Update app.py

app.py

@@ -9,7 +9,7 @@ import re
 from huggingface_hub import hf_hub_download
 import tempfile
 import numpy as np
-from typing import List, Tuple, Dict, Any # REQUIRED FOR MCP
+from typing import List, Tuple, Dict, Any
 
 # --- 1. CONFIGURATION & SECRETS ---
 GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
@@ -164,31 +164,19 @@ except Exception as e:
     model = None
 
 # --- 5. MAIN UI PIPELINE (Orchestrator) ---
+# Used for the Web Interface (Returns complex Objects)
 
 def process_pipeline(image, conf_threshold):
-    """
-    Main function used by the Web UI. 
-    Chains detection -> analytics -> translation.
-    """
     if image is None: return None, "", "", None, "", None, []
     if model is None: return None, "Error: Model not loaded.", "", None, "", None, []
 
     try:
-        # 1. Detect
         img_w, img_h = image.size
         annotated_img, detections, crops = core_detect(image, conf_threshold)
-        
-        # 2. Extract Keywords
         unique_codes = list(set([d['code'] for d in detections]))
         mapped_words = [gardiner_map.get(code, f"[{code}]") for code in unique_codes]
-        
-        # 3. Translate
         mystical, academic = core_translate(mapped_words)
-        
-        # 4. Analytics
         analytics_plot = core_analytics(detections, img_w, img_h)
-        
-        # 5. Reports
         text_report = f"Total Symbols: {len(detections)}\nUnique Codes: {', '.join(unique_codes)}"
         json_output = {"count": len(detections), "detections": detections}
         formatted_mystical = f"""<div class="mystical-container"><h3>✨ THE ANCIENT WHISPER</h3><p>{mystical}</p></div>"""
@@ -198,40 +186,53 @@ def process_pipeline(image, conf_threshold):
     except Exception as e:
         return None, f"System Failure: {str(e)}", "", None, str(e), None, []
 
-# --- 6. MCP API FUNCTIONS (Granular & Typed) ---
-# IMPORTANT: These functions use Type Hints so Gradio knows how to define the MCP Tool.
+# --- 6. MCP API FUNCTIONS (Optimized for Claude) ---
+# Changes: Short Names, File Path Returns (No Base64)
 
-def api_detect_only(image: Image.Image, conf: float = 0.25) -> Tuple[Image.Image, Any]:
-    """API: Returns JSON detection data and annotated image."""
+def api_detect(image: Image.Image, conf: float = 0.25) -> Tuple[str, Dict[str, Any]]:
+    """
+    detect: Scans image for hieroglyphs. 
+    Returns: 1. File path to the annotated image. 2. JSON summary of findings.
+    """
     ann_img, dets, _ = core_detect(image, conf)
-    return ann_img, {"count": len(dets), "detections": dets}
+    
+    # SAVE to temp file and return PATH string
+    with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as t:
+        ann_img.save(t.name)
+        path = t.name
+        
+    return path, {"count": len(dets), "detections": dets}
 
-def api_translate_only(keywords_text: str) -> Tuple[str, str]:
-    """API: Translates a comma-separated string of keywords."""
+def api_translate(keywords_text: str) -> Tuple[str, str]:
+    """
+    translate: Takes comma-separated codes (e.g. 'G43, X1'). Returns Mystical & Academic text.
+    """
     if isinstance(keywords_text, str):
         keywords = [k.strip() for k in keywords_text.split(',')]
     else:
         keywords = ["Unknown"]
     mystical, academic = core_translate(keywords)
-    # Strip HTML tags for clean API text
     clean_mystical = re.sub('<[^<]+?>', '', mystical) 
     return clean_mystical, academic
 
-def api_get_supported_codes() -> Dict[str, Any]:
-    """API: Returns the full Gardiner list."""
-    return gardiner_data
-
-def api_get_analytics(json_data: Dict[str, Any]) -> Image.Image:
-    """API: Generates a plot Image from JSON detection data."""
-    # MCP cannot display interactive plots, so we convert to Image
+def api_analytics(json_data: Dict[str, Any]) -> str:
+    """
+    analytics: Takes JSON detection data. 
+    Returns: File path to the generated statistical chart image.
+    """
     dets = json_data.get("detections", [])
     fig = core_analytics(dets, 1000, 1000)
     
-    # Save figure to buffer and reload as PIL Image
-    buf = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
-    fig.savefig(buf.name, format='png', facecolor='#0f0f23')
+    # SAVE to temp file and return PATH string
+    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as t:
+        fig.savefig(t.name, format='png', facecolor='#0f0f23')
+        path = t.name
     plt.close(fig)
-    return Image.open(buf.name)
+    return path
+
+def api_list_codes() -> Dict[str, Any]:
+    """list_codes: Returns the full supported Gardiner code database."""
+    return gardiner_data
 
 # --- 7. HTML GENERATORS ---
 
@@ -408,50 +409,50 @@ with gr.Blocks(title="Rosetta Decoder Ultimate") as demo:
     gr.HTML(trail_script)
     
     # --- Hidden API Buttons for MCP (Granular Access) ---
-    # These buttons are not visible in the UI but expose the API endpoints for Claude
-    # We call the TYPED functions here so Gradio registers the tool correctly.
+    # These buttons define the TOOLS for Claude.
+    # Note: We output 'gr.Textbox' for images now, so it returns the FILE PATH string.
     
     with gr.Column(visible=False):
-        # 1. Detect Only
-        btn_mcp_detect = gr.Button("MCP Detect")
-        api_detect_out_img = gr.Image()
+        # 1. Detect (Returns Path & JSON)
+        btn_mcp_detect = gr.Button("Detect")
+        api_detect_out_path = gr.Textbox()
         api_detect_out_json = gr.JSON()
         btn_mcp_detect.click(
-            fn=api_detect_only, 
+            fn=api_detect, 
             inputs=[gr.Image(label="Input Image"), gr.Number(value=0.25, label="Conf")], 
-            outputs=[api_detect_out_img, api_detect_out_json], 
-            api_name="detect_hieroglyphs"
+            outputs=[api_detect_out_path, api_detect_out_json], 
+            api_name="detect" # Short name
         )
 
-        # 2. Translate Only
-        btn_mcp_trans = gr.Button("MCP Translate")
+        # 2. Translate
+        btn_mcp_trans = gr.Button("Translate")
         api_trans_out_mystical = gr.Textbox()
         api_trans_out_academic = gr.Textbox()
         btn_mcp_trans.click(
-            fn=api_translate_only, 
+            fn=api_translate, 
             inputs=[gr.Textbox(label="Keywords")], 
             outputs=[api_trans_out_mystical, api_trans_out_academic], 
-            api_name="translate_hieroglyphs"
+            api_name="translate" # Short name
         )
 
-        # 3. Analytics Only (Returns IMAGE for MCP)
-        btn_mcp_analytics = gr.Button("MCP Analytics")
-        api_analytics_out = gr.Image() # Changed to Image for MCP
+        # 3. Analytics (Returns Path)
+        btn_mcp_analytics = gr.Button("Analytics")
+        api_analytics_out_path = gr.Textbox() 
         btn_mcp_analytics.click(
-            fn=api_get_analytics, 
+            fn=api_analytics, 
             inputs=[gr.JSON(label="Data")], 
-            outputs=[api_analytics_out], 
-            api_name="get_analytics"
+            outputs=[api_analytics_out_path], 
+            api_name="analytics" # Short name
         )
 
         # 4. Get List
-        btn_mcp_list = gr.Button("MCP List")
+        btn_mcp_list = gr.Button("List")
         api_list_out = gr.JSON()
         btn_mcp_list.click(
-            fn=api_get_supported_codes, 
+            fn=api_list_codes, 
             inputs=[], 
             outputs=[api_list_out], 
-            api_name="get_supported_codes"
+            api_name="list_codes"
         )
 
     # --- Visible UI ---
@@ -496,7 +497,7 @@ with gr.Blocks(title="Rosetta Decoder Ultimate") as demo:
         # TAB 3: SETUP
         with gr.TabItem("🤖 SYSTEM SETUP"):
             gr.HTML(guide_html)
-            # Expanded code box as requested
+            # Expanded Code Box
             gr.Code(value=claude_json_content, language="json", label="claude_desktop_config.json", interactive=False, lines=30)
 
         # TAB 4: GARDINER CODES