Upgrade: Structured JSON Analysis & UI Scroll Fix

agent.py

@@ -3,6 +3,7 @@ import time
 import logging
 import tempfile
 import hashlib
+import json
 from google import genai
 from google.genai import types
 from config import Settings
@@ -22,67 +23,60 @@ def get_file_hash(filepath):
 def get_or_upload_file(client, filepath):
     """Uploads file only if it doesn't already exist in Gemini (deduplication)."""
     file_hash = get_file_hash(filepath)
-    
-    # Check if file with this hash name already exists
     try:
         for f in client.files.list(config={'page_size': 50}):
             if f.display_name == file_hash and f.state.name == "ACTIVE":
-                logger.info(f"♻️ Smart Cache Hit: Using existing file {file_hash}")
+                logger.info(f"♻️ Smart Cache Hit: {file_hash}")
                 return f
     except Exception:
         pass
-
-    logger.info(f"wm Uploading new file: {filepath} (Hash: {file_hash})")
+    logger.info(f"wm Uploading new file: {file_hash}")
     return client.files.upload(file=filepath, config={'display_name': file_hash})
 
-def analyze_videos(state):
-    # Note: This function is kept for LangGraph compatibility if needed,
-    # but the main logic is now in analyze_only below.
-    return analyze_only(state['video_a_local_path'], state['video_c_local_path'], state.get('job_id'))
-
 def analyze_only(path_a, path_c, job_id=None):
     update_job_status(job_id, "analyzing", 10, "Director checking file cache...")
     client = genai.Client(api_key=Settings.GOOGLE_API_KEY)
     
     try:
-        # 1. Smart Upload
         file_a = get_or_upload_file(client, path_a)
         file_c = get_or_upload_file(client, path_c)
         
-        # 2. Wait for processing
         while file_a.state.name == "PROCESSING" or file_c.state.name == "PROCESSING":
-            update_job_status(job_id, "analyzing", 20, "Google is processing video geometry...")
+            update_job_status(job_id, "analyzing", 20, "Google processing video...")
             time.sleep(2)
             file_a = client.files.get(name=file_a.name)
             file_c = client.files.get(name=file_c.name)
-        
-        # 3. THE V2.7 'VFX DIRECTOR' PROMPT
+
         prompt = """
-        You are a VFX Director specializing in surreal, seamless video morphing.
-        
-        Task: Analyze the visual composition, lighting, and primary shapes of Video A (Start) and Video C (End).
-        Goal: Write a visual prompt for a 2-second intermediate video (Video B) that semantically transforms A into C.
-        
-        Strict Rules:
-        1. DO NOT use words like "dissolve", "fade", "cut", or "transition".
-        2. Describe a PHYSICAL transformation. How does the texture of A become the texture of C?
-        3. Match the lighting evolution (e.g., "The golden hour light creates deep shadows that morph into...")
-        4. Find a connecting shape (e.g., "The curve of the river flows upwards to match the curve of the jawline").
-        
-        Output: ONLY the final visual prompt text. Keep it under 40 words.
+        You are a VFX Director. Analyze Video A and Video C.
+        Return a JSON object with exactly these keys:
+        {
+            "analysis_a": "Brief description of Video A's lighting, subject, and camera movement.",
+            "analysis_c": "Brief description of Video C's lighting, subject, and camera movement.",
+            "visual_prompt_b": "A surreal, seamless morphing prompt that transforms A into C. DO NOT use words like 'dissolve' or 'cut'. Focus on shape and texture transformation."
+        }
         """
-        
         update_job_status(job_id, "analyzing", 30, "Director drafting creative morph...")
         
-        res = client.models.generate_content(model="gemini-2.0-flash-exp", contents=[prompt, file_a, file_c])
-        return {"prompt": res.text, "status": "success"}
+        # Request JSON output
+        res = client.models.generate_content(
+            model="gemini-2.0-flash-exp", 
+            contents=[prompt, file_a, file_c],
+            config=types.GenerateContentConfig(response_mime_type="application/json")
+        )
+        
+        data = json.loads(res.text)
+        return {
+            "analysis_a": data.get("analysis_a", ""),
+            "analysis_c": data.get("analysis_c", ""),
+            "prompt": data.get("visual_prompt_b", res.text),
+            "status": "success"
+        }
     except Exception as e:
-        logger.error(f"Analysis Error: {e}")
         return {"detail": str(e), "status": "error"}
 
 def generate_only(prompt, path_a, path_c, job_id, style, audio, neg, guidance, motion):
     update_job_status(job_id, "generating", 50, "Production started (Veo 3.1)...")
-    
     full_prompt = f"{style} style. {prompt} Soundtrack: {audio}"
     if neg:
         full_prompt += f" --no {neg}"
@@ -91,19 +85,17 @@ def generate_only(prompt, path_a, path_c, job_id, style, audio, neg, guidance, m
         if Settings.GCP_PROJECT_ID:
             client = genai.Client(vertexai=True, project=Settings.GCP_PROJECT_ID, location=Settings.GCP_LOCATION)
             op = client.models.generate_videos(
-                model='veo-3.1-generate-preview',
-                prompt=full_prompt,
+                model='veo-3.1-generate-preview', 
+                prompt=full_prompt, 
                 config=types.GenerateVideosConfig(number_of_videos=1)
             )
             
             while not op.done:
                 time.sleep(5)
-                # Ideally check status here if possible, or just wait loop
-            
+                
             if op.result and op.result.generated_videos:
                 vid = op.result.generated_videos[0]
                 bridge_path = None
-                
                 if vid.video.uri:
                     bridge_path = tempfile.mktemp(suffix=".mp4")
                     download_blob(vid.video.uri, bridge_path)
@@ -117,12 +109,9 @@ def generate_only(prompt, path_a, path_c, job_id, style, audio, neg, guidance, m
                         final_output = stitch_videos(path_a, bridge_path, path_c, final_cut_path)
                         update_job_status(job_id, "completed", 100, "Done!", video_url=bridge_path, merged_video_url=final_output)
                     except Exception as e:
-                        logger.error(f"Stitch failed: {e}")
                         update_job_status(job_id, "completed", 100, "Stitch failed, showing bridge.", video_url=bridge_path)
                     return
-
     except Exception as e:
         update_job_status(job_id, "error", 0, f"Error: {e}")
         return
-
     update_job_status(job_id, "error", 0, "Generation failed.")

server.py

@@ -8,6 +8,7 @@ from utils import get_history_from_gcs
 
 app = FastAPI(title="Continuity", description="AI Video Bridging Service")
 app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
+
 os.makedirs("outputs", exist_ok=True)
 app.mount("/outputs", StaticFiles(directory="outputs"), name="outputs")
 
@@ -42,19 +43,26 @@ def read_root():
 def analyze_endpoint(video_a: UploadFile = File(...), video_c: UploadFile = File(...)):
     try:
         rid = str(uuid.uuid4())
-        ext_a = os.path.splitext(video_a.filename)[1] or ".mp4"
-        ext_c = os.path.splitext(video_c.filename)[1] or ".mp4"
-        pa = os.path.join("outputs", f"{rid}_a{ext_a}")
-        pc = os.path.join("outputs", f"{rid}_c{ext_c}")
+        pa = os.path.join("outputs", f"{rid}_a.mp4")
+        pc = os.path.join("outputs", f"{rid}_c.mp4")
+        
         with open(pa, "wb") as b:
             shutil.copyfileobj(video_a.file, b)
         with open(pc, "wb") as b:
             shutil.copyfileobj(video_c.file, b)
-        
+            
         res = analyze_only(os.path.abspath(pa), os.path.abspath(pc), job_id=rid)
+        
         if res.get("status") == "error":
             raise HTTPException(500, res.get("detail"))
-        return {"prompt": res["prompt"], "video_a_path": os.path.abspath(pa), "video_c_path": os.path.abspath(pc)}
+            
+        return {
+            "analysis_a": res.get("analysis_a"),
+            "analysis_c": res.get("analysis_c"),
+            "prompt": res["prompt"],
+            "video_a_path": os.path.abspath(pa),
+            "video_c_path": os.path.abspath(pc)
+        }
     except Exception as e:
         raise HTTPException(500, str(e))
 
@@ -71,9 +79,11 @@ async def generate_endpoint(
 ):
     if not os.path.exists(video_a_path) or not os.path.exists(video_c_path):
         raise HTTPException(400, "Videos not found.")
+        
     job_id = str(uuid.uuid4())
     with open(f"outputs/{job_id}.json", "w") as f:
         json.dump({"status": "queued", "progress": 0, "log": "Queued..."}, f)
+        
     await job_queue.add_job(generate_only, prompt, video_a_path, video_c_path, job_id, style, audio_prompt, negative_prompt, guidance_scale, motion_strength)
     return {"job_id": job_id}
 

stitch_continuity_dashboard/code.html

@@ -113,7 +113,8 @@
     </header>
 
     <!-- Main Stage: Scrollable Content -->
-    <main class="flex-1 w-full overflow-y-auto relative flex flex-col items-center pt-8 pb-32">
+    <!-- FIX: Increased padding bottom to pb-[32rem] (~512px) to clear floating controls -->
+    <main class="flex-1 w-full overflow-y-auto relative flex flex-col items-center pt-8 pb-[32rem]">
         <div class="w-full max-w-6xl mx-auto flex items-center justify-center gap-4 md:gap-8 lg:gap-12 px-4">
 
             <!-- SCENE A -->
@@ -224,8 +225,23 @@
                         class="text-xs text-gray-500 hover:text-white uppercase tracking-wider">Reset</button>
                 </div>
             </div>
+
+            <!-- NEW: Structured Analysis Display -->
+            <div class="grid grid-cols-2 gap-4 mb-2">
+                <div class="bg-white/5 p-2 rounded-lg border border-white/10">
+                    <span class="text-[9px] font-bold text-primary uppercase">Scene A Analysis</span>
+                    <p id="analysis-a-text" class="text-[10px] text-gray-300 h-10 overflow-y-auto mt-1 leading-tight">
+                        Waiting for analysis...</p>
+                </div>
+                <div class="bg-white/5 p-2 rounded-lg border border-white/10">
+                    <span class="text-[9px] font-bold text-primary uppercase">Scene C Analysis</span>
+                    <p id="analysis-c-text" class="text-[10px] text-gray-300 h-10 overflow-y-auto mt-1 leading-tight">
+                        Waiting for analysis...</p>
+                </div>
+            </div>
+
             <div><label class="text-[10px] font-bold text-gray-500 uppercase tracking-widest mb-1 block">Visual
-                    Direction</label><textarea id="prompt-box" rows="4"
+                    Direction (Bridge B)</label><textarea id="prompt-box" rows="3"
                     class="w-full bg-black/20 border border-white/10 rounded-lg p-3 text-sm text-white focus:border-primary focus:ring-1 focus:ring-primary outline-none resize-none"></textarea>
             </div>
             <div class="grid grid-cols-2 gap-4">
@@ -370,6 +386,11 @@
             document.getElementById("analysis-panel").classList.remove("hidden");
             document.getElementById("review-panel").classList.add("hidden");
             document.getElementById("prompt-box").value = "";
+
+            // Reset Analysis Fields
+            document.getElementById("analysis-a-text").innerText = "Waiting for analysis...";
+            document.getElementById("analysis-c-text").innerText = "Waiting for analysis...";
+
             currentVideoAPath = "";
             currentVideoCPath = "";
 
@@ -393,6 +414,11 @@
                 const res = await fetch("/analyze", { method: "POST", body: fd });
                 const data = await res.json();
                 document.getElementById("prompt-box").value = data.prompt;
+
+                // Populate Analysis Fields
+                document.getElementById("analysis-a-text").innerText = data.analysis_a || "No details found.";
+                document.getElementById("analysis-c-text").innerText = data.analysis_c || "No details found.";
+
                 currentVideoAPath = data.video_a_path;
                 currentVideoCPath = data.video_c_path;
                 document.getElementById("analysis-panel").classList.add("hidden");