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Dockerfile

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+
+FROM python:3.11
+
+WORKDIR /app
+
+COPY ./requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD ["python", "server.py"]

requirements.txt

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+uvloop
+sentence_transformers
+litserve
+--extra-index-url https://download.pytorch.org/whl/cpu 

server.py

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+from sentence_transformers import SentenceTransformer
+import litserve as ls
+
+class EmbeddingAPI(ls.LitAPI):
+    def setup(self, device):
+        self.instruction = "Represent this sentence for searching relevant passages: "
+        self.model = SentenceTransformer('BAAI/bge-large-en-v1.5', device=device)
+
+    def decode_request(self, request):
+        return request["input"]
+
+    def predict(self, query):
+        return self.model.encode([self.instruction + query], normalize_embeddings=True)
+
+    def encode_response(self, output):
+        return {"embedding": output[0].tolist()}
+
+if __name__ == "__main__":
+    api = EmbeddingAPI()
+    server = ls.LitServer(api, devices="cpu")
+    server.run(port=7860)