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rag_api

danny-avila/rag_api

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

GitHub Website

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

67views this month

901 stars404 forksLast push Aug 15, 2026 Python MIT

Decision brief

Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration

Good fit when

When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
If your use case benefits from the efficiency of PostgreSQL/pgvector combination, where scalable vector search operations are required.

Avoid when

Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints.
Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.

Observed Jul 11, 2026 · Source: enrich:decision_facts

rag_api alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Steady (35d since push); As of Sep 20, 2026
Provenance: Not a fork · Personal account; As of Sep 20, 2026
Security (OSV): No lockfile; As of Jul 11, 2026

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

Install

pip install rag_api

PyPI

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Evidence and technical details

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

Overview

A FastAPI-based API for ID-based retrieval-augmented generation (RAG) systems, integrated with Langchain and using PostgreSQL/pgvector as the vector database.

Capability facts

Deploy: Self-host
Source: dockerfile:Dockerfile · Sep 20, 2026
Docker: Dockerfile present
Source: dockerfile:Dockerfile · Sep 20, 2026
Languages: python
Source: github.language · Sep 20, 2026

Compatibility

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

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

ollowing commands (preferably in a [virtual environment](https://realpython.com/python-virtual-environments-a-primer/))

Source link

README

Getting Started Configure file based on section below Setup pgvector database: Run an existing PSQL/PGVector setup, or, Docker: (also starts RAG API) or, use docker just for DB: Run API : Docker: (also starts PSQL/pgvector) or, use docker just for RAG API: Local: Make sure to set...

For agents

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

/tools/danny-avila-rag-api.md GET /api/graphcanon/tools/danny-avila-rag-api GET /api/graphcanon/graph?tool=danny-avila-rag-api