Update app.py

app.py

@@ -116,10 +116,21 @@ PIPELINE_CONFIGS = {
 }
 
 @spaces.GPU
-def process_htr(image_path: str, document_type: Literal["letter_english", "letter_swedish", "spread_english", "spread_swedish"] = "letter_english", output_format: Literal["txt", "alto", "page", "json"] = DEFAULT_OUTPUT, custom_settings: Optional[str] = None):
-    """Process handwritten text recognition and return extracted text with specified format file."""
-    if image_path is None:
-        return "Error: No image provided", None
+def process_htr(image_path: str, document_type: Literal["letter_english", "letter_swedish", "spread_english", "spread_swedish"] = "letter_swedish", output_format: Literal["txt", "alto", "page", "json"] = DEFAULT_OUTPUT, custom_settings: Optional[str] = None) -> str:
+    """
+    Process handwritten text recognition and return extracted text with specified format file.
+    
+    Args:
+        image_path (str): Path to the image file to process
+        document_type (str): Type of document processing template to use
+        output_format (str): Output format for the processed file
+        custom_settings (str): Optional custom pipeline settings as JSON
+        
+    Returns:
+        str: The path to the output file or error message
+    """
+    if not image_path:
+        return "Error: No image provided"
 
     try:
         original_filename = Path(image_path).stem or "output"
@@ -128,7 +139,7 @@ def process_htr(image_path: str, document_type: Literal["letter_english", "lette
             try:
                 config = json.loads(custom_settings)
             except json.JSONDecodeError:
-                return "Error: Invalid JSON in custom_settings parameter", None
+                return "Error: Invalid JSON in custom_settings parameter"
         else:
             config = PIPELINE_CONFIGS[document_type]
 
@@ -138,7 +149,7 @@ def process_htr(image_path: str, document_type: Literal["letter_english", "lette
         try:
             processed_collection = pipeline.run(collection)
         except Exception as pipeline_error:
-            return f"Error: Pipeline execution failed: {str(pipeline_error)}", None
+            return f"Error: Pipeline execution failed: {str(pipeline_error)}"
 
         temp_dir = Path(tempfile.mkdtemp())
         export_dir = temp_dir / output_format
@@ -155,12 +166,13 @@ def process_htr(image_path: str, document_type: Literal["letter_english", "lette
                 output_file_path = new_path
                 break
         
-        extracted_text = extract_text_from_collection(processed_collection)
-
-        return extracted_text, output_file_path
+        if output_file_path and os.path.exists(output_file_path):
+            return output_file_path
+        else:
+            return "Error: Failed to generate output file"
         
     except Exception as e:
-        return f"Error: HTR processing failed: {str(e)}", None
+        return f"Error: HTR processing failed: {str(e)}"
 
 def extract_text_from_collection(collection: Collection) -> str:
     text_lines = []
@@ -175,20 +187,17 @@ def create_htrflow_mcp_server():
         fn=process_htr,
         inputs=[
             gr.Image(type="filepath", label="Upload Image or Enter URL"),
-            gr.Dropdown(choices=["letter_english", "letter_swedish", "spread_english", "spread_swedish"], value="letter_english", label="Document Type"),
+            gr.Dropdown(choices=["letter_english", "letter_swedish", "spread_english", "spread_swedish"], value="letter_swedish", label="Document Type"),
             gr.Dropdown(choices=CHOICES, value=DEFAULT_OUTPUT, label="Output Format"),
-            gr.Textbox(label="Custom Settings (JSON)", placeholder="Optional custom pipeline settings"),
-        ],
-        outputs=[
-            gr.Textbox(label="Extracted Text", lines=10),
-            gr.File(label="Download Output File")
+            gr.Textbox(label="Custom Settings (JSON)", placeholder="Optional custom pipeline settings", value=""),
         ],
+        outputs=gr.File(label="Download Output File"),
         title="HTRflow MCP Server",
-        description="Process handwritten text from uploaded file or URL and get extracted text with output file in specified format",
+        description="Process handwritten text from uploaded file or URL and get output file in specified format",
         api_name="process_htr",
     )
     return demo
 
 if __name__ == "__main__":
     demo = create_htrflow_mcp_server()
-    demo.launch(mcp_server=True)
+    demo.launch(mcp_server=True, share=False, debug=True)