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    RAG-AI-Agent

    RAG-AI-Agent

    paanjoe March 20, 2025
    3 copies 0 downloads

    R&D RAG AI Agent by consuming vary documents. This serve as a personal experiment with AI

    RAG AI Application

    A Retrieval-Augmented Generation (RAG) application that enables users to chat with their PDF documents using Google's Gemini AI model.

    This is for my personal experiment use only & educational purposes.

    Features

    • PDF document upload and processing
    • Vector embeddings generation using Gemini API
    • Similarity search using pgvector
    • Conversational AI with context from uploaded documents
    • Dark/Light mode support
    • User-provided API key management

    Tech Stack

    Frontend

    • Next.js 14
    • React
    • Flowbite UI Components
    • TailwindCSS

    Backend

    • FastAPI
    • LangChain
    • Google Gemini API
    • PyPDF

    Database

    • Supabase
    • PostgreSQL with pgvector extension

    Technical Architecture

    graph TB
        subgraph Frontend["Frontend (Next.js)"]
            UI[User Interface]
            Upload[PDF Upload Component]
            Chat[Chat Component]
            Theme[Theme Provider]
        end
    
        subgraph Backend["Backend (FastAPI)"]
            API[FastAPI Endpoints]
            RAG[RAG Service]
            PDF[PDF Processor]
            LLM[Gemini LLM]
        end
    
        subgraph Database["Vector Database (Supabase)"]
            PG[PostgreSQL]
            Vector[pgvector]
            Embed[Embeddings Storage]
        end
    
        %% User Flow
        User((User)) -->|1. Uploads PDF| Upload
        Upload -->|2. Send PDF| API
        API -->|3. Process| PDF
        PDF -->|4. Generate Embeddings| RAG
        RAG -->|5. Store Vectors| Vector
    
        %% Chat Flow
        User -->|6. Ask Question| Chat
        Chat -->|7. Query| API
        API -->|8. Get Context| RAG
        RAG -->|9. Search Similar| Vector
        Vector -->|10. Return Context| RAG
        RAG -->|11. Generate Answer| LLM
        LLM -->|12. Response| API
        API -->|13. Display Answer| Chat
    
        %% Styling
        classDef frontend fill:#47B4B6,stroke:#333,stroke-width:2px;
        classDef backend fill:#FF9776,stroke:#333,stroke-width:2px;
        classDef database fill:#7C3AED,stroke:#333,stroke-width:2px;
        classDef user fill:#4CAF50,stroke:#333,stroke-width:2px;
    
        class UI,Uplo
    

    Tags

    aiartificial-intelligencegeminirag

    Comments

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