| from fastapi import FastAPI |
| from pydantic import BaseModel |
| from sentence_transformers import SentenceTransformer |
| import uvicorn |
|
|
| app = FastAPI() |
| model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2") |
|
|
| class EmbedRequest(BaseModel): |
| inputs: str | list[str] |
|
|
| @app.post("/embed") |
| def embed(req: EmbedRequest): |
| texts = req.inputs if isinstance(req.inputs, list) else [req.inputs] |
| embeddings = model.encode(texts, normalize_embeddings=True) |
| return embeddings.tolist() |
|
|
| @app.get("/health") |
| def health(): |
| return {"status": "ok", "model": "all-MiniLM-L6-v2"} |
|
|
| if __name__ == "__main__": |
| uvicorn.run(app, host="0.0.0.0", port=7860) |
