Update app.py

app.py

@@ -13,7 +13,6 @@ from google.genai import types as genai_types
 from google.adk.tools import ToolContext, FunctionTool
 import logging
 #from google.adk.tools import built_in_code_execution
-from google.adk.code_executors import BuiltInCodeExecutor
 from google.adk.tools import agent_tool
 
 
@@ -24,35 +23,34 @@ from google.adk.tools import agent_tool
 
 
 logging.basicConfig(level=logging.ERROR)
-from google.adk.tools import agent_tool
+#from google.adk.tools import agent_tool
 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(response.json())} 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."))])
 
 
 
@@ -95,14 +93,14 @@ def submit_questions(answers: list[str]) -> Dict[str, Any]:
 responses_api = FunctionTool(func= answer_questions)
 submit_api = FunctionTool(func=submit_questions)
 
-class QuestionAnswerer(LlmAgent):
-    async def _run_async_impl(self, ctx: InvocationContext) -> AsyncGenerator[Event, None]:
-        questions_to_answer = ctx.session_service.get('fetched_questions', [])
-        for q in questions_to_answer:
-            answer = await self._llm(messages=[types.ChatMessage(role="user", parts=[types.Part(text=q)])])
-            yield Event(author=self.name, content=answer.content)
+# class QuestionAnswerer(LlmAgent):
+#     async def _run_async_impl(self, ctx: InvocationContext) -> AsyncGenerator[Event, None]:
+#         questions_to_answer = ctx.session_service.get('fetched_questions', [])
+#         for q in questions_to_answer:
+#             answer = await self._llm(messages=[types.ChatMessage(role="user", parts=[types.Part(text=q)])])
+#             yield Event(author=self.name, content=answer.content)
 
-qa = QuestionAnswerer(name = 'qa_1', model="gemini-2.0-flash", description="Question Answerer")
+# qa = QuestionAnswerer(name = 'qa_1', model="gemini-2.0-flash", description="Question Answerer")
 
 
 
@@ -132,9 +130,9 @@ code_agent = LlmAgent(
 )
 
 ,
-    #tools=[built_in_code_execution], 
+    # tools=[built_in_code_execution], 
     # Add the responses_api agent as a tool
-    sub_agents=[responses_api]
+    #sub_agents=[responses_api]
 )
 
 
@@ -151,7 +149,7 @@ search_agent = LlmAgent(
 ,
     tools=[google_search], 
     # Add the responses_api agent as a tool
-    sub_agents=[responses_api]
+    #sub_agents=[responses_api]
 )
 
 image_agent = LlmAgent(
@@ -162,8 +160,11 @@ image_agent = LlmAgent(
     ),
     instruction = (
     "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], sub_agents=[responses_api]
+   # tools=[google_search], 
+    # Add the responses_api agent as a tool
+    #sub_agents=[responses_api]
 )
 
 
@@ -177,7 +178,9 @@ youtube_agent = LlmAgent(
     "Get the youtube link associated use Gemini to watch the video and answer the provided question ")
 
 ,
-   tools=[google_search], sub_agents=[responses_api]
+   # tools=[google_search], 
+    # Add the responses_api agent as a tool
+    #sub_agents=[responses_api]
 )
 
 root_agent = LlmAgent(
@@ -199,27 +202,27 @@ root_agent = LlmAgent(
     tools=[responses_api,submit_api,agent_tool.AgentTool(agent = code_agent),\
            agent_tool.AgentTool(agent = search_agent), agent_tool.AgentTool(youtube_agent), agent_tool.AgentTool(image_agent)], 
     # Add the responses_api agent as a tool
-    sub_agents=[responses_api]
+    #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, \
@@ -227,16 +230,16 @@ session = session_service.create_session(app_name=APP_NAME, \
                                         session_id=SESSION_ID)
 
 runner = Runner(agent=root_agent, app_name=APP_NAME, session_service=session_service)
-def send_query_to_agent(root_agent, query, session):
-    session = session
-    content = types.Content(role='user', parts=[types.Part(text=query)])
+# # def send_query_to_agent(root_agent, query, session):
+# #     session = session
+# #     content = types.Content(role='user', parts=[types.Part(text=query)])
 
 
 
 
-async def main():
-    await process_questions_and_answer()
+# # async def main():
+# #     await process_questions_and_answer()
 
-if __name__ == "__main__":
-    import asyncio
-    asyncio.run(main())
+# # if __name__ == "__main__":
+# #     import asyncio
+# #     asyncio.run(main())