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| from sentence_transformers import SentenceTransformer | |
| import litserve as ls | |
| from fastapi import Depends, HTTPException | |
| from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer | |
| import os | |
| class EmbeddingAPI(ls.LitAPI): | |
| def setup(self, device): | |
| self.model = SentenceTransformer( | |
| 'GokulRajaR/embeddinggemma-300m-qat-q8_0-unquantized', | |
| device=device, | |
| trust_remote_code=True, | |
| token=os.getenv("HF_TOKEN") | |
| ) | |
| def decode_request(self, request): | |
| return request | |
| def predict(self, query): | |
| return self.model.encode_query(query) | |
| def encode_response(self, output): | |
| return output.tolist() | |
| def authorize(self, auth: HTTPAuthorizationCredentials = Depends(HTTPBearer())): | |
| if auth.scheme != "Bearer" or auth.credentials != os.getenv("auth_token"): | |
| raise HTTPException(status_code=401, detail="Bad token") | |
| if __name__ == "__main__": | |
| api = EmbeddingAPI() | |
| server = ls.LitServer(api, devices="cpu", accelerator="cpu") | |
| server.run(port=7860) | |