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Eduard van Valkenburg
a2856d3b92
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent โ 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file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since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/ โ 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
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Multi-Agent
This sample demonstrates how to host multiple AI agents with different tools in a single worker-client setup using the Durable Task Scheduler.
Key Concepts Demonstrated
- Hosting multiple agents (WeatherAgent and MathAgent) in a single worker process.
- Each agent with its own specialized tools and instructions.
- Interacting with different agents using separate conversation threads.
- Worker-client architecture for multi-agent systems.
Environment Setup
See the README.md file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
Running the Sample
With the environment setup, you can run the sample using the combined approach or separate worker and client processes:
Option 1: Combined (Recommended for Testing)
cd samples/04-hosting/durabletask/02_multi_agent
python sample.py
Option 2: Separate Processes
Start the worker in one terminal:
python worker.py
In a new terminal, run the client:
python client.py
The client will interact with both agents:
Starting Durable Task Multi-Agent Client...
Using taskhub: default
Using endpoint: http://localhost:8080
================================================================================
Testing WeatherAgent
================================================================================
Created weather conversation thread: <guid>
User: What is the weather in Seattle?
๐ง [TOOL CALLED] get_weather(location=Seattle)
โ [TOOL RESULT] {'location': 'Seattle', 'temperature': 72, 'conditions': 'Sunny', 'humidity': 45}
WeatherAgent: The current weather in Seattle is sunny with a temperature of 72ยฐF and 45% humidity.
================================================================================
Testing MathAgent
================================================================================
Created math conversation thread: <guid>
User: Calculate a 20% tip on a $50 bill
๐ง [TOOL CALLED] calculate_tip(bill_amount=50.0, tip_percentage=20.0)
โ [TOOL RESULT] {'bill_amount': 50.0, 'tip_percentage': 20.0, 'tip_amount': 10.0, 'total': 60.0}
MathAgent: For a $50 bill with a 20% tip, the tip amount is $10.00 and the total is $60.00.
Viewing Agent State
You can view the state of both agents in the Durable Task Scheduler dashboard:
- Open your browser and navigate to
http://localhost:8082 - In the dashboard, you can view:
- The state of both WeatherAgent and MathAgent entities (dafx-WeatherAgent, dafx-MathAgent)
- Each agent's conversation state across multiple interactions