Update app.py

app.py

@@ -28,29 +28,29 @@ url = 'https://agents-course-unit4-scoring.hf.space/questions'
 headers = {'accept': 'application/json'}
 response = requests.get(url, headers=headers)
 
-class responses_api(BaseAgent):
-    async def _run_async_impl(self, ctx: InvocationContext)-> AsyncGenerator[Event, None]:
-        # This method is called when the agent is run
-        # You can implement your logic here
-        # For example, you can call an external API or perform some calculations
-        # and return the result
-        url = 'https://agents-course-unit4-scoring.hf.space/questions'
-        headers = {'accept': 'application/json'}
-        response = requests.get(url, headers=headers)
-        for i in response.json():
-            if i['file_name'] != '':
-                url_file = f"https://agents-course-unit4-scoring.hf.space/files/{i['task_id']}"
-                question = i['question']
-                prompt = f"{question} and the file is {url_file}, give the final answer only"
-            else:
-                question = i['question']
-                prompt = f"{question} give the final answer only"
-            existing_responses = ctx.session.state.get("user:responses", [])
-            existing_responses.append(prompt)
-            ctx.session_state["user:responses"] = existing_responses
-
-            # Optionally, yield a single event to indicate completion or provide some output
-            yield Event(author=self.name, content=types.Content(parts=[types.Part(text=f"Fetched {len(questions_data)} questions.")]))
+# class responses_api(BaseAgent):
+#     async def _run_async_impl(self, ctx: InvocationContext)-> AsyncGenerator[Event, None]:
+#         # This method is called when the agent is run
+#         # You can implement your logic here
+#         # For example, you can call an external API or perform some calculations
+#         # and return the result
+#         url = 'https://agents-course-unit4-scoring.hf.space/questions'
+#         headers = {'accept': 'application/json'}
+#         response = requests.get(url, headers=headers)
+#         for i in response.json():
+#             if i['file_name'] != '':
+#                 url_file = f"https://agents-course-unit4-scoring.hf.space/files/{i['task_id']}"
+#                 question = i['question']
+#                 prompt = f"{question} and the file is {url_file}, give the final answer only"
+#             else:
+#                 question = i['question']
+#                 prompt = f"{question} give the final answer only"
+#             existing_responses = ctx.session.state.get("user:responses", [])
+#             existing_responses.append(prompt)
+#             ctx.session_state["user:responses"] = existing_responses
+
+#             # Optionally, yield a single event to indicate completion or provide some output
+#             yield Event(author=self.name, content=types.Content(parts=[types.Part(text=f"Fetched {len(questions_data)} questions.")]))
 
 
 
@@ -162,9 +162,9 @@ image_agent = LlmAgent(
     "Get the image file from the link associated in the prompt use Gemini to watch the video and answer the provided question ")
 
 ,
-    tools=[google_search], 
-    # Add the responses_api agent as a tool
-    sub_agents=[responses_api]
+    # tools=[google_search], 
+    # # Add the responses_api agent as a tool
+    # sub_agents=[responses_api]
 )
 
 
@@ -205,24 +205,24 @@ root_agent = LlmAgent(
     sub_agents=[responses_api]
 )
 
-root_agent = LlmAgent(
-    name='gaiaAgent',
-    model="gemini-2.5-pro-preview-05-06",
-    description=(
-        "You are a smart agent that can answer any questions provided access the given files and answer"
-    ),
-    instruction = (
-    "You are a helpful agent. When the user asks to get the questions or makes a similar request, "
-    "invoke base agent. "
-    "Once you the answers check if are in correct format. "
-    #"Collect all such dictionaries in a list (do not include any backslashes), and pass this list to the 'submit_api' tool to submit the answers."
-)
-
-,
-    #tools=[submit_api], 
-    # Add the responses_api agent as a tool
-    sub_agents=[base_agent]
-)
+# root_agent = LlmAgent(
+#     name='gaiaAgent',
+#     model="gemini-2.5-pro-preview-05-06",
+#     description=(
+#         "You are a smart agent that can answer any questions provided access the given files and answer"
+#     ),
+#     instruction = (
+#     "You are a helpful agent. When the user asks to get the questions or makes a similar request, "
+#     "invoke base agent. "
+#     "Once you the answers check if are in correct format. "
+#     #"Collect all such dictionaries in a list (do not include any backslashes), and pass this list to the 'submit_api' tool to submit the answers."
+# )
+
+# ,
+#     #tools=[submit_api], 
+#     # Add the responses_api agent as a tool
+#     sub_agents=[base_agent]
+# )
 
 session_service = InMemorySessionService()
 session = session_service.create_session(app_name=APP_NAME, \