This is a submission for the Open Source AI Challenge with pgai and Ollama
What I Built
Code Review Assistant
Code Review Assistant is an AI-powered tool that helps developers improve their code quality through automated code analysis, similarity checking, and best practice recommendations. The application leverages PostgreSQL's AI capabilities and open-source models to provide intelligent code review suggestions.
- Code storage in PostgreSQL with pgvector extension
- Code embeddings generation using Ollama's CodeLlama
- Similarity search using vector comparison
- Code analysis and suggestions using CodeLlama
- API endpoint for code review requests
Demo
Code Review Assistant
What I Built
Code Review Assistant is an AI-powered tool that helps developers improve their code quality through automated code analysis, similarity checking, and best practice recommendations. The application leverages PostgreSQL's AI capabilities and open-source models to provide intelligent code review suggestions.
Key Features
- 🔍 Automated code analysis using CodeLlama
- 💡 Smart suggestions for code improvements
- 🔄 Similar code pattern detection
- 📝 Automatic code documentation generation
- 🗄️ Efficient vector storage and similarity search
- 🚀 Real-time analysis and feedback
Tools Used
PostgreSQL Extensions
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pgvector
- Used for storing and querying code embeddings
- Implements efficient similarity search using vector operations
- Powers the similar code pattern detection feature
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pgvectorscale
- Enhances vector search performance with IVFFlat indexing
- Optimizes query performance for large code repositories
- Enables efficient scaling of the vector database
-
pgai
- Integrates AI capabilities directly within PostgreSQL
- Facilitates real-time code analysis
- Enhances vector operations performance
-
pgai Vectorizer
- Generates embeddings for code…
Tools Used
PostgreSQL Extensions
-
pgvector
- Used for storing and querying code embeddings
- Implements efficient similarity search using vector operations
- Powers the similar code pattern detection feature
-
pgvectorscale
- Enhances vector search performance with IVFFlat indexing
- Optimizes query performance for large code repositories
- Enables efficient scaling of the vector database
-
pgai
- Integrates AI capabilities directly within PostgreSQL
- Facilitates real-time code analysis
- Enhances vector operations performance
-
pgai Vectorizer
- Generates embeddings for code snippets
- Provides efficient vector representation of code
- Enables semantic similarity comparison
Other Tools
-
Node.js & Express: Backend server implementation
-
Ollama: Open-source model hosting and inference
-
CodeLlama: Code analysis and suggestion generation
-
Docker: Containerization (optional)
Prize Category Qualification
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Open-source Models from Ollama ✅
- Utilizes CodeLlama through Ollama for code analysis
- Implements embedding generation using open-source models
- Leverages Ollama's API for real-time inference
-
Vectorizer Vibe ✅
- Implements pgai Vectorizer for efficient embedding creation
- Uses vectorizer for semantic code analysis
- Optimizes embedding storage and retrieval
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All the Extensions! ✅
- Implements all three PostgreSQL extensions:
- pgvector for vector operations
- pgvectorscale for performance optimization
- pgai for AI integration
Developer Experience and Final Thoughts
Building Experience
- Successfully integrated multiple PostgreSQL extensions
- Leveraged open-source models for code analysis
- Created an efficient vector-based similarity search system
- Implemented real-time code analysis and suggestion generation
Technical Achievements
- Efficient vector storage and retrieval system
- Scalable architecture for large code repositories
- Real-time code analysis and suggestion generation
- Seamless integration of multiple AI capabilities
Future Improvements
- Add support for more programming languages
- Implement batch processing for large codebases
- Add user authentication and project management
- Enhance documentation generation capabilities
