Implement initial project structure and setup

Dockerfile

@@ -0,0 +1,18 @@
+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.10
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+# Copy requirements first to leverage Docker cache
+COPY --chown=user requirements.txt /app/
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Copy the rest of the application
+COPY --chown=user . /app
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -0,0 +1,15 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from sentence_transformers import SentenceTransformer
+
+app = FastAPI()
+
+model = SentenceTransformer('sentence-transformers/LaBSE')
+
+class EmbedRequest(BaseModel):
+    text: str
+
+@app.post("/vectorize")
+async def embed_text(request: EmbedRequest):
+    return model.encode(request.text)
+

requirements.txt

@@ -0,0 +1,4 @@
+fastapi
+uvicorn[standard]
+pydantic
+sentence-transformers