Data & Research · GitHub ·9 ★

on-your-data-with-streamlit

Showcase the use of Azure OpenAI's native On Your Data feature and integrates it with Streamlit, a robust framework for developing web applications purely in Python. The goal is to create an MVP for RAG with the most streamlined architecture possible.

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Details

Author
charliewei0716
Category
Data & Research
Platform
GitHub
Framework
openai
Language
bicep
Stars
9
First indexed
2026-05-15
Last active
2024-08-24
Directory sync
2026-05-15
@charliewei0716

Overview

Showcase the use of Azure OpenAI's native On Your Data feature and integrates it with Streamlit, a robust framework for developing web applications purely in Python. The goal is to create an MVP for RAG with the most streamlined architecture possible.

Quick start

git

git clone https://github.com/charliewei0716/on-your-data-with-streamlit

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What on-your-data-with-streamlit can do

frameworkragdata
  • Framework — framework task automation.
  • Rag — Retrieves grounded context before answering.
  • Data — Reads, transforms, and analyses structured data.

Frequently asked questions

What is on-your-data-with-streamlit?
Showcase the use of Azure OpenAI's native On Your Data feature and integrates it with Streamlit, a robust framework for developing web applications purely in Python. The goal is to create an MVP for RAG with the most streamlined architecture possible.
How do I install on-your-data-with-streamlit?
Use git: `git clone https://github.com/charliewei0716/on-your-data-with-streamlit`. Full setup details on the source page linked above.
Is on-your-data-with-streamlit open source?
on-your-data-with-streamlit is published on GitHub.
What are alternatives to on-your-data-with-streamlit?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Profile data for on-your-data-with-streamlit is sourced from GitHub, published by charliewei0716.

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