Initial model sever setup

Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY ./app.py /code/app.py
+
+EXPOSE 7860
+
+CMD ["uvicorn","app:app","--host","0.0.0.0","--port","7860"]

app.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from sentence_transformers import SentenceTransformer
+import logging
+
+logging.basicConfig(level=logging.INFO)
+logger=logging.getLogger(__name__)
+
+logger.info("Server Starting")
+try:
+    logger.info("Loading model")
+    model=SentenceTransformer("Sid-the-sloth/leetcode_unixcoder_final")
+    logger.info("Model Loaded")
+except:
+    logger.error("Failed to load Model")
+    model=None
+
+app=FastAPI()
+
+#Req and Response Pydantic models
+class EmbedRequest(BaseModel):
+    text : str
+
+class EmbedResponse(BaseModel):
+    embedding: list[float]
+
+@app.get("/")
+def root_status():
+    return {"status":"ok","model":model is not None}
+
+@app.post("/embed",response_model=EmbedResponse)
+def get_embedding(request: EmbedRequest):
+    if model is None:
+        HTTPException(status_code=503,detail="Model could not be loaded")
+    try:
+        embedding=model.encode(request.text).tolist()
+        return EmbedResponse(embedding=embedding)
+    except Exception as e:
+        logger.error("Error during embedding generation %s",e)
+        return HTTPException(status_code=500,detail="Error generating embeddings")

requirements.txt

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+fastapi==0.116.1
+uvicorn==0.35.0
+sentence-transformers==5.1.0
+torch==2.8.0
+python-dotenv==1.1.1
+pydantic