mirror of
https://github.com/hwchase17/langchain
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149 lines
4.6 KiB
Plaintext
149 lines
4.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "1edb9e6b",
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"metadata": {},
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"source": [
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"# ChatGPT Plugin Retriever\n",
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"\n",
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"This notebook shows how to use the ChatGPT Retriever Plugin within LangChain."
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]
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},
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{
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"cell_type": "markdown",
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"id": "074b0004",
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"metadata": {},
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"source": [
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"## Create\n",
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"\n",
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"First, let's go over how to create the ChatGPT Retriever Plugin.\n",
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"\n",
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"To set up the ChatGPT Retriever Plugin, please follow instructions [here](https://github.com/openai/chatgpt-retrieval-plugin).\n",
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"\n",
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"You can also create the ChatGPT Retriever Plugin from LangChain document loaders. The below code walks through how to do that."
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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": "bbe89ca0",
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"metadata": {},
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"outputs": [],
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"source": [
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"# STEP 1: Load\n",
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"\n",
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"# Load documents using LangChain's DocumentLoaders\n",
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"# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html\n",
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"\n",
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"from langchain.document_loaders.csv_loader import CSVLoader\n",
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"loader = CSVLoader(file_path='../../document_loaders/examples/example_data/mlb_teams_2012.csv')\n",
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"data = loader.load()\n",
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"\n",
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"\n",
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"# STEP 2: Convert\n",
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"\n",
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"# Convert Document to format expected by https://github.com/openai/chatgpt-retrieval-plugin\n",
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"from typing import List\n",
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"from langchain.docstore.document import Document\n",
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"import json\n",
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"\n",
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"def write_json(path: str, documents: List[Document])-> None:\n",
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" results = [{\"text\": doc.page_content} for doc in documents]\n",
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" with open(path, \"w\") as f:\n",
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" json.dump(results, f, indent=2)\n",
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"\n",
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"write_json(\"foo.json\", data)\n",
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"\n",
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"# STEP 3: Use\n",
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"\n",
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"# Ingest this as you would any other json file in https://github.com/openai/chatgpt-retrieval-plugin/tree/main/scripts/process_json\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0474661d",
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"metadata": {},
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"source": [
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"## Using the ChatGPT Retriever Plugin\n",
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"\n",
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"Okay, so we've created the ChatGPT Retriever Plugin, but how do we actually use it?\n",
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"\n",
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"The below code walks through how to do that."
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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": "39d6074e",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.retrievers import ChatGPTPluginRetriever"
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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": "33fd23d1",
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"metadata": {},
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"outputs": [],
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"source": [
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"retriever = ChatGPTPluginRetriever(url=\"http://0.0.0.0:8000\", bearer_token=\"foo\")"
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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": "16250bdf",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Document(page_content=\"This is Alice's phone number: 123-456-7890\", lookup_str='', metadata={'id': '456_0', 'metadata': {'source': 'email', 'source_id': '567', 'url': None, 'created_at': '1609592400.0', 'author': 'Alice', 'document_id': '456'}, 'embedding': None, 'score': 0.925571561}, lookup_index=0),\n",
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" Document(page_content='This is a document about something', lookup_str='', metadata={'id': '123_0', 'metadata': {'source': 'file', 'source_id': 'https://example.com/doc1', 'url': 'https://example.com/doc1', 'created_at': '1609502400.0', 'author': 'Alice', 'document_id': '123'}, 'embedding': None, 'score': 0.6987589}, lookup_index=0),\n",
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" Document(page_content='Team: Angels \"Payroll (millions)\": 154.49 \"Wins\": 89', lookup_str='', metadata={'id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631_0', 'metadata': {'source': None, 'source_id': None, 'url': None, 'created_at': None, 'author': None, 'document_id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631'}, 'embedding': None, 'score': 0.697888613}, lookup_index=0)]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"retriever.get_relevant_documents(\"alice's phone number\")"
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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": "c8b5794b",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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