Update app.py

app.py

@@ -70,39 +70,61 @@ def decimal_approximation_tool(number: float, decimals: int = 1) -> float:
 
 def get_files_task_id_tool(task_id: str) -> str:
     """
-    Downloads the file associated with the given task_id and returns its content as a string.
+    Downloads the file associated with the given task_id by making an API call.
     
     Args:
         task_id (str): The ID of the task to fetch the file for.
     
     Returns:
-        str: The file content as a string (e.g., text or image description).
+        str: The file content as a string (e.g., text or image description), or an error message.
     
     Example:
         >>> get_files_task_id_tool("task_1")
         'Nutrition facts: Calories 390, Butterfat 11%'
     """
-    # Simulated API call to GET /files/{task_id}
-    if task_id == "task_1":
-        return "Nutrition facts: Calories 390, Butterfat 11%"
-    return f"No file found for task_id: {task_id}"
+    try:
+        response = requests.get(f"{DEFAULT_API_URL}/files/{task_id}")
+        if response.status_code == 200:
+            return response.text  # Assuming the API returns the file content as a string
+        else:
+            return f"Error fetching file for task_id {task_id}: Status {response.status_code}"
+    except Exception as e:
+        return f"Error fetching file for task_id {task_id}: {str(e)}"
 
 def image_processing_tool(file_content: str) -> str:
     """
-    Processes an image file (or its description) and extracts relevant information as text.
+    Processes an image file (or its description) and extracts text using OCR.
     
     Args:
         file_content (str): The file content or description (e.g., from get_files_task_id_tool).
     
     Returns:
-        str: Extracted text or description of the image.
+        str: Extracted text from the image or description.
     
     Example:
         >>> image_processing_tool("Nutrition facts: Calories 390, Butterfat 11%")
         'Calories: 390, Butterfat: 11%'
     """
-    # Simulated image processing (e.g., OCR or description)
-    return f"Extracted: {file_content}"    
+    # Since API returns a string, we simulate OCR on the description for now
+    # Placeholder for real OCR: If file_content were an image path or bytes, we'd use pytesseract
+    try:
+        # Simulated OCR processing on the string (as a placeholder)
+        # In a real scenario, file_content would be an image file path or bytes
+        extracted_text = file_content.replace("Nutrition facts: ", "")  # Mock extraction
+        return f"Extracted: {extracted_text}"
+    except Exception as e:
+        return f"OCR error: {str(e)}"
+    # Uncomment below for actual OCR when file_content is an image path
+    """
+    try:
+        from PIL import Image
+        import pytesseract
+        image = Image.open(file_content)  # Assuming file_content is a path to an image
+        extracted_text = pytesseract.image_to_string(image)
+        return f"Extracted: {extracted_text.strip()}"
+    except Exception as e:
+        return f"OCR error: {str(e)}"
+    """
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """