Langchain conversational retrieval chain prompt github. vectorstores import Qdrant from langchain.

Use the following pieces of context to answer the question at the end. LangChain Expression Language (LCEL) LCEL is the foundation of many of LangChain's components, and is a declarative way to compose chains. Jun 7, 2023 · I think what you are looking for may be solved by passing the prompt in a dict object {"prompt": PROMPT} to the combine_docs_chain_kwargs parameter of ConversationalRetrievalChain. 2. I hope you're doing well. LCEL was designed from day 1 to support putting prototypes in production, with no code changes, from the simplest “prompt + LLM” chain to the most complex chains. I would like to get the scores of the matching documents with my query. LangChain has a number of components designed to help build Q&A applications, and RAG applications more generally. Attributes: model (LangchainChatModel): The LangChain chat model. The NAIVE_RETRY_PROMPT is a default prompt provided in the RetryOutputParser class, you can replace it with your custom prompt if needed. Hi @JoAmps!Nice to see you again on the LangChain repository. Updated the Retrieval-Generation Chain: I updated the rag_chain to use the new history_aware_retriever and question_answer_chain. For your requirement to reply to greetings but not to irrelevant questions, you can use the response_if_no_docs_found parameter in the from_llm method of ConversationalRetrievalChain. For example, for a given question, the sources that appear within the answer could like this 1. __init__ () self. This will log the full prompt into the terminal (or notebook) output. Oct 16, 2023 · import os from dotenv import load_dotenv from langchain. I commit to help with one of those options 👆; Example Code Jun 13, 2023 · From what I understand, you reported an issue regarding the condense_question_prompt parameter not being considered in the Conversational Retriever Chain. {"payload":{"allShortcutsEnabled":false,"fileTree":{"langchain/src/chains":{"items":[{"name":"api","path":"langchain/src/chains/api","contentType":"directory"},{"name Sep 21, 2023 · In the LangChainJS framework, you can use custom prompt templates for both standalone question generation chain and the QAChain in the ConversationalRetrievalQAChain class. The expected behavior is that the chain should take the given TEST_PROMPT while sending the prompt to the LLM, but this is not happening in the original behavior. document_loaders import TextLoader from May 13, 2023 · prompt_template = ''' You are a Bioinformatics expert with immense knowledge and experience in the field. {context} Question: {question} Helpful Answer:""" QA_CHAIN_PROMPT = PromptTemplate. The algorithm for this chain consists of three parts: 1. ConversationalRetrievalChain. The ConversationChain is a more versatile chain designed for managing conversations. chat_models import ChatOpenAI from langchain. py which contains both CONDENSE_QUESTION_PROMPT and QA_PROMPT. You can find more details about the Mar 10, 2011 · System Info. agents import create_csv_agent from langchain. combine_documents import create_stuff_documents_chain qa_system_prompt = """You are an assistant for question-answering tasks. prompts import ChatPromptTemplate, SystemMessagePromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate os. In ChatOpenAI from LangChain, setting the streaming variable to True enables this functionality. base. Overview: LCEL and its benefits. Streaming is a feature that allows receiving incremental results in a streaming format when generating long conversations or text. stream method will by default stream each key in a sequence. condense_question_prompt: The prompt to use to condense the chat history and new question into a standalone question. llms import OpenAI from langchain_community. It only recognizes the first four rows of a CSV file. _publish_chat_history: Publish chat history to Kafka. So far so good, I managed to get feed it custom texts and it answers questions based on the text, but for some reason it doesn't remember the previous answers. some text (source) or 1. Retrieval augmented generation (RAG) with a chain and a vector store. Is there any way of twerking this prompt so that it should give email of customer support that I will provide in prompt. \ Use the following pieces of retrieved context to answer the question. load (file) return chat_history # Modify this part of the create_conversational_retrieval_agent function # Assume chat Jul 8, 2023 · I'm Dosu, and I'm here to help the LangChain team manage our backlog. so that when a user queries for something, it determines if it should use the Conv retrieval chain or the other functions such as sending an email function, and it seems I need to use the import json from langchain. js starter app. Note: Here we focus on Q&A for unstructured data. I don't know when it does not know something. memory import The chain constructed by create_retrieval_chain returns a dict with keys "input", "context", and "answer". Jul 3, 2023 · This chain takes in chat history (a list of messages) and new questions, and then returns an answer to that question. text_splitter import CharacterTextSplitter from langchain. chains import (. If the whole conversation was passed into retrieval, there may be unnecessary information there that would distract from retrieval. [1m> Entering new ConversationChain chain [0m Prompt after formatting: [32;1m [1;3mThe following is a friendly conversation between a human and an AI. If the AI does not know the answer to a question, it truthfully says it does not know. redis and langchain. This sample solution creates a generative AI financial services agent powered by Amazon Bedrock. But there's no mention of qa_prompt in ConversationalRetrievalChain, or its base chain 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. The condense_question_prompt parameter in Python corresponds to the May 6, 2023 · You signed in with another tab or window. But, retrieval may produce different results with subtle changes in query wording or if the embeddings do not capture the semantics of the data well. from_template(template) May 10, 2023 · I'm Dosu, and I'm here to help the LangChain team manage their backlog. Based on the similar issues and solutions found in the LangChain repository, you can achieve this by using the ConversationalRetrievalChain class in Sep 21, 2023 · In the context shared, the 'QAChain' is created using the loadQAStuffChain function with a custom prompt defined by QA_CHAIN_PROMPT. some text (source) 2. memory import ConversationBufferMemory from langchain. Use the chat history and the new question to create a “standalone question”. environ['OPENAI_API_KEY Aug 7, 2023 · Types of Splitters in LangChain. chains. prompts import PromptTemplate import time from langchain. The max_retries parameter is optional and defaults to 1 if not provided. callbacks import StreamingStdOutCallbackHandler import pandas as pd from docx import Document from nltk. conversational_retrieval. Jul 10, 2023 · For a more efficient solution, you might need to modify the retrieval system itself to support filtering, which would require changes in the underlying code of LangChain. from_llm. Mar 26, 2024 · I searched the LangChain documentation with the integrated search. The template parameter is a string that defines the structure of the prompt, and the input_variables parameter is a list of variable names that will be replaced in the template. The . Motivation Dec 2, 2023 · In this example, the PromptTemplate class is used to define the custom prompt. prompts import PromptTemplate import time Sep 2, 2023 · You signed in with another tab or window. 9, but it is recommended to transition to create_retrieval_chain for future compatibility and improvements. 229 SO: Windows, Linux Ubuntu and Mac. This modification allows the ConversationalRetrievalChain to use the content from a file for retrieval instead of the original retriever. Hello, Thank you for your question. To get started, you'll first need to install the langchain-groq package: %pip install -qU langchain-groq. It from langchain. The 'standalone question generation chain' generates standalone questions, while 'QAChain' performs the question-answering task. The process of bringing the appropriate information and inserting it into the model prompt is known as Retrieval Augmented Generation (RAG). It then performs the standard retrieval steps of looking up relevant documents from the retriever and passing those documents and the question into a question answering chain to return a response. I suggested adding a condition in the code to handle "Hello" messages differently, bypassing the ConversationalRetrievalChain. vectorstores import Chroma from langchain. \ If you don't know the answer, just say that you don't know. If you find this solution helpful and believe it could benefit other users, I encourage you to make a pull request to update the LangChain documentation. conversational_retrieval is where ConversationalRetrievalChain lives in the Langchain source code. I understand that you're having trouble with the response_if_no_docs_found parameter in the ConversationalRetrievalChain class. Mar 9, 2013 · Hi, @pradeepdev-1995!I'm Dosu, and I'm here to help the LangChain team manage their backlog. This can be due to the complexity of the prompt or the performance of the language model used. I am using Conversational Retrieval Chain to make conversation bot with my documents. load() embeddings = OpenAIEm pip install -U langchain-cli. Args: llm: The default language model to use at every part of this chain (eg in both the question generation and the answering) retriever: The retriever to use to fetch relevant documents from. This chain is responsible for answering the user’s question based on the retrieved context and the chat history. Apr 2, 2023 · langchain. From what I understand, the issue you reported is that the ConversationalRetrievalChain method is returning the prompt instead of the answer. I know you can filter with the search_kwargs={"score_threshold": 0. Nov 23, 2023 · 🤖. 0. 5-turbo") # Data Ingestion. token_buffer import ConversationTokenBufferMemory # Example function to load chat history def load_chat_history (filepath: str): with open (filepath, 'r') as file: chat_history = json. The question_generator chain might be taking a long time to generate a new question. They are named as such to reflect their roles in the conversational retrieval process. Specifically: Simple chat. To pass an instance of llamaCPP into LangChain's conversational retrieval chain that uses a retriever, you need to create an instance of the ConversationalRetrievalChain class and pass the llamaCPP instance as the retriever argument. Apr 30, 2024 · Modified the Question-Answering Chain: I updated the question_answer_chain to use the new system prompt. from_llm in v0. Request an API key and set it as an environment variable: export GROQ_API_KEY=<YOUR API KEY>. The DEFAULT_REFINE_PROMPT and DEFAULT_TEXT_QA_PROMPT templates can be used for refining answers and generating questions respectively. To create a conversational question-answering chain, you will need a retriever. This is done so that this question can be passed into the retrieval step to fetch relevant documents. I want a chat over a document that contains memory of the conversation so I have to use the latter. You signed in with another tab or window. From what I understand, you are facing an issue with setting the max_tokens limit using ConversationalRetrievalChain . You can find more details about it in the context provided. I built a FastAPI endpoint where users can ask questions from the ai. Nov 24, 2023 · In the JavaScript version of LangChain, the ConversationalRetrievalQAChain. 2 days ago · The algorithm for this chain consists of three parts: 1. some text sources: source 1, source 2, while the source variable within the Jun 2, 2023 · Before we close this issue, we wanted to check if it is still relevant to the latest version of the LangChain repository. These two parameters — {history} and {input} — are passed to the LLM within the prompt template we just saw, and the output that we (hopefully) return is simply the predicted continuation of the conversation. py file. You switched accounts on another tab or window. Resolution: Optimize the prompt used for question generation or use a more efficient language model. chains import create_retrieval_chain from langchain. Aug 23, 2023 · # Note: If this is the first prompt in a chat conversation by the user, langchain # will *not* attempt to rephrase the question and you'll need to update this # class to act accordingly. return cls(\nTypeError: langchain. And add the following code to your server. 11 LangChain: 0. Both have the same logic under the hood but one takes in a list of text Nov 15, 2023 · Based on the issues and discussions in the LangChain repository, it seems that you can configure LangChain to return answers only from the ingested database, rather than using its pre-trained information. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days. This is done so that this question can be passed into the retrieval step to fetch relevant Mar 10, 2011 · Same working principle as in the source files combine_docs_chain = load_qa_chain(llm = llm, chain_type = 'stuff', prompt = stuff_prompt ) #create a custom combine_docs_chain Create the ConversationalRetrievalChain. Use the chat history and the new question to create a "standalone question". . 10. utilities import SQLDatabase from langchain. chains import create_sql_query_chain from langchain. Ensure that the custom retriever's get_relevant_documents method returns a list of Document objects, as the rest of the chain expects documents in this format. chain_type: The chain type to use Dec 21, 2023 · http_chat_async: Perform one-time HTTP chat using similarity search and AI. If you don't know the answer, just say that you don't know, don't try to make up an answer. Here is an example of how you Nov 10, 2023 · Hi, @afedotov-align, I'm helping the LangChain team manage their backlog and am marking this issue as stale. from_llm() object with the custom combine_docs_chain Jul 18, 2023 · In response to your query, ConversationChain and ConversationalRetrievalChain serve distinct roles within the LangChain framework. Hi people, I'm using ConversationalRetrievalChain without any modifications, and in 90% of the cases, it responds by repeating words and entire phrases, like in the examples below: Distance-based vector database retrieval embeds (represents) queries in high-dimensional space and finds similar embedded documents based on "distance". Jun 29, 2023 · System Info ConversationalRetrievalChain with Question Answering with sources llm = OpenAI(temperature=0) question_generator = LLMChain(llm=llm, prompt=CONDENSE_QUESTION_PROMPT) doc_chain = load_qa . You signed out in another tab or window. It showcases how to use and combine LangChain modules for several use cases. llms import OpenAI from langchain. This method creates a new instance of ConversationalRetrievalQAChain from a BaseLanguageModel and a BaseRetriever. py file: Aug 31, 2023 · The idea is, that I have a vector store with a conversational retrieval chain. I don't want bot to say. Jun 8, 2023 · QA_PROMPT_DOCUMENT_CHAT = """You are a helpful AI assistant. chains import ConversationalRetrievalChain, StuffDocumentsChain, LLMChain from langchain_core. Here, we feed in information about the conversation history between the human and AI. The text splitters in Lang Chain have 2 methods — create documents and split documents. You need to pass the second prompt when you are using the create_prompt method. vectorstores import Chroma from langchain. Below is an example: from langchain_community. Follow-up question: in "step 1", are you able to override the default behavior of passing in chat history? Oct 21, 2023 · from langchain. Answer my questions based on your knowledge and our older conversation. loader = CSVLoader(file_path=filepath, encoding="utf-8") data = loader. Mar 6, 2024 · Hey @2narayana, great to see you diving into another interesting challenge with LangChain!How have things been since our last chat? Based on the context provided, it seems like you want to filter the documents in the VectorDB Retriever based on their metadata. This template scaffolds a LangChain. class LLMStreamingCallbackHandler (StreamingStdOutCallbackHandler): def __init__ (self, add_to_buffer: Callable) -> None: super (). If you want to add this to an existing project, you can just run: langchain app add rag-conversation. if there is more than 1 output keys: use the relevant output key for the chain for example in ConversationalRetrievalChain Apr 26, 2023 · I am having issues with using ConversationalRetrievalChain to chat with a CSV file. Here is the relevant By default, this is set to "AI", but you can set this to be anything you want. Note that if you change this, you should also change the prompt used in the chain to reflect this naming change. Alternatively, you may configure the API key when you initialize ChatGroq. Jan 10, 2024 · Let's make your experience with LangChain as smooth as possible together! 🚀. I hope this helps! If you have any other questions, feel free to ask. From what I understand, Dosubot has provided a comprehensive response with code snippets and references, outlining the steps to create the chain in LangChain and wrap it in a Flask server for storing chat history. Here's how you can do it: 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. Nov 6, 2023 · The prompt should obtain a chatbot response from the LLM via the retrieval augmented generation methods (ConversationalRetrievalChain or RetrievalQA) in langchain but failed to do so as the current configuration is unable to support local tokenizer. Note that here only the "answer" key is streamed token-by-token, as the other components-- such as retrieval-- do not support token-level streaming. Answering complex, multi-step questions with agents. Let's walk through an example of that in the example below. prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_community. memory import ConversationTokenBufferMemory from langchain_community. To use a custom prompt template with a 'persona' variable, you need to modify the prompt_template and PROMPT in the prompt. embeddings. My code: def create_chat_agent(): llm = ChatOpenAI(temperature=0, model_name="gpt-3. Here's how you can use them: Haven't figured it out yet, but what's interesting is that it's providing sources within the answer variable. chat_message_histories import RedisChatMessageHistory # Define the prompts contextualize_q_system_prompt May 18, 2023 · edited. memory. from_llm method. To create a new LangChain project and install this as the only package, you can do: langchain app new my-app --package rag-conversation. js + Next. When I use RetrievalQA I get better answers than when I use ConversationalRetrievalChain. As for the load_qa function, it is used to load a question answering chain with sources. openai import OpenAIEmbeddings from langchain. Document Retrieval Delay: Jul 3, 2023 · Hello, Based on the names, I would think RetrievalQA or RetrievalQAWithSourcesChain is best served to support a question/answer based support chatbot, but we are getting good results with Conversat from langchain_core. If you don't know the answer, just say that you don't know. If you are interested for RAG over May 6, 2023 · A conversational agent will access the conversation history and only use the . ibizabroker suggests a Aug 17, 2023 · So far, the only workaround that I found out is querying the chain using an external chat history, like this: chain({"question": query, "chat_history":"dummy chat history"}) Thank you in advance for your help. document_loaders import TextLoader from langchain. Here's an example of how you can do this: from langchain. embeddings import HuggingFaceInstructEmbeddings from langchain. ConversationalRetrievalChain() got multiple values for keyword argument 'que Dec 3, 2023 · I am wondering if anyone has a work around using ConversationalRetrievalChain to retrieve documents with their sources, and prevent the chain from returning sources for questions without sources. Contribute to langchain-ai/langchain development by creating an account on GitHub. Nov 8, 2023 · This is done so that this question can be passed into the retrieval step to fetch relevant documents. from langchain. Oct 17, 2023 · In this example, "second_prompt" is the placeholder for the second prompt. To continue talking to Dosu , mention @dosu . The AI is talkative and provides lots of specific details from its context. It generates responses based on the context of the conversation and doesn't necessarily rely on document retrieval. py file Jun 17, 2023 · > Entering new StuffDocumentsChain chain > Entering new LLMChain chain Prompt after formatting: System: Use the following pieces of context to answer the users question. Prompt engineering / tuning is sometimes done to manually address these problems, but can be You can continue using ConversationalRetrievalChain. However, it does not work properly in RetrievalQA or ConversationalRetrievalChain. Answer. Reload to refresh your session. I used the GitHub search to find a similar question and didn't find it. The agent can assist users with finding their Jan 9, 2024 · from langchain. ----- Q&A Knowledge Base 1 Q&A Knowledge Base 1. finished Oct 10, 2023 · const CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT = `Given the following conversation and a follow up question, return the conversation history excerpt that includes any relevant context to the question if it exists and rephrase the follow up question to be a standalone question. Based on the information provided and the current state of the LangChain codebase, the ConversationalRetrievalChain class does not support tone modification or language translation. How Adding a prompt template to conversational retrieval chain giving the code: `template= """Use the following pieces of context to answer the question at the end. This parameter should be an instance of a chain that combines documents, such as the StuffDocumentsChain. On the other hand, if you want to respond based on the conversation history and document context simultaneously, then might want to try a custom chain and prompt. const qa_template = `You are a helpful assistant! You will answer all questions. Aug 13, 2023 · Yes, it is indeed possible to combine a simple chat agent that answers user questions with a document retrieval chain for specific inquiries from your documents in the LangChain framework. chains. Jul 12, 2023 · From what I understand, you reported an issue where continuously sending "Hello" messages to the conversational retrieval chain resulted in incorrect answers. qa_with_sources import load_qa_with_sources_chain from langchain. How do I add memory + custom prompt with multiple inputs to Retrieval QA in langchain? Apr 29, 2023 · I've been following the examples in the Langchain docs and I've noticed that the answers I get back from different methods are inconsistent. Aug 31, 2023 · In this example, the AI prefix is set to "AI Assistant" and the Human prefix is set to "Friend". Python: 3. 8} But still I want to get the similarity scores in the output. The {history} is where conversational memory is used. prompts import ChatPromptTemplate, PromptTemplate, format_document from langchain_core . Mar 31, 2023 · If you are using memory with each chain type. fromLLM method is equivalent to the Python ConversationalRetrievalChain. Returning structured output from an LLM call. In that same location is a module called prompts. callbacks import get_openai_callback from langchain. Based on my understanding, you were experiencing issues with the accuracy of the output when using the conversational retrieval chain with memory. documents import Document Apr 2, 2023 · Saved searches Use saved searches to filter your results more quickly Apr 26, 2023 · Hello! I am building an ai assistant, with the help of langchain's ConversationRetrievalChain. query = "How are you doing?" result = chain({"question": query, "chat_history": chat_history}) result['answer'] """ I'm doing well, thank you. Jul 19, 2023 · Studying AI and LangChain, and I was trying to make a conversational chatbot. Commit to Help. _qa_task: Helper method to execute the QA task in a separate thread. chains import ConversationalRetrievalChain from langchain. If only the new question was passed in, then relevant context may be lacking. Mar 13, 2023 · I want to pass documents like we do with load_qa_with_sources_chain but I want memory so I was trying to do same thing with conversation chain but I don't see a way to pass documents along with it. chains import ConversationalRetrievalChain from langchain. Oct 16, 2023 · from langchain. chat_models import ChatOpenAI from langchain_community. from_llm, and I want to create other functions such as send an email, etc. Apr 4, 2023 · const question_generator_template = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question. This can be achieved by using the QUESTION_PROMPT and COMBINE_PROMPT templates defined in the map_reduce_prompt. tokenize import sent_tokenize, word_tokenize Groq specializes in fast AI inference. Here's an example of it in action: Jul 16, 2023 · I wasn't able to do that with RetrievalQA as it was not allowing for multiple custom inputs in custom prompt. Aug 29, 2023 · System Info Getting error: got multiple values for keyword argument- question_generator . if the chain output has only one key memory will get the output by default. Aug 7, 2023 · Answer generated by a 🤖. embeddings import HuggingFaceEmbeddings from langchain_core. llm=llm, verbose=True, memory=ConversationBufferMemory() Oct 23, 2023 · If the parsing fails, it will automatically retry using the retry_chain (which is an instance of LLMChain) up to max_retries times. embeddings import HuggingFaceBgeEmbeddings import langchain from langchain_community. Jan 26, 2024 · from langchain_community. If it is, please let us know by commenting on this issue. Dec 23, 2023 · I am using langchain. You can use the following pieces of context to answer the question at the end. chat_message_histories import ChatMessageHistory. Jul 19, 2023 · To pass context to the ConversationalRetrievalChain, you can use the combine_docs_chain parameter when initializing the chain. I have loaded a sample pdf file, chunked it and stored the embeddings in vector store which I am using as a retriever and passing to Retreival QA chain. Amazon Bedrock is a fully managed service that makes leading foundation models from AI companies available through an API along with developer tooling to help build and scale generative AI applications. If the question is not related to the context, politely respond that you are teached to only answer questions that are related to the context. I store the previous messages in my db. They accept a config with a key ( "session_id" by default) that specifies what conversation history to fetch and prepend to the input, and append the output to the same conversation history. Any advices ? Last option I know would be to write my own custom chain which accepts sources and also preserve memory. runnables import RunnableMap , RunnablePassthrough from langchain_openai import ChatOpenAI , OpenAIEmbeddings Oct 11, 2023 · from langchain. Current conversation: System: 🦜🔗 Build context-aware reasoning applications. 🦜🔗 Build context-aware reasoning applications. vectorstores. vectorstores import Qdrant from langchain. I wanted to let you know that we are marking this issue as stale. document_loaders import DirectoryLoader from langchain. some text 2. txt documents when it thinks that the query is related to the Tool description. prompts import (ChatPromptTemplate, HumanMessagePromptTemplate, SystemMessagePromptTemplate,) from langchain_core. _get_qa_chain: Get the conversational retrieval chain for handling chat. jq hb or af eq xd xl zd jr bv