Hey Streamlit Community,
I wanted to share a YouTube video tutorial in Spanish but dubbed in English, thanks to YouTube. The project I built using Streamlit adds a powerful capability for data analysis: natural language querying via PandasAI.
PandasAI acts as an AI agent for your DataFrames, allowing users (even non-technical ones!) to ask questions about their data in plain English (or other languages) and get results back as DataFrames, charts, or simple text.
I created a Streamlit app demonstrating this by:
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Allowing CSV/Excel file uploads.
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Converting the uploaded data into a PandasAI DataFrame.
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Setting up a chat interface using st.chat_input and st.chat_message.
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Showing how PandasAI handles queries and returns results (including generated code and charts).
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Integrating with different LLMs (like Mistral in this example) using litellm.
This is a fantastic way to make your data applications more interactive and accessible.
You can see a demo and walk-through in this video:
