Update app.py

app.py

@@ -391,8 +391,8 @@ def validate_and_generate_documentation(api_url, headers, gemini_output, functio
     """
     Uses the Hugging Face Inference API to generate clean and relevant documentation using Qwen.
     """
-    # Clean Gemini output
     cleaned_gemini_output = extract_cleaned_gemini_output(gemini_output)
+    gemini_output_length = len(cleaned_gemini_output)  # Record the length of the cleaned Gemini output
 
     # Generate the refined prompt for Qwen
     prompt = f"""
@@ -433,7 +433,6 @@ def validate_and_generate_documentation(api_url, headers, gemini_output, functio
     5. Return only the required information for the above tasks, and exclude everything else.
     """
 
-    # Prepare payload and call API
     payload = {"inputs": prompt, "parameters": {"max_new_tokens": 1024}}
     response = requests.post(api_url, headers=headers, json=payload)
 
@@ -441,7 +440,11 @@ def validate_and_generate_documentation(api_url, headers, gemini_output, functio
     if response.status_code == 200:
         api_response = response.json()
         output = api_response.get("generated_text", "") if isinstance(api_response, dict) else api_response[0].get("generated_text", "")
-        return clean_output(output)
+
+        # Remove the Gemini content from the top of the Qwen output
+        trimmed_output = output[gemini_output_length:].strip()
+
+        return clean_output(trimmed_output)  # Final cleanup if necessary
     else:
         raise ValueError(f"Error during API call: {response.status_code}, {response.text}")