No-Code AI Workflow Builder

This project is a full-stack web application that allows users to visually design, build, and interact with intelligent workflows. Users can connect components to handle queries, retrieve knowledge from documents, and generate responses from Large Language Models (LLMs).

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✨ Features

• Visual Workflow Canvas: Drag-and-drop interface for building custom workflows.
• KnowledgeBase Integration: Upload PDF documents for Retrieval-Augmented Generation (RAG).
• LLM Engine: Connect to powerful LLMs like OpenAI's GPT and Google's Gemini.
• Interactive Chat: Test and interact with your built workflows through a chat interface.

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🛠️ Tech Stack

• Frontend: React.js, Vite, React Flow, Tailwind CSS
• Backend: FastAPI (Python)
• Databases:
  • PostgreSQL: For storing metadata (documents, workflows).
  • ChromaDB: For storing vector embeddings.
• AI & Services:
  • Embeddings: OpenAI Embeddings
  • LLMs: OpenAI GPT, Google Gemini
  • Document Parsing: PyMuPDF

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Backend routes

curl -X POST "http://localhost:8000/api/v1/upload" \
  -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@document.pdf"

Query Document (using curl):

curl -X POST "http://localhost:8000/api/v1/query" \
  -H "accept: application/json" \
  -H "Content-Type: application/json" \
  -d '{"query": "What is the main topic of the document?"}'

🏁 Getting Started

Prerequisites

• Node.js (v18 or higher)
• Python (v3.10 or higher)
• Postgres Database Url
• An OpenAI API Key

Installation & Setup

1. Clone the repository:

   git clone [https://github.com/your-username/your-repo-name.git](https://github.com/your-username/your-repo-name.git)
   cd your-repo-name

2. Setup Backend:

   • Navigate to the backend folder: cd backend
   • Create a virtual environment: python -m venv venv and activate it.
   • Install dependencies: pip install -r requirements.txt
   • Copy the example environment file: cp .env.example .env
   • Update .env with your OpenAI API Key and postgres database credentials.

3. Setup Frontend:

   • Navigate to the frontend folder: cd ../frontend

   • Install dependencies: npm install

   • From the root directory, start the PostgreSQL and ChromaDB containers:

   docker-compose up -d

4. Run the Application:

   • Terminal 1 (Backend):

     cd backend
     # Make sure your virtual environment is active
     python main.py

   • Terminal 2 (Frontend):

     cd frontend
     npm run dev

Your application should now be running, with the frontend available at http://localhost:5173 and the backend at http://localhost:8000.

More detailed Code Documentation: https://docs.google.com/document/d/10TlLCBmtMV5ClIkvPf6kxelhiUSHNIKBQ7PbgQ6zEik/edit?usp=sharing