340 lines
42 KiB
Plaintext
340 lines
42 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "6e9a4f41",
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"metadata": {},
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"source": [
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"<div style=\"background-color:#000;\"><img src=\"pqn.png\"></img></div>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fd709f5c",
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"metadata": {},
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"source": [
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"This code integrates LangChain library functionalities to process and query PDF documents using OpenAI's language model. It loads a PDF file, splits it into pages, and stores these pages in a vector database (ChromaDB). It then creates a toolkit to interact with the vector store and uses an agent executor to query the database based on user input. This is useful for extracting and querying information from structured documents like financial reports."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "58bade97",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "ce47c00a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.llms import OpenAI\n",
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"from langchain.document_loaders import PyPDFLoader\n",
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"from langchain.vectorstores import Chroma\n",
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"from langchain.agents.agent_toolkits import (\n",
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" create_vectorstore_agent,\n",
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" VectorStoreToolkit,\n",
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" VectorStoreInfo,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "18b8f141",
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"metadata": {},
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"source": [
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"Set the OpenAI API key for authentication"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "7a0ddde1",
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"metadata": {},
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"outputs": [],
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"source": [
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"os.environ[\"OPENAI_API_KEY\"] = \"\"\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "9cb3ca7c",
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"metadata": {},
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"source": [
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"Create an instance of the OpenAI language model with specified parameters"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "396ba311",
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"metadata": {},
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"outputs": [
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{
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"ename": "AuthenticationError",
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"evalue": "Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-nzJ5u***************************************N1s3. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mAuthenticationError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[20], line 9\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mopenai\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m OpenAI\n\u001b[1;32m 4\u001b[0m client \u001b[38;5;241m=\u001b[39m OpenAI(\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# This is the default and can be omitted\u001b[39;00m\n\u001b[1;32m 6\u001b[0m api_key\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msk-nzJ5uA1io2NoFJNj6Z67T3BlbkFJr0ictKLQNDqKkEsCN1s3\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 7\u001b[0m )\n\u001b[0;32m----> 9\u001b[0m chat_completion \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompletions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrole\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\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\n\u001b[1;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcontent\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSay this is a test\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 14\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgpt-3.5-turbo\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 17\u001b[0m \u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/openai/_utils/_utils.py:274\u001b[0m, in \u001b[0;36mrequired_args.<locals>.inner.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 272\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[1;32m 273\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[0;32m--> 274\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",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/openai/resources/chat/completions.py:815\u001b[0m, in \u001b[0;36mCompletions.create\u001b[0;34m(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, presence_penalty, response_format, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m 775\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[1;32m 776\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[1;32m 777\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 812\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[1;32m 813\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 814\u001b[0m validate_response_format(response_format)\n\u001b[0;32m--> 815\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[1;32m 816\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[1;32m 817\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[1;32m 818\u001b[0m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m 819\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[1;32m 820\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[1;32m 821\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43maudio\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43maudio\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 822\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[1;32m 823\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[1;32m 824\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[1;32m 825\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[1;32m 826\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[1;32m 827\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmax_completion_tokens\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_completion_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 828\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[1;32m 829\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmetadata\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 830\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmodalities\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodalities\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 831\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[1;32m 832\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[1;32m 833\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[1;32m 834\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[1;32m 835\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 \u001b[49m\u001b[43mseed\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 836\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mservice_tier\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mservice_tier\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 837\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstop\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 838\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstore\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstore\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 839\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstream\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 840\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstream_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 841\u001b[0m \u001b[43m \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[1;32m 842\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[1;32m 843\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[1;32m 844\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[1;32m 845\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[1;32m 846\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[1;32m 847\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 848\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[1;32m 849\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 850\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[1;32m 851\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[1;32m 852\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 853\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[1;32m 854\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[1;32m 855\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[1;32m 856\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
|
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/openai/_base_client.py:1277\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m 1263\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[1;32m 1264\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 1265\u001b[0m path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1272\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[1;32m 1273\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 1274\u001b[0m opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[1;32m 1275\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[1;32m 1276\u001b[0m )\n\u001b[0;32m-> 1277\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",
|
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/openai/_base_client.py:954\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m 951\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 952\u001b[0m retries_taken \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m--> 954\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[1;32m 955\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[1;32m 956\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[1;32m 957\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[1;32m 958\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[1;32m 959\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 960\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
|
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/openai/_base_client.py:1058\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, retries_taken, stream, stream_cls)\u001b[0m\n\u001b[1;32m 1055\u001b[0m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[1;32m 1057\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[0;32m-> 1058\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[1;32m 1060\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[1;32m 1061\u001b[0m cast_to\u001b[38;5;241m=\u001b[39mcast_to,\n\u001b[1;32m 1062\u001b[0m options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1066\u001b[0m retries_taken\u001b[38;5;241m=\u001b[39mretries_taken,\n\u001b[1;32m 1067\u001b[0m )\n",
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"\u001b[0;31mAuthenticationError\u001b[0m: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-nzJ5u***************************************N1s3. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}"
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]
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}
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],
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"source": [
|
|
"import os\n",
|
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"from openai import OpenAI\n",
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"\n",
|
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"client = OpenAI(\n",
|
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" # This is the default and can be omitted\n",
|
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" api_key=\"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\",\n",
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")\n",
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"\n",
|
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"chat_completion = client.chat.completions.create(\n",
|
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" messages=[\n",
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" {\n",
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" \"role\": \"user\",\n",
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" \"content\": \"Say this is a test\",\n",
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" }\n",
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" ],\n",
|
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" model=\"gpt-3.5-turbo\",\n",
|
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")"
|
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]
|
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 5,
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"id": "6ebf63b0",
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"metadata": {},
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"outputs": [],
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"source": [
|
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"llm = OpenAI(temperature=0.1, verbose=True)"
|
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]
|
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},
|
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{
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"cell_type": "markdown",
|
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"id": "e5e50726",
|
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"metadata": {},
|
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"source": [
|
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"Initialize a PDF loader for the specified file"
|
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 8,
|
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"id": "681ccbf2",
|
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"metadata": {},
|
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"outputs": [],
|
|
"source": [
|
|
"loader = PyPDFLoader(\"apple.pdf\")"
|
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]
|
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},
|
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{
|
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"cell_type": "markdown",
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"id": "41e538eb",
|
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"metadata": {},
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"source": [
|
|
"Split the PDF into individual pages for processing"
|
|
]
|
|
},
|
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{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
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"id": "adf3f45c",
|
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"metadata": {},
|
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"outputs": [],
|
|
"source": [
|
|
"pages = loader.load_and_split()"
|
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]
|
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},
|
|
{
|
|
"cell_type": "markdown",
|
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"id": "fbbc170b",
|
|
"metadata": {},
|
|
"source": [
|
|
"Load the split pages into a Chroma vector database for efficient querying"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
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"execution_count": 14,
|
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"id": "964eaa4a",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "ValueError",
|
|
"evalue": "You must provide an embedding function to compute embeddings.https://docs.trychroma.com/guides/embeddings",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
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"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m store \u001b[38;5;241m=\u001b[39m \u001b[43mChroma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_documents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcollection_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mannualreport\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/langchain_community/vectorstores/chroma.py:878\u001b[0m, in \u001b[0;36mChroma.from_documents\u001b[0;34m(cls, documents, embedding, ids, collection_name, persist_directory, client_settings, client, collection_metadata, **kwargs)\u001b[0m\n\u001b[1;32m 876\u001b[0m texts \u001b[38;5;241m=\u001b[39m [doc\u001b[38;5;241m.\u001b[39mpage_content \u001b[38;5;28;01mfor\u001b[39;00m doc \u001b[38;5;129;01min\u001b[39;00m documents]\n\u001b[1;32m 877\u001b[0m metadatas \u001b[38;5;241m=\u001b[39m [doc\u001b[38;5;241m.\u001b[39mmetadata \u001b[38;5;28;01mfor\u001b[39;00m doc \u001b[38;5;129;01min\u001b[39;00m documents]\n\u001b[0;32m--> 878\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_texts\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 879\u001b[0m \u001b[43m \u001b[49m\u001b[43mtexts\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtexts\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 880\u001b[0m \u001b[43m \u001b[49m\u001b[43membedding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43membedding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 881\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetadatas\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadatas\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 882\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 883\u001b[0m \u001b[43m \u001b[49m\u001b[43mcollection_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcollection_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 884\u001b[0m \u001b[43m \u001b[49m\u001b[43mpersist_directory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpersist_directory\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 885\u001b[0m \u001b[43m \u001b[49m\u001b[43mclient_settings\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclient_settings\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 886\u001b[0m \u001b[43m \u001b[49m\u001b[43mclient\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 887\u001b[0m \u001b[43m \u001b[49m\u001b[43mcollection_metadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcollection_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 888\u001b[0m \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\u001b[1;32m 889\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/langchain_community/vectorstores/chroma.py:842\u001b[0m, in \u001b[0;36mChroma.from_texts\u001b[0;34m(cls, texts, embedding, metadatas, ids, collection_name, persist_directory, client_settings, client, collection_metadata, **kwargs)\u001b[0m\n\u001b[1;32m 836\u001b[0m chroma_collection\u001b[38;5;241m.\u001b[39madd_texts(\n\u001b[1;32m 837\u001b[0m texts\u001b[38;5;241m=\u001b[39mbatch[\u001b[38;5;241m3\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m batch[\u001b[38;5;241m3\u001b[39m] \u001b[38;5;28;01melse\u001b[39;00m [],\n\u001b[1;32m 838\u001b[0m metadatas\u001b[38;5;241m=\u001b[39mbatch[\u001b[38;5;241m2\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m batch[\u001b[38;5;241m2\u001b[39m] \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 839\u001b[0m ids\u001b[38;5;241m=\u001b[39mbatch[\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m 840\u001b[0m )\n\u001b[1;32m 841\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 842\u001b[0m \u001b[43mchroma_collection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd_texts\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtexts\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtexts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadatas\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadatas\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 843\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m chroma_collection\n",
|
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/langchain_community/vectorstores/chroma.py:313\u001b[0m, in \u001b[0;36mChroma.add_texts\u001b[0;34m(self, texts, metadatas, ids, **kwargs)\u001b[0m\n\u001b[1;32m 311\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(e\u001b[38;5;241m.\u001b[39margs[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m msg)\n\u001b[1;32m 312\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 313\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m 314\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m empty_ids:\n\u001b[1;32m 315\u001b[0m texts_without_metadatas \u001b[38;5;241m=\u001b[39m [texts[j] \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m empty_ids]\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/langchain_community/vectorstores/chroma.py:299\u001b[0m, in \u001b[0;36mChroma.add_texts\u001b[0;34m(self, texts, metadatas, ids, **kwargs)\u001b[0m\n\u001b[1;32m 297\u001b[0m ids_with_metadata \u001b[38;5;241m=\u001b[39m [ids[idx] \u001b[38;5;28;01mfor\u001b[39;00m idx \u001b[38;5;129;01min\u001b[39;00m non_empty_ids]\n\u001b[1;32m 298\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 299\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_collection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupsert\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 300\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetadatas\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadatas\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 301\u001b[0m \u001b[43m \u001b[49m\u001b[43membeddings\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43membeddings_with_metadatas\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 302\u001b[0m \u001b[43m \u001b[49m\u001b[43mdocuments\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtexts_with_metadatas\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 303\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids_with_metadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 304\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 305\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 306\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpected metadata value to be\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(e):\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/chromadb/api/models/Collection.py:298\u001b[0m, in \u001b[0;36mCollection.upsert\u001b[0;34m(self, ids, embeddings, metadatas, documents, images, uris)\u001b[0m\n\u001b[1;32m 267\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mupsert\u001b[39m(\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 269\u001b[0m ids: OneOrMany[ID],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 279\u001b[0m uris: Optional[OneOrMany[URI]] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 280\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 281\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Update the embeddings, metadatas or documents for provided ids, or create them if they don't exist.\u001b[39;00m\n\u001b[1;32m 282\u001b[0m \n\u001b[1;32m 283\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 290\u001b[0m \u001b[38;5;124;03m None\u001b[39;00m\n\u001b[1;32m 291\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 292\u001b[0m (\n\u001b[1;32m 293\u001b[0m ids,\n\u001b[1;32m 294\u001b[0m embeddings,\n\u001b[1;32m 295\u001b[0m metadatas,\n\u001b[1;32m 296\u001b[0m documents,\n\u001b[1;32m 297\u001b[0m uris,\n\u001b[0;32m--> 298\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_and_prepare_upsert_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 299\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43membeddings\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadatas\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdocuments\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mimages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muris\u001b[49m\n\u001b[1;32m 300\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 302\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_client\u001b[38;5;241m.\u001b[39m_upsert(\n\u001b[1;32m 303\u001b[0m collection_id\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mid,\n\u001b[1;32m 304\u001b[0m ids\u001b[38;5;241m=\u001b[39mids,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 308\u001b[0m uris\u001b[38;5;241m=\u001b[39muris,\n\u001b[1;32m 309\u001b[0m )\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/chromadb/api/models/CollectionCommon.py:546\u001b[0m, in \u001b[0;36mCollectionCommon._validate_and_prepare_upsert_request\u001b[0;34m(self, ids, embeddings, metadatas, documents, images, uris)\u001b[0m\n\u001b[1;32m 544\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m embeddings \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 545\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m documents \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 546\u001b[0m embeddings \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_embed\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdocuments\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 547\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 548\u001b[0m embeddings \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_embed(\u001b[38;5;28minput\u001b[39m\u001b[38;5;241m=\u001b[39mimages)\n",
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"File \u001b[0;32m~/Documents/Development/python/strategy-lab1/.venv/lib/python3.10/site-packages/chromadb/api/models/CollectionCommon.py:577\u001b[0m, in \u001b[0;36mCollectionCommon._embed\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 575\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_embed\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: Any) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Embeddings:\n\u001b[1;32m 576\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_embedding_function \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 577\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 578\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou must provide an embedding function to compute embeddings.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 579\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://docs.trychroma.com/guides/embeddings\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 580\u001b[0m )\n\u001b[1;32m 581\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_embedding_function(\u001b[38;5;28minput\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28minput\u001b[39m)\n",
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"\u001b[0;31mValueError\u001b[0m: You must provide an embedding function to compute embeddings.https://docs.trychroma.com/guides/embeddings"
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]
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}
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],
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"source": [
|
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"store = Chroma.from_documents(pages, collection_name=\"annualreport\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "dbd9b7f5",
|
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"metadata": {},
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"source": [
|
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"Create a VectorStoreInfo object to hold metadata about the vector store"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4fd45821",
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"metadata": {},
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"outputs": [],
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"source": [
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"vectorstore_info = VectorStoreInfo(\n",
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" name=\"apple\",\n",
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" description=\"Apple quarterly consolidated financials\",\n",
|
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" vectorstore=store,\n",
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")"
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]
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},
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{
|
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"cell_type": "markdown",
|
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"id": "9db55c3d",
|
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"metadata": {},
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"source": [
|
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"Convert the vector store information into a toolkit for LangChain"
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": null,
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"id": "40f81c28",
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"metadata": {},
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"outputs": [],
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"source": [
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"toolkit = VectorStoreToolkit(vectorstore_info=vectorstore_info)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "288a7fd0",
|
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"metadata": {},
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"source": [
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"Create an agent executor that uses the language model and toolkit for querying"
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]
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},
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{
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"cell_type": "code",
|
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"execution_count": null,
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"id": "2bee8094",
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"metadata": {},
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"outputs": [],
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"source": [
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"agent_executor = create_vectorstore_agent(llm=llm, toolkit=toolkit, verbose=True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "961d1da5",
|
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"metadata": {},
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"source": [
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"Prompt the user to enter a search term for querying the document"
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]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "445ea906",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"prompt = input(\"Enter your search term: \")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "c6b36ac3",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "NameError",
|
|
"evalue": "name 'agent_executor' is not defined",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[13], line 5\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m prompt:\n\u001b[1;32m 2\u001b[0m \n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# Pass the user input to the agent executor for processing\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43magent_executor\u001b[49m\u001b[38;5;241m.\u001b[39mrun(prompt)\n\u001b[1;32m 7\u001b[0m \u001b[38;5;66;03m# Print the response from the language model to the screen\u001b[39;00m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(response)\n",
|
|
"\u001b[0;31mNameError\u001b[0m: name 'agent_executor' is not defined"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"if prompt:\n",
|
|
"\n",
|
|
" # Pass the user input to the agent executor for processing\n",
|
|
"\n",
|
|
" response = agent_executor.run(prompt)\n",
|
|
"\n",
|
|
" # Print the response from the language model to the screen\n",
|
|
"\n",
|
|
" print(response)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "8a4cac29",
|
|
"metadata": {},
|
|
"source": [
|
|
"<a href=\"https://pyquantnews.com/\">PyQuant News</a> is where finance practitioners level up with Python for quant finance, algorithmic trading, and market data analysis. Looking to get started? Check out the fastest growing, top-selling course to <a href=\"https://gettingstartedwithpythonforquantfinance.com/\">get started with Python for quant finance</a>. For educational purposes. Not investment advise. Use at your own risk."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"jupytext": {
|
|
"cell_metadata_filter": "-all",
|
|
"main_language": "python",
|
|
"notebook_metadata_filter": "-all"
|
|
},
|
|
"kernelspec": {
|
|
"display_name": ".venv",
|
|
"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": "3.10.11"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|