{ "cells": [ { "cell_type": "markdown", "id": "74148cee", "metadata": {}, "source": [ "# Question Answering with Sources\n", "\n", "This notebook walks through how to use LangChain for question answering with sources over a list of documents. It covers three different chain types: `stuff`, `map_reduce`, and `refine`. For a more in depth explanation of what these chain types are, see [here](../../explanation/combine_docs.md)." ] }, { "cell_type": "markdown", "id": "ca2f0efc", "metadata": {}, "source": [ "### Prepare Data\n", "First we prepare the data. For this example we do similarity search over a vector database, but these documents could be fetched in any manner (the point of this notebook to highlight what to do AFTER you fetch the documents)." ] }, { "cell_type": "code", "execution_count": 1, "id": "78f28130", "metadata": {}, "outputs": [], "source": [ "from langchain.embeddings.openai import OpenAIEmbeddings\n", "from langchain.embeddings.cohere import CohereEmbeddings\n", "from langchain.text_splitter import CharacterTextSplitter\n", "from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch\n", "from langchain.vectorstores.faiss import FAISS\n", "from langchain.docstore.document import Document" ] }, { "cell_type": "code", "execution_count": 2, "id": "4da195a3", "metadata": {}, "outputs": [], "source": [ "with open('../state_of_the_union.txt') as f:\n", " state_of_the_union = f.read()\n", "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n", "texts = text_splitter.split_text(state_of_the_union)\n", "\n", "embeddings = OpenAIEmbeddings()" ] }, { "cell_type": "code", "execution_count": 3, "id": "5ec2b55b", "metadata": {}, "outputs": [], "source": [ "docsearch = FAISS.from_texts(texts, embeddings, metadatas=[{\"source\": i} for i in range(len(texts))])" ] }, { "cell_type": "code", "execution_count": 4, "id": "5286f58f", "metadata": {}, "outputs": [], "source": [ "query = \"What did the president say about Justice Breyer\"\n", "docs = docsearch.similarity_search(query)" ] }, { "cell_type": "code", "execution_count": 5, "id": "005a47e9", "metadata": {}, "outputs": [], "source": [ "from langchain.chains.qa_with_sources import load_qa_with_sources_chain\n", "from langchain.llms import OpenAI" ] }, { "cell_type": "markdown", "id": "d82f899a", "metadata": {}, "source": [ "### The `stuff` Chain\n", "\n", "This sections shows results of using the `stuff` Chain to do question answering with sources." ] }, { "cell_type": "code", "execution_count": 6, "id": "fc1a5ed6", "metadata": {}, "outputs": [], "source": [ "chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type=\"stuff\")" ] }, { "cell_type": "code", "execution_count": 7, "id": "e239964b", "metadata": {}, "outputs": [], "source": [ "docs = [Document(page_content=t, metadata={\"source\": i}) for i, t in enumerate(texts[:3])]" ] }, { "cell_type": "code", "execution_count": 8, "id": "7d766417", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'output_text': ' The president did not mention Justice Breyer.\\nSOURCES: 0-pl, 1-pl, 2-pl'}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = \"What did the president say about Justice Breyer\"\n", "chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)" ] }, { "cell_type": "markdown", "id": "c5dbb304", "metadata": {}, "source": [ "### The `map_reduce` Chain\n", "\n", "This sections shows results of using the `map_reduce` Chain to do question answering with sources." ] }, { "cell_type": "code", "execution_count": 9, "id": "921db0a4", "metadata": {}, "outputs": [], "source": [ "chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type=\"map_reduce\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "e417926a", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.\n", "Token indices sequence length is longer than the specified maximum sequence length for this model (1546 > 1024). Running this sequence through the model will result in indexing errors\n" ] }, { "data": { "text/plain": [ "{'output_text': ' The president did not mention Justice Breyer.\\nSOURCES: 0, 1, 2'}" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = \"What did the president say about Justice Breyer\"\n", "chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)" ] }, { "cell_type": "markdown", "id": "5bf0e1ab", "metadata": {}, "source": [ "### The `refine` Chain\n", "\n", "This sections shows results of using the `refine` Chain to do question answering with sources." ] }, { "cell_type": "code", "execution_count": 11, "id": "904835c8", "metadata": {}, "outputs": [], "source": [ "chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type=\"refine\")" ] }, { "cell_type": "code", "execution_count": 12, "id": "f60875c6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'output_text': \"\\n\\nThe president did not mention Justice Breyer in his speech to the European Parliament, which focused on building a coalition of freedom-loving nations to confront Putin, unifying European allies, countering Russia's lies with truth, and enforcing powerful economic sanctions. Source: 2\"}" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = \"What did the president say about Justice Breyer\"\n", "chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "929620d0", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "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": "3.10.8" } }, "nbformat": 4, "nbformat_minor": 5 }