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Decision brief
UltraRAG is a low-code framework for building retrieval-augmented generation pipelines with Python.
Good fit when
- You require a straightforward setup with uv package manager or Docker support
- Need to create complex RAG pipelines without extensive coding knowledge
Avoid when
- Prefer tools that do not rely on specific package managers like uv
- Require more customization in pipeline creation beyond what low-code environments offer
Observed Jul 14, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (1d since push)
- As of today
- Provenance
- Not a fork · Organization account
- As of today
- Security (OSV)
- 2 low (2 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install UltraRAGHow it fits your stack(9)
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Alternative
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Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
UltraRAG offers a framework to build complex retrieval-augmented generation pipelines with low-code requirements.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 18, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 18, 2026
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 18, 2026
- Languages
- python
Source: github.language+pyproject.toml · Aug 18, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 18, 2026)
We strongly recommend using [uv](https://github.com/astral-sh/uv) to manage Python environments and dependencies, as it can greatly improve installation speed.Source link
Tags
README
📦 Installation
We provide two installation methods: local source code installation (recommended using uv for package management) and Docker container deployment.
Method 1: Source Code Installation
We strongly recommend using uv to manage Python environments and dependencies, as it can greatly improve installation speed.
Prepare Environment
If you haven't installed uv yet, please execute:
---
## Direct installation
pip install uv==0.12.0
---
# Full installation
uv pip install -e ".[all]"
---
# On-demand installation
uv pip install -e ".[retriever]"
Method 2: Docker Container Deployment
If you prefer not to configure a local Python environment, you can deploy using Docker.
Get Code and Images
---
# Option A: Pull from Docker Hub
docker pull hdxin2002/ultrarag:v0.3.0-base-cpu # Base version (CPU)
docker pull hdxin2002/ultrarag:v0.3.0-base-gpu # Base version (GPU)
docker pull hdxin2002/ultrarag:v0.3.0 # Full version (GPU)
---
### Verify Installation
After installation, run the following example command to check if the environment is normal:
```shell
ultrarag run examples/experiments/sayhello.yaml
If you see the following output, the installation is successful:
Hello, UltraRAG v3!
🚀 Quick Start
We provide complete tutorial examples from beginner to advanced. Whether you are conducting academic research or building industrial applications, you can find guidance here. Welcome to visit the Documentation for more details.
For agents
This page has a .md twin and JSON over the API.