110 lines
2.6 KiB
Markdown
110 lines
2.6 KiB
Markdown
# RPA Vision V3 - Status Update
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**Date**: 22 Novembre 2024
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## 🎯 Current Status
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✅ **Phase 2 - CLIP Embedders: COMPLÉTÉ**
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## ✅ Completed
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### Phase 1: Data Models
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- RawSession, ScreenState, UIElement, StateEmbedding, WorkflowGraph
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- JSON serialization/deserialization
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- Unit tests
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### Phase 2: Embedding System
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- FusionEngine (multi-modal fusion)
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- FAISSManager (vector search)
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- Similarity calculations
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- **CLIP Embedders (ViT-B-32, 512D)** ✅
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## ⏳ In Progress
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**Task 2.9**: Integrate CLIP into StateEmbeddingBuilder
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## 🚀 Quick Test
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```bash
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# Test CLIP embedders
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bash rpa_vision_v3/test_clip.sh
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# Expected output:
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# ✅ Dimension: 512
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# ✅ Similarity Login/SignIn: 0.899
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# ✅ Test CLIP réussi !
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```
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## 📊 Metrics
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- **Model**: OpenCLIP ViT-B-32
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- **Dimension**: 512D
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- **Text embedding**: <10ms
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- **Image embedding**: ~50ms (CPU)
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- **Model size**: ~350MB
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## 📁 Key Files
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```
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rpa_vision_v3/
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├── PHASE2_CLIP_COMPLETE.md # Phase 2 summary
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├── SESSION_22NOV_CLIP.md # Session notes
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├── NEXT_SESSION.md # Next steps guide
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├── test_clip.sh # Quick test script
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├── core/embedding/
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│ ├── clip_embedder.py # CLIP embedder ✅
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│ ├── fusion_engine.py # Multi-modal fusion ✅
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│ ├── faiss_manager.py # Vector search ✅
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│ └── state_embedding_builder.py # To integrate ⏳
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└── examples/
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└── test_clip_simple.py # CLIP test ✅
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```
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## 🎯 Next Steps
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1. **Task 2.9**: Integrate CLIP into StateEmbeddingBuilder
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- Replace random vectors with real CLIP embeddings
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- Test with real ScreenStates
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- Validate similarity metrics
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2. **Phase 3**: UI Detection
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- VLM integration
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- Semantic classification
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- Dual embeddings
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3. **Phase 4**: Workflow Graphs
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- Graph construction
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- State matching
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- Pattern detection
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## 📚 Documentation
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- [Full Status](rpa_vision_v3/PHASE2_CLIP_COMPLETE.md)
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- [Session Notes](rpa_vision_v3/SESSION_22NOV_CLIP.md)
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- [Next Session Guide](rpa_vision_v3/NEXT_SESSION.md)
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- [Task List](rpa_vision_v3/docs/specs/tasks.md)
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- [README](rpa_vision_v3/README.md)
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## 🔧 Environment
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```bash
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# Use geniusia2 venv (has all dependencies)
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source geniusia2/venv/bin/activate
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# Or install in new venv
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cd rpa_vision_v3
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bash install_dependencies.sh
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```
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## ✨ Highlights
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- ✅ CLIP embedders fully functional
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- ✅ Text similarity: 0.899 for similar terms
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- ✅ Image-text similarity working
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- ✅ Batch processing supported
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- ✅ All vectors normalized (L2 norm = 1.0)
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---
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**Ready to continue?** See [NEXT_SESSION.md](rpa_vision_v3/NEXT_SESSION.md) for detailed next steps.
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