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{
"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 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\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
}
|