Update app.py

app.py

@@ -1,34 +1,44 @@
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from sentence_transformers import SentenceTransformer
-import os
-
-# Initialize FastAPI
-app = FastAPI(title="Davidic Sermon Embeddings API")
-
-# Load model at startup
-# We use all-MiniLM-L6-v2 which is small and fast on CPU
-print("Loading model...")
-model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
-print("Model loaded.")
-
-class EmbedRequest(BaseModel):
-    text: str
-
-@app.get("/")
-def health_check():
-    return {"status": "running", "model": "all-MiniLM-L6-v2"}
-
-@app.post("/embed")
-def embed(request: EmbedRequest):
-    try:
-        # Generate embedding
-        # tolist() converts numpy array to standard python list
-        embedding = model.encode(request.text).tolist()
-        return embedding
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from sentence_transformers import SentenceTransformer
+import os
+
+# Initialize FastAPI
+app = FastAPI(title="Davidic Sermon Embeddings API")
+
+# Add CORS Middleware to allow requests from Vercel
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Allows all origins
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Load model at startup
+# We use all-MiniLM-L6-v2 which is small and fast on CPU
+print("Loading model...")
+model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+print("Model loaded.")
+
+class EmbedRequest(BaseModel):
+    text: str
+
+@app.get("/")
+def health_check():
+    return {"status": "running", "model": "all-MiniLM-L6-v2"}
+
+@app.post("/embed")
+def embed(request: EmbedRequest):
+    try:
+        # Generate embedding
+        # tolist() converts numpy array to standard python list
+        embedding = model.encode(request.text).tolist()
+        return embedding
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)