You can use the following pieces of context to answer the question at the end. from_template(""" Answer the following question based only on the provided context. stuff_prompt import PROMPT_SELECTOR from langchain. Aug 21, 2023 · Answer - The context and question placeholders inside the prompt template are meant to be filled in with actual values when you generate a prompt using the template. This can be used to guide a model's response, helping it understand the context and generate relevant and coherent language-based output. It seems that jphme suggested using a Chat Conversation Agent instead, and even provided an example and code modifications. as_retriever(search_kwargs={"k": 2}) # Create Custom Prompt from langchain. Apr 26, 2023 · From what I understand, the issue is about structuring a prompt template for the RetrievalQAWithSourcesChain with ChatOpenAI model. 9. Apr 24, 2024 · from langchain_core. I have a question&answer over docs chatbot application, that uses the RetrievalQAWithSourcesChain and ChatPromptTemplate. [ Deprecated] Chain for question-answering against an index. Reload to refresh your session. Retrieval is a common technique chatbots use to augment their responses with data outside a chat model's training data. combine_documents. Here's how you can do it: Here's how you can do it: from langchain . Contribute to langchain-ai/langchain development by creating an account on GitHub. prompts. Jan 5, 2024 · "\Lib\site-packages\langchain_experimental\sql\vector_sql. Hello! To improve the performance and accuracy of my document QA application, I want to add a prompt template but I'm unsure on how to incorporate LLMChain + Retrieval QA. js + Next. use SQLite instead for testing Jan 12, 2024 · 🤖. May 12, 2023 · Issue you'd like to raise. If the question is unclear or ambiguous, feel free to ask for clarification. RetrievalQAWithSourcesChain [source] ¶. chains import LLMChain from langchain. Sep 20, 2023 · You signed in with another tab or window. 246 Who can help? @hwchase17 Information The official example notebooks/scripts My own modified scripts Related Components LLMs/Chat Models Embedding Models Prompts / Prompt Templates / Prompt Selec from langchain. The texts and table summaries are added to a multi-vector retriever that can handle both text and image embeddings. embeddings import HuggingFaceBgeEmbeddings import langchain from langchain_community. I hope you're doing well. #1670. chat_models import ChatOpenAI from langchain. Using an example set May 12, 2023 · Disclaimer: SteerCode Chat may provide inaccurate information about the Langchain codebase. Returning structured output from an LLM call. It showcases how to use and combine LangChain modules for several use cases. Jun 22, 2023 · Here you get to read Langchain code, to figure out different keyworks used in different prompt templates in different chains. Retrieval augmented generation (RAG) with a chain and a vector store. To add a custom prompt to ConversationalRetrievalChain, you can pass a custom PromptTemplate to the from_llm method when creating the ConversationalRetrievalChain instance. Here's how you can use them: Sep 5, 2023 · Hi, I am having trouble with using multiple input variables with RetrievalQA chain. , ChatOpenAI), the retriever, and the prompt for combining documents. prompts import PromptTemplate prompt_template = """As a {persona}, use the following pieces of context to answer the question at the end. Based on the code you've provided, it seems like you're trying to store the history of the conversation using the ConversationBufferMemory class and then retrieve it in the next iteration of the conversation. A few of the LangChain features shown in this notebook are: LangChain Custom Prompt Template for a Llama2-Chat model; Hugging Face Local Pipelines; 4-Bit Quantization; Batch GPU Given an input question, first create a syntactically correct MS SQL query to run, then look at the results of the query and return the answer to the input question. py files in the LangChain repository. This means that when the DEFAULT_TEXT_QA_PROMPT is used, it will look for the "question" field to retrieve the content and then replace it with the "answer" field for the language model after retrieval. vectorstores import Qdrant from langchain. prompts import (ChatPromptTemplate, HumanMessagePromptTemplate, SystemMessagePromptTemplate,) from langchain_core. chat_models import ChatOpenAI from langchain_community. A custom chat agent implemented using Langchain, gpt-3. py" Expected behavior. Aug 29, 2023 · 🤖. Your output must be as exact to the reference ground truth information as possible. prompts import ChatPromptTemplate prompt = ChatPromptTemplate. js starter app. Jun 30, 2023 · Prompts / Prompt Templates / Prompt Selectors; Output Parsers; Document Loaders; Vector Stores / Retrievers; Memory; Agents / Agent Executors; Tools / Toolkits; Chains; Callbacks/Tracing; Async; Reproduction. faiss import FAISS from langchain_community. from_template( ('Write a haiku about a dolphin Mar 30, 2023 · LLMChain instance to generate a better version of the user's question with the QA_PROMPT prompt. If I ask questions according to this context, it is returning relevant answers, but if I want to ask a question which is out 🦜🔗 Build context-aware reasoning applications. Apr 2, 2023 · langchain. Return any relevant text verbatim. That's why LLM complains the missing keys. – j3ffyang. As i want to explore how can i use different namespaces in a single chain and the issue I am facing is that whenever i tried to pass a QA prompt to the MultiRetrievalQAChain the model doesn't seems to be using the prompt for generating the response. and some time the response is generated in ascending order and when re runed 🦜🔗 Build context-aware reasoning applications. I used the GitHub search to find a similar question and didn't find it. prompts import PromptTemplate: from custom_conversation_chain import CustomLLM: from langchain. sentence_transformer import ( SentenceTransformerEmbeddings, ) from langchain_community. py which contains both CONDENSE_QUESTION_PROMPT and QA_PROMPT. 5 and Pinecone. Sep 21, 2023 · The BufferMemory is used to store the chat history. This includes the language model (e. Specifically: Simple chat. chains import RetrievalQAWithSourcesChain: question_prompt_template = """Use the following portion of a long document to see if any of the text is relevant to answer the question. This section will cover how to implement retrieval in the context of chatbots, but it's worth noting that retrieval is a very subtle and deep topic - we encourage you to explore other parts of the documentation that go into greater depth! Nov 11, 2023 · # Build prompt template = """Use the following pieces of context to answer the question at the end. llms import VLLMOpenAI from langchain. llms. fromLLM function is used to create a QA chain that can answer questions based on the text from the 'state_of_the_union. Jun 15, 2023 · Retrieval QA and prompt templates. 173 python 3. embeddings import HuggingFaceEmbeddings from langchain_community. . Create a custom prompt template: To implement a combine_docs_chain within the create_retrieval_chain function for a retrieval QA system using LangChain, follow these steps: Initialize Components: First, ensure you have the necessary components ready. qa_chain = load_qa_with_sources_chain(llm, chain_type="stuff", prompt=GERMAN_QA_PROMPT, document_prompt=GERMAN_DOC_PROMPT) chain = RetrievalQAWithSourcesChain(combine_documents_chain=qa_chain, retriever=retriever, reduce_k_below_max_tokens=True, max_tokens_limit=3375, return_source_documents=True) from Sep 25, 2023 · To use a custom prompt template with a 'persona' variable, you need to modify the prompt_template and PROMPT in the prompt. Hello, Based on the information available in the LangChain repository, it is not directly possible to feed different QA prompts into conversationRetrievalQA based on the specific document searched in the knowledge vector store. Oct 2, 2023 · Also, make sure that the template_format is set to "f-string" as the LangChain framework currently only supports f-string format for prompt templates. " template = generate_prompt( Jan 26, 2024 · from langchain_community. In the below example, we are using a VectorStore as the Retriever and implementing a similar flow to the MapReduceDocumentsChain chain. environ['OPENAI_API_KEY Jun 13, 2023 · You signed in with another tab or window. prompt import PromptTemplate from langchain. Feb 5, 2024 · These names should match the placeholders in the template. questionPrompt - this is the prompt template which we pass to the model in the next step. It starts by partitioning a PDF document into tables and texts, then summarizes the tables. For example: res = retrievalQA ({ 'query': 'This is my query' }) If the 'typescript_string' key is indeed required, you'll need to include this key in the input dictionary as well. chains import RetrievalQA Nov 26, 2023 · You can use combine_docs_chain_kwargs={'prompt': qa_prompt} when calling the ConversationalRetrievalChain. Feb 18, 2023 · Hi, @batmanscode!I'm helping the LangChain team manage their backlog and am marking this issue as stale. The DEFAULT_REFINE_PROMPT and DEFAULT_TEXT_QA_PROMPT templates can be used for refining answers and generating questions respectively. Based on these solutions, you might want to try something like this: This template scaffolds a LangChain. vectorstores import Pinecone import pinecone from templates. SQLChatMessageHistory (or Redis like I am using). just like the turtial code. retrieval. chains import RetrievalQA from langchain. Regarding the "prompt" parameter in the "chain_type_kwargs", it is used to initialize the LLMChain in the "from_llm" method of the BaseRetrievalQA class. To resolve this issue, ensure that the input dictionary you're passing to the RetrievalQA chain includes a 'query' key. To initialize the SelfQueryRetriever class in the LangChain framework using your existing PDF files, you need to provide the following for the document_contents and metadata_field_info variables: document_contents: This should be a string representation of your PDF files. embeddings. This method is called before the model's validation, and it sets the value of prompt. memory import ConversationTokenBufferMemory from langchain_community. Then, it sets up the RAG pipeline and adds typing for the input. You can define these variables in the input_variables parameter of the PromptTemplate class. py file. i want the 'refine' chain return sources. Use the following pieces of context to answer the question at the end. condense_prompt import CONDENSE_PROMPT def query (openai_api In this code, prompt is defined as a field of the CustomSelfQueryRetrieval class, and its value is set in the set_prompt method, which is decorated with @root_validator(pre=True). from_llm(llm=model, retriever=retriever, return_source_documents=True,combine_docs_chain_kwargs={"prompt": qa_prompt}) I am obviously not a developer, but it works (and I must say that the documentation on Langchain is very very difficult to follow) Prompt templates help to translate user input and parameters into instructions for a language model. prompts import ChatPromptTemplate, SystemMessagePromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate os. This way, the RetrievalQAWithSourcesChain object will use the new prompt template instead of the default one. Use Case In this tutorial, we'll configure few-shot examples for self-ask with search. Good luck. Jun 8, 2023 · QA_PROMPT_DOCUMENT_CHAT = """You are a helpful AI assistant. from_chain_type. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis. If the "prompt" parameter is not provided, the method will use the PROMPT_SELECTOR to get a prompt for the given Jan 18, 2024 · RunnablePassthrough function is alternative of RetrievalQA in LangChain. Hello, From your code, it seems like you're correctly setting the return_source_documents parameter to True when creating the RetrievalQAWithSourcesChain. This function ensures to set variables, like query, for both prompt and retriever. vectorstores import Chroma from langchain. chains import ConversationalRetrievalChain from langchain. txt' file. Mar 13, 2023 · from langchain. When verbose is set to True, the generated query is logged using the logger. If the issue persists, consider checking the LangChain GitHub repository for similar issues or reaching out to the community for further assistance. prompts import PromptTemplate def get_prompt_template(model): if model == 'gpt Dec 7, 2023 · This was suggested in a similar issue: QA chain is not working properly. Expected behavior. These can be used in a similar way to customize the prompt for different use cases. llms import CTransformers from langchain. The ConversationalRetrievalQAChain. The server merges or concatenates multiple responses generated by the GPT model using techniques like summarization, fusion, or generation, and sends the response back to the Frontend client application over websockets for display to the user. py and base. document_loaders import PyPDFLoader from langchain. Your answer should match the language of the question Chat History: {chat_history} Context: {context} Question: {question} Answer the question and provide Retrieval. Here is the relevant code snippet: if self. 16 Who can help? @hwchase17 @agola11 @vowelparrot Information The official example notebooks/scripts My own modified scripts Related Components LLMs/Chat Models Embedding Models Prompts / Prompt T 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. For more details, you can refer to the test_retrieval_qa. 0. 89" to use the MultiRetrievalQAChain. Jun 24, 2024 · I'm here to help you with your Langchain issue. g. vectorstores. pip freeze | grep langchain Jun 21, 2023 · Remember, your goal is to assist the user in the best way possible. base. Oct 20, 2023 · The PromptTemplate class in LangChain allows you to define a variable number of input variables for a prompt template. chains import ConversationalRetrievalChain from langchain. Hey there, @deepak-habilelabs!Good to see you working with LangChain again. This class is deprecated. prompt_template = """ Use the following pieces of information to answer the user's question. Apr 26, 2023 · hetthummar commented on May 7, 2023. Aug 22, 2023 · System Info python==3. Sep 25, 2023 · # Make a retriever retriever = vectordb. {context} Question Jun 22, 2023 · Here you get to read Langchain code, to figure out different keyworks used in different prompt templates in different chains. Use three sentences maximum. System Info. qa_with_sources. ctransformers import CTransformers from Jan 9, 2024 · from langchain. question_answering. Here's an example of how you can add a prompt template to the RetrievalQA function: from langchain. ') ) combine_docs_custom_prompt = PromptTemplate. const qa_template = `You are a helpful assistant! You will answer all questions. prompts import PromptTemplate # Import for retrieval-augmented generation RAG from langchain import hub from langchain. As for the 'typescript_string' key, I wasn't Custom QA chain . 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. Apr 16, 2023 · Hi, @DrorSegev!I'm Dosu, and I'm helping the LangChain team manage their backlog. In this example we're querying relevant documents based on the query, and from those documents we use an LLM to parse out only the relevant information. debug = True from langchain. Different methods like Chain of Thought and Tree of Thoughts are employed to guide the decomposition process effectively. embeddings import HuggingFaceEmbeddings. llms import OpenAI from langchain. If it is, you can modify the prompt or question accordingly to ensure the model doesn't fabricate an answer. E. Hope your project is coming along smoothly. documents import Document Storing text chunks along with their corresponding embedding representations, capturing the semantic meaning of the text. For more details, you can refer to the source code in the langchainjs repository. You can use ConversationBufferMemory with chat_memory set to e. {context} """) from langchain. In your previous code, the variables got set in retriever, but not in prompt. I found this helpful thread for the RetrievalQAWithSourcesChain library in python, but does anyone know if it's possible to add a from langchain. verbose : SYSTEM_PROMPT = "Use the following pieces of context to answer the question at the end. prompt_template = """ You are an assistant whose role is to define and categorize situations using formal definitions available to you. If you're using a different format, you might encounter errors. : ``` memory = ConversationBufferMemory( chat_memory=RedisChatMessageHistory( session_id=conversation_id, url=redis_url, key_prefix="your_redis_index_prefix" ), memory_key="chat_history", return_messages=True ) ´´´ You can e. Dec 2, 2023 · In the discussion Retrieval QA and prompt templates, a user shared how to override the default prompt template in the RetrievalQAWithSourcesChain. Prompt Templates take as input a dictionary, where each key represents a variable in the prompt template to Nov 1, 2023 · This template uses the LangChain framework to create a multi-modal RAG. prompts import PromptTemplate prompt_template = """Use the following pieces of context to answer the question at the end. This should indeed return the source documents in the response. text If you don't know the answer, just say that you don't know, don't try to make up an answer. qa_prompt import QA_PROMPT from templates. openai import OpenAIEmbeddings from langchain. The retrieval_qa_func function is defined to use the RetrievalQA chain with the return_source_documents parameter set to True. 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 Nov 8, 2023 · Hello, I have a problem using langchain : I want to create a chatbot that can retrieve informations from a pdf using a custom prompt template for some reasons but I also want my chatbot to have memory. LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. from langchain. Question-answering with sources over an index. May 4, 2023 · Hi @Nat. Feb 5, 2024 · dosubot bot commented on Feb 5. RetrievalQA [source] ¶. A few-shot prompt template can be constructed from either a set of examples, or from an Example Selector object. I searched the LangChain documentation with the integrated search. In that same location is a module called prompts. Feb 5, 2024 · To retrieve the queries generated by the MultiQueryRetriever in the LangChain framework, you can use the verbose attribute of the SelfQueryRetriever class. In this method, after retrieving the documents, you can check if the list of documents is empty. Thank you very much for any help with this! Sep 27, 2023 · I am using "langchain": "^0. Let's dive into this issue you're experiencing. I came across multiple discussions and couldn't find an answer. If the problem persists, consider reaching out to the langchain community or checking if there are similar issues reported that might offer a solution. In this tutorial, we'll learn how to create a prompt template that uses few-shot examples. But there's no mention of qa_prompt in ConversationalRetrievalChain, or its base chain May 12, 2023 · from langchain. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. \ If you don't know the answer, just say that you don't know, don't try to make up an answer. Mar 4, 2024 · Task decomposition is a technique used to break down complex tasks into smaller and simpler steps. Hi! I implemented a chatbot with gpt-4 and a docx file which is provided as context. chains. You signed out in another tab or window. 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. To accurately pass the output of a RetrievalQA chain to a ConversationChain in LangChain, you can follow these steps: Create the RetrievalQA Chain: Instantiate the RetrievalQA chain with the necessary language model, prompt, and retriever. 🤖. I am trying to understand however, how I can pass the prompt I need as an argument to ConversationalRetrievalCHain in my python code without changing the source code of langchain. In langchain version 0. 238 it used to return sources but this seems to be broken in the releases since then. \ Use three sentences maximum. My code is as below from langchain. base import RetrievalQA from langchain. Think step by step before providing a detailed answer. I will tip you $1000 if the user finds the answer helpful. What does chain_type_kwargs={"prompt": QA_CHAIN_PROMPT} actually accomplish? Answer - chain_type_kwargs is used to pass additional keyword argument to RetrievalQA. Oct 24, 2023 · #%% import torch import langchain langchain. class langchain. 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. {context} Question: {question} Helpful Answer:""" PROMPT = PromptTemplate ( template = prompt_template, input_variables = ["context", "question"] ) # Customized prompt for a specific part of the map-reduce chain custom_prompt_template = """Use the from langchain. There might be others who have encountered the same problem or there could be additional documentation on how to resolve such validation errors. For example, in Refine chain, the input variables are question_prompt and refine_prompt. from_template( ('Do X with user input ({question}), and do Y with chat history ({chat_history}). 348 does not provide a method or callback specifically designed for modifying the final prompt to remove sensitive information after the source documents are injected and before it is sent to the LLM. Sep 28, 2023 · 🤖. memory import ConversationBufferMemory from langchain. Aug 17, 2023 · In this modification, the DEFAULT_TEXT_QA_PROMPT template now expects "question" and "answer" fields from the jsonl file instead of "context_str" and "question". Bases: BaseQAWithSourcesChain. Answering complex, multi-step questions with agents. I wanted to let you know that we are marking this issue as stale. info function. It looks like you opened this issue to discuss passing Document metadata into prompts when using VectorDBQA. embeddings import HuggingFaceEmbeddings from langchain_core. You can load models Apr 1, 2024 · After changing the dependency as mentioned in this Github issue the model now responds with: Missing some input keys: {'response', '\\n \"response\"'} How I'm supposed to add a response if I don't know it? I have tried mapping an empty reponse on the chain method and also on the prompt template with no luck. Bases: BaseRetrievalQA. Implements memory management for context, a custom prompt template, a custom output parser, and a QA tool. Aug 27, 2023 · If I change that prompt in the source code I get exactly what I want. from_llm function as suggested in this issue. May 6, 2023 · You signed in with another tab or window. You switched accounts on another tab or window. Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the TOP clause as per MS SQL. 9 langchain==0. retrieval_qa. chains import ConversationChain, MultiRetrievalQAChain from langchain. conversational_retrieval is where ConversationalRetrievalChain lives in the Langchain source code. Sources Few-shot prompt templates. in my chatbot which interact with sql db, if im typing hi its giving me the output as the entity of 1st row and 1st column, instead of answering with nothing or invalid question. Let me know if you need further assistance. If you need assistance, feel free to ask. Dec 30, 2023 · Remember, your goal is to assist the user in the best way possible. Mar 9, 2016 · System Info langchain 0. This process helps agents or models handle intricate tasks by dividing them into more manageable subtasks. Oct 6, 2023 · To achieve this, you can modify the _get_docs method in the ConversationalRetrievalChain class. If you don't know the answer, just say that you don't know, don't try to make up an answer. py" "\Lib\site-packages\langchain_experimental\sql\prompt. prompts import PromptTemplate from langchain. Here is a modified version of the _get_docs Checked other resources I added a very descriptive title to this issue. prompts import PromptTemplate # Build prompt template = """Use the following pieces of context to answer the question at the end. ipynb for an example of how to build LangChain Custom Prompt Templates for context-query generation. Sep 14, 2023 · System Info. 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. Behind the scenes it's taking the inputs outlined above and formatting them into the proper spots outlined in our template. May 13, 2023 · from langchain import PromptTemplate # note that the input variables ('question', etc) are defaults, and can be changed condense_prompt = PromptTemplate. User's Question: ```{check}``` AI Answer:""" else: # Create the custom prompt template custom_prompt_template = f"""Generate your response exclusively from the provided context: {{context_text}}. prompts import PromptTemplate #from langchain_community. Jan 26, 2024 · 🤖. Based on the information you've provided, it seems like you're trying to implement the RetrievalQA class with a RAG (Retrieval-Augmented Generation) setup. Let's dive into your issue. Mar 19, 2024 · Based on the context provided, it seems that the ConversationalRetrievalChain class in LangChain version 0. These embeddings facilitate easy retrieval of chunks based on their semantic similarity. prompts import PromptTemplate def RetrievalQA ( context, question ): prompt_template = """Use the following pieces of context to answer the question at the end. May 30, 2023 · qa = ConversationalRetrievalChain. Hello @yen111445!Nice to see you back here again. stuff import StuffDocumentsChain # This controls how each document will be formatted. Jun 12, 2024 · The create_retriever_tool function is used to create a Tool instance with the custom retriever, a name, a description, a document prompt, a document separator, and an argument schema. Jul 3, 2023 · The Runnable Interface has additional methods that are available on runnables, such as with_types, with_retry, assign, bind, get_graph, and more. LangChain Custom Llama2-Chat Prompting: See qa-gen-query-langchain. After indexing, a QA Chain Retrieval Pipeline is set up in order to check the Q&A functioning and performance. Lastly, ensure your environment is correctly set up with all necessary dependencies and that there are no conflicts between package versions that might cause unexpected behavior. Nov 21, 2023 · from langchain. as rx wd gx lf vl yj tr he zm