Retrievalqa prompt. To pass custom prompts to the RetrievalQA abstraction in LangChain, you can use the from_llm class method of the BaseRetrievalQA class. Subscribe. npm install @langchain/openai @langchain/community. If you don't know the answer, just say that you don Nov 22, 2023 · To access the prompt used in RetrievalQAWithSourcesChain along with the embeddings (documents), you can follow the steps below: To access the prompt, you can set verbose=True when creating the RetrievalQAWithSourcesChain. A major point to note is the results will depend heavily on May 24, 2023 · How can I add a custom chain prompt for Conversational Retrieval QA Chain? When I ask a question that is unrelated to the context I stored in Pinecone, the Conversational Retrieval QA Chain currently answers with some random text. Nov 16, 2023 · It works perfectly. See the below example with ref to your provided sample code: The combine_docs_chain_kwargs parameter is used to pass the custom prompt to the ConversationalRetrievalChain. In its initial release (08/05/2023), the hub is limited to prompt management, but we plan to add support for other artifacts soon. Also, same question like @blazickjp is there a way to add chat memory to this ?. as_retriever(), + verbose=True, ) > Entering new RetrievalQA chain . from_chain_type? or, how do I add a custom prompt to ConversationalRetrievalChain?I hope you found a solution that worked Aug 30, 2023 · First documents are searched, for example via classic MB25/keyword searches or via neural information seek. Nov 8, 2023 · 🤖. AIアプリ開発入門 - LangChain & Streamlit による ChatGPT API 徹底活用. Should contain all inputs specified in Chain. Note: Here we focus on Q&A for unstructured data. The RetrievalQA chain's prompt template, as shown in your context, requires two input variables: context and question. We release ChatGPT-RetrievalQA dataset in a similar format to the MSMarco dataset, which is a popular dataset for training retrieval models. chains. Sep 26, 2023 · I had the same issue after upgrading langchain to a version >0. RetrievalQA is a method for question-answering tasks, utilizing an index to retrieve relevant documents or text chunks, it suits for straightforward Q&A applications. Apr 24, 2023 · prompt object is defined as: PROMPT = PromptTemplate (template=template, input_variables= ["summaries", "question"]) expecting two inputs summaries and question. However, when I attempt to execute the chains, I'm encountering the following error: ValueError: Missing some input keys RetrievalQA Prompt Error: Missing some input keys #16260. Prompt Versioning ensure deployment stability by selecting specific prompt versions over the 'latest'. Using custom prompt for RetrievalQA. this is my code, i add a PromptTemplate to RetrievalQA. as_retriever(search_kwargs={"k": 2}), chain_type_kwar Dec 14, 2023 · Im trying to create a conversational chatbot with ConversationalRetrievalChain with prompt template and memory and get error: ValueError: Missing some input keys: {'chat_history'}. Aug 2, 2023 · vectordb=Weaviate (client,'Document', 'page_content') qa_chain = RetrievalQA. QA over documents. from_template(template)# Run chain # LLM from langchain. The query should be a dictionary that includes both context and question keys. How to use Custom Prompts for RetrievalQA on LLaMA-2 7B. This is my code: `from llama_cpp import Llama. It is useful for chat, QA, or other applications that rely on passing context to an LLM. To handle this, I'm utilizing the MultiPromptChain from langchain to determine which chain to route the inputs to. Nov 9, 2023 · 1 Answer. def get_new_prompt(): custom_template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question. If questions are asked where there is no relevant context available, please answer from what you know. But there's no mention of qa_prompt in ConversationalRetrievalChain, or its base chain Sep 12, 2023 · RetrievalQA. Sep 1, 2023 · This is the prompt template I have for this: template = """Answer the question in your own words from the context given to you. Apr 2, 2023 · langchain. q4_0 model. , 2023) ToolQA (Zhuang et al. • Make sure the dock can be located near a power outlet and a strong WiFi signal. g Jun 8, 2023 · I'm having trouble setting up the successful usage of a custom QA prompt template that includes input variables with my RetrievalQA. Sep 5, 2023 · Getting error: ValueError: Missing some input keys: {'query'} when using sequential chain with RetrievalQA So I was trying to make a basic helper chatbot that would use a document. 1271. Sources. Best, Dosu. 192 with FAISS vectorstore. To resolve this issue, you need to ensure that the input you're providing to the MultiPromptChain includes a query key. prompts import PromptTemplate. In that same location is a module called prompts. Jul 24, 2023 · Prompts: This module allows you to build dynamic prompts using templates. Oct 22, 2023 · I am using Django, and Langchain with OpenAI to generate responses to my prompts. Jul 6, 2023 · I tried to build a chatbot for job applicants by using the RetrievalQA chain and retrieve info from a csv file. 5 Prompt Templates; Aug 7, 2023 · RetrievalQA chain with Prompt. I have created a RetrievalQA chain and now want to speed up the process. LLMs/Chat Models; Embedding Models; Prompts / Prompt Templates / Prompt Selectors; Output Parsers; Document Loaders; Vector Stores Details. This post explains on a high level how such a Retrieval Augmented Generation pipeline can be implemented. chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type="stuff", prompt=PROMPT) query = "What did Nov 6, 2023 · I'm working on a vector store qa bot to store docs from a csv file using langchain+chroma to create a vector store. Currently, I was doing it in two steps, getting the answer from this chain and then chat chai with the answer and custom prompt + memory to provide the final reply. Jul 15, 2023 · You can use the condense_question_prompt parameter while initializing the ConversationalRetrievalChain. We will use the RetrievalQA chain this time, which can use our vector store as a source for the context information. import { HNSWLib } from "@langchain/community Sign up with email Already have an account? Log in. LangChainに実装されているRetrievalQAは、大量の（ベクトル化された）テキストデータの中からユーザーの質問に合致する情報を迅速に検索 Jul 3, 2023 · Chain for having a conversation based on retrieved documents. Dec 22, 2023 · LangChainにはRAGを実装したRetrievalQAというAPIが用意されています。 本APIを利用すれば、簡単にRAGを実装できますが、ベクトルデータによる絞り込みに用いるテキストチャンクと、LLMの回答作成時に用いるそれを使い分ける仕組みはまでは用意されていません。 Mar 12, 2024 · from haystack. Jun 30, 2023 · This way, the RetrievalQAWithSourcesChain object will use the new prompt template instead of the default one. Use the chat history and the new question to create a “standalone question”. This will ensure that the "context" key is present in the dictionary, and the format method will be able to find it when formatting the document based on the prompt template. chains import RetrievalQA from langchain. If Feb 26, 2024 · A. 27. I'm here to assist you with your questions and help you navigate any issues you might come across with LangChain. , 2023) FreshQA (Vu et al. The algorithm for this chain consists of three parts: 1. as_retriever(search_type="mmr"), memory=memory, chain_type_kwargs={'prompt': prompt}) how to add streaming in my code i am using fastapi and i am getting streaming response using qa. Another user suggested using verbose=True to see the full prompt logged into the terminal or notebook output. , 2023) A. This method takes an optional prompt parameter, which you can use to pass your custom PromptTemplate instance. """Chain for question-answering against a vector database. Hello @valkryhx!. First, the prompt that condenses conversation history plus current user input (condense_question_prompt), and second, the prompt that instructs the Chain on how to return a final response to the user (which happens in the combine_docs_chain). Mar 30, 2023 · Prompt Engineering. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. combine_documents. prompts import ChatPromptTemplate, MessagesPlaceholder. The document and the chatbot is supposed to support Indonesian. This will log the full prompt into the terminal (or notebook) output. Please read our Data Security Sep 25, 2023 · I understand you're trying to use a custom prompt template with a 'persona' variable in the RetrievalQA chain in LangChain and you're also curious about how the RetrievalQA chain handles custom input variables. GenerativeModel(model_name="gemini-pro", generation_config=generation_config) prompt1_1 = f"Given the following last conversation log, if user question is related to previous user question then formulate a question that would be the most relevant to provide the user with an answer otherwise don't formulate question leave it as it May 6, 2023 · How can we add Prompt in RetrievalQA #14123. 👎. May 12, 2023 · How do i add memory to RetrievalQA. RetrievalQA Prompt Error: Missing some input keys. Nov 28, 2023 · The metric was Recall@5, to emulate a RAG scenario where we provided the top five most relevant passages as context in the prompt for the LLM model to respond to the question. return_only_outputs ( bool) – Whether to return only outputs in the response. PrivateDocBot Created using langchain and chainlit 🔥🔥 It also streams using langchain just like ChatGpt it displays word by word and Oct 8, 2023 · In the above code, replace "your_context_here" with the actual context to be used. • For the most reliable connection, we recommend running Ethernet to the dock. My code is as below from langchain. The LangChain hub offers version-specific prompt pulling to enhance deployment consistency. It empowers us to interact In this walkthrough, you will get started using the hub to manage prompts for a retrieval QA chain. pipeline(prompt, max_length=100)[0]['generated_text'] # @alvas: I've totally no idea what this in langchain does, so I copied it verbatim. Here is my code: Nov 20, 2023 · To achieve this, you can employ the LangChain RetrievalQA, which augments the initial prompt with the most similar documents from the vector store. I hope this helps! If you have any other questions, feel free to ask. You will go through the following steps: Load prompt from Hub. input_keys except for inputs that will be set by the chain’s memory. from_chain_type(llm=chat, chain_type="stuff", retriever=docsearch. globals import set_verbose, set_debug set_debug(True) set_verbose(True) Oct 20, 2023 · I have one issue I struggle with. prompts import PromptTemplate # This text splitter is used to create the parent documents - The big chunks parent_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=400) # This text splitter is used to create the child documents - The small chunks # It should 您可以轻松指定要在 RetrievalQA 链中加载和使用的不同链类型。有关这些类型的更详细的步骤，请参见 此笔记本。 有两种加载不同链类型的方法。首先，您可以在 from_chain_type 方法中指定链类型参数。这允许您传递要使用的链类型的名称。 May 20, 2023 · building a prompt using only relevant information from our document sources. The first way to do so is by changing the AI prefix in the conversation summary. May 12, 2023 · from langchain. Then using this chain object, provide a prompt to the LLM as asked below. here's my c Using the "latest" version of a prompt in production can introduce unforeseen issues. Run Chain. 1 Details of RetrievalQA Constructions. MultiPromptChain: This chain routes input between multiple prompts. 3 days ago · Source code for langchain. privateGPT 是基于 llama-cpp-python 和 LangChain 等的一个开源项目，旨在提供本地化文档分析并利用大模型来进行交互问答的接口。. retrieval_qa. But when I am try to use the RetrievalQA chain then it only works with cli and not streaming the tokens to the chainlit ui. In this tutorial, we'll illustrate this with a RetrievalQA chain. Using local models. You might be wondering what Prompt Engineering is. Data security is important to us. The respective tokenizer for the model. Runnable PromptTemplate: streamline the process of saving prompts to the hub from the playground and integrating them into runnable chains. llms import OpenAI from langchain. from_chain_type (OpenAI (temperature=0),chain_type_kwargs= {"prompt":PROMPT},chain_type="stuff", ) no option to add retriever. stuff_prompt import PROMPT_SELECTOR from langchain. Closed How do i use system prompt template inside conversational retrieval chain? #14191. run but when i am returning it it just returning as a whole string, how to fix that Jun 10, 2023 · text = self. In our main experiments, we train on ChatGPT responses and evaluate on human responses. I used Blue Cheese's solution but the problem with using RetrievalQA is that it calls a combine_documents_chain which costs time and the result is discarded. Provide a clear and concise response that summarizes the key points and information presented in the text. RetrievalQA Chain: use prompts from the hub in an example RAG pipeline. Let’s walk through an example of that in the example below. You can only chose one. 162, code updated. You must only answer with a JSON with the following keys: source_name the source_type, and source_path. if stop is not None: # This is a bit hacky, but I can't figure out a better way to enforce # stop tokens when making calls to huggingface_hub. Jul 3, 2023 · Parameters. Jul 5, 2023 · from langchain. LangChain has integrations with many open-source LLMs that can be run locally. Sep 5, 2023 · RetrievalQA while using multiple input parameters in Promptemplate Hi, I am having trouble with using multiple input variables with RetrievalQA chain. It can adapt to different LLM types depending on the context window size and input variables used as context, such as Jun 8, 2023 · 使用privateGPT进行多文档问答. If you don't provide a prompt, the method will use the default prompt for the given language model. * * Chat history will be an empty string if it's the first question. Additionally, the new context shared provides examples of other prompt templates that can be used, such as DEFAULT_REFINE_PROMPT and DEFAULT_TEXT_QA_PROMPT. The preference is a string, resume, and text under the try statement are all strings. from_chain_type, but when a send a prompt it's not work, in this example the bot not call me "bob". base. from_chain_type? or, how do I add a custom prompt to ConversationalRetrievalChain? For the past 2 weeks ive been trying to make a chatbot that can chat over documents (so not in just a semantic search/qa so with memory) but also with a custom prompt. from_chain_type(llm=chat_llm, retriever=chroma_db. Most Pertinent Question Picker — Pick one question most pertinent to the original question This prompt picks one question from the list of unanswered questions that is the most pertinent to the original question. Open This was Aug 31, 2023 · from langchain. ChatPromptTemplate. from langchain. cpp兼容的大模型文件对文档内容进行提问 For training, a set of random responses can be used as non-relevant answers. The first thing we need to do is initialize a text-generation pipeline with Hugging Face transformers. prompts import PromptTemplate template = """Verwenden die folgenden Kontextinformationen, um die Frage am Ende zu beantworten. To only get the source documents I subclassed RetrievalQA. Sep 25, 2023 · 1. You can define prompt like this. . Initialize Chain. chat_models import AzureChatOpenAI from langchain. While I'm not a human, rest assured that I'm designed to provide technical guidance, answer your queries, and help you become a better contributor to our project. > Finished chain. prompts import PromptTemplate llm=AzureChatOpenAI( deployment_name="", openai_api_version="", ) prompt_template = """Use the following pieces of context to answer the question at the end. I wanted to chain a RetrievalQA chain that searches document for information and outputs the relevant info and then use a s Jun 21, 2023 · from langchain. * * inputVariables: ["chatHistory", "context", "question"] */ const questionPrompt = PromptTemplate. RealTimeQA (Kasai et al. Let’s try to understand a little bit better what’s going on underneath the hood. When I run my code It does stream the OpenAI output in the terminal, but it returns the output as a whole to the client once the streaming has ended. First, we define the prompt template. ggmlv3. つくりながら学ぶ！. pnpm. py file. prompts import PromptTemplate def get_prompt_template(model): if model == &#39 Jul 6, 2023 · 感谢开源！ 我想做一组Retrieval QA的测试，请问用什么prompt比较合适，我试了几个prompt都不太好，比如下面这个internLM-7b-chat会用英文来回答，而直接使用chat接口回答都很简短。 prompt_template = f"""User: 已知信息： {context} 根据上述已知信息，专业的回答用户的问题。如果无法从中得到答案，请说 “抱歉 Dec 19, 2023 · QA_CHAIN_PROMPT = PromptTemplate. Use this when you have multiple potential prompts you could use to respond and want to route to just one The process of bringing the appropriate information and inserting it into the model prompt is known as Retrieval Augmented Generation (RAG). dosubot added area: embeddings auto:bug labels 20 hours ago. I was trying to enable streaming using Server-Sent-Events (SSE) in my API function. Nevertheless, I am not sure how to use them correctly while calling RetrievalQA chain. llms import LlamaCpp. By setting return_source_documents=True , you gain visibility into the exact documents used to generate the answer as part of the response, allowing you to verify the accuracy of the answer. chains import RetrievalQA qa_chain = RetrievalQA. – Dec 19, 2023 · 1. Intro. 01 はじめに 02 まずは環境準備をしよう 03 最初のAI May 30, 2023 · @RijoanulHasanShanto Thanks a lot! Yes, just added that. i want to add a context before send a prompt to my gpt model. memory import ConversationBufferMemory from langchain. I'm building a document QA bot. LangChain has a number of components designed to help build Q&A applications, and RAG applications more generally. Initializing the Hugging Face Pipeline. cpp , GPT4All, and llamafile underscore the importance of running LLMs locally. It is possible to fine-tune GPT-3 by creating a custom model trained on the documents you would like to analyze. versuche nicht eine Antwort zu erfinden. nodes import PromptNode, PromptTemplate, AnswerParser rag_prompt = PromptTemplate ( prompt = """Synthesize a comprehensive answer from the following text for the given question. These can be used in a similar way to customize the prompt for different use cases. Aug 27, 2023 · model = genai. This issue is similar to #3425 I am using LangChain v0. (when calling the . Custom prompts for chain types that aren't "stuff" in RetrievalQA; Unable to add qa_prompt to ConversationalRetrievalChain. Additional Information: • I have ensured that the retriever information is correctly formatted as a dictionary. My code is following: Jul 3, 2023 · Parameters. May 5, 2023 · Initial Answer: You can't pass PROMPT directly as a param on ConversationalRetrievalChain. RetrievalQAとは？. 4K subscribers. • Make sure the touch screen's WiFi or Ethernet connection is on the same network as your controller and that the signal is strong. Instead, I want to provide a prompt to the chain to answer the question based on the given context. stuff import StuffDocumentsChain # This controls how each document will be formatted. The top search results are passed as context in the prompts of the Large Language Models to generate the answers. The official example notebooks/scripts; My own modified scripts; Related Components. """ from __future__ import annotations import inspect Aug 2, 2023 · Feature request When I use RetrievalQA, I need to add and reorder the content retrieved by retriever qa = RetrievalQA. fromTemplate (` Use the following pieces of context to answer the question at the end. from langchain_core. prompts import PromptTemplate prompt_template = """ Given the question from the user, you must figure out which data source you must use. The Pipeline requires three things that we must initialize first, those are: A LLM, in this case it will be meta-llama/Llama-2-13b-chat-hf. weissenbacherpwc opened this issue 20 hours ago · 1 comment. #16260. from_chain_type. 1. inputs ( Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects only one param. May 13, 2023 · There are two prompts that can be customized here. By default, this is set to “AI”, but you can set this to be anything you want. from langchain import PromptTemplate. Jun 28, 2023 · 使われているChainやAgentによっては出るみたいだがRetrievalQAでは途中経過も最終的な結果も出力されない. But from what I see, LangChain use English in the prompt that's used in the QARetrieval Module. streaming_stdout import StreamingStdOutCallbackHandler import requests import json # QA chain from langchain. The popularity of projects like PrivateGPT , llama. PDFに質問しよう (後編: RetrievalQA)｜つくりながら学ぶ！. I am using PALM model for my project to answer from the vector store. prompts import PromptTemplate from langchain. Retrieval Question-Answering (QA) is an impressive technology that excels at extracting answers from a given context. Here's how you can do it: Mar 28, 2023 · You can see my prompt is very short, but it says: InvalidRequestError: This model's maximum context length is 4097 tokens, however you requested 6990 tokens (6734 in your prompt; 256 for the completion). I need to have variable number of input variables for prompt template which I use in RetrievalQA chain. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis. The work-around right now is that I need to edit the langchain in my node_modules directly, so the prompt is now in Nov 21, 2023 · from langchain. Wenn du die Antwort nicht kennst, sag einfach, dass du es nicht weisst. Sign up for free to join this conversation on GitHub . Use Cases. RetrievalQAWithSourcesChain is an extension of RetrievalQA that chained together multiple sources of information, providing context and transparency in constructing LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. I am running the chain locally on a Macbook Pro (Apple M2 Max) with 64GB RAM, and 12 cores. By continuing, you agree to our Terms of Service. * Create a prompt template for generating an answer based on context and * a question. Finally, the run() method is executed on the defined instance of RetrievalQA(), using the query text as the input argument: Jun 9, 2023 · How do i add memory to RetrievalQA. py which contains both CONDENSE_QUESTION_PROMPT and QA_PROMPT. Azure OpenAIのチャットモデルを定義し、RetrievalQAチェーンを定義します。RetrievalQAでベクトルストアを利用したい場合は、as_retriever()のメソッドを呼び出してRetrievalクラスに変換する必要があります。それではQAチェーンを実行してみましょう。 Oct 4, 2023 · To customize the system message of the RetrievalQA's chain_type to map_reduce in your application, you can modify the from_chain_type method in the BaseRetrievalQA class and also adjust the prompt_template in the map_reduce_prompt. llm=llm, chain_type="stuff", retriever=vectorstore. Aug 28, 2023 · The prompt here is tuned such that the newly generated questions do not overlap with the existing list of questions. Aug 19, 2023 · How to use Custom Prompts for RetrievalQA on LLaMA-2 7B - YouTube. 0. Open. Enable verbose and debug; from langchain. conversational_retrieval is where ConversationalRetrievalChain lives in the Langchain source code. from_chain_type( llm, retriever Aug 18, 2023 · I'm using multiple RetrievalQA chains, each with different formatting instructions and prompt templates. We create a ChatPromptTemplate which contains our base system prompt and an input variable for the question. Apr 16, 2023 · From what I understand, you were asking if there is a way to log or inspect the prompt sent to the OpenAI API when using RetrievalQA. llm=llm May 18, 2023 · qa = RetrievalQA. 1. But generally, given that it is necessary to pass context as an input_variable to the PROMPT_TEMPLATE, I was wondering if there was a way to access that variable inside the prompt. At the moment, the generation of the text takes too long (1-2minutes) with the qunatized Mixtral 8x7B-Instruct model from "TheBloke". Here's an example of how you Nov 18, 2023 · chain_type_kwargs={"prompt": prompt}, return_source_documents=True) return qa_chain. from_llm(). 0:00 / 13:39. The prompt template has instructions about Sep 27, 2023 · この記事では、RetrievalQAという便利なツールを使って、ChatGPTを活用した情報検索方法を紹介します。. Sam Witteveen. In the below example, we are using a VectorStore as the Retriever, along with a RunnableSequence to do question answering. Jun 20, 2023 · RetrievalQA() is the question-answering chain that takes as input arguments the LLM via the llm parameter, the chain type to use via the chain_type parameter, and the retriever via the retriever parameter. #!/usr/bin/env python3. For example, here we show how to run GPT4All or LLaMA2 locally (e. Information. However, what is passed in only question (as query) and NOT summaries. Jul 5, 2023 · Planning the installation. question_answering. This is a prompt for retrieval-augmented-generation. Oct 25, 2023 · from langchain. See here for setup instructions for these LLMs. Again, the chain will wrap our prompt with some text instructing it to only use the information provided for answering the questions. Who can help? No response. Apr 25, 2023 · EDIT: My original tool definition doesn't work anymore as of 0. . However, besides costs for training we would also need a lot of high-quality examples, ideally vetted by human experts (according to the documentation). May 22, 2023 · May 22, 2023. Photo by Ana Municio on Unsplash. To use a custom prompt template with a 'persona' variable, you need to modify the prompt_template and PROMPT in the prompt. Context: {context} Chat history: {chat_history} Human: {question} Assistant:""" My prompt is as follows: Oct 3, 2023 · Expected Behavior: The RetrievalQA class should accept and handle multiple retrievers from FAISS vector database without raising any errors. from_llm This allows us to pass in a list of Messages to the prompt using the “chat_history” input key, and these messages will be inserted after the system message and before the human message containing the latest question. callbacks. In this walkthrough, you will get started using the hub to manage prompts for a retrieval QA chain. manager import CallbackManager from langchain. Jul 10, 2023 · Chat History: {chat_history} Follow Up Input: {question} Standalone question:`; // Prompt for the actual question const QA_PROMPT = `You are a helpful AI assistant for sales reps to answer questions about product features and technicals specifications. Please reduce your prompt; or completion length. 用户可以利用privateGPT对本地文档进行分析，并且利用GPT4All或llama. chains import LLMChain from langchain. Use the following pieces of context to answer the question at the end. prompts import PromptTemplate # Build prompt template = """Use the following pieces of context to answer the question at the end. We compared our model’s information retrieval accuracy to a number of well-known embedding models made available by the AI community, including ones trained on non Oct 15, 2023 · Using RetrievalQA chain, connect LLM with vectordb. Note that if you change this, you should also change the prompt used in the chain to reflect this naming change. i use orca-mini-3b. py file Oct 24, 2023 · Another 2 options to print out the full chain, including prompt. Try using the combine_docs_chain_kwargs param to pass your PROMPT. RetrievalQA: Retriever: This chain first does a retrieval step to fetch relevant documents, then passes those documents into an LLM to generate a response. This chain takes in chat history (a list of messages) and new questions, and then returns an answer to that question. chains import LLMChain,QAWithSourcesChain. qf eg uf qj rl ub vl ag fk am