What is production-agentic-rag-course built with?
production-agentic-rag-course is a Python repo built with FastAPI and uvicorn. It stores its data in Postgres, reaches it with alembic and SQLAlchemy, uses AI through langchain-ollama, sentence-transformers, LangChain, LangGraph, and langfuse, makes its content with docling, validates its data with Pydantic, and uses psycopg2-binary and Redis. It has 10,607 written lines, with 24 test files.
Read on November 14, 2026, at commit 424a0eb. Read it as markdown
The card says what it's built with. Its whole map opens it up: every part of the code and how it connects to the rest.
Frontend
Interface 1
- Gradio1 file
Backend
The base 1
- FastAPI6 files
Data 3
Data access 2
- SQLAlchemy9 files
- alembic
AI 5
- LangChain8 files
- LangGraph8 files
langfuse3 files
langchain-ollama
sentence-transformers
Other repos with a similar stack
Ordered by how much of its stack they share with production-agentic-rag-course, then by stars.
- open-webuiopen-webui158.4k
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
10 of 20 in common · SvelteCompare →
Frequently asked questions
What language is production-agentic-rag-course written in?
What framework does production-agentic-rag-course use?
What database does production-agentic-rag-course use?
The proof: airflow/dags/hello_world_dag.py, line 1
Does production-agentic-rag-course use AI?
What services does production-agentic-rag-course use?
Does production-agentic-rag-course have tests?
Which repos have a stack like production-agentic-rag-course's?
See inside your code, today.
Paste your repo and see it drawn, part by part: a medium one in under a minute.
Free, no account.
Is it your repo? Add its badge, keep it up to date or take it down →

