51 lines
1.9 KiB
Markdown
51 lines
1.9 KiB
Markdown
# AI Agent Resources
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This directory contains resources specifically designed to help AI agents understand and work with the USDA Vision Camera System.
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## Directory Structure
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### `/guides/`
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Contains comprehensive guides for AI agents:
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- `AI_AGENT_INSTRUCTIONS.md` - Specific instructions for AI agents working with this system
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- `AI_INTEGRATION_GUIDE.md` - Guide for integrating AI capabilities with the camera system
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### `/examples/`
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Contains practical examples and demonstrations:
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- `demos/` - Python demo scripts showing various system capabilities
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- `notebooks/` - Jupyter notebooks with interactive examples and tests
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### `/references/`
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Contains API references and technical specifications:
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- `api-endpoints.http` - HTTP API endpoint examples
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- `api-tests.http` - API testing examples
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- `streaming-api.http` - Streaming API examples
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- `camera-api.types.ts` - TypeScript type definitions for the camera API
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## Key Learning Resources
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1. **System Architecture**: Review the main system structure in `/usda_vision_system/`
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2. **Configuration**: Study `config.json` for system configuration options
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3. **API Documentation**: Check `/docs/api/` for API specifications
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4. **Feature Guides**: Review `/docs/features/` for feature-specific documentation
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5. **Test Examples**: Examine `/tests/` for comprehensive test coverage
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## Quick Start for AI Agents
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1. Read `guides/AI_AGENT_INSTRUCTIONS.md` first
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2. Review the demo scripts in `examples/demos/`
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3. Study the API references in `references/`
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4. Examine test files to understand expected behavior
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5. Check configuration options in the root `config.json`
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## System Overview
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The USDA Vision Camera System is a multi-camera monitoring and recording system with:
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- Real-time camera streaming
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- MQTT-based automation
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- Auto-recording capabilities
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- RESTful API interface
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- Web-based camera preview
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- Comprehensive logging and monitoring
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For detailed system documentation, see the `/docs/` directory.
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