https://github.com/aabboudi/multimodal-rag-api

Multimodal RAG system for LLMs served using FastAPI.
https://github.com/aabboudi/multimodal-rag-api

chromadb fastapi langchain python rag

Last synced: 26 days ago
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Multimodal RAG system for LLMs served using FastAPI.

• Host: GitHub
• URL: https://github.com/aabboudi/multimodal-rag-api
• Owner: aabboudi
• Created: 2024-09-23T17:32:44.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-16T11:31:59.000Z (about 2 months ago)
• Last Synced: 2024-11-16T12:26:21.811Z (about 2 months ago)
• Topics: chromadb, fastapi, langchain, python, rag
• Language: Python
• Homepage:
• Size: 22.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Multimodal RAG System for LLMs

This project implements a multimodal RAG (Retrieval-Augmented Generation) system for large language models, enabling you to query files through API endpoints. Please note that the API expects the Ollama server to be running.

### Technologies Used

- [FastAPI](https://fastapi.tiangolo.com/): to build the API

- [LangChain](https://www.langchain.com/): to manage language model interactions

- [Chroma](https://www.trychroma.com/): to store and handle multimodal data

### Installation

Clone the repo

```bash

git clone https://github.com/aabboudi/multimodal-rag-api.git

cd multimodal-rag-api

```

Create and activate a virtual environment

```bash

python -m venv venv

\venv\Scripts\activate

```

Install dependencies

```bash

pip install -r requirements.txt

```

Run the server

```bash

fastapi dev app/main.py

```

### Usage

After running the server, you can send queries to the API endpoints to interact with the multimodal RAG system. Queries can be sent through the docs, Postman, or the command line.