Azure-Samples/chat-with-your-data-solution-accelerator
A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices. observed · 2026-08-28
Health v2 · maintenance only
94/100
- Activity 99
- Release rhythm 94
- Longevity 84
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 6.5
- age_days: 1185
- days_rel: 41
- days_push: 8
- n_releases_24m: 27
Adoption not part of the score
1178 stars · 646 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Microsoft solution accelerator that deploys a ChatGPT-style Q&A experience grounded in your own documents, using Azure OpenAI models and Azure AI Search (or PostgreSQL with pgvector) for retrieval. It packages a React frontend, FastAPI backend, and Azure Functions ingestion worker, deployable into your own Azure subscription with a single 'azd up'.
Use cases
- chat with your own documents
- build a Q&A bot over company knowledge base
- grounded answers with citations to source files
- deploy a RAG solution on Azure
- index contracts and policies for natural-language search
- internal assistant over product manuals
- enterprise document question answering
When to choose
- You want a quick, Microsoft-supported starting point for a RAG chat app on Azure
- Your data lives in Azure and you want Azure AI Search or pgvector retrieval
- You need a full-stack reference implementation with frontend, backend, and ingestion pipeline
- You want responsible-AI features like content safety integrated out of the box
When to avoid
- You need a turnkey production system with no customization - it is explicitly a starting point
- You want to avoid Azure or cloud vendor lock-in
- You need on-premises or fully local deployment
- You want a minimal library to embed RAG in an existing app rather than a full application
Facets
application · maturity active
rag chatbot search-engine llm-inference web-framework file-upload chat-interface large-language-models artificial-intelligence chatbots cloud-computing self-hosted cloud python self-hosted azure-openai azure-ai-search solution-accelerator azd-templates azure-container-apps pgvector cosmos-db fastapi react document-qa citations retrieval-augmented-generation docker web-server
10 sources
- readme: https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator · fetched 2026-08-28 · 21fdfa1ff6f3
- homepage: https://azure.microsoft.com/products/search · fetched 2026-08-29 · ecfaeb27996a
- site_page: https://azure.microsoft.com/en-us/pricing · fetched 2026-08-29 · 00efb76f6f5f
- site_page: https://azure.microsoft.com/en-us/pricing/purchase-options/azure-account · fetched 2026-08-29 · 35e939cc84cf
- site_page: https://azure.microsoft.com/en-us/pricing/free-services · fetched 2026-08-29 · 70646498ead5
- site_page: https://azure.microsoft.com/en-us/pricing/purchase-options · fetched 2026-08-29 · c9d226f1c97e
- site_page: https://azure.microsoft.com/en-us/pricing/calculator · fetched 2026-08-29 · 73898700cc14
- site_page: https://azure.microsoft.com/en-us/pricing/offers/savings-plans · fetched 2026-08-29 · 223be1d556a1
- site_page: https://azure.microsoft.com/en-us/pricing/offers/reservations · fetched 2026-08-29 · 40e427678ee4
- site_page: https://azure.microsoft.com/en-us/pricing/offers/hybrid-benefit · fetched 2026-08-29 · 4654db5179c0
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Azure-Samples/chat-with-your-data-solution-accelerator | main | 94 |
For agents
markdown · JSON · MCP: product_card(name="Azure-Samples/chat-with-your-data-solution-accelerator")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem