feat: Natural chat AI, TTS speed 1.3x, HF upload to text_story folder

modules/text_story/router.py

@@ -105,31 +105,49 @@ async def generate_text_story_video(job_id: str, request: TextStoryRequest):
             output_dir=temp_dir
         )
         
-        # ============ STEP 5: Save Final Video ============
-        update_job(job_id, "processing", 90, "Saving video...")
+        # ============ STEP 5: Upload to HF Dataset ============
+        update_job(job_id, "processing", 90, "Uploading to cloud...")
         
-        # Create output directory
+        # Create local output directory
         videos_dir = os.path.join("videos", "text_story")
         os.makedirs(videos_dir, exist_ok=True)
         
         final_path = os.path.join(videos_dir, f"text_story_{job_id}.mp4")
         shutil.copy2(output_path, final_path)
         
-        # Also save to persistent storage if available
-        persistent_dir = "/data/videos/text_story"
-        if os.path.exists("/data"):
-            os.makedirs(persistent_dir, exist_ok=True)
-            shutil.copy2(output_path, os.path.join(persistent_dir, f"text_story_{job_id}.mp4"))
+        # Upload to HF Dataset using shared module
+        cloud_url = None
+        try:
+            from pathlib import Path
+            from modules.shared.services.hf_storage import HFStorageClient
+            
+            hf_repo = os.getenv("HF_REPO", "")
+            hf_token = os.getenv("HF_TOKEN", "")
+            
+            if hf_repo and hf_token:
+                hf_client = HFStorageClient(repo_id=hf_repo, token=hf_token)
+                cloud_url = hf_client.upload_video(
+                    local_path=Path(final_path),
+                    video_id=f"text_story_{job_id}",
+                    folder="text_story"  # Upload to text_story folder
+                )
+                if cloud_url:
+                    logger.info(f"TextStory: Uploaded to HF: {cloud_url}")
+        except Exception as e:
+            logger.warning(f"TextStory: HF upload failed: {e}")
         
         # Cleanup temp
         shutil.rmtree(temp_dir, ignore_errors=True)
         
-        video_url = f"/api/text-story/{job_id}/video"
+        # Use cloud URL if available, otherwise local
+        video_url = cloud_url or f"/api/text-story/{job_id}/video"
         update_job(job_id, "ready", 100, "Complete!", video_url=video_url)
         logger.info(f"TextStory: Job {job_id} completed successfully")
         
     except Exception as e:
         logger.error(f"TextStory: Job {job_id} failed - {e}")
+        import traceback
+        logger.error(traceback.format_exc())
         update_job(job_id, "failed", 0, error=str(e))
         
         # Cleanup on failure
@@ -263,24 +281,32 @@ async def ai_generate_conversation(request: AiGenerateRequest):
     
     tone_instruction = tone_prompts.get(request.tone, tone_prompts["emotional"])
     
-    system_prompt = f"""You are a viral content script writer. Generate a fake text message conversation.
+    system_prompt = f"""You are a viral content script writer. Generate a NATURAL fake text message conversation.
 
 RULES:
-1. Create exactly {request.message_count} messages
-2. Alternate between Person A ({request.person_a_name}) and Person B ({request.person_b_name})
-3. {tone_instruction}
-4. Make it engaging and viral-worthy
-5. Keep messages short (1-3 sentences each)
-6. End with impact (twist or emotional ending)
+1. Create approximately {request.message_count} messages (can be slightly more or less)
+2. Person A is "{request.person_a_name}" (sender: "A") - shown on right side (blue bubbles)
+3. Person B is "{request.person_b_name}" (sender: "B") - shown on left side (gray bubbles)
+4. {tone_instruction}
+5. NATURAL CHAT PATTERN - same person CAN send multiple messages in a row! Examples:
+   - Person sends a message, then follows up with another right after
+   - "Wait" ... "I need to tell you something"
+   - "Are you there?" ... "Hello??"
+   - Breaking long thoughts into 2-3 short messages
+6. Keep messages SHORT (1-2 sentences max per message)
+7. Usually B starts first (the "other" person initiates)
+8. End with impact (twist, cliffhanger, or emotional ending)
+9. Make it viral-worthy and engaging
 
 OUTPUT FORMAT (strict JSON):
 {{
     "messages": [
-        {{"sender": "B", "text": "message from {request.person_b_name}"}},
-        {{"sender": "A", "text": "message from {request.person_a_name}"}},
+        {{"sender": "B", "text": "Hey..."}},
+        {{"sender": "B", "text": "We need to talk"}},
+        {{"sender": "A", "text": "What's up?"}},
         ...
     ],
-    "ending_text": "Optional ending text like 'To be continued...'"
+    "ending_text": "To be continued..."
 }}
 
 Only output valid JSON, nothing else."""

modules/text_story/services/tts_handler.py

@@ -52,7 +52,8 @@ class TTSHandler:
                 payload = {
                     "model": "kokoro",
                     "input": text,
-                    "voice": voice
+                    "voice": voice,
+                    "speed": 1.3  # Faster voice for engaging content
                 }
                 
                 async with session.post(