* Python: fix OpenAI Azure routing and provider samples Prefer OpenAI when OPENAI_API_KEY is present unless Azure is explicitly requested. Clarify constructor docs, keep deprecated Azure wrappers compatible with stricter settings validation, and refresh the provider samples and tests to use the current client patterns. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix bandit * Python: align OpenAI embedding Azure routing Extend the shared OpenAI-vs-Azure routing and credential behavior to the embedding client, add Azure embedding regression coverage, and refresh the embedding samples to use the generic client path. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix embedding client pyright check Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: thin OpenAI embedding wrapper Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: document embedding overload routing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix callable OpenAI key routing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix Azure credential routing tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: address OpenAI review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: narrow Azure routing markers Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: refine OpenAI model fallback order Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: narrow Azure deployment docs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove embedding routing wording Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: run embedding Azure integration tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * changed variable name * Python: expand OpenAI package README Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * clarified readme * Python: fix Azure OpenAI integration setup Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: correct Azure integration env mapping Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated code to fix int tests * test updates * test fix * fix test setup * updates to tests and setup * remove openai assistants int tests * improvements in int tests * fix env var * fix env vars * fix azure responses test * trigger actions --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Microsoft Agent Framework Python Weather Agent sample (M365 Agents SDK)
This sample demonstrates a simple Weather Forecast Agent built with the Python Microsoft Agent Framework, exposed through the Microsoft 365 Agents SDK compatible endpoints. The agent accepts natural language requests for a weather forecast and responds with a textual answer. It supports multi-turn conversations to gather required information.
Prerequisites
- Python 3.11+
- uv for fast dependency management
- devtunnel
- Microsoft 365 Agents Toolkit for playground/testing
- Access to OpenAI or Azure OpenAI with a model like
gpt-4o-mini
Configuration
Set the following environment variables:
# Common
export PORT=3978
export USE_ANONYMOUS_MODE=True # set to false if using auth
# OpenAI
export OPENAI_API_KEY="..."
export OPENAI_CHAT_MODEL="..."
Installing Dependencies
From the repository root or the sample folder:
uv sync
Running the Agent Locally
# Activate environment first if not already
source .venv/bin/activate # (Windows PowerShell: .venv\Scripts\Activate.ps1)
# Run the weather agent demo
python m365_agent_demo/app.py
The agent starts on http://localhost:3978. Health check: GET /api/health.
QuickStart using Agents Playground
-
Install (if not already):
winget install agentsplayground -
Start the Python agent locally:
python m365_agent_demo/app.py -
Start the playground:
agentsplayground -
Chat with the Weather Agent.
QuickStart using WebChat (Azure Bot)
To test via WebChat you can provision an Azure Bot and point its messaging endpoint to your agent.
-
Create an Azure Bot (choose Client Secret auth for local tunneling).
-
Create a
.envfile in this sample folder with the following (replace placeholders):# Authentication / Agentic configuration USE_ANONYMOUS_MODE=False CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID="<client-id>" CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET="<client-secret>" CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID="<tenant-id>" CONNECTIONS__SERVICE_CONNECTION__SETTINGS__SCOPES=https://graph.microsoft.com/.default AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__TYPE=AgenticUserAuthorization AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__SCOPES=https://graph.microsoft.com/.default AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__ALTERNATEBLUEPRINTCONNECTIONNAME=https://graph.microsoft.com/.default -
Host dev tunnel:
devtunnel host -p 3978 --allow-anonymous -
Set the bot Messaging endpoint to:
https://<tunnel-host>/api/messages -
Run your local agent:
python m365_agent_demo/app.py -
Use "Test in WebChat" in Azure Portal.
Federated Credentials or Managed Identity auth types typically require deployment to Azure App Service instead of tunneling.
Troubleshooting
- 404 on
/api/messages: Ensure you are POSTing and using the correct tunnel URL. - Empty responses: Check model key / quota and ensure environment variables are set.
- Auth errors when anonymous disabled: Validate MSAL config matches your Azure Bot registration.