diff --git a/examples/agno/agno_basic_agents.py b/examples/agno/agno_basic_agents.py index 25a0cd41f..1a7227125 100644 --- a/examples/agno/agno_basic_agents.py +++ b/examples/agno/agno_basic_agents.py @@ -68,11 +68,10 @@ def demonstrate_basic_agents(): ) # Create a team with coordination mode - # The "coordinate" mode allows agents to work together and share information + # The team allows agents to work together and share information team = Team( - name="News and Weather Team", - mode="coordinate", # Agents will coordinate their responses members=[news_agent, weather_agent], + name="News and Weather Team", ) # Run a task that requires team coordination diff --git a/examples/agno/agno_research_team.py b/examples/agno/agno_research_team.py index 8fbb89a7a..f5932e00e 100644 --- a/examples/agno/agno_research_team.py +++ b/examples/agno/agno_research_team.py @@ -167,15 +167,14 @@ def demonstrate_research_team(): # Create collaborative team with advanced features agent_team = Team( - name="Discussion Team", - mode="collaborate", - model=OpenAIChat("gpt-4o"), members=[ reddit_researcher, hackernews_researcher, academic_paper_researcher, twitter_researcher, ], + name="Discussion Team", + model=OpenAIChat("gpt-4o"), instructions=[ "You are a discussion master coordinating a research team.", "Facilitate productive discussion between all researchers.", @@ -183,10 +182,6 @@ def demonstrate_research_team(): "Guide the team towards a comprehensive understanding of the topic.", "You have to stop the discussion when you think the team has reached a consensus.", ], - success_criteria="The team has reached a consensus with insights from all perspectives.", - enable_agentic_context=True, - add_context=True, - show_tool_calls=True, markdown=True, debug_mode=True, show_members_responses=True, diff --git a/examples/agno/agno_workflow_setup.py b/examples/agno/agno_workflow_setup.py index a2d21967e..7c82556d0 100644 --- a/examples/agno/agno_workflow_setup.py +++ b/examples/agno/agno_workflow_setup.py @@ -15,7 +15,7 @@ """ -from agno.agent import Agent, RunResponse +from agno.agent import Agent, RunOutput import agentops from dotenv import load_dotenv from agno.workflow import Workflow @@ -52,7 +52,7 @@ class CacheWorkflow(Workflow): # This agent will be used to generate responses when cache misses occur agent = Agent(model=OpenAIChat(id="gpt-4o-mini"), description="General purpose agent for generating responses") - def run(self, message: str) -> Iterator[RunResponse]: + def run(self, message: str) -> Iterator[RunOutput]: """ Execute the workflow with caching logic. @@ -66,14 +66,14 @@ def run(self, message: str) -> Iterator[RunResponse]: message: The input query to process Yields: - RunResponse: Streamed response chunks + RunOutput: Streamed response chunks """ logger.info(f"Checking cache for '{message}'") if self.session_state.get(message): logger.info(f"Cache hit for '{message}'") # Return cached response immediately (no API call needed) - yield RunResponse(run_id=self.run_id, content=self.session_state.get(message)) + yield RunOutput(run_id=self.run_id, content=self.session_state.get(message)) return logger.info(f"Cache miss for '{message}'") @@ -99,11 +99,11 @@ def demonstrate_workflows(): try: workflow = CacheWorkflow() - response: Iterator[RunResponse] = workflow.run(message="Tell me a joke.") + response: Iterator[RunOutput] = workflow.run(message="Tell me a joke.") pprint_run_response(response, markdown=True, show_time=True) - response: Iterator[RunResponse] = workflow.run(message="Tell me a joke.") + response: Iterator[RunOutput] = workflow.run(message="Tell me a joke.") pprint_run_response(response, markdown=True, show_time=True) diff --git a/examples/agno/requirements.txt b/examples/agno/requirements.txt index 58d6a0cfd..5aff48e37 100644 --- a/examples/agno/requirements.txt +++ b/examples/agno/requirements.txt @@ -5,4 +5,4 @@ googlesearch-python pycountry arxiv pypdf -duckduckgo-search \ No newline at end of file +ddgs