u/umairmehmood

Been using Chainlit with LangChain for a while now on production legal AI apps — streaming agent responses, multi-step tool calls, the whole thing. Curious what others in this community have built with this combo and where the pain points are.

For me the rough edges have been:

• Auth in embedded/Copilot mode when the parent app already handles auth — the password_auth_callback flow gets messy fast
• Chat history persistence since LiteralAI shut down — self-hosting their open-sourced data layer works but it's extra ops nobody budgeted for
• WebSocket disconnects under moderate load — Chainlit drops connections and there's no built-in session recovery, you have to roll your own
• Debugging LangChain agent steps inside Chainlit's step visualizer when chains get deep — it can get noisy
• Mounting Chainlit inside an existing FastAPI app — the ASGI mount patterns are barely documented

What have you shipped? RAG pipelines, agents, internal tooling? And what forced you to reach for a workaround or abandon Chainlit entirely for something else?

PS: Claude helped me to write this as it knows my pain points while building with chainlit.