🚀 LangGraph Blog Writing Agent

An AI-powered Blog Writing Agent built using LangGraph, LangChain, Google Gemini, and Tavily Search. This project demonstrates the evolution of a blog-writing agent from a basic implementation to a research-enhanced, image-capable workflow while also providing a frontend and backend application for generating high-quality blog content.

✨ Features

• 📝 Generate complete blog articles from a topic
• 🔍 Research-powered content generation using Tavily Search
• 🧠 Multi-step agent workflow with LangGraph
• 🎯 Improved prompting techniques for better outputs
• 🖼️ AI-assisted image generation support
• 🌐 Interactive frontend application
• ⚡ Backend API for blog generation
• 📚 Progressive learning notebooks demonstrating agent development

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🏗️ Project Structure

LangGraph-Blog-Writing-Agent/
│
├── bwa_frontend.py
├── bwa_backend.py
│
├── 1_bwa_basic.ipynb
├── 2_bwa_improved_prompting.ipynb
├── 3_bwa_research.ipynb
├── 4_bwa_research_fine_tuned.ipynb
├── 5_bwa_image.ipynb
│
├── tavily_test.ipynb
│
├── ai_unpacked_the_weeks_top_developments_in_funding_research_and_regulation_may_24-31_2026.md
│
├── requirements.txt
├── .gitignore
└── README.md

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📖 Notebook Roadmap

1️⃣ Basic Blog Writing Agent

File: 1_bwa_basic.ipynb

• Introduction to LangGraph
• Basic blog generation workflow
• Single-agent content creation

2️⃣ Improved Prompting

File: 2_bwa_improved_prompting.ipynb

• Advanced prompt engineering
• Better structure and readability
• Enhanced blog quality

3️⃣ Research Agent

File: 3_bwa_research.ipynb

• Integrates external research
• Uses search tools for fact gathering
• Produces more informative content

4️⃣ Fine-Tuned Research Workflow

File: 4_bwa_research_fine_tuned.ipynb

• Improved research pipeline
• Better source utilization
• Higher quality article generation

5️⃣ Image-Enhanced Blog Agent

File: 5_bwa_image.ipynb

• Adds image generation capabilities
• Creates richer blog content
• Demonstrates multimodal workflows

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🛠️ Tech Stack

AI & Agent Frameworks

• LangGraph
• LangChain

LLM

• Google Gemini

Search & Research

• Tavily Search API

Frontend

• Streamlit

Backend

• Python

Utilities

• Python Dotenv
• Requests

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⚙️ Installation

Clone Repository

git clone https://github.com/KA18202005/LangGraph-Blog-Writing-Agent.git
cd LangGraph-Blog-Writing-Agent

Create Virtual Environment

python -m venv venv

Windows

venv\Scripts\activate

Linux/macOS

source venv/bin/activate

Install Dependencies

pip install -r requirements.txt

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🔑 Environment Variables

Create a .env file in the project root:

GOOGLE_API_KEY=your_google_api_key
TAVILY_API_KEY=your_tavily_api_key

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▶️ Running the Application

Start Backend

python bwa_backend.py

Start Frontend

streamlit run bwa_frontend.py

Open the local Streamlit URL displayed in the terminal.

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🔄 Agent Workflow

User Topic
     │
     ▼
Planning Agent
     │
     ▼
Research Agent
     │
     ▼
Content Generation Agent
     │
     ▼
Refinement Agent
     │
     ▼
Image Generation
     │
     ▼
Final Blog Output

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📄 Sample Output

The repository includes an example generated article:

ai_unpacked_the_weeks_top_developments_in_funding_research_and_regulation_may_24-31_2026.md

This demonstrates the quality and structure of the generated blog content.

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🎯 Learning Outcomes

By exploring this project, you'll learn:

• LangGraph fundamentals
• Agent-based workflow design
• Prompt engineering techniques
• Research-Augmented Generation (RAG)
• Search tool integration
• AI content creation pipelines
• Streamlit application development

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🚀 Future Improvements

• Multiple LLM support
• SEO optimization module
• Blog export to PDF/DOCX
• Citation generation
• Multi-language blog generation
• Publishing directly to CMS platforms

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🤝 Contributing

Contributions are welcome.

1. Fork the repository
2. Create a feature branch

git checkout -b feature-name

3. Commit your changes

git commit -m "Add feature"

4. Push to GitHub

git push origin feature-name

5. Open a Pull Request

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⭐ Support

If you found this project helpful:

• ⭐ Star the repository
• 🍴 Fork the repository
• 🚀 Share it with others

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👨‍💻 Author

Kavya Agarwal

GitHub: https://github.com/KA18202005

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Built with ❤️ using LangGraph, LangChain, Gemini, and Tavily Search.