AI Agents Hub

A powerful multi-agent system built with Streamlit that provides three specialized AI agents for different tasks: Knowledge Processing, Code Analysis, and Code Review.

Features

1. Knowledge Agent

• Processes and answers questions based on provided PDF documents
• Uses advanced embeddings for accurate information retrieval
• Supports context-aware responses using the deepseek-r1 model

2. Code Analysis Agent

• Analyzes code quality and structure
• Provides detailed reports on:
  • Code maintainability
  • Performance considerations
  • Best practices
  • Potential improvements

3. Code Review Agent

• Performs comprehensive code reviews
• Identifies:
  • Code quality issues
  • Potential bugs
  • Security concerns
  • Performance bottlenecks
• Suggests specific improvements and fixes

Prerequisites

• Python 3.8+
• Ollama with the following models:
  • deepseek-r1
  • nomic-embed-text

Installation

1. Clone the repository:

git clone <repository-url>
cd <repository-name>

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

# Windows PowerShell
$env:OPENAI_BASE_URL="your-openai-base-url"
$env:OPENAI_API_KEY="your-openai-api-key"

Usage

1. Start the application:

streamlit run deepseek-rag-agents-ui.py

2. Select an agent from the sidebar:

   • Knowledge Agent: For querying PDF documents
   • Code Analysis: For analyzing code quality
   • Code Review: For detailed code reviews

3. Based on the selected agent:

   • For Knowledge Agent: Type your question in the chat input
   • For Code Analysis/Review: Paste your code in the text area and click the respective button

Project Structure

.
├── README.md
├── requirements.txt
├── deepseek-rag-agents-ui.py    # Main Streamlit UI
├── knowledge_agent.py           # Knowledge processing agent
├── code_analysis_agent.py       # Code analysis agent
├── code_review_agent.py         # Code review agent
├── code_analysis_docs.md        # Documentation for code analysis
└── code_review_docs.md          # Documentation for code review

Configuration

Each agent can be configured through their respective files:

• knowledge_agent.py: Configure PDF processing and knowledge base settings
• code_analysis_agent.py: Customize code analysis parameters
• code_review_agent.py: Adjust code review preferences

Error Handling

The application includes comprehensive error handling:

• Graceful handling of initialization errors
• Clear error messages for users
• Proper resource cleanup
• Timeout handling for long-running operations

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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

Acknowledgments

• Built with Streamlit
• Uses Ollama for AI models
• Powered by the praisonaiagents package