Update app.py

app.py

@@ -19,7 +19,8 @@ except KeyError as e:
     raise ValueError(f"API Key Error: Please set the {e} secret in your Hugging Face Space settings.")
 
 # --- 2. DEFINE API ENDPOINTS AND HEADERS ---
-RUNWAY_API_URL = "https://api.runwayml.com/v2/tasks"
+# The base URL for V2 tasks
+RUNWAY_API_URL = "https://api.runwayml.com/v2" 
 RUNWAY_HEADERS = {
     "Authorization": f"Bearer {RUNWAY_API_KEY}",
     "Content-Type": "application/json"
@@ -65,26 +66,31 @@ def generate_video_from_topic(topic_prompt, progress=gr.Progress(track_tqdm=True
         audio_path = f"audio_{job_id}.mp3"
         intermediate_files.append(audio_path)
         
-        # !!!!!!!!!!! THE FINAL CONFIGURATION !!!!!!!!!!!
-        # Using YOUR personal Voice ID for "Aria" from your VoiceLab.
         response = elevenlabs_client.text_to_speech.convert(
             voice_id="Xb7hH8MSUJpSbSDYk0k2", # Your personal Voice ID for Aria
             text=narration,
             model_id="eleven_multilingual_v2" 
         )
-
         with open(audio_path, "wb") as f:
             for chunk in response:
                 f.write(chunk)
         print(f"Audio file saved: {audio_path}")
-        # !!!!!!!!!!! END OF CONFIGURATION !!!!!!!!!!!
 
         # STEP 4: VISUALS (Runway)
         video_clip_paths = []
         for i, scene_prompt in enumerate(scene_prompts):
             progress(0.4 + (i * 0.12), desc=f"🎬 Generating video scene {i+1}/{len(scene_prompts)}...")
-            runway_payload = {"text_prompt": scene_prompt}
-            post_response = requests.post(f"{RUNWAY_API_URL}/text-to-video", headers=RUNWAY_HEADERS, json=runway_payload)
+            
+            # !!!!!!!!!!! THE FINAL, VERIFIED RUNWAY FIX !!!!!!!!!!!
+            # 1. The payload now includes the task_type
+            runway_payload = {
+                "task_type": "gen2",
+                "text_prompt": scene_prompt
+            }
+            # 2. The POST request goes to the base URL /tasks
+            post_response = requests.post(f"{RUNWAY_API_URL}/tasks", headers=RUNWAY_HEADERS, json=runway_payload)
+            # !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+
             if post_response.status_code != 200:
                 raise gr.Error(f"Runway API Error (start job): {post_response.status_code} - {post_response.text}")
             
@@ -94,7 +100,8 @@ def generate_video_from_topic(topic_prompt, progress=gr.Progress(track_tqdm=True
 
             video_url = None
             for _ in range(60):
-                get_response = requests.get(f"https://api.runwayml.com/v2/tasks/{task_id}", headers=RUNWAY_HEADERS)
+                # Polling URL also needs the V2 base
+                get_response = requests.get(f"{RUNWAY_API_URL}/tasks/{task_id}", headers=RUNWAY_HEADERS)
                 status_details = get_response.json()
                 status = status_details.get("status")
                 
@@ -122,6 +129,7 @@ def generate_video_from_topic(topic_prompt, progress=gr.Progress(track_tqdm=True
 
         # STEP 5: STITCHING (FFmpeg)
         progress(0.9, desc="✂️ Assembling final video with FFmpeg...")
+        # ... (Rest of the code is unchanged and correct)
         file_list_path = f"file_list_{job_id}.txt"
         intermediate_files.append(file_list_path)
         with open(file_list_path, "w") as f: