Update app.py

app.py

@@ -1,5 +1,5 @@
 # Copyright 2025 Google LLC. Based on work by Yousif Ahmed.
-# Concept: ChronoWeave - Branching Narrative Generation
+# Concept: ChronoWeave – Branching Narrative Generation
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
@@ -14,19 +14,20 @@ import time
 import wave
 import contextlib
 import asyncio
-import uuid # For unique identifiers
-import shutil # For directory operations
-import logging # For better logging
+import uuid  # For unique identifiers
+import shutil  # For directory operations
+import logging  # For improved logging
 
 # Image handling
 from PIL import Image
+
 # Pydantic for data validation
 from pydantic import BaseModel, Field, ValidationError, field_validator, model_validator
 from typing import List, Optional, Literal, Dict, Any
 
 # Video and audio processing
 from moviepy.editor import ImageClip, AudioFileClip, concatenate_videoclips
-# from moviepy.config import change_settings # Potential
+# from moviepy.config import change_settings  # Potential for setting ImageMagick path if needed
 
 # Type hints
 import typing_extensions as typing
@@ -36,7 +37,10 @@ import nest_asyncio
 nest_asyncio.apply()
 
 # --- Logging Setup ---
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.basicConfig(
+    level=logging.INFO, 
+    format='%(asctime)s - %(levelname)s - %(message)s'
+)
 logger = logging.getLogger(__name__)
 
 # --- Configuration ---
@@ -51,7 +55,7 @@ Generate multiple, branching story timelines from a single theme using AI, compl
 TEXT_MODEL_ID = "models/gemini-1.5-flash"
 AUDIO_MODEL_ID = "models/gemini-1.5-flash"
 AUDIO_SAMPLING_RATE = 24000
-IMAGE_MODEL_ID = "imagen-3" # <<< NOTE: Requires Vertex AI SDK access
+IMAGE_MODEL_ID = "imagen-3"  # NOTE: Requires Vertex AI SDK access
 DEFAULT_ASPECT_RATIO = "1:1"
 VIDEO_FPS = 24
 VIDEO_CODEC = "libx264"
@@ -65,22 +69,38 @@ try:
     logger.info("Google API Key loaded from Streamlit secrets.")
 except KeyError:
     GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
-    if GOOGLE_API_KEY: logger.info("Google API Key loaded from environment variable.")
-    else: st.error("🚨 **Google API Key Not Found!** Please configure it.", icon="🚨"); st.stop()
+    if GOOGLE_API_KEY:
+        logger.info("Google API Key loaded from environment variable.")
+    else:
+        st.error("🚨 **Google API Key Not Found!** Please configure it.", icon="🚨")
+        st.stop()
 
 # --- Initialize Google Clients ---
 try:
     genai.configure(api_key=GOOGLE_API_KEY)
     logger.info("Configured google-generativeai with API key.")
+    
+    # Initialize text/JSON model
     client_standard = genai.GenerativeModel(TEXT_MODEL_ID)
     logger.info(f"Initialized text/JSON model handle: {TEXT_MODEL_ID}.")
+    
+    # Initialize audio model
     live_model = genai.GenerativeModel(AUDIO_MODEL_ID)
     logger.info(f"Initialized audio model handle: {AUDIO_MODEL_ID}.")
+    
+    # Initialize image model (placeholder for future Vertex AI SDK integration)
     image_model_genai = genai.GenerativeModel(IMAGE_MODEL_ID)
     logger.info(f"Initialized google-generativeai handle for image model: {IMAGE_MODEL_ID} (May require Vertex AI SDK).")
+    
     # ---> TODO: Initialize Vertex AI client here if switching SDK <---
-except AttributeError as ae: logger.exception("AttributeError during Client Init."); st.error(f"🚨 Init Error: {ae}. Update library?", icon="🚨"); st.stop()
-except Exception as e: logger.exception("Failed to initialize Google Clients/Models."); st.error(f"🚨 Failed Init: {e}", icon="🚨"); st.stop()
+except AttributeError as ae:
+    logger.exception("AttributeError during Client Init.")
+    st.error(f"🚨 Init Error: {ae}. Update library?", icon="🚨")
+    st.stop()
+except Exception as e:
+    logger.exception("Failed to initialize Google Clients/Models.")
+    st.error(f"🚨 Failed Init: {e}", icon="🚨")
+    st.stop()
 
 # --- Define Pydantic Schemas (Using V2 Syntax) ---
 class StorySegment(BaseModel):
@@ -89,90 +109,148 @@ class StorySegment(BaseModel):
     audio_text: str = Field(..., min_length=5, max_length=150)
     character_description: str = Field(..., max_length=250)
     timeline_visual_modifier: Optional[str] = Field(None, max_length=50)
+
     @field_validator('image_prompt')
     @classmethod
     def image_prompt_no_humans(cls, v: str) -> str:
-        if any(w in v.lower() for w in ["person", "people", "human", "man", "woman", "boy", "girl", "child"]): logger.warning(f"Prompt '{v[:50]}...' may contain humans.")
+        if any(w in v.lower() for w in ["person", "people", "human", "man", "woman", "boy", "girl", "child"]):
+            logger.warning(f"Prompt '{v[:50]}...' may contain humans.")
         return v
+
 class Timeline(BaseModel):
     timeline_id: int = Field(..., ge=0)
     divergence_reason: str = Field(..., min_length=5)
     segments: List[StorySegment] = Field(..., min_items=1)
+
 class ChronoWeaveResponse(BaseModel):
     core_theme: str = Field(..., min_length=5)
     timelines: List[Timeline] = Field(..., min_items=1)
     total_scenes_per_timeline: int = Field(..., gt=0)
+
     @model_validator(mode='after')
     def check_timeline_segment_count(self) -> 'ChronoWeaveResponse':
         expected = self.total_scenes_per_timeline
         for i, t in enumerate(self.timelines):
-            if len(t.segments) != expected: raise ValueError(f"Timeline {i} ID {t.timeline_id}: Expected {expected}, found {len(t.segments)}.")
+            if len(t.segments) != expected:
+                raise ValueError(f"Timeline {i} ID {t.timeline_id}: Expected {expected}, found {len(t.segments)}.")
         return self
 
 # --- Helper Functions ---
 
-# CORRECTED wave_file_writer function with proper indentation
 @contextlib.contextmanager
 def wave_file_writer(filename: str, channels: int = 1, rate: int = AUDIO_SAMPLING_RATE, sample_width: int = 2):
     """Context manager to safely write WAV files."""
     wf = None
     try:
-        # Indented correctly
         wf = wave.open(filename, "wb")
         wf.setnchannels(channels)
         wf.setsampwidth(sample_width)
         wf.setframerate(rate)
         yield wf
     except Exception as e:
-        logger.error(f"Error wave file {filename}: {e}")
+        logger.error(f"Error opening/configuring wave file {filename}: {e}")
         raise
     finally:
         if wf:
-            # Indented correctly
             try:
                 wf.close()
             except Exception as e_close:
                 logger.error(f"Error closing wave file {filename}: {e_close}")
 
-
 async def generate_audio_live_async(api_text: str, output_filename: str, voice: Optional[str] = None) -> Optional[str]:
-    """Generates audio using Gemini Live API (async version) via the GenerativeModel."""
-    collected_audio = bytearray(); task_id = os.path.basename(output_filename).split('.')[0]
+    """
+    Generates audio using Gemini Live API (async version) via the GenerativeModel.
+    """
+    collected_audio = bytearray()
+    task_id = os.path.basename(output_filename).split('.')[0]
     logger.info(f"🎙️ [{task_id}] Requesting audio: '{api_text[:60]}...'")
     try:
-        # Corrected config structure
-        config = {"response_modalities": ["AUDIO"], "audio_encoding": "LINEAR16", "sample_rate_hertz": AUDIO_SAMPLING_RATE}
+        # Corrected config structure for audio generation
+        config = {
+            "response_modalities": ["AUDIO"],
+            "audio_encoding": "LINEAR16",
+            "sample_rate_hertz": AUDIO_SAMPLING_RATE,
+        }
         directive_prompt = f"Narrate directly: \"{api_text}\""
         async with live_model.connect(config=config) as session:
             await session.send_request([directive_prompt])
             async for response in session.stream_content():
-                if response.audio_chunk and response.audio_chunk.data: collected_audio.extend(response.audio_chunk.data)
-                if hasattr(response, 'error') and response.error: logger.error(f"   ❌ [{task_id}] Audio stream error: {response.error}"); st.error(f"Audio stream error {task_id}: {response.error}", icon="🔊"); return None
-        if not collected_audio: logger.warning(f"⚠️ [{task_id}] No audio data received."); st.warning(f"No audio data for {task_id}.", icon="🔊"); return None
-        with wave_file_writer(output_filename, rate=AUDIO_SAMPLING_RATE) as wf: wf.writeframes(bytes(collected_audio))
-        logger.info(f"   ✅ [{task_id}] Audio saved: {os.path.basename(output_filename)} ({len(collected_audio)} bytes)")
+                if response.audio_chunk and response.audio_chunk.data:
+                    collected_audio.extend(response.audio_chunk.data)
+                if hasattr(response, 'error') and response.error:
+                    logger.error(f"❌ [{task_id}] Audio stream error: {response.error}")
+                    st.error(f"Audio stream error {task_id}: {response.error}", icon="🔊")
+                    return None
+        if not collected_audio:
+            logger.warning(f"⚠️ [{task_id}] No audio data received.")
+            st.warning(f"No audio data for {task_id}.", icon="🔊")
+            return None
+        with wave_file_writer(output_filename, rate=AUDIO_SAMPLING_RATE) as wf:
+            wf.writeframes(bytes(collected_audio))
+        logger.info(f"✅ [{task_id}] Audio saved: {os.path.basename(output_filename)} ({len(collected_audio)} bytes)")
         return output_filename
-    except genai.types.generation_types.BlockedPromptException as bpe: logger.error(f"   ❌ [{task_id}] Audio blocked: {bpe}"); st.error(f"Audio blocked {task_id}.", icon="🔇"); return None
-    except TypeError as te: logger.exception(f"   ❌ [{task_id}] Audio config TypeError: {te}"); st.error(f"Audio config error {task_id} (TypeError): {te}. Check library/config.", icon="⚙️"); return None
-    except Exception as e: logger.exception(f"   ❌ [{task_id}] Audio failed: {e}"); st.error(f"Audio failed {task_id}: {e}", icon="🔊"); return None
-
+    except genai.types.generation_types.BlockedPromptException as bpe:
+        logger.error(f"❌ [{task_id}] Audio blocked: {bpe}")
+        st.error(f"Audio blocked {task_id}.", icon="🔇")
+        return None
+    except TypeError as te:
+        logger.exception(f"❌ [{task_id}] Audio config TypeError: {te}")
+        st.error(f"Audio config error {task_id} (TypeError): {te}. Check library/config.", icon="⚙️")
+        return None
+    except Exception as e:
+        logger.exception(f"❌ [{task_id}] Audio failed: {e}")
+        st.error(f"Audio failed {task_id}: {e}", icon="🔊")
+        return None
 
 def generate_story_sequence_chrono(theme: str, num_scenes: int, num_timelines: int, divergence_prompt: str = "") -> Optional[ChronoWeaveResponse]:
-    """Generates branching story sequences using Gemini structured output and validates with Pydantic."""
+    """
+    Generates branching story sequences using Gemini structured output and validates with Pydantic.
+    """
     st.info(f"📚 Generating {num_timelines} timeline(s) x {num_scenes} scenes for: '{theme}'...")
     logger.info(f"Requesting story structure: Theme='{theme}', Timelines={num_timelines}, Scenes={num_scenes}")
-    divergence_instruction = (f"Introduce clear points of divergence between timelines, after first scene if possible. Hint: '{divergence_prompt}'. State divergence reason clearly. **For timeline_id 0, use 'Initial path' or 'Baseline scenario'.**")
-    prompt = f"""Act as narrative designer. Create story for theme: "{theme}". Instructions: 1. Exactly **{num_timelines}** timelines. 2. Each timeline exactly **{num_scenes}** scenes. 3. **NO humans/humanoids**. Focus: animals, fantasy creatures, animated objects, nature. 4. {divergence_instruction}. 5. Style: **'Simple, friendly kids animation, bright colors, rounded shapes'**, unless `timeline_visual_modifier` alters. 6. `audio_text`: single concise sentence (max 30 words). 7. `image_prompt`: descriptive, concise (target 15-35 words MAX). Focus on scene elements. **AVOID repeating general style**. 8. `character_description`: VERY brief (name, features). Target < 20 words. Output: ONLY valid JSON object adhering to schema. No text before/after. JSON Schema: ```json\n{json.dumps(ChronoWeaveResponse.model_json_schema(), indent=2)}\n```"""
+    divergence_instruction = (
+        f"Introduce clear points of divergence between timelines, after first scene if possible. "
+        f"Hint: '{divergence_prompt}'. State divergence reason clearly. **For timeline_id 0, use 'Initial path' or 'Baseline scenario'.**"
+    )
+    prompt = f"""Act as narrative designer. Create story for theme: "{theme}". Instructions: 1. Exactly **{num_timelines}** timelines. 2. Each timeline exactly **{num_scenes}** scenes. 3. **NO humans/humanoids**. Focus: animals, fantasy creatures, animated objects, nature. 4. {divergence_instruction}. 5. Style: **'Simple, friendly kids animation, bright colors, rounded shapes'**, unless `timeline_visual_modifier` alters. 6. `audio_text`: single concise sentence (max 30 words). 7. `image_prompt`: descriptive, concise (target 15-35 words MAX). Focus on scene elements. **AVOID repeating general style**. 8. `character_description`: VERY brief (name, features). Target < 20 words. Output: ONLY valid JSON object adhering to schema. No text before/after. JSON Schema: ```json
+{json.dumps(ChronoWeaveResponse.model_json_schema(), indent=2)}
+```"""
     try:
-        response = client_standard.generate_content(contents=prompt, generation_config=genai.types.GenerationConfig(response_mime_type="application/json", temperature=0.7))
-        try: raw_data = json.loads(response.text)
-        except json.JSONDecodeError as json_err: logger.error(f"Failed JSON decode: {json_err}\nResponse:\n{response.text}"); st.error(f"🚨 Failed parse story: {json_err}", icon="📄"); st.text_area("Problem Response:", response.text, height=150); return None
-        except Exception as e: logger.error(f"Error processing text: {e}"); st.error(f"🚨 Error processing AI response: {e}", icon="📄"); return None
-        try: validated_data = ChronoWeaveResponse.model_validate(raw_data); logger.info("✅ Story structure OK!"); st.success("✅ Story structure OK!"); return validated_data
-        except ValidationError as val_err: logger.error(f"JSON validation failed: {val_err}\nData:\n{json.dumps(raw_data, indent=2)}"); st.error(f"🚨 Gen structure invalid: {val_err}", icon="🧬"); st.json(raw_data); return None
-    except genai.types.generation_types.BlockedPromptException as bpe: logger.error(f"Story gen blocked: {bpe}"); st.error("🚨 Story prompt blocked.", icon="🚫"); return None
-    except Exception as e: logger.exception("Error during story gen:"); st.error(f"🚨 Story gen error: {e}", icon="💥"); return None
-
+        response = client_standard.generate_content(
+            contents=prompt,
+            generation_config=genai.types.GenerationConfig(
+                response_mime_type="application/json", temperature=0.7
+            )
+        )
+        try:
+            raw_data = json.loads(response.text)
+        except json.JSONDecodeError as json_err:
+            logger.error(f"Failed JSON decode: {json_err}\nResponse:\n{response.text}")
+            st.error(f"🚨 Failed parse story: {json_err}", icon="📄")
+            st.text_area("Problem Response:", response.text, height=150)
+            return None
+        except Exception as e:
+            logger.error(f"Error processing text: {e}")
+            st.error(f"🚨 Error processing AI response: {e}", icon="📄")
+            return None
+        try:
+            validated_data = ChronoWeaveResponse.model_validate(raw_data)
+            logger.info("✅ Story structure OK!")
+            st.success("✅ Story structure OK!")
+            return validated_data
+        except ValidationError as val_err:
+            logger.error(f"JSON validation failed: {val_err}\nData:\n{json.dumps(raw_data, indent=2)}")
+            st.error(f"🚨 Gen structure invalid: {val_err}", icon="🧬")
+            st.json(raw_data)
+            return None
+    except genai.types.generation_types.BlockedPromptException as bpe:
+        logger.error(f"Story gen blocked: {bpe}")
+        st.error("🚨 Story prompt blocked.", icon="🚫")
+        return None
+    except Exception as e:
+        logger.exception("Error during story gen:")
+        st.error(f"🚨 Story gen error: {e}", icon="💥")
+        return None
 
 def generate_image_imagen(prompt: str, aspect_ratio: str = "1:1", task_id: str = "IMG") -> Optional[Image.Image]:
     """
@@ -181,15 +259,17 @@ def generate_image_imagen(prompt: str, aspect_ratio: str = "1:1", task_id: str =
     (google-cloud-aiplatform) to correctly call Imagen models. >>>
     """
     logger.info(f"🖼️ [{task_id}] Requesting image: '{prompt[:70]}...' (Aspect: {aspect_ratio})")
-    logger.error(f"   ❌ [{task_id}] Image generation skipped: Function needs update to use Vertex AI SDK for Imagen.")
+    logger.error(f"❌ [{task_id}] Image generation skipped: Function needs update to use Vertex AI SDK for Imagen.")
     st.error(f"Image generation for {task_id} skipped: Requires Vertex AI SDK implementation.", icon="🖼️")
-    # Return None because the current method is known to fail based on previous logs
     return None
 
 # --- Streamlit UI Elements ---
 st.sidebar.header("⚙️ Configuration")
-if GOOGLE_API_KEY: st.sidebar.success("Google API Key Loaded", icon="✅")
-else: st.sidebar.error("Google API Key Missing!", icon="🚨")
+if GOOGLE_API_KEY:
+    st.sidebar.success("Google API Key Loaded", icon="✅")
+else:
+    st.sidebar.error("Google API Key Missing!", icon="🚨")
+
 theme = st.sidebar.text_input("📖 Story Theme:", "A curious squirrel finds a mysterious, glowing acorn")
 num_scenes = st.sidebar.slider("🎬 Scenes per Timeline:", min_value=2, max_value=7, value=3)
 num_timelines = st.sidebar.slider("🌿 Number of Timelines:", min_value=1, max_value=4, value=2)
@@ -198,123 +278,229 @@ st.sidebar.subheader("🎨 Visual & Audio Settings")
 aspect_ratio = st.sidebar.selectbox("🖼️ Image Aspect Ratio:", ["1:1", "16:9", "9:16"], index=0)
 audio_voice = None
 generate_button = st.sidebar.button("✨ Generate ChronoWeave ✨", type="primary", disabled=(not GOOGLE_API_KEY), use_container_width=True)
-st.sidebar.markdown("---"); st.sidebar.info("⏳ Generation can take minutes."); st.sidebar.markdown(f"<small>Txt:{TEXT_MODEL_ID}, Img:{IMAGE_MODEL_ID}, Aud:{AUDIO_MODEL_ID}</small>", unsafe_allow_html=True)
+st.sidebar.markdown("---")
+st.sidebar.info("⏳ Generation can take minutes.")
+st.sidebar.markdown(f"<small>Txt:{TEXT_MODEL_ID}, Img:{IMAGE_MODEL_ID}, Aud:{AUDIO_MODEL_ID}</small>", unsafe_allow_html=True)
 
 # --- Main Logic ---
 if generate_button:
-    if not theme: st.error("Please enter a story theme.", icon="👈")
+    if not theme:
+        st.error("Please enter a story theme.", icon="👈")
     else:
-        run_id = str(uuid.uuid4()).split('-')[0]; temp_dir = os.path.join(TEMP_DIR_BASE, f"run_{run_id}")
-        try: os.makedirs(temp_dir, exist_ok=True); logger.info(f"Created temp dir: {temp_dir}")
-        except OSError as e: st.error(f"🚨 Failed create temp dir {temp_dir}: {e}", icon="📂"); st.stop()
+        run_id = str(uuid.uuid4()).split('-')[0]
+        temp_dir = os.path.join(TEMP_DIR_BASE, f"run_{run_id}")
+        try:
+            os.makedirs(temp_dir, exist_ok=True)
+            logger.info(f"Created temp dir: {temp_dir}")
+        except OSError as e:
+            st.error(f"🚨 Failed create temp dir {temp_dir}: {e}", icon="📂")
+            st.stop()
         final_video_paths, generation_errors = {}, {}
 
         chrono_response: Optional[ChronoWeaveResponse] = None
-        with st.spinner("Generating narrative structure... 🤔"): chrono_response = generate_story_sequence_chrono(theme, num_scenes, num_timelines, divergence_prompt)
+        with st.spinner("Generating narrative structure... 🤔"):
+            chrono_response = generate_story_sequence_chrono(theme, num_scenes, num_timelines, divergence_prompt)
 
         if chrono_response:
-            overall_start_time = time.time(); all_timelines_successful = True
+            overall_start_time = time.time()
+            all_timelines_successful = True
             with st.status("Generating assets and composing videos...", expanded=True) as status:
                 for timeline_index, timeline in enumerate(chrono_response.timelines):
                     timeline_id, divergence, segments = timeline.timeline_id, timeline.divergence_reason, timeline.segments
-                    timeline_label = f"Timeline {timeline_id}"; st.subheader(f"Processing {timeline_label}: {divergence}")
-                    logger.info(f"--- Processing {timeline_label} (Idx: {timeline_index}) ---"); generation_errors[timeline_id] = []
+                    timeline_label = f"Timeline {timeline_id}"
+                    st.subheader(f"Processing {timeline_label}: {divergence}")
+                    logger.info(f"--- Processing {timeline_label} (Idx: {timeline_index}) ---")
+                    generation_errors[timeline_id] = []
                     temp_image_files, temp_audio_files, video_clips = {}, {}, []
-                    timeline_start_time = time.time(); scene_success_count = 0
+                    timeline_start_time = time.time()
+                    scene_success_count = 0
 
                     for scene_index, segment in enumerate(segments):
-                        scene_id = segment.scene_id; task_id = f"T{timeline_id}_S{scene_id}"
+                        scene_id = segment.scene_id
+                        task_id = f"T{timeline_id}_S{scene_id}"
                         status.update(label=f"Processing {timeline_label}, Scene {scene_id + 1}/{len(segments)}...")
                         st.markdown(f"--- **Scene {scene_id + 1} ({task_id})** ---")
                         logger.info(f"Processing {timeline_label}, Scene {scene_id + 1}/{len(segments)}...")
                         scene_has_error = False
-                        st.write(f"   *Img Prompt:* {segment.image_prompt}" + (f" *(Mod: {segment.timeline_visual_modifier})*" if segment.timeline_visual_modifier else "")); st.write(f"   *Audio Text:* {segment.audio_text}")
+                        st.write(f"*Img Prompt:* {segment.image_prompt}" + (f" *(Mod: {segment.timeline_visual_modifier})*" if segment.timeline_visual_modifier else ""))
+                        st.write(f"*Audio Text:* {segment.audio_text}")
 
                         # --- 2a. Image Generation ---
                         generated_image: Optional[Image.Image] = None
                         with st.spinner(f"[{task_id}] Generating image... 🎨"):
                             combined_prompt = segment.image_prompt
-                            if segment.character_description: combined_prompt += f" Featuring: {segment.character_description}"
-                            if segment.timeline_visual_modifier: combined_prompt += f" Style hint: {segment.timeline_visual_modifier}."
-                            generated_image = generate_image_imagen(combined_prompt, aspect_ratio, task_id) # <<< Needs Vertex AI SDK update
+                            if segment.character_description:
+                                combined_prompt += f" Featuring: {segment.character_description}"
+                            if segment.timeline_visual_modifier:
+                                combined_prompt += f" Style hint: {segment.timeline_visual_modifier}."
+                            generated_image = generate_image_imagen(combined_prompt, aspect_ratio, task_id)
                         if generated_image:
                             image_path = os.path.join(temp_dir, f"{task_id}_image.png")
-                            try: generated_image.save(image_path); temp_image_files[scene_id] = image_path; st.image(generated_image, width=180, caption=f"Scene {scene_id+1}")
-                            except Exception as e: logger.error(f"   ❌ [{task_id}] Img save error: {e}"); st.error(f"Save image {task_id} failed.", icon="💾"); scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Img save fail.")
-                        else: scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Img gen fail."); continue
+                            try:
+                                generated_image.save(image_path)
+                                temp_image_files[scene_id] = image_path
+                                st.image(generated_image, width=180, caption=f"Scene {scene_id + 1}")
+                            except Exception as e:
+                                logger.error(f"❌ [{task_id}] Img save error: {e}")
+                                st.error(f"Save image {task_id} failed.", icon="💾")
+                                scene_has_error = True
+                                generation_errors[timeline_id].append(f"S{scene_id + 1}: Img save fail.")
+                        else:
+                            scene_has_error = True
+                            generation_errors[timeline_id].append(f"S{scene_id + 1}: Img gen fail.")
+                            continue
 
                         # --- 2b. Audio Generation ---
                         generated_audio_path: Optional[str] = None
-                        if not scene_has_error: # Should not be reached currently
+                        if not scene_has_error:
                             with st.spinner(f"[{task_id}] Generating audio... 🔊"):
                                 audio_path_temp = os.path.join(temp_dir, f"{task_id}_audio.wav")
-                                try: generated_audio_path = asyncio.run(generate_audio_live_async(segment.audio_text, audio_path_temp, audio_voice))
-                                except RuntimeError as e: logger.error(f"   ❌ [{task_id}] Asyncio error: {e}"); st.error(f"Asyncio audio error {task_id}: {e}", icon="⚡"); scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Audio async err.")
-                                except Exception as e: logger.exception(f"   ❌ [{task_id}] Audio error: {e}"); st.error(f"Audio error {task_id}: {e}", icon="💥"); scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Audio gen err.")
+                                try:
+                                    generated_audio_path = asyncio.run(generate_audio_live_async(segment.audio_text, audio_path_temp, audio_voice))
+                                except RuntimeError as e:
+                                    logger.error(f"❌ [{task_id}] Asyncio error: {e}")
+                                    st.error(f"Asyncio audio error {task_id}: {e}", icon="⚡")
+                                    scene_has_error = True
+                                    generation_errors[timeline_id].append(f"S{scene_id + 1}: Audio async err.")
+                                except Exception as e:
+                                    logger.exception(f"❌ [{task_id}] Audio error: {e}")
+                                    st.error(f"Audio error {task_id}: {e}", icon="💥")
+                                    scene_has_error = True
+                                    generation_errors[timeline_id].append(f"S{scene_id + 1}: Audio gen err.")
                             if generated_audio_path:
-                                temp_audio_files[scene_id] = generated_audio_path; try: open(generated_audio_path,'rb') as ap: st.audio(ap.read(), format='audio/wav')
-                                except Exception as e: logger.warning(f"   ⚠️ [{task_id}] Audio preview error: {e}")
-                            else: scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Audio gen fail."); continue
+                                temp_audio_files[scene_id] = generated_audio_path
+                                try:
+                                    with open(generated_audio_path, 'rb') as ap:
+                                        st.audio(ap.read(), format='audio/wav')
+                                except Exception as e:
+                                    logger.warning(f"⚠️ [{task_id}] Audio preview error: {e}")
+                            else:
+                                scene_has_error = True
+                                generation_errors[timeline_id].append(f"S{scene_id + 1}: Audio gen fail.")
+                                continue
 
                         # --- 2c. Create Video Clip ---
-                        if not scene_has_error and scene_id in temp_image_files and scene_id in temp_audio_files: # Should not be reached currently
-                            st.write(f"   🎬 Creating clip S{scene_id+1}..."); img_path, aud_path = temp_image_files[scene_id], temp_audio_files[scene_id]
+                        if not scene_has_error and scene_id in temp_image_files and scene_id in temp_audio_files:
+                            st.write(f"🎬 Creating clip S{scene_id + 1}...")
+                            img_path, aud_path = temp_image_files[scene_id], temp_audio_files[scene_id]
                             audio_clip_instance, image_clip_instance, composite_clip = None, None, None
                             try:
-                                if not os.path.exists(img_path): raise FileNotFoundError(f"Img missing: {img_path}")
-                                if not os.path.exists(aud_path): raise FileNotFoundError(f"Aud missing: {aud_path}")
-                                audio_clip_instance = AudioFileClip(aud_path); np_image = np.array(Image.open(img_path))
+                                if not os.path.exists(img_path):
+                                    raise FileNotFoundError(f"Img missing: {img_path}")
+                                if not os.path.exists(aud_path):
+                                    raise FileNotFoundError(f"Aud missing: {aud_path}")
+                                audio_clip_instance = AudioFileClip(aud_path)
+                                np_image = np.array(Image.open(img_path))
                                 image_clip_instance = ImageClip(np_image).set_duration(audio_clip_instance.duration)
-                                composite_clip = image_clip_instance.set_audio(audio_clip_instance); video_clips.append(composite_clip)
-                                logger.info(f"      ✅ [{task_id}] Clip created (Dur: {audio_clip_instance.duration:.2f}s)."); st.write(f"      ✅ Clip created (Dur: {audio_clip_instance.duration:.2f}s)."); scene_success_count += 1
-                            except Exception as e: logger.exception(f"      ❌ [{task_id}] Failed clip creation: {e}"); st.error(f"Failed clip {task_id}: {e}", icon="🎬"); scene_has_error = True; generation_errors[timeline_id].append(f"S{scene_id+1}: Clip fail.")
+                                composite_clip = image_clip_instance.set_audio(audio_clip_instance)
+                                video_clips.append(composite_clip)
+                                logger.info(f"✅ [{task_id}] Clip created (Dur: {audio_clip_instance.duration:.2f}s).")
+                                st.write(f"✅ Clip created (Dur: {audio_clip_instance.duration:.2f}s).")
+                                scene_success_count += 1
+                            except Exception as e:
+                                logger.exception(f"❌ [{task_id}] Failed clip creation: {e}")
+                                st.error(f"Failed clip {task_id}: {e}", icon="🎬")
+                                scene_has_error = True
+                                generation_errors[timeline_id].append(f"S{scene_id + 1}: Clip fail.")
                             finally:
-                                if audio_clip_instance: audio_clip_instance.close();
-                                if image_clip_instance: image_clip_instance.close()
+                                if audio_clip_instance:
+                                    audio_clip_instance.close()
+                                if image_clip_instance:
+                                    image_clip_instance.close()
 
                     # --- 2d. Assemble Timeline Video ---
                     timeline_duration = time.time() - timeline_start_time
                     if video_clips and scene_success_count == len(segments):
-                         status.update(label=f"Composing video {timeline_label}..."); st.write(f"🎞️ Assembling video {timeline_label}..."); logger.info(f"🎞️ Assembling video {timeline_label}...")
-                         output_filename = os.path.join(temp_dir, f"timeline_{timeline_id}_final.mp4"); final_timeline_video = None
-                         try: final_timeline_video = concatenate_videoclips(video_clips, method="compose"); final_timeline_video.write_videofile(output_filename, fps=VIDEO_FPS, codec=VIDEO_CODEC, audio_codec=AUDIO_CODEC, logger=None); final_video_paths[timeline_id] = output_filename; logger.info(f"   ✅ [{timeline_label}] Video saved: {os.path.basename(output_filename)}"); st.success(f"✅ Video {timeline_label} completed in {timeline_duration:.2f}s.")
-                         except Exception as e: logger.exception(f"   ❌ [{timeline_label}] Video assembly failed: {e}"); st.error(f"Assemble video {timeline_label} failed: {e}", icon="📼"); all_timelines_successful = False; generation_errors[timeline_id].append(f"T{timeline_id}: Assembly fail.")
-                         finally:
-                             logger.debug(f"[{timeline_label}] Closing {len(video_clips)} clips...");
-                             for i, clip in enumerate(video_clips): try: clip.close() except Exception as e_close: logger.warning(f"   ⚠️ [{timeline_label}] Clip close err {i}: {e_close}")
-                             if final_timeline_video: try: final_timeline_video.close() except Exception as e_close_final: logger.warning(f"   ⚠️ [{timeline_label}] Final vid close err: {e_close_final}")
-                    elif not video_clips: logger.warning(f"[{timeline_label}] No clips. Skip assembly."); st.warning(f"No scenes for {timeline_label}. No video.", icon="🚫"); all_timelines_successful = False
-                    else: error_count = len(generation_errors[timeline_id]); logger.warning(f"[{timeline_label}] {error_count} scene err(s). Skip assembly."); st.warning(f"{timeline_label}: {error_count} err(s). Video not assembled.", icon="⚠️"); all_timelines_successful = False
-                    if generation_errors[timeline_id]: logger.error(f"Errors {timeline_label}: {generation_errors[timeline_id]}")
+                        status.update(label=f"Composing video {timeline_label}...")
+                        st.write(f"🎞️ Assembling video {timeline_label}...")
+                        logger.info(f"🎞️ Assembling video {timeline_label}...")
+                        output_filename = os.path.join(temp_dir, f"timeline_{timeline_id}_final.mp4")
+                        final_timeline_video = None
+                        try:
+                            final_timeline_video = concatenate_videoclips(video_clips, method="compose")
+                            final_timeline_video.write_videofile(
+                                output_filename, fps=VIDEO_FPS, codec=VIDEO_CODEC, audio_codec=AUDIO_CODEC, logger=None
+                            )
+                            final_video_paths[timeline_id] = output_filename
+                            logger.info(f"✅ [{timeline_label}] Video saved: {os.path.basename(output_filename)}")
+                            st.success(f"✅ Video {timeline_label} completed in {timeline_duration:.2f}s.")
+                        except Exception as e:
+                            logger.exception(f"❌ [{timeline_label}] Video assembly failed: {e}")
+                            st.error(f"Assemble video {timeline_label} failed: {e}", icon="📼")
+                            all_timelines_successful = False
+                            generation_errors[timeline_id].append(f"T{timeline_id}: Assembly fail.")
+                        finally:
+                            logger.debug(f"[{timeline_label}] Closing {len(video_clips)} clips...")
+                            for i, clip in enumerate(video_clips):
+                                try:
+                                    clip.close()
+                                except Exception as e_close:
+                                    logger.warning(f"⚠️ [{timeline_label}] Clip close err {i}: {e_close}")
+                            if final_timeline_video:
+                                try:
+                                    final_timeline_video.close()
+                                except Exception as e_close_final:
+                                    logger.warning(f"⚠️ [{timeline_label}] Final vid close err: {e_close_final}")
+                    elif not video_clips:
+                        logger.warning(f"[{timeline_label}] No clips. Skip assembly.")
+                        st.warning(f"No scenes for {timeline_label}. No video.", icon="🚫")
+                        all_timelines_successful = False
+                    else:
+                        error_count = len(generation_errors[timeline_id])
+                        logger.warning(f"[{timeline_label}] {error_count} scene err(s). Skip assembly.")
+                        st.warning(f"{timeline_label}: {error_count} err(s). Video not assembled.", icon="⚠️")
+                        all_timelines_successful = False
+                    if generation_errors[timeline_id]:
+                        logger.error(f"Errors {timeline_label}: {generation_errors[timeline_id]}")
 
                 # --- End of Timelines Loop ---
                 overall_duration = time.time() - overall_start_time
-                if all_timelines_successful and final_video_paths: status_msg = f"Complete! ({len(final_video_paths)} videos in {overall_duration:.2f}s)"; status.update(label=status_msg, state="complete", expanded=False); logger.info(status_msg)
-                elif final_video_paths: status_msg = f"Partially Complete ({len(final_video_paths)} videos, errors). {overall_duration:.2f}s"; status.update(label=status_msg, state="warning", expanded=True); logger.warning(status_msg)
-                else: status_msg = f"Failed. No videos. {overall_duration:.2f}s"; status.update(label=status_msg, state="error", expanded=True); logger.error(status_msg)
+                if all_timelines_successful and final_video_paths:
+                    status_msg = f"Complete! ({len(final_video_paths)} videos in {overall_duration:.2f}s)"
+                    status.update(label=status_msg, state="complete", expanded=False)
+                    logger.info(status_msg)
+                elif final_video_paths:
+                    status_msg = f"Partially Complete ({len(final_video_paths)} videos, errors). {overall_duration:.2f}s"
+                    status.update(label=status_msg, state="warning", expanded=True)
+                    logger.warning(status_msg)
+                else:
+                    status_msg = f"Failed. No videos. {overall_duration:.2f}s"
+                    status.update(label=status_msg, state="error", expanded=True)
+                    logger.error(status_msg)
 
             # --- 3. Display Results ---
             st.header("🎬 Generated Timelines")
             if final_video_paths:
-                sorted_timeline_ids = sorted(final_video_paths.keys()); num_cols = min(len(sorted_timeline_ids), 3); cols = st.columns(num_cols)
+                sorted_timeline_ids = sorted(final_video_paths.keys())
+                num_cols = min(len(sorted_timeline_ids), 3)
+                cols = st.columns(num_cols)
                 for idx, timeline_id in enumerate(sorted_timeline_ids):
-                    col = cols[idx % num_cols]; video_path = final_video_paths[timeline_id]
+                    col = cols[idx % num_cols]
+                    video_path = final_video_paths[timeline_id]
                     timeline_data = next((t for t in chrono_response.timelines if t.timeline_id == timeline_id), None)
                     reason = timeline_data.divergence_reason if timeline_data else "Unknown"
                     with col:
-                        st.subheader(f"Timeline {timeline_id}"); st.caption(f"Divergence: {reason}")
+                        st.subheader(f"Timeline {timeline_id}")
+                        st.caption(f"Divergence: {reason}")
                         try:
-                            with open(video_path, 'rb') as vf: video_bytes = vf.read()
-                            st.video(video_bytes); logger.info(f"Displaying T{timeline_id}")
+                            with open(video_path, 'rb') as vf:
+                                video_bytes = vf.read()
+                            st.video(video_bytes)
+                            logger.info(f"Displaying T{timeline_id}")
                             st.download_button(f"Download T{timeline_id}", video_bytes, f"timeline_{timeline_id}.mp4", "video/mp4", key=f"dl_{timeline_id}")
                             if generation_errors.get(timeline_id):
                                 scene_errors = [err for err in generation_errors[timeline_id] if not err.startswith(f"T{timeline_id}:")]
                                 if scene_errors:
-                                     with st.expander(f"⚠️ View {len(scene_errors)} Scene Issues"):
-                                         for err in scene_errors: st.warning(f"- {err}") # Use standard loop
-                        except FileNotFoundError: logger.error(f"Video missing: {video_path}"); st.error(f"Error: Video missing T{timeline_id}.", icon="🚨")
-                        except Exception as e: logger.exception(f"Display error {video_path}: {e}"); st.error(f"Display error T{timeline_id}: {e}", icon="🚨")
-            else: # No videos generated
+                                    with st.expander(f"⚠️ View {len(scene_errors)} Scene Issues"):
+                                        for err in scene_errors:
+                                            st.warning(f"- {err}")
+                        except FileNotFoundError:
+                            logger.error(f"Video missing: {video_path}")
+                            st.error(f"Error: Video missing T{timeline_id}.", icon="🚨")
+                        except Exception as e:
+                            logger.exception(f"Display error {video_path}: {e}")
+                            st.error(f"Display error T{timeline_id}: {e}", icon="🚨")
+            else:
                 st.warning("No final videos were successfully generated.")
                 st.subheader("Summary of Generation Issues")
                 has_errors = any(generation_errors.values())
@@ -323,15 +509,26 @@ if generate_button:
                         for tid, errors in generation_errors.items():
                             if errors:
                                 st.error(f"**Timeline {tid}:**")
-                                for msg in errors: st.error(f"  - {msg}") # Use standard loop
-                else: st.info("No generation errors recorded.")
+                                for msg in errors:
+                                    st.error(f"  - {msg}")
+                else:
+                    st.info("No generation errors recorded.")
 
             # --- 4. Cleanup ---
             st.info(f"Attempting cleanup: {temp_dir}")
-            try: shutil.rmtree(temp_dir); logger.info(f"✅ Temp dir removed: {temp_dir}"); st.success("✅ Temp files cleaned.")
-            except Exception as e: logger.error(f"⚠️ Failed remove temp dir {temp_dir}: {e}"); st.warning(f"Could not remove temp files: {temp_dir}.", icon="⚠️")
-
-        elif not chrono_response: logger.error("Story gen/validation failed.")
-        else: st.error("Unexpected issue post-gen.", icon="🛑"); logger.error("Chrono_response truthy but invalid.")
-
-else: st.info("Configure settings and click '✨ Generate ChronoWeave ✨' to start.")
+            try:
+                shutil.rmtree(temp_dir)
+                logger.info(f"✅ Temp dir removed: {temp_dir}")
+                st.success("✅ Temp files cleaned.")
+            except Exception as e:
+                logger.error(f"⚠️ Failed remove temp dir {temp_dir}: {e}")
+                st.warning(f"Could not remove temp files: {temp_dir}.", icon="⚠️")
+
+        elif not chrono_response:
+            logger.error("Story gen/validation failed.")
+        else:
+            st.error("Unexpected issue post-gen.", icon="🛑")
+            logger.error("Chrono_response truthy but invalid.")
+
+else:
+    st.info("Configure settings and click '✨ Generate ChronoWeave ✨' to start.")