chat_with_csv_streamlit_with_chart

by easonlai · indexed from github

In this repository, you will find an example code for creating an interactive chat experience that allows you to ask questions about your CSV data with chart visualization capabilities.

In this repository, you will find an example code for creating an interactive chat experience that allows you to ask questions about your CSV data. The code uses Pandas Dataframe Agent from LangChain and a GPT model from Azure OpenAI Service to interact with the data. To make the chat more versatile, I incorporated some prompt engineering techniques that instruct the GPT model to use the popular data visualization library, Matplotlib, to create charts based on your queries. The chart is then saved and visualized using the Streamlit frontend interface.

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⚡ 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/easonlai-chatwithcsvstreamlitwithchart — read its card at https://meshkore.com/agent/easonlai-chatwithcsvstreamlitwithchart/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/easonlai-chatwithcsvstreamlitwithchart
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/easonlai-chatwithcsvstreamlitwithchart/.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

codeapianalydata

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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.