organization · inferred from evidence
langchain-ai
The organization maintaining the LangChain repository.
- create_tool_calling_agent raises ValueError: This function requires a .bind_tools method be implemented on...
Wrapping a chat model with .with_fallbacks([fallback_model]) and passing the result to create_tool_calling_agent raised ValueError: This function requires a .bind_tools method be implemented on the LLM. The same error also hit AzureChatOpen
- LangSmith Python SDK memory grows in long-running apps (RunTree kept in memory)
Long-running Python app using LangGraph/LangChain (asyncio.gather with create_task, one graph per task). Memory grows steadily over time, but only when LangSmith tracing is enabled. tracemalloc and objgraph show RunTree objects accumulating
- LangGraph InvalidUpdateError: Must write to at least one of [...] (state channel name mismatch)
Running a LangGraph plan-and-execute style graph raised "langgraph.errors.InvalidUpdateError: Must write to at least one of ['input', 'plan', 'past_steps', 'response']" at runtime, even though the graph compiled without issues. The node's u
- OpenAIEmbeddings fails against Azure OpenAI: Too many inputs for model
Using langchain's OpenAIEmbeddings against Azure OpenAI failed with "InvalidRequestError: Too many inputs for model None. The max number of inputs is 1." Azure's embedding endpoint only accepts one input per request, so the default batched
- ValueError: create_tool_calling_agent requires .bind_tools on the LLM when using with_fallbacks
Wrapping a chat model with .with_fallbacks([fallback_model]) and passing the result to create_tool_calling_agent raised ValueError: This function requires a .bind_tools method be implemented on the LLM. The same error also hit AzureChatOpen
- streaming not working when using bind_tools with ChatOllama - llm.stream() returns no tokens
Streaming chat responses from an Ollama model (e.g. llama3.1:70b via ChatOllama, or ChatOpenAI pointed at Ollama's /v1 endpoint) with tools bound via llm.bind_tools([...]).stream(). With tools bound, streaming produced no tokens at all and
- Error in RootListenersTracer.on_chain_end callback: KeyError('answer') while streaming a RAG chain
Building a conversational RAG chatbot with create_retrieval_chain wrapped in RunnableWithMessageHistory (input_messages_key="input", history_messages_key="chat_history", output_messages_key="answer"). Calling astream() on the chain printed