setup required deps and create a route for embedding text

Dockerfile

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+FROM python:3.12-slim
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade pip
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from sentence_transformers import SentenceTransformer
+
+app = FastAPI()
+model = SentenceTransformer("mabosaimi/bge-m3-text2tables")
+
+
+class Query(BaseModel):
+    query: str
+
+
+@app.post("/embed")
+async def embed_query(data: Query):
+    embedding = model.encode(data.query)
+    return {"embedding": embedding.tolist()}

requirements.txt

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+fastapi==0.95.2
+uvicorn[standard]==0.23.1
+sentence-transformers==5.1.0
+transformers==4.56.1
+torch==2.8.0
+accelerate==1.10.1
+datasets==4.0.0
+tokenizers==0.22.0