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Python: restructure: Python samples into progressive 01-05 layout (#3862)
* 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file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since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
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import uuid
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from agent_framework import tool
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from agent_framework.azure import AzureAIAgentClient
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from agent_framework.mem0 import Mem0Provider
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from azure.identity.aio import AzureCliCredential
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def retrieve_company_report(company_code: str, detailed: bool) -> str:
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if company_code != "CNTS":
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raise ValueError("Company code not found")
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if not detailed:
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return "CNTS is a company that specializes in technology."
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return (
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"CNTS is a company that specializes in technology. "
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"It had a revenue of $10 million in 2022. It has 100 employees."
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)
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async def main() -> None:
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"""Example of memory usage with Mem0 context provider."""
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print("=== Mem0 Context Provider Example ===")
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# Each record in Mem0 should be associated with agent_id or user_id or application_id or thread_id.
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# In this example, we associate Mem0 records with user_id.
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user_id = str(uuid.uuid4())
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# For Azure authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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# For Mem0 authentication, set Mem0 API key via "api_key" parameter or MEM0_API_KEY environment variable.
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentClient(credential=credential).as_agent(
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name="FriendlyAssistant",
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instructions="You are a friendly assistant.",
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tools=retrieve_company_report,
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context_provider=Mem0Provider(user_id=user_id),
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) as agent,
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):
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# First ask the agent to retrieve a company report with no previous context.
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# The agent will not be able to invoke the tool, since it doesn't know
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# the company code or the report format, so it should ask for clarification.
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query = "Please retrieve my company report"
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result}\n")
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# Now tell the agent the company code and the report format that you want to use
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# and it should be able to invoke the tool and return the report.
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query = "I always work with CNTS and I always want a detailed report format. Please remember and retrieve it."
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print(f"User: {query}")
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result = await agent.run(query)
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print(f"Agent: {result}\n")
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# Mem0 processes and indexes memories asynchronously.
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# Wait for memories to be indexed before querying in a new thread.
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# In production, consider implementing retry logic or using Mem0's
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# eventual consistency handling instead of a fixed delay.
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print("Waiting for memories to be processed...")
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await asyncio.sleep(12) # Empirically determined delay for Mem0 indexing
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print("\nRequest within a new thread:")
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# Create a new thread for the agent.
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# The new thread has no context of the previous conversation.
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thread = agent.get_new_thread()
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# Since we have the mem0 component in the thread, the agent should be able to
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# retrieve the company report without asking for clarification, as it will
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# be able to remember the user preferences from Mem0 component.
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query = "Please retrieve my company report"
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print(f"User: {query}")
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result = await agent.run(query, thread=thread)
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print(f"Agent: {result}\n")
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if __name__ == "__main__":
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asyncio.run(main())
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