fix port

README.md

@@ -8,3 +8,6 @@ pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Space URL
+https://ids75912-ctaianimalclassifierfastapi.hf.space/docs

main.py

@@ -25,7 +25,7 @@ import traceback
 import logging
 from tensorflow import keras
 
-app = FastAPI(title="1.3 - AI Model Deployment")
+app = FastAPI(title="1.3 - AI Model Deployment - HF Hub + FastAPI",)
 ''' browser: http://localhost:8000/docs'''
 
 from fastapi.middleware.cors import CORSMiddleware
@@ -67,40 +67,6 @@ hf_hub_download(repo_id, filename="model.weights.h5", repo_type="model", local_d
     # 2) load it
 model = tf.keras.models.load_model(local_model_dir)
 logging.info(f"Model loaded successfully from {local_model_dir}")
-# except Exception as e:
-#     # Primary download attempt failed -> try streamed fallback which writes directly
-#     # into local_model_dir (avoids internal temp/move when those operations are blocked).
-#     primary_err = e
-#     logging.error("Primary hf_hub_download failed, attempting streamed fallback: %s", e)
-#     try:
-#         for filename in ("config.json", "metadata.json", "model.weights.h5"):
-#             url = hf_hub_url(repo_id=repo_id, filename=filename, repo_type='model')
-#             logging.info(f"Streaming {filename} from {url} into {local_model_dir}")
-#             resp = requests.get(url, stream=True, timeout=60)
-#             resp.raise_for_status()
-#             # write to a temp file inside the target dir then move atomically
-#             with tempfile.NamedTemporaryFile(dir=local_model_dir, delete=False) as tmpf:
-#                 for chunk in resp.iter_content(chunk_size=8192):
-#                     if chunk:
-#                         tmpf.write(chunk)
-#                 tmp_path = tmpf.name
-#             final_path = os.path.join(local_model_dir, filename)
-#             try:
-#                 shutil.move(tmp_path, final_path)
-#             except Exception:
-#                 # if atomic move fails, try copy+remove
-#                 shutil.copy(tmp_path, final_path)
-#                 os.remove(tmp_path)
-
-#         # After streamed download, try loading
-#         model = tf.keras.models.load_model(local_model_dir)
-#         logging.info(f"Model loaded successfully from {local_model_dir} after streamed fallback")
-#     except Exception as e2:
-#         model_load_error = f"primary: {primary_err}; fallback: {e2}"
-#         tb = traceback.format_exc()
-#         logging.error("Streamed fallback failed: %s", e2)
-#         logging.error(tb)
-#         model = None
 
 
 @app.post('/upload/image')
@@ -123,13 +89,7 @@ async def uploadImage(img: UploadFile = File(...)):
 @app.get("/")
 def read_root() -> Dict[str, Any]:
     """Root endpoint."""
-    return {"message": "Hello from FastAPI in "}
-
-
-# @app.post("/echo")
-# async def echo(payload: Dict[str, Any]) -> Dict[str, Any]:
-#     """Echo back the received JSON payload."""
-#     return {"echo": payload}
+    return {"message": "Hello from FastAPI in 1.3 - AI Model Deployment - HF Hub + FastAPI"}
 
 
 @app.get("/version")
@@ -155,4 +115,4 @@ if __name__ == "__main__":
 	# Run with: conda run -n gradio uvicorn main:app --reload
 	import uvicorn
 
-	uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
+	uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True) # 7860 instead of 8000