usda-vision/camera-management-api/ai_agent

AI Agent Resources

This directory contains resources specifically designed to help AI agents understand and work with the USDA Vision Camera System.

Directory Structure

/guides/

Contains comprehensive guides for AI agents:

• AI_AGENT_INSTRUCTIONS.md - Specific instructions for AI agents working with this system
• AI_INTEGRATION_GUIDE.md - Guide for integrating AI capabilities with the camera system

/examples/

Contains practical examples and demonstrations:

• demos/ - Python demo scripts showing various system capabilities
• notebooks/ - Jupyter notebooks with interactive examples and tests

/references/

Contains API references and technical specifications:

• api-endpoints.http - HTTP API endpoint examples
• api-tests.http - API testing examples
• streaming-api.http - Streaming API examples
• camera-api.types.ts - TypeScript type definitions for the camera API

Key Learning Resources

1. System Architecture: Review the main system structure in /usda_vision_system/
2. Configuration: Study config.json for system configuration options
3. API Documentation: Check /docs/api/ for API specifications
4. Feature Guides: Review /docs/features/ for feature-specific documentation
5. Test Examples: Examine /tests/ for comprehensive test coverage

Quick Start for AI Agents

1. Read guides/AI_AGENT_INSTRUCTIONS.md first
2. Review the demo scripts in examples/demos/
3. Study the API references in references/
4. Examine test files to understand expected behavior
5. Check configuration options in the root config.json

System Overview

The USDA Vision Camera System is a multi-camera monitoring and recording system with:

• Real-time camera streaming
• MQTT-based automation
• Auto-recording capabilities
• RESTful API interface
• Web-based camera preview
• Comprehensive logging and monitoring

For detailed system documentation, see the /docs/ directory.