Files
agent-framework/python/samples/getting_started/orchestrations/concurrent_agents.py
T
Eduard van Valkenburg 0521f5bed8 Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747)
* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse

Simplify the public API by removing redundant 'Chat' prefix from core types:
- ChatAgent -> Agent
- RawChatAgent -> RawAgent
- ChatMessage -> Message
- ChatClientProtocol -> SupportsChatGetResponse

Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision.

No backward compatibility aliases - this is a clean breaking change.

* [BREAKING] Rename Agent chat_client parameter to client

* Fix rebase issues: WorkflowMessage references and broken markdown links

* Fix formatting and lint issues from code quality checks

* Fix import ordering in workflow sample files

* fixed rebase

* Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename

- Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests
- Fix isinstance check in A2A agent to use A2AMessage instead of Message
- Fix import in test_workflow_observability.py (Message→WorkflowMessage)

* Fix lint, fmt, and sample errors after ChatMessage→Message rename

- Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs)
- Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample
- Fix _normalize_messages→normalize_messages in custom agent sample
- Fix context.terminate→raise MiddlewareTermination in middleware samples
- Fix with_update_hook→with_transform_hook in override middleware sample
- Add TOptions_co import back to custom_chat_client sample
- Add noqa for FastAPI File() default in chatkit sample
- Fix B023 loop variable capture in weather agent sample

* fix: update Agent constructor calls from chat_client to client in declaration-only tool tests

* fix: add register_cleanup to devui lazy-loading proxy and type stub

* fixed tests and updated new pieces

* fix agui typevar

* fix merge errors

* fix merge conflicts

* fiux merge

* Remove unused links

---------

Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
2026-02-10 23:04:32 +00:00

131 lines
5.1 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
from typing import Any
from agent_framework import Message
from agent_framework.azure import AzureOpenAIChatClient
from agent_framework.orchestrations import ConcurrentBuilder
from azure.identity import AzureCliCredential
"""
Sample: Concurrent fan-out/fan-in (agent-only API) with default aggregator
Build a high-level concurrent workflow using ConcurrentBuilder and three domain agents.
The default dispatcher fans out the same user prompt to all agents in parallel.
The default aggregator fans in their results and yields output containing
a list[Message] representing the concatenated conversations from all agents.
Demonstrates:
- Minimal wiring with ConcurrentBuilder(participants=[...]).build()
- Fan-out to multiple agents, fan-in aggregation of final ChatMessages
- Workflow completion when idle with no pending work
Prerequisites:
- Azure OpenAI access configured for AzureOpenAIChatClient (use az login + env vars)
- Familiarity with Workflow events (WorkflowEvent)
"""
async def main() -> None:
# 1) Create three domain agents using AzureOpenAIChatClient
client = AzureOpenAIChatClient(credential=AzureCliCredential())
researcher = client.as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
),
name="researcher",
)
marketer = client.as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
),
name="marketer",
)
legal = client.as_agent(
instructions=(
"You're a cautious legal/compliance reviewer. Highlight constraints, disclaimers, and policy concerns"
" based on the prompt."
),
name="legal",
)
# 2) Build a concurrent workflow
# Participants are either Agents (type of SupportsAgentRun) or Executors
workflow = ConcurrentBuilder(participants=[researcher, marketer, legal]).build()
# 3) Run with a single prompt and pretty-print the final combined messages
events = await workflow.run("We are launching a new budget-friendly electric bike for urban commuters.")
outputs = events.get_outputs()
if outputs:
print("===== Final Aggregated Conversation (messages) =====")
for output in outputs:
messages: list[Message] | Any = output
for i, msg in enumerate(messages, start=1):
name = msg.author_name if msg.author_name else "user"
print(f"{'-' * 60}\n\n{i:02d} [{name}]:\n{msg.text}")
"""
Sample Output:
===== Final Aggregated Conversation (messages) =====
------------------------------------------------------------
01 [user]:
We are launching a new budget-friendly electric bike for urban commuters.
------------------------------------------------------------
02 [researcher]:
**Insights:**
- **Target Demographic:** Urban commuters seeking affordable, eco-friendly transport;
likely to include students, young professionals, and price-sensitive urban residents.
- **Market Trends:** E-bike sales are growing globally, with increasing urbanization,
higher fuel costs, and sustainability concerns driving adoption.
- **Competitive Landscape:** Key competitors include brands like Rad Power Bikes, Aventon,
Lectric, and domestic budget-focused manufacturers in North America, Europe, and Asia.
- **Feature Expectations:** Customers expect reliability, ease-of-use, theft protection,
lightweight design, sufficient battery range for daily city commutes (typically 25-40 miles),
and low-maintenance components.
**Opportunities:**
- **First-time Buyers:** Capture newcomers to e-biking by emphasizing affordability, ease of
operation, and cost savings vs. public transit/car ownership.
...
------------------------------------------------------------
03 [marketer]:
**Value Proposition:**
"Empowering your city commute: Our new electric bike combines affordability, reliability, and
sustainable design—helping you conquer urban journeys without breaking the bank."
**Target Messaging:**
*For Young Professionals:*
...
------------------------------------------------------------
04 [legal]:
**Constraints, Disclaimers, & Policy Concerns for Launching a Budget-Friendly Electric Bike for Urban Commuters:**
**1. Regulatory Compliance**
- Verify that the electric bike meets all applicable federal, state, and local regulations
regarding e-bike classification, speed limits, power output, and safety features.
- Ensure necessary certifications (e.g., UL certification for batteries, CE markings if sold internationally) are obtained.
**2. Product Safety**
- Include consumer safety warnings regarding use, battery handling, charging protocols, and age restrictions.
...
""" # noqa: E501
if __name__ == "__main__":
asyncio.run(main())