SAGE Applications - Real-world AI applications built on SAGE framework
Project description
SAGE Applications
Real-world AI applications built on the SAGE framework, showcasing end-to-end solutions for various domains.
Overview
isage-apps provides production-ready applications demonstrating SAGE's capabilities:
- Video Intelligence: Multi-model video analysis pipeline with CLIP and MobileNetV3
- Medical Diagnosis: AI-assisted medical image analysis for healthcare
Installation
Basic Installation
pip install isage-apps
Install with Specific Applications
# Video intelligence only
pip install isage-apps[video]
# Medical diagnosis only
pip install isage-apps[medical]
# All applications
pip install isage-apps[all]
Development Installation
cd packages/sage-apps
pip install -e ".[dev]"
๐ Quick Start
# Run video intelligence demo
pip install isage-apps[video]
python -m sage.apps.video.video_intelligence_pipeline --video path/to/video.mp4
# Run medical diagnosis demo
pip install isage-apps[medical]
python -m sage.apps.medical_diagnosis.run_diagnosis
Applications
1. Video Intelligence
Advanced video analysis pipeline combining multiple AI models:
- Frame sampling and preprocessing
- Zero-shot scene understanding (CLIP)
- Object classification (MobileNetV3)
- Temporal anomaly detection
- Sliding-window summarization
- Keyed event aggregation
Quick Start:
pip install isage-apps[video]
python -m sage.apps.video.video_intelligence_pipeline --video path/to/video.mp4
Features:
- Multi-model inference pipeline
- Real-time processing with SAGE operators
- Structured JSON output (timeline, summary, events)
- Console progress monitoring
- Graceful degradation (works offline with cached models)
Documentation: See sage/apps/video/README_intelligence_demo.md
2. Medical Diagnosis
AI-assisted diagnostic system for medical imaging:
- Multi-agent architecture (diagnostic, image analysis, report generation)
- Knowledge-based reasoning
- Structured medical reports
- Training and evaluation tools
Quick Start:
pip install isage-apps[medical]
python -m sage.apps.medical_diagnosis.run_diagnosis
Features:
- Agent-based diagnostic workflow
- Medical knowledge base integration
- Configurable diagnostic criteria
- Report generation
Documentation: See sage/apps/medical_diagnosis/README.md
Package Structure
sage-apps/
โโโ src/sage/apps/
โ โโโ __init__.py
โ โโโ video/ # Video intelligence application
โ โ โโโ video_intelligence_pipeline.py
โ โ โโโ operators/ # SAGE operators for video
โ โ โโโ config/ # Configuration files
โ โ โโโ README_intelligence_demo.md
โ โโโ medical_diagnosis/ # Medical diagnosis application
โ โโโ run_diagnosis.py
โ โโโ agents/ # Diagnostic agents
โ โโโ config/ # Agent configurations
โ โโโ data/ # Medical datasets
โ โโโ README.md
โโโ tests/ # Application tests
Dependencies
Core Framework
isage-common- Common utilitiesisage-kernel- Runtime and operatorsisage-middleware- Services (SageVDB, SageFlow, NeuroMem)isage-libs- Operator libraries
Application-Specific
Video Intelligence:
opencv-python- Video processingtorch- Deep learningtransformers- CLIP and language models
Medical Diagnosis:
pillow- Image processingscikit-learn- ML utilities
Usage Examples
Video Intelligence
from sage.apps.video.video_intelligence_pipeline import main
# Run with custom video
main(["--video", "my_video.mp4", "--max-frames", "100"])
Medical Diagnosis
from sage.apps.medical_diagnosis.run_diagnosis import run_diagnosis
# Run diagnostic pipeline
run_diagnosis(config_path="config/agent_config.yaml")
Development
Running Tests
pytest tests/
Code Quality
# Format code
black src/
# Lint
ruff check src/
# Type checking
mypy src/
CI/CD Notes
Video Intelligence:
- Requires HuggingFace model downloads (~170MB)
- Tagged with
@test:skipin CI due to network restrictions - Test locally with:
python -m sage.apps.video.video_intelligence_pipeline
Medical Diagnosis:
- Works in CI (uses local data)
- Test with:
pytest tests/test_medical_diagnosis.py
Contributing
See CONTRIBUTING.md for guidelines.
License
MIT License - see LICENSE for details.
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