openai-code/ARCH.md

An unofficial proxy layer that lets you use Anthropic Claude Code with any OpenAI API backend.

# Architecture of the Vector Database Implementation

## Overview
The vector database is designed to efficiently store, retrieve, and manage embeddings of documents. It leverages OpenAI's embedding models to create vector representations of text, enabling semantic search and similarity comparisons. This architecture supports scalability and performance optimization for large datasets.

## Components

### 1. **Core Functions**
- **Embedding Creation**: Utilizes OpenAI's API to generate embeddings from text input.
- **Storage Management**: Handles the storage and retrieval of embeddings from disk, ensuring data persistence.
- **Search Functionality**: Implements cosine similarity to find the closest embeddings to a given query.

### 2. **Data Structure**
The main data structure used is an array of documents, where each document is represented as an object containing:
- `path`: The file path of the document.
- `embedding`: The vector representation of the document.
- `hash`: A hash of the document's content for integrity checks.

### 3. **Key Algorithms**
- **Matrix Multiplication**: Optimized for performance using loop unrolling techniques to compute dot products between vectors.
- **Normalization**: Ensures embeddings are unit vectors for accurate cosine similarity calculations.

### 4. **File Operations**
- **Load/Store**: Functions to load embeddings from disk and store them back, using JSON format for serialization.
- **Indexing**: Automatically indexes new documents and updates existing ones based on changes in their content.

### 5. **Error Handling**
Robust error handling is implemented to manage API failures, file read/write errors, and data integrity issues.

## Conclusion
This architecture provides a scalable and efficient solution for managing vector embeddings, enabling advanced search capabilities and integration with various applications. Future improvements may include enhanced error handling and support for additional data formats.