4601c6fca8
- Vision Encoder Service (OpenCLIP ViT-L/14, GPU-accelerated)
- FastAPI app with text/image embedding endpoints (768-dim)
- Docker support with NVIDIA GPU runtime
- Port 8001, health checks, model info API
- Qdrant Vector Database integration
- Port 6333/6334 (HTTP/gRPC)
- Image embeddings storage (768-dim, Cosine distance)
- Auto collection creation
- Vision RAG implementation
- VisionEncoderClient (Python client for API)
- Image Search module (text-to-image, image-to-image)
- Vision RAG routing in DAGI Router (mode: image_search)
- VisionEncoderProvider integration
- Documentation (5000+ lines)
- SYSTEM-INVENTORY.md - Complete system inventory
- VISION-ENCODER-STATUS.md - Service status
- VISION-RAG-IMPLEMENTATION.md - Implementation details
- vision_encoder_deployment_task.md - Deployment checklist
- services/vision-encoder/README.md - Deployment guide
- Updated WARP.md, INFRASTRUCTURE.md, Jupyter Notebook
- Testing
- test-vision-encoder.sh - Smoke tests (6 tests)
- Unit tests for client, image search, routing
- Services: 17 total (added Vision Encoder + Qdrant)
- AI Models: 3 (qwen3:8b, OpenCLIP ViT-L/14, BAAI/bge-m3)
- GPU Services: 2 (Vision Encoder, Ollama)
- VRAM Usage: ~10 GB (concurrent)
Status: Production Ready ✅
53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
import asyncio
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import nats
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import json
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async def main():
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# Connect to NATS
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nc = await nats.connect('nats://localhost:4222')
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print("Connected to NATS")
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# Get JetStream context
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js = nc.jetstream()
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print("Got JetStream context")
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# Create STREAM_RAG
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try:
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stream_config = {
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"name": "STREAM_RAG",
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"description": "Stream for RAG ingestion events",
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"subjects": ["parser.document.parsed", "rag.document.ingested", "rag.document.indexed"],
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"retention": "workqueue",
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"storage": "file",
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"replicas": 3,
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"max_bytes": -1,
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"max_age": 0,
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"max_msgs": -1
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}
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await js.add_stream(
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name="STREAM_RAG",
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subjects=stream_config["subjects"],
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retention=nats.RetentionPolicy.WORK_QUEUE,
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storage=nats.StorageType.FILE,
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replicas=3
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)
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print("STREAM_RAG created successfully")
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# Verify stream exists
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streams = await js.streams_info()
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for stream in streams:
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if stream.config.name == "STREAM_RAG":
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print(f"Verified STREAM_RAG: {stream.config.name}")
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print(f"Subjects: {stream.config.subjects}")
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return
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print("STREAM_RAG created but not verified")
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except Exception as e:
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print(f"Error creating stream: {e}")
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# Close connection
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await nc.close()
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if __name__ == "__main__":
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asyncio.run(main()) |