Update app.py

app.py

@@ -22,92 +22,68 @@ def generate_jwt_token():
     """Generate JWT token for API authentication"""
     payload = {
         "iss": ACCESS_KEY_ID,
-        "exp": int(time.time()) + 1800,  # 30 minutes expiration
-        "nbf": int(time.time()) - 5     # Not before 5 seconds ago
+        "exp": int(time.time()) + 1800,
+        "nbf": int(time.time()) - 5
     }
-    try:
-        token = jwt.encode(payload, ACCESS_KEY_SECRET, algorithm="HS256")
-        return token if isinstance(token, str) else token.decode('utf-8')
-    except Exception as e:
-        logger.error(f"JWT generation failed: {str(e)}")
-        return None
+    return jwt.encode(payload, ACCESS_KEY_SECRET, algorithm="HS256")
 
-# ===== IMAGE VALIDATION =====
-def validate_image(image_path):
-    """Check if image meets API requirements"""
+# ===== FACE VALIDATION =====
+def validate_face_image(image_path):
+    """Check if image contains exactly one face"""
     try:
-        # Check file size
+        # In production, you'd use face detection here
+        # For demo, we'll just check basic image properties
         size_mb = os.path.getsize(image_path) / (1024 * 1024)
         if size_mb > 10:
             return False, "Image too large (max 10MB)"
-        
-        # Check file extension
-        ext = os.path.splitext(image_path)[1].lower()
-        if ext not in ['.jpg', '.jpeg', '.png']:
-            return False, "Invalid format (only JPG/PNG)"
-            
         return True, ""
     except Exception as e:
         return False, f"Image validation error: {str(e)}"
 
 # ===== API FUNCTIONS =====
-def create_image_task(image_base64, prompt):
-    """Create image generation task"""
-    token = generate_jwt_token()
-    if not token:
-        return None, "Authentication failed"
-    
+def create_face_transform_task(image_base64, prompt, strength=0.97):
+    """Create face transformation task with high reference strength"""
     headers = {
-        "Authorization": f"Bearer {token}",
+        "Authorization": f"Bearer {generate_jwt_token()}",
         "Content-Type": "application/json"
     }
     
     payload = {
-        "model_name": "kling-v2",  # Recommended model
-        "prompt": prompt or "Transform into a vibrant artistic style",
+        "model_name": "kling-v2-1",  # Best for face transformation
+        "prompt": prompt,
         "image": image_base64,
-        "resolution": "1k",  # Start with 1k for faster results
+        "image_reference": "face",  # Critical for face transformation
+        "image_fidelity": strength,  # 0.97 = 97% reference strength
+        "resolution": "1k",
         "aspect_ratio": "1:1",
         "n": 1
     }
     
     try:
-        response = requests.post(
-            CREATE_TASK_ENDPOINT,
-            json=payload,
-            headers=headers,
-            timeout=30
-        )
+        response = requests.post(CREATE_TASK_ENDPOINT, json=payload, headers=headers)
         response.raise_for_status()
         return response.json(), None
     except requests.exceptions.RequestException as e:
         logger.error(f"API request failed: {str(e)}")
-        if hasattr(e, 'response') and e.response:
-            logger.error(f"API response: {e.response.text}")
-        return None, f"API request failed: {str(e)}"
+        return None, f"API Error: {str(e)}"
 
 def check_task_status(task_id):
     """Check task completion status"""
-    token = generate_jwt_token()
-    if not token:
-        return None, "Authentication failed"
-    
-    headers = {"Authorization": f"Bearer {token}"}
+    headers = {"Authorization": f"Bearer {generate_jwt_token()}"}
     status_url = f"{API_BASE_URL}/v1/images/generations/{task_id}"
     
     try:
-        response = requests.get(status_url, headers=headers, timeout=30)
+        response = requests.get(status_url, headers=headers)
         response.raise_for_status()
         return response.json(), None
     except requests.exceptions.RequestException as e:
-        logger.error(f"Status check failed: {str(e)}")
         return None, f"Status check failed: {str(e)}"
 
 # ===== MAIN PROCESSING =====
-def generate_image(image_path, prompt):
-    """Handle complete image generation workflow"""
+def transform_face(image_path, prompt, strength=0.97):
+    """Handle face transformation workflow"""
     # Validate image
-    is_valid, error_msg = validate_image(image_path)
+    is_valid, error_msg = validate_face_image(image_path)
     if not is_valid:
         return None, error_msg
     
@@ -118,8 +94,8 @@ def generate_image(image_path, prompt):
     except Exception as e:
         return None, f"Failed to process image: {str(e)}"
     
-    # Create task
-    task_response, error = create_image_task(image_base64, prompt)
+    # Create task with face reference
+    task_response, error = create_face_transform_task(image_base64, prompt, strength)
     if error:
         return None, error
     
@@ -127,10 +103,10 @@ def generate_image(image_path, prompt):
         return None, f"API error: {task_response.get('message', 'Unknown error')}"
     
     task_id = task_response["data"]["task_id"]
-    logger.info(f"Task created: {task_id}")
+    logger.info(f"Face transformation task created: {task_id}")
     
-    # Poll for results (max 10 minutes)
-    for _ in range(60):
+    # Poll for results
+    for _ in range(30):  # Max 5 minutes (10s intervals)
         task_data, error = check_task_status(task_id)
         if error:
             return None, error
@@ -140,14 +116,14 @@ def generate_image(image_path, prompt):
         if status == "succeed":
             image_url = task_data["data"]["task_result"]["images"][0]["url"]
             try:
-                response = requests.get(image_url, timeout=30)
+                response = requests.get(image_url)
                 response.raise_for_status()
-                output_path = Path(f"/tmp/kling_output_{task_id}.png")
+                output_path = Path(f"/tmp/kling_face_{task_id}.png")
                 with open(output_path, "wb") as f:
                     f.write(response.content)
                 return str(output_path), None
             except Exception as e:
-                return None, f"Failed to download result: {str(e)}"
+                return None, f"Failed to save result: {str(e)}"
                 
         elif status in ("failed", "canceled"):
             error_msg = task_data["data"].get("task_status_msg", "Unknown error")
@@ -155,55 +131,73 @@ def generate_image(image_path, prompt):
             
         time.sleep(10)
     
-    return None, "Task timed out after 10 minutes"
+    return None, "Task timed out after 5 minutes"
 
 # ===== GRADIO INTERFACE =====
-def process_interface(image, prompt):
+def process_interface(image, prompt, strength):
     if not image:
-        return None, None, "Please upload an image first"
+        return None, None, "Please upload an image with a clear face"
     
-    output_path, error = generate_image(image, prompt)
+    output_path, error = transform_face(image, prompt, strength/100)
     if error:
-        logger.error(f"Generation failed: {error}")
         return None, None, error
     
-    return output_path, output_path, "Success! Image generated"
+    return output_path, output_path, "Face transformation successful!"
 
-with gr.Blocks(title="Kling AI Image Generator") as app:
-    gr.Markdown("## 🎨 Kling AI Image-to-Image Transformation")
+with gr.Blocks(title="Kling AI Face Transformer") as app:
+    gr.Markdown("## 👤 Kling AI Face Transformation")
+    gr.Markdown("Transform faces with high precision (97% reference strength)")
     
     with gr.Row():
         with gr.Column():
             gr.Markdown("### Input Settings")
             image_input = gr.Image(
                 type="filepath",
-                label="Upload Image",
-                sources=["upload"]
+                label="Upload Face Image",
+                sources=["upload"],
+                height=300
             )
             prompt_input = gr.Textbox(
-                label="Transformation Prompt",
-                placeholder="Describe the desired style (e.g. 'watercolor painting')"
+                label="Transformation Style",
+                placeholder="Describe the new style (e.g. 'anime character', 'oil painting portrait')"
+            )
+            strength_slider = gr.Slider(
+                minimum=80,
+                maximum=100,
+                value=97,
+                step=1,
+                label="Reference Strength (%)",
+                info="Higher values preserve more facial features"
             )
-            generate_btn = gr.Button("Generate", variant="primary")
+            generate_btn = gr.Button("Transform Face", variant="primary")
             
             gr.Markdown("### Requirements")
             gr.Markdown("""
-            - **Image Requirements**:
-              - Max size: 10MB
-              - Formats: JPG, PNG
-              - Min dimensions: 300x300px
-              - Aspect ratio between 1:2.5 and 2.5:1
+            - **Must contain exactly one clear face**
+            - Max size: 10MB
+            - Formats: JPG, PNG
+            - Min resolution: 300x300px
             """)
             
         with gr.Column():
             gr.Markdown("### Output")
-            output_image = gr.Image(label="Generated Image", interactive=False)
-            output_file = gr.File(label="Download Result", file_types=["image/png"])
-            status_output = gr.Textbox(label="Status", interactive=False)
+            output_image = gr.Image(
+                label="Transformed Face", 
+                interactive=False,
+                height=400
+            )
+            output_file = gr.File(
+                label="Download Result",
+                file_types=["image/png"]
+            )
+            status_output = gr.Textbox(
+                label="Status",
+                interactive=False
+            )
     
     generate_btn.click(
         fn=process_interface,
-        inputs=[image_input, prompt_input],
+        inputs=[image_input, prompt_input, strength_slider],
         outputs=[output_image, output_file, status_output]
     )