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0e05c824e9
Add a complete example demonstrating dirty workers with sentence-transformers for text embeddings via FastAPI: - EmbeddingApp DirtyApp that loads and manages the ML model - FastAPI endpoints for /embed and /health - Docker and docker-compose configuration - Integration tests with numpy similarity checks - GitHub Actions CI workflow
30 lines
617 B
Python
30 lines
617 B
Python
from fastapi import FastAPI
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from pydantic import BaseModel
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from gunicorn.dirty.client import get_dirty_client
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app = FastAPI()
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class EmbedRequest(BaseModel):
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texts: list[str]
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class EmbedResponse(BaseModel):
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embeddings: list[list[float]]
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@app.post("/embed", response_model=EmbedResponse)
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async def embed(request: EmbedRequest):
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client = get_dirty_client()
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result = client.execute(
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"embedding_service.embedding_app:EmbeddingApp",
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"embed",
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request.texts
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)
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return EmbedResponse(embeddings=result)
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@app.get("/health")
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async def health():
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return {"status": "ok"}
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