A comprehensive research project focused on exploring and documenting the latest developments in AI technology, with particular emphasis on Large Language Models (LLMs) and their applications. This project utilizes CrewAI for orchestrating AI agents to gather, analyze, and synthesize information about cutting-edge AI advancements.
- Automated AI research gathering and analysis
- Structured documentation of AI developments
- Integration with multiple AI data sources
- Comprehensive report generation
- Version-controlled research findings
- Collaborative AI agent interactions
- Python
- CrewAI Framework
- LangChain
- Markdown
- Git/GitHub
- Python-dotenv
- AI agent orchestration and management
- Research automation techniques
- Technical documentation best practices
- Version control for research projects
- Data synthesis and analysis
- Collaborative AI systems development
- Visual Studio Code
- Git and GitHub
- CrewAI framework
- Markdown documentation
- Python libraries for AI research
- Environment management tools
Project structure and dependency configuration using requirements.txt and environment variables.
Details of the AI research gathering and analysis system.
How the project organizes and maintains research findings.
Example of generated research reports and findings.
- Clone the repository
- Install dependencies:
pip install -r requirements.txt - Configure environment variables
- Run the research system:
python main.py