I am trying to practice langchain on google colab and by using the google flab model to do chaining and when i run the code I get this error Bad request: Authorization header is correct, but the token seems invalid.

I am trying to use arize-phoenix to perform eval on my langchain RAG pipeline however the get_qa_with_reference(px.Client()) function always returns None. Below is the code

I have two chains

I think I may be fundamentally misunderstanding something with Langchain.

I would like to reconstruct an object of langchain_core.messages.ai.AIMessage from the dict obtained from an object of type langchain_core.messages.ai.AIMessage.

I am trying to take a bunch of java files and create an embedding to be used by a LLM.

TypeError Traceback (most recent call last)
Cell In[33], line 3
1 file_path=”vector_index.pkl”
2 with open(file_path, “wb”) as f:
—-> 3 pickle.dump(vectorindex_openai, f)

I have a csv which has format as follows

I’m using a chatbot which is created by python langchain. In that I’m sending requests to the several LLM models (OPENAI , Claude, GEMINI). When I send requests to llm, first I summarize my previous chat. For summarize it I send my previous chats with a prompt mentioning to summarize this chat. It is done by ConversationSummaryBufferMemory using llm = ChatOpenAI(temperature=0, model_name=GPT3_MODEL) . By then I got that summary of the chat history and I stored it in a variable. After when I send my query to the LLM, I send it with the prompt , query and the summery of chat history that I have stored in a variable. But in the verbose I can see whole the chat history in the prompt instead of the summery of the previous chat.

I am trying to use langchain to query a structured SQL database and I have followed the documentation exactly on the langchain website but I keep getting an error on how I am trying to submit my SQL command. There error I get says: