Create app.py

app.py

@@ -0,0 +1,25 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from sentence_transformers import SentenceTransformer
+import uvicorn, os
+
+MODEL_ID = os.getenv("EMB_MODEL", "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
+model = SentenceTransformer(MODEL_ID)
+app = FastAPI()
+
+class Req(BaseModel):
+    texts: list[str]
+
+@app.get("/health")
+def health():
+    return {"ok": True}
+
+@app.post("/generate")
+def emb(r: Req):
+    if not r.texts:
+        return {"vectors": []}
+    vecs = model.encode(r.texts, convert_to_numpy=True).tolist()
+    return {"vectors": vecs}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)