Bringing smart data with artificial intelligence
Production-agentic-rag-course offers hands-on training in the development of agent-based fetch-assisted production (agentic RAG) systems that automate the processes of retrieving information from complex data sources. Based on the Python language, this resource teaches the technical architecture required to create scalable and production-level artificial intelligence applications.
Updates
- October 3, 2026: Stars 8,216 → 9,265, latest release week7.0 (November 26, 2025).
- August 2, 2026: Stars 6,536 → 8,216, latest release week7.0 (November 26, 2025).
What you get
- Establishing the necessary infrastructure for RAG systems at the production level.
- Applying hybrid search and intelligent data processing methods.
- Developing agent-based decision mechanisms with LangGraph.
Installation
git clone <repository-url>
cd arxiv-paper-curator
# 2. Configure environment (IMPORTANT!)
cp .env.example .env
# The .env file contains all necessary configuration for OpenSearch,
# arXiv API, and service connections. Defaults work out of the box.
# You need to add Jina embeddings free api key and langfuse keys (check the blogs)
# 3. Install dependencies
uv sync
# 4. Start all services
docker compose up --build -d
# 5. Verify everything works
curl http://localhost:8000/api/v1/healthRunning it
git clone --branch <WEEK_TAG> https://github.com/jamwithai/arxiv-paper-curator
cd arxiv-paper-curator
uv sync
docker compose down -v
docker compose up --build -d
# Replace <WEEK_TAG> with: week1.0, week2.0, etc.If you don't write code
I want to develop an academic research assistant using the production-agentic-rag-course project. For the basic installation of the project, after downloading the repository with the git clone command, I need to configure the .env file and install the dependencies with uv sync. Then, I want to verify that the system is working at http://localhost:8000/api/v1/health by starting all services with the docker compose up --build -d command. Can you guide me about the API keys and service configurations I should pay attention to in this process?
Repository: https://github.com/jamwithai/production-agentic-rag-course. Follow the official instructions in the README of this repository for setup and execution.
Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.
Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.
If an API key is required, do not ask me to type it into the chat. Show me how to add it to the .env file and ensure this file is not pushed to Git.
Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-03: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.