   ],
   "source": [
    "!python --version"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "gpuType": "T4",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}