README.md

metadata

title: Blog-Writing-Agent
emoji: 🎓
colorFrom: blue
colorTo: green
sdk: docker
app_file: main.py
pinned: false
short_description: This is the Agentic Blog Writing Agent

✍️ Bloggig - AI Blog Writing Agent

Bloggig is a sophisticated AI-powered agent designed to transform a single topic into a professional, research-backed blog post complete with AI-generated visuals. Built with LangGraph and FastAPI, it orchestrates a complex pipeline of research, planning, writing, and image generation to deliver high-quality content in real-time.

🚀 Key Features

• 🌐 Autonomous Research: Integrates with Tavily AI to perform deep web searches and gather factual evidence.
• 📋 Intelligent Planning: Generates structured blog plans tailored to specific audiences and tones.
• ✍️ Parallel Writing Pipeline: Uses a worker-reducer architecture to generate multiple blog sections simultaneously for maximum efficiency.
• 🎨 AI-Generated Visuals: Automatically plans and generates relevant images using Stable Diffusion XL (via Hugging Face Inference).
• 💻 Modern ChatGPT-like UI: A sleek, dark-themed dashboard featuring:
  • Real-time Streaming: Watch the AI's "thought process" and pipeline progression via WebSockets.
  • Markdown Rendering: Beautifully formatted blog previews with syntax highlighting.
  • History Management: Browse, view, and manage previously generated blogs.
• 📦 Export & Management:
  • Download as ZIP: Get the full markdown file along with all generated image assets.
  • Clean Deletion: Permanent removal of blogs and their associated images with a single click.

🛠️ Tech Stack

• Backend: FastAPI, LangGraph, Pydantic, Uvicorn.
• AI Models: Bedrock Converse API (LLM), Stable Diffusion XL (Images).
• Search Engine: Tavily AI.
• Frontend: Semantic HTML5, Vanilla CSS (Glassmorphism), Marked.js, Highlight.js.
• Tools: UV (Python package manager), Git.

⚙️ Installation & Setup

1. Clone the Repository

git clone https://github.com/VashuTheGreat/Blog-Writing-Agent.git
cd Blog-Writing-Agent

2. Install Dependencies

Using uv (recommended):

uv sync

Or using pip:

pip install -r requirements.txt

3. Environment Variables

Create a .env file in the root directory and add your credentials:

HF_TOKEN=your_huggingface_token
TAVILY_API_KEY=your_tavily_api_key
AWS_ACCESS_KEY_ID=your_aws_key
AWS_SECRET_ACCESS_KEY=your_aws_secret
AWS_REGION=your_aws_region

🏃 Running the Application

Start the FastAPI server:

python Application/app.py

The application will be available at http://localhost:8000.

📂 Project Structure

• Application/: Contains the web server (app.py) and the frontend (index.html).
• src/graph/: Core LangGraph implementation (nodes, edges, and logic).
• src/components/: External integrations (Tavily search, Image generation).
• src/models/: Pydantic models for state management and structured output.
• results/: Directory where generated markdown blogs are saved.
• images/: Directory where generated images are stored.
• src/utils/: Utility functions (e.g., blog deletion logic).

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.