Update app.py

app.py

@@ -12,16 +12,13 @@ from huggingface_hub import login
 
 # --- 1. Configuration and Authentication ---
 
-# IMPORTANT: Replace with your Google Cloud Project ID
-GCP_PROJECT_ID = "gen-lang-client-0193353123" # Make sure this is replaced!
-GCP_LOCATION = "us-central1"
-MODEL_ID = "veo-3.0-generate-preview"
-API_ENDPOINT = f"{GCP_LOCATION}-aiplatform.googleapis.com"
-PREDICT_URL = f"https://{API_ENDPOINT}/v1/projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/publishers/google/models/{MODEL_ID}:predictLongRunning"
-FETCH_URL = f"https://{API_ENDPOINT}/v1/projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/publishers/google/models/{MODEL_ID}:fetchPredictOperation"
+# <<< START: CODE UPDATE >>>
+# Load configuration from Hugging Face Secrets instead of hardcoding.
+GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID")
+GCP_LOCATION = os.environ.get("GCP_LOCATION")
+# <<< END: CODE UPDATE >>>
 
-
-# --- Authentication Block ---
+# --- Authentication and Sanity Checks Block ---
 
 # Part A: Hugging Face Hub Authentication
 hf_token = os.environ.get("HF_TOKEN")
@@ -33,26 +30,42 @@ else:
 
 # Part B: Google Cloud Authentication
 creds_json_str = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS_JSON")
-if not creds_json_str:
-    print("FATAL: 'GOOGLE_APPLICATION_CREDENTIALS_JSON' secret not found. App cannot authenticate with Google Cloud.")
+
+# Check if all necessary secrets are loaded
+if not all([GCP_PROJECT_ID, GCP_LOCATION, creds_json_str]):
+    # This block runs if any of the crucial secrets are missing.
+    missing_secrets = []
+    if not GCP_PROJECT_ID: missing_secrets.append("GCP_PROJECT_ID")
+    if not GCP_LOCATION: missing_secrets.append("GCP_LOCATION")
+    if not creds_json_str: missing_secrets.append("GOOGLE_APPLICATION_CREDENTIALS_JSON")
+    
+    error_message = f"FATAL: The following required secrets are missing: {', '.join(missing_secrets)}. Please set them in the Space settings."
+    print(error_message)
+    # Define a dummy function to show a clear error in the UI.
     def generate_video(prompt):
-        raise gr.Error("Authentication failed. Server is missing Google Cloud credentials. Please check the Hugging Face Space secrets.")
+        raise gr.Error(error_message)
 else:
+    # This block runs only if all secrets are present.
+    print("All required secrets (GCP Project, Location, Credentials, HF Token) are loaded.")
+    
+    # Construct API URLs now that we have the project and location
+    MODEL_ID = "veo-3.0-generate-preview"
+    API_ENDPOINT = f"{GCP_LOCATION}-aiplatform.googleapis.com"
+    PREDICT_URL = f"https://{API_ENDPOINT}/v1/projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/publishers/google/models/{MODEL_ID}:predictLongRunning"
+    FETCH_URL = f"https://{API_ENDPOINT}/v1/projects/{GCP_PROJECT_ID}/locations/{GCP_LOCATION}/publishers/google/models/{MODEL_ID}:fetchPredictOperation"
+
     with open("gcp_creds.json", "w") as f:
         f.write(creds_json_str)
     
     SCOPES = ["https://www.googleapis.com/auth/cloud-platform"]
     credentials, _ = google.auth.load_credentials_from_file("gcp_creds.json", scopes=SCOPES)
-    print("GCP credentials loaded successfully.")
-
 
     def get_access_token():
         auth_req = google.auth.transport.requests.Request()
         credentials.refresh(auth_req)
         return credentials.token
 
-    # --- 2. Core Video Generation Logic (WITH FINAL FIX) ---
-
+    # --- 2. Core Video Generation Logic ---
     def generate_video(prompt: str):
         if not prompt:
             raise gr.Error("Prompt cannot be empty.")
@@ -65,7 +78,6 @@ else:
                 "Authorization": f"Bearer {access_token}",
                 "Content-Type": "application/json",
             }
-
             payload = {
                 "instances": [{"prompt": prompt}],
                 "parameters": {
@@ -74,92 +86,55 @@ else:
                     "includeRaiReason": True, "generateAudio": True,
                 }
             }
-            
             response = requests.post(PREDICT_URL, headers=headers, json=payload)
             response.raise_for_status() 
-
             operation_name = response.json()["name"]
             print(f"Successfully submitted job. Operation Name: {operation_name}")
 
             MAX_POLL_ATTEMPTS = 60 
             for i in range(MAX_POLL_ATTEMPTS):
-                status_message = f"Status: Job submitted. Polling for result (Attempt {i+1}/{MAX_POLL_ATTEMPTS})... Please wait."
-                yield status_message, None
-
+                yield f"Status: Polling for result (Attempt {i+1}/{MAX_POLL_ATTEMPTS})...", None
                 access_token = get_access_token()
                 headers["Authorization"] = f"Bearer {access_token}"
-                
                 fetch_payload = {"operationName": operation_name}
                 poll_response = requests.post(FETCH_URL, headers=headers, json=fetch_payload)
                 poll_response.raise_for_status()
-                
                 poll_result = poll_response.json()
 
                 if poll_result.get("done"):
                     print("Job finished successfully.")
-                    print(f"Full successful response payload: {json.dumps(poll_result, indent=2)}")
-
                     response_data = poll_result.get("response", {})
-                    
-                    # <<< FIX: Changed "predictions" to "videos" to match the actual API response >>>
                     if "videos" in response_data and response_data["videos"]:
                         video_base64 = response_data["videos"][0]["bytesBase64Encoded"]
                         video_bytes = base64.b64decode(video_base64)
-                        
                         temp_video_path = "generated_video.mp4"
                         with open(temp_video_path, "wb") as f:
                             f.write(video_bytes)
-                        
-                        yield "Status: Done! Video generated successfully.", temp_video_path
+                        yield "Status: Done! Video generated.", temp_video_path
                         return
                     else:
-                        error_message = "Video generation finished, but the content was blocked by safety filters or another issue prevented video creation."
-                        print(f"ERROR: {error_message}")
-                        raise gr.Error(error_message)
-                
+                        raise gr.Error("Video generation finished, but content was blocked or another issue occurred.")
                 time.sleep(10)
-
-            raise gr.Error("Operation timed out after several minutes.")
-
-        except requests.exceptions.HTTPError as e:
-            print(f"HTTP Error: {e.response.text}")
-            raise gr.Error(f"API Error: {e.response.status_code}. Details: {e.response.text}")
+            raise gr.Error("Operation timed out.")
         except Exception as e:
-            print(f"An error occurred in the generation process: {e}")
+            print(f"An error occurred: {e}")
             raise gr.Error(str(e))
 
-
-# --- 3. Gradio User Interface (Unchanged) ---
-
+# --- 3. Gradio User Interface ---
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🎬 Vertex AI VEO Video Generator")
-    gr.Markdown(
-        "Generate short videos from a text prompt using Google's VEO model. "
-        "Generation can take several minutes. Please be patient."
-    )
-    
+    gr.Markdown("Generate short videos from a text prompt using Google's VEO model.")
     with gr.Row():
         with gr.Column(scale=1):
-            prompt_input = gr.Textbox(
-                label="Prompt",
-                placeholder="A majestic lion roaming the savanna at sunrise, cinematic 4K.",
-                lines=3
-            )
+            prompt_input = gr.Textbox(label="Prompt", placeholder="A majestic lion...", lines=3)
             submit_button = gr.Button("Generate Video", variant="primary")
-
         with gr.Column(scale=1):
             status_output = gr.Markdown("Status: Ready")
             video_output = gr.Video(label="Generated Video", interactive=False)
-            
     gr.Examples(
-        examples=[
-            "A high-speed drone shot flying through a futuristic city with flying vehicles.",
-            "A raccoon happily eating popcorn in a movie theater, cinematic lighting.",
-            "A beautiful time-lapse of a flower blooming, from bud to full blossom, ultra-realistic.",
-        ],
+        ["A high-speed drone shot flying through a futuristic city with flying vehicles."],
         inputs=prompt_input,
     )
-
     submit_button.click(
         fn=generate_video,
         inputs=prompt_input,