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rags

run-llama/rags

Build ChatGPT over your data with natural language

GitHub

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

83views this month

6.5k stars656 forksLast push Apr 5, 2024 Python MIT

Decision brief

Decision-critical facts for 'rags':

Good fit when

When leveraging natural language queries over proprietary user data using OpenAI services.
If you require a framework that integrates seamlessly with Streamlit to build conversational agents.

Avoid when

Not suitable if you seek solutions not dependent on OpenAI's services as the underlying framework is tightly coupled with OpenAI APIs.
Avoid using rags if your project involves sensitive or highly confidential data since it requires integrating API keys, potentially posing security concerns.

Requirements:: Installation leverages poetry for dependency management.; Setup requires configuration with OpenAI key and potentially creating a virtual environment.

Observed Jul 12, 2026 · Source: enrich:decision_facts

rags alternatives Trust report

rags vs botpress rags vs kotaemon rags vs Langchain-Chatchat

Verify the decision

Maintenance and security

Full trust report

Maintenance: Dormant (865d since push); As of Aug 18, 2026
Provenance: Not a fork · Organization account; As of Aug 18, 2026
Security (OSV): 38 low (38 low); As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Backing

Company context for LlamaIndex. Display-only - separate from trust and ranking.

Company: LlamaIndex·GitHub org profile·Jul 11, 2026
Funding: $19,000,000 (2024-02)·GraphCanon curated seed (public press)·Jul 11, 2026
Commercial model: Open core·GraphCanon curated seed·Jul 11, 2026

Install

pip install rags

PyPI

How it fits your stack(17)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

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Same-category neighbours not already linked as typed edges.

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A framework for building conversational agents that leverage user data using natural language queries and OpenAI services.

Capability facts

Languages: python
Source: github.language+pyproject.toml · Aug 18, 2026

Graph entities

LlamaIndexcompany LlamaIndexframework

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 18, 2026)

e `rags` project folder. We recommend creating a virtual env for dependencies (`python3 -m venv .venv`).

Source link

README

Installation and Setup Clone this project, go into the project folder. We recommend creating a virtual env for dependencies ( ). By default, we use OpenAI for both the builder agent as well as the generated RAG agent. Add in the home folder. Then put the following: Then run the a...

For agents

This page has a .md twin and JSON over the API.

/tools/run-llama-rags.md GET /api/graphcanon/tools/run-llama-rags GET /api/graphcanon/graph?tool=run-llama-rags