Update app.py

app.py

@@ -384,8 +384,7 @@ def extract_functions(gemini_output):
 
 def validate_and_generate_documentation(api_url, headers, gemini_output, file_contents, functionality_description):
     """
-    Uses the Hugging Face Inference API to generate documentation based on Gemini output.
-    Ensures that the output matches the expected format without unnecessary details.
+    Uses the Hugging Face Inference API to generate complete documentation without truncation or prompts.
     """
     # Generate the refined prompt for the Qwen model
     prompt = f"""
@@ -421,27 +420,42 @@ def validate_and_generate_documentation(api_url, headers, gemini_output, file_co
     """
 
     # Send the prompt to the Hugging Face API
-    payload = {"inputs": prompt}
+    payload = {"inputs": prompt, "parameters": {"max_new_tokens": 2048}}
     response = requests.post(api_url, headers=headers, json=payload)
 
-    # Handle the API response
     if response.status_code == 200:
         api_response = response.json()
-        if isinstance(api_response, list):  # If response is a list, extract the first element
-            output = api_response[0].get("generated_text", "No output generated.")
-        elif isinstance(api_response, dict):  # Handle dict response
-            output = api_response.get("generated_text", "No output generated.")
-        else:
-            raise ValueError("Unexpected response format from Hugging Face API.")
-        
-        # Clean the output to exclude any unnecessary details
-        return output
-    else:
-        raise ValueError(f"Error: {response.status_code}, {response.text}")
+        full_output = ""
+
+        # Handle multi-part outputs by looping until all content is retrieved
+        while isinstance(api_response, list) or isinstance(api_response, dict):
+            if isinstance(api_response, list):
+                output = api_response[0].get("generated_text", "")
+            elif isinstance(api_response, dict):
+                output = api_response.get("generated_text", "")
+            else:
+                break
 
+            full_output += output
 
+            # If the response indicates more content, request the next chunk
+            if "end_of_text" in output or len(output.strip()) == 0:
+                break
 
+            # Prepare the payload for continuation
+            payload = {"inputs": full_output, "parameters": {"max_new_tokens": 2048}}
+            response = requests.post(api_url, headers=headers, json=payload)
 
+            if response.status_code == 200:
+                api_response = response.json()
+            else:
+                raise ValueError(f"Error during continuation: {response.status_code}, {response.text}")
+
+        # Clean the output to exclude prompts
+        cleaned_output = clean_output(full_output)
+        return cleaned_output
+    else:
+        raise ValueError(f"Error: {response.status_code}, {response.text}")
 
 def generate_documentation_page():
     st.subheader(f"Generate Documentation for {st.session_state.current_project}")
@@ -494,6 +508,7 @@ def generate_documentation_page():
 
 
 
+
 #------------------------------------------------------------------------------------------------------------------------------------------------------------------------