Update app.py

app.py

@@ -54,31 +54,24 @@ def create_labeled_zip(image, detections):
     zip_path = os.path.join(tempfile.gettempdir(), "rosetta_glyphs.zip")
     
     try:
-        # Load a font (try-except block for system compatibility)
         try:
-            # Try loading a standard font, fallback to default if fails
             font = ImageFont.truetype("arial.ttf", 16)
         except IOError:
             font = ImageFont.load_default()
 
         for i, d in enumerate(detections):
-            # Crop
             box = d['box']
             crop = image.crop((box[0], box[1], box[2], box[3]))
             
-            # Prepare Label
             label_text = f"{d['code']} {int(d['confidence']*100)}%"
             draw = ImageDraw.Draw(crop)
             
-            # Calculate text size using textbbox (newer PIL versions)
             left, top, right, bottom = draw.textbbox((0, 0), label_text, font=font)
             text_w = right - left
             text_h = bottom - top
             
             img_w, img_h = crop.size
             
-            # Draw background rectangle (bottom right)
-            # Check if image is too small for label, if so, skip drawing to avoid crash
             if img_w > text_w and img_h > text_h:
                 rect_x0 = img_w - text_w - 4
                 rect_y0 = img_h - text_h - 4
@@ -88,11 +81,9 @@ def create_labeled_zip(image, detections):
                 draw.rectangle([rect_x0, rect_y0, rect_x1, rect_y1], fill="black")
                 draw.text((rect_x0 + 2, rect_y0), label_text, fill="white", font=font)
             
-            # Save crop
             filename = f"{d['code']}_{i}.png"
             crop.save(os.path.join(zip_dir, filename))
 
-        # Create Zip
         shutil.make_archive(zip_path.replace('.zip', ''), 'zip', zip_dir)
         return zip_path
         
@@ -122,7 +113,6 @@ def core_detect(image, conf_threshold):
                 conf = float(box.conf[0])
                 xyxy = box.xyxy[0].tolist()
                 
-                # Create detection object
                 detection = {
                     "code": code,
                     "description": gardiner_map.get(code, "Unknown"),
@@ -130,8 +120,6 @@ def core_detect(image, conf_threshold):
                     "box": xyxy
                 }
                 detections.append(detection)
-                
-                # Create crop (Clean crop for Gallery display)
                 crop_img = image.crop((xyxy[0], xyxy[1], xyxy[2], xyxy[3]))
                 crops.append((crop_img, f"{code}\n({int(conf*100)}%)"))
                 
@@ -239,11 +227,9 @@ def process_pipeline(image, conf_threshold):
         annotated_img, detections, crops = core_detect(image, conf_threshold)
         
         # 2. Prepare Downloads
-        # A. Annotated Image
         ann_path = os.path.join(tempfile.gettempdir(), "annotated_hieroglyphs.jpg")
         annotated_img.save(ann_path)
         
-        # B. Zip File with Labels
         zip_path = create_labeled_zip(image, detections)
         
         # 3. Extract Keywords & Translate
@@ -265,16 +251,18 @@ def process_pipeline(image, conf_threshold):
         print(f"Pipeline Error: {e}")
         return None, None, None, f"System Failure: {str(e)}", "", None, str(e), None, []
 
-# --- 6. MCP API FUNCTIONS ---
+# --- 6. MCP API FUNCTIONS (RENAMED FOR CLAUDE) ---
 
-def detect_hieroglyphs_api(image: Image.Image, conf: float = 0.25) -> Tuple[str, Dict[str, Any]]:
+def detect_glyphs(image: Image.Image, conf: float = 0.25) -> Tuple[str, Dict[str, Any]]:
+    """Detects hieroglyphs in an image. Returns path to annotated image and JSON data."""
     ann_img, dets, _ = core_detect(image, conf)
     with tempfile.NamedTemporaryFile(dir="/tmp/gradio_results", suffix=".jpg", delete=False) as t:
         ann_img.save(t.name)
         path = t.name
     return path, {"count": len(dets), "detections": dets}
 
-def translate_codes_api(keywords_text: str) -> Tuple[str, str]:
+def translate_story(keywords_text: str) -> Tuple[str, str]:
+    """Translates a list of codes or keywords into a mystical story and academic text."""
     if isinstance(keywords_text, str):
         keywords = [k.strip() for k in keywords_text.split(',')]
     else:
@@ -283,7 +271,8 @@ def translate_codes_api(keywords_text: str) -> Tuple[str, str]:
     clean_mystical = re.sub('<[^<]+?>', '', mystical) 
     return clean_mystical, academic
 
-def get_analytics_chart_api(json_data: Dict[str, Any]) -> str:
+def get_stats(json_data: Dict[str, Any]) -> str:
+    """Generates analytics charts from detection JSON. Returns path to chart image."""
     dets = json_data.get("detections", [])
     fig = core_analytics(dets, 640, 640) 
     if fig is None: return "No data."
@@ -293,7 +282,8 @@ def get_analytics_chart_api(json_data: Dict[str, Any]) -> str:
     plt.close(fig)
     return path
 
-def list_all_codes_api() -> Dict[str, Any]:
+def list_codes() -> Dict[str, Any]:
+    """Returns the full dictionary of supported Gardiner codes and descriptions."""
     return gardiner_data
 
 # --- 7. HTML GENERATORS ---
@@ -406,9 +396,10 @@ guide_html = """
 </div>
 """
 
+# CHANGED: "gradio" key changed to "Rosetta Decoder"
 claude_json_content = """{
   "mcpServers": {
-    "gradio": {
+    "Rosetta Decoder": {
       "command": "npx",
       "args": [
         "mcp-remote",
@@ -439,18 +430,19 @@ with gr.Blocks(title="Rosetta Decoder Ultimate") as demo:
     gr.HTML(trail_script)
     
     # --- MCP TOOL REGISTRATION LAYER (Hidden) ---
+    # CHANGED: Renamed API names to be short verbs (detect, translate, etc.)
     with gr.Row(visible=False):
         btn_detect = gr.Button("Detect")
-        btn_detect.click(fn=detect_hieroglyphs_api, inputs=[gr.Image(label="img"), gr.Number(label="conf")], outputs=[gr.Textbox(label="path"), gr.JSON(label="json")], api_name="detect")
+        btn_detect.click(fn=detect_glyphs, inputs=[gr.Image(label="img"), gr.Number(label="conf")], outputs=[gr.Textbox(label="path"), gr.JSON(label="json")], api_name="detect")
         
         btn_trans = gr.Button("Translate")
-        btn_trans.click(fn=translate_codes_api, inputs=[gr.Textbox(label="text")], outputs=[gr.Textbox(label="mystic"), gr.Textbox(label="academic")], api_name="translate")
+        btn_trans.click(fn=translate_story, inputs=[gr.Textbox(label="text")], outputs=[gr.Textbox(label="mystic"), gr.Textbox(label="academic")], api_name="translate")
         
         btn_anal = gr.Button("Analytics")
-        btn_anal.click(fn=get_analytics_chart_api, inputs=[gr.JSON(label="data")], outputs=[gr.Textbox(label="chart_path")], api_name="analytics")
+        btn_anal.click(fn=get_stats, inputs=[gr.JSON(label="data")], outputs=[gr.Textbox(label="chart_path")], api_name="analyze")
         
         btn_list = gr.Button("List")
-        btn_list.click(fn=list_all_codes_api, inputs=[], outputs=[gr.JSON(label="data")], api_name="list_codes")
+        btn_list.click(fn=list_codes, inputs=[], outputs=[gr.JSON(label="data")], api_name="list_codes")
 
     # --- Visible UI ---
     with gr.Row(elem_classes="header-row"):