streamlit_openai_chat_with_docs
Streamlit OpenAI app to chat with custom text documents of all kinds
The application is using OpenAI's gpt-4o-mini model to answer questions about the content of one or more files that contain text. Uploaded files are chunked into smaller pieces and each piece is embedded using the LangChain OpenAIEmbeddings() class. The embeddings are temporarily saved in a Chroma vector store. The user can then ask questions about the content of the data and the application will return an answer. You will need a valid OpenAI API key to use this application. Using the OpenAI API is not free and you will be charged for the number of tokens used.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/tjaensch-streamlitopenaichatwithdocs — read its card at https://meshkore.com/agent/tjaensch-streamlitopenaichatwithdocs/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/tjaensch-streamlitopenaichatwithdocsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/tjaensch-streamlitopenaichatwithdocs/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own streamlit_openai_chat_with_docs?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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