I’ve encountered an error while working with the langchain_core langchain-openailibrary and I’m hoping someone can assist me in resolving this issue.

I’m currently working with two LangChain agents (Pandas agents) to retrieve information from large tabular datasets. I originally had both datasets (Iris and Titanic) in a single agent, but separating them into two agents has improved my inference accuracy.

I would like to ask about LangChain for LLM in python.

I am trying to create a chatbot which can take input and generate query based on fined tuned model and provided schema. It was working fine previously but now every scenario which was working fine is generating wrong results/query I am using openai gpt3.5turbo Here’s my code

I’m using LangChain’s load_summarize_chain function combined with map_reduce and gpt-3.5-turbo-instruct to summarize multiple documents within a specific folder. Each folder has a unique ID and contains documents related to a single topic. For example, a folder with the ID ‘xyz123’ contains only documents related to cooking, and I expect the summary output to solely reflect cooking-related content.

On the following code I’m unable to resolve this error:

I used Python LangChain UnstructuredURLLoader to retrieve all our products in our company website for RAG purpose. The products were on different pages in the company website.

I’m trying to build a RAG with langchain. I’d like to consider the chat history and to be able to produce citations. I’ve followed the tutorial on Langchain but I struggle to put together history and citations.