sequence_with_functions.py
"""
Sequence With Functions
=======================
Demonstrates sequencing function steps and agent/team steps with sync, async, and streaming runs.
"""
import asyncio
from textwrap import dedent
from typing import AsyncIterator, Iterator
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from agno.workflow.types import StepInput, StepOutput
from agno.workflow.workflow import Workflow
# ---------------------------------------------------------------------------
# Create Agents
# ---------------------------------------------------------------------------
web_agent = Agent(
name="Web Agent",
model=OpenAIChat(id="gpt-4o-mini"),
tools=[WebSearchTools()],
role="Search the web for the latest news and trends",
)
hackernews_agent = Agent(
name="Hackernews Agent",
model=OpenAIChat(id="gpt-4o-mini"),
tools=[HackerNewsTools()],
role="Extract key insights and content from Hackernews posts",
)
writer_agent = Agent(
name="Writer Agent",
model=OpenAIChat(id="gpt-4o-mini"),
instructions="Write a blog post on the topic",
)
# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
research_team = Team(
name="Research Team",
members=[hackernews_agent, web_agent],
instructions="Research tech topics from Hackernews and the web",
)
# ---------------------------------------------------------------------------
# Define Function Steps
# ---------------------------------------------------------------------------
def prepare_input_for_web_search_sync(step_input: StepInput) -> StepOutput:
topic = step_input.input
return StepOutput(
content=dedent(
f"""\
I'm writing a blog post on the topic
<topic>
{topic}
</topic>
Search the web for atleast 10 articles\
"""
)
)
def prepare_input_for_writer_sync(step_input: StepInput) -> StepOutput:
topic = step_input.input
research_team_output = step_input.previous_step_content
return StepOutput(
content=dedent(
f"""\
I'm writing a blog post on the topic:
<topic>
{topic}
</topic>
Here is information from the web:
<research_results>
{research_team_output}
<research_results>\
"""
)
)
def prepare_input_for_web_search_sync_stream(
step_input: StepInput,
) -> Iterator[StepOutput]:
topic = step_input.input
content = dedent(
f"""\
I'm writing a blog post on the topic
<topic>
{topic}
</topic>
Search the web for atleast 10 articles\
"""
)
yield StepOutput(content=content)
def prepare_input_for_writer_sync_stream(step_input: StepInput) -> Iterator[StepOutput]:
topic = step_input.input
research_team_output = step_input.previous_step_content
content = dedent(
f"""\
I'm writing a blog post on the topic:
<topic>
{topic}
</topic>
Here is information from the web:
<research_results>
{research_team_output}
</research_results>\
"""
)
yield StepOutput(content=content)
async def prepare_input_for_web_search_async(step_input: StepInput) -> StepOutput:
topic = step_input.input
return StepOutput(
content=dedent(
f"""\
I'm writing a blog post on the topic
<topic>
{topic}
</topic>
Search the web for atleast 10 articles\
"""
)
)
async def prepare_input_for_writer_async(step_input: StepInput) -> StepOutput:
topic = step_input.input
research_team_output = step_input.previous_step_content
return StepOutput(
content=dedent(
f"""\
I'm writing a blog post on the topic:
<topic>
{topic}
</topic>
Here is information from the web:
<research_results>
{research_team_output}
<research_results>\
"""
)
)
async def prepare_input_for_web_search_async_stream(
step_input: StepInput,
) -> AsyncIterator[StepOutput]:
topic = step_input.input
content = dedent(
f"""\
I'm writing a blog post on the topic
<topic>
{topic}
</topic>
Search the web for atleast 10 articles\
"""
)
yield StepOutput(content=content)
async def prepare_input_for_writer_async_stream(
step_input: StepInput,
) -> AsyncIterator[StepOutput]:
topic = step_input.input
research_team_output = step_input.previous_step_content
content = dedent(
f"""\
I'm writing a blog post on the topic:
<topic>
{topic}
</topic>
Here is information from the web:
<research_results>
{research_team_output}
</research_results>\
"""
)
yield StepOutput(content=content)
# ---------------------------------------------------------------------------
# Create Workflows
# ---------------------------------------------------------------------------
sync_workflow = Workflow(
name="Blog Post Workflow",
description="Automated blog post creation from Hackernews and the web",
db=SqliteDb(
session_table="workflow_session",
db_file="tmp/workflow.db",
),
steps=[
prepare_input_for_web_search_sync,
research_team,
prepare_input_for_writer_sync,
writer_agent,
],
)
sync_stream_workflow = Workflow(
name="Blog Post Workflow",
description="Automated blog post creation from Hackernews and the web",
db=SqliteDb(
session_table="workflow_session",
db_file="tmp/workflow.db",
),
steps=[
prepare_input_for_web_search_sync_stream,
research_team,
prepare_input_for_writer_sync_stream,
writer_agent,
],
)
async_workflow = Workflow(
name="Blog Post Workflow",
description="Automated blog post creation from Hackernews and the web",
db=SqliteDb(
session_table="workflow_session",
db_file="tmp/workflow.db",
),
steps=[
prepare_input_for_web_search_async,
research_team,
prepare_input_for_writer_async,
writer_agent,
],
)
async_stream_workflow = Workflow(
name="Blog Post Workflow",
description="Automated blog post creation from Hackernews and the web",
db=SqliteDb(
session_table="workflow_session",
db_file="tmp/workflow.db",
),
steps=[
prepare_input_for_web_search_async_stream,
research_team,
prepare_input_for_writer_async_stream,
writer_agent,
],
)
# ---------------------------------------------------------------------------
# Run Workflow
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# Sync
sync_workflow.print_response(
input="AI trends in 2024",
markdown=True,
)
# Sync Streaming
sync_stream_workflow.print_response(
input="AI trends in 2024",
markdown=True,
stream=True,
)
# Async
asyncio.run(
async_workflow.aprint_response(
input="AI trends in 2024",
markdown=True,
)
)
# Async Streaming
asyncio.run(
async_stream_workflow.aprint_response(
input="AI trends in 2024",
markdown=True,
stream=True,
)
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno ddgs fastapi openai sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
sequence_with_functions.py, then run:python sequence_with_functions.py