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Eduard van Valkenburg
a2856d3b92
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
3.5 KiB
3.5 KiB
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_ID="..."
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.