fixed built_in_code_executors bug

app.py

@@ -12,7 +12,8 @@ from typing import AsyncGenerator
 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.tools import built_in_code_execution
+from google.adk.code_executors import BuiltInCodeExecutor
 from google.adk.tools import agent_tool
 
 
@@ -23,34 +24,34 @@ 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(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."))])
 
 
 
@@ -93,14 +94,14 @@ 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")
 
 
 
@@ -117,6 +118,7 @@ SESSION_ID="1234"
 code_agent = LlmAgent(
     name='codegaiaAgent',
     model="gemini-2.5-pro-preview-05-06",
+    code_executor=BuiltInCodeExecutor(),
     description=(
         "You are a smart agent that can write and execute code and answer any questions provided access the given files and answer"
     ),
@@ -130,9 +132,9 @@ 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]
 )
 
 
@@ -149,7 +151,7 @@ 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(
@@ -160,11 +162,8 @@ 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], 
-    # Add the responses_api agent as a tool
-    #sub_agents=[responses_api]
+   tools=[google_search], sub_agents=[responses_api]
 )
 
 
@@ -178,9 +177,7 @@ youtube_agent = LlmAgent(
     "Get the youtube link associated 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], sub_agents=[responses_api]
 )
 
 root_agent = LlmAgent(
@@ -202,27 +199,27 @@ 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."
 )
 
-# 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]
-# )
+,
+    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, \
@@ -230,16 +227,16 @@ 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())