Merge branch 'modelscope-api-refactor-8866516818649816546' into copilot/sub-pr-5

Co-authored-by: neverbiasu <90372299+neverbiasu@users.noreply.github.com>

.github/workflows/ruff.yml

@@ -1,25 +0,0 @@
-name: Ruff
-
-on:
-  push:
-    branches: ["master"]
-  pull_request:
-
-jobs:
-  ruff:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.11"
-
-      - name: Install Ruff
-        run: pip install ruff
-
-      - name: Run Ruff check
-        run: ruff check .

nodes.py

@@ -9,13 +9,9 @@ import logging
 
 BASE_URL = "https://api-inference.modelscope.cn/v1"
 
-MODELSCOPE_API_KEY = os.getenv("MODELSCOPE_API_KEY") or os.getenv(
-    "MODELSCOPE_ACCESS_TOKEN"
-)
+MODELSCOPE_API_KEY = os.getenv("MODELSCOPE_API_KEY") or os.getenv("MODELSCOPE_ACCESS_TOKEN")
 
-DEFAULT_SYSTEM_PROMPT = (
-    "You are a helpful and harmless assistant. Answer concisely and helpfully."
-)
+DEFAULT_SYSTEM_PROMPT = "You are a helpful and harmless assistant. Answer concisely and helpfully."
 
 # Constants
 PLACEHOLDER_MODEL_ID = "Model ID"
@@ -29,7 +25,7 @@ logger = logging.getLogger(__name__)
 
 class ModelScopeBase:
     """Base class for ModelScope nodes with common functionality."""
-
+    
     def _resolve_key(self, api_key: Optional[str]) -> str:
         """Resolve API key from input or environment variables."""
         key = api_key or MODELSCOPE_API_KEY
@@ -41,35 +37,41 @@ class ModelScopeBase:
 
     def _sanitize_text(self, text: str) -> str:
         """Sanitize text for ComfyUI showText node compatibility.
-
+        
         Args:
             text: Raw text string
-
+            
         Returns:
             str: Sanitized text safe for display
         """
         if not isinstance(text, str):
             text = str(text)
-
+        
+        # Remove or replace problematic characters
         import re
-
-        text = re.sub(r"[\x00-\x08\x0B\x0C\x0E-\x1F\x7F]", "", text)
-
-        text = re.sub(r"\s+", " ", text).strip()
-
+        
+        # Remove null bytes and other control characters except common ones
+        text = re.sub(r'[\x00-\x08\x0B\x0C\x0E-\x1F\x7F]', '', text)
+        
+        # Normalize whitespace
+        text = re.sub(r'\s+', ' ', text).strip()
+        
+        # Ensure text is not empty
         if not text:
             text = "[Empty Response]"
-
+        
+        # Limit length if extremely long (optional safeguard)
         max_length = 10000
         if len(text) > max_length:
             text = text[:max_length] + "...[truncated]"
-
+        
+        # Ensure proper encoding
         try:
-            text.encode("utf-8").decode("utf-8")
+            text.encode('utf-8').decode('utf-8')
         except UnicodeError:
             # Fallback: replace problematic characters
-            text = text.encode("utf-8", errors="replace").decode("utf-8")
-
+            text = text.encode('utf-8', errors='replace').decode('utf-8')
+        
         return text
 
     def _get_pil_image_module(self):
@@ -81,21 +83,22 @@ class ModelScopeBase:
 
     def _download_image_from_url(self, url: str, headers: Optional[dict] = None) -> object:
         """Download image from URL and convert to ComfyUI IMAGE format.
-
+        
         Args:
             url: Image URL to download
             headers: HTTP headers for authentication (optional)
             
         Returns:
             torch.Tensor: Image tensor in ComfyUI format [B, H, W, C]
-
+            
         Raises:
             RuntimeError: If download or conversion fails
         """
         try:
             import torch
             import numpy as np
-
+            
+            # Download image
             response = requests.get(url, headers=headers, timeout=30)
             response.raise_for_status()
             
@@ -112,18 +115,19 @@ class ModelScopeBase:
             
             # Convert PIL to numpy array
             image_np = np.array(image).astype(np.float32) / 255.0
-
+            
+            # Convert to torch tensor with ComfyUI format [B, H, W, C]
             image_tensor = torch.from_numpy(image_np)[None,]
-
+            
             return image_tensor
-
+            
         except Exception as e:
             raise RuntimeError(f"Failed to download image: {e}") from e
 
 
 class ModelScopeChatBase(ModelScopeBase):
     """Base class for chat-based ModelScope nodes."""
-
+    
     def _extract_text(self, data: dict) -> str:
         """Extract text content from chat completion response.
         Tries to read choices[0].message.content (string or list) and falls back to str(data).
@@ -218,21 +222,22 @@ class ModelScopeLLM(ModelScopeChatBase):
         request_timeout: int = 30,
     ) -> Tuple[str]:
         """Execute text generation using ModelScope LLM.
-
+        
         Args:
             model_id: ModelScope LLM model identifier
             prompt: User text prompt for the model
             system_prompt: Optional system prompt for assistant behavior
             api_key: Optional API key override
             request_timeout: Request timeout in seconds
-
+            
         Returns:
             tuple: Single-element tuple with LLM response text
-
+            
         Raises:
             ValueError: If inputs are invalid
             RuntimeError: If API call or processing fails
         """
+        # Validate inputs
         if not prompt.strip():
             raise ValueError("Prompt cannot be empty")
 
@@ -298,13 +303,13 @@ class ModelScopeLLM(ModelScopeChatBase):
 
         elapsed = time.time() - start_time
         print(f"LLM inference completed in {elapsed:.1f}s")
-
+        
         return (text,)
 
 
 class ModelScopeVLM(ModelScopeChatBase):
     """ModelScope Visual Language Model node for image-text conversations.
-
+    
     Supports analyzing images with text prompts using ModelScope VLM models.
     Handles various image input formats and provides robust error handling.
     """
@@ -312,7 +317,7 @@ class ModelScopeVLM(ModelScopeChatBase):
     @classmethod
     def INPUT_TYPES(cls):
         """Define input types and validation rules for VLM processing.
-
+        
         Returns:
             dict: Input type definitions with validation parameters
         """
@@ -388,7 +393,7 @@ class ModelScopeVLM(ModelScopeChatBase):
         request_timeout: int = 120,
     ) -> Tuple[str]:
         """Execute vision-language model inference on image and text.
-
+        
         Args:
             model_id: ModelScope VLM model identifier
             image_url: URL of image to analyze
@@ -396,25 +401,27 @@ class ModelScopeVLM(ModelScopeChatBase):
             system_prompt: Optional system prompt for assistant behavior
             api_key: Optional API key override
             request_timeout: Request timeout in seconds
-
+            
         Returns:
             tuple: Single-element tuple with VLM response text
-
+            
         Raises:
             ValueError: If inputs are invalid
             RuntimeError: If API call or processing fails
         """
+        # Validate inputs
         if not image_url.strip():
             raise ValueError("Image URL cannot be empty")
         if not prompt.strip():
             raise ValueError("Prompt cannot be empty")
-
-        if not (image_url.startswith("http://") or image_url.startswith("https://")):
+            
+        # Validate image URL format
+        if not (image_url.startswith('http://') or image_url.startswith('https://')):
             raise ValueError("Image URL must be a valid HTTP/HTTPS URL")
 
         key = self._resolve_key(api_key)
         system_prompt = system_prompt or DEFAULT_SYSTEM_PROMPT
-
+        
         url = f"{BASE_URL}/chat/completions"
         headers = {
             "Authorization": f"Bearer {key}",
@@ -456,6 +463,7 @@ class ModelScopeVLM(ModelScopeChatBase):
 
         start_time = time.time()
         try:
+            # Use longer timeout for VLM inference
             resp = requests.post(
                 url,
                 headers=headers,
@@ -486,7 +494,7 @@ class ModelScopeVLM(ModelScopeChatBase):
 
         elapsed = time.time() - start_time
         print(f"VLM inference completed in {elapsed:.1f}s")
-
+        
         return (text,)
 
 
@@ -587,7 +595,7 @@ class ModelScopeImageGenerator(ModelScopeBase):
                         "tooltip": "ModelScope API key. If empty, reads from MODELSCOPE_API_KEY env var.",
                     },
                 ),
-            },
+            }
         }
 
     RETURN_TYPES = ("IMAGE",)
@@ -611,7 +619,7 @@ class ModelScopeImageGenerator(ModelScopeBase):
         loras: Optional[str] = None,
     ) -> Tuple[object]:
         """Generate image using ModelScope API.
-
+        
         Args:
             model_id: ModelScope model identifier
             prompt: Text description of desired image
@@ -626,7 +634,7 @@ class ModelScopeImageGenerator(ModelScopeBase):
             
         Returns:
             tuple: Single-element tuple containing image tensor
-
+            
         Raises:
             RuntimeError: If API call or image processing fails
         """
@@ -679,9 +687,7 @@ class ModelScopeImageGenerator(ModelScopeBase):
             resp = requests.post(url, headers=headers_with_charset, data=data_bytes, timeout=60)
             resp.raise_for_status()
         except requests.RequestException as e:
-            raise RuntimeError(
-                f"Network error calling ModelScope Image API: {e}"
-            ) from e
+            raise RuntimeError(f"Network error calling ModelScope Image API: {e}") from e
 
         try:
             data = resp.json()