Files
agent-framework/python/samples/02-agents/context_providers/simple_context_provider.py
T
Eduard van Valkenburg a2856d3b92 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- One superseded minimal_sample.py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
2026-02-12 17:36:36 +00:00

123 lines
4.8 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
from collections.abc import MutableSequence, Sequence
from typing import Any
from agent_framework import Agent, Context, ContextProvider, Message, SupportsChatGetResponse
from agent_framework.azure import AzureAIClient
from azure.identity.aio import AzureCliCredential
from pydantic import BaseModel
class UserInfo(BaseModel):
name: str | None = None
age: int | None = None
class UserInfoMemory(ContextProvider):
def __init__(self, client: SupportsChatGetResponse, user_info: UserInfo | None = None, **kwargs: Any):
"""Create the memory.
If you pass in kwargs, they will be attempted to be used to create a UserInfo object.
"""
self._chat_client = client
if user_info:
self.user_info = user_info
elif kwargs:
self.user_info = UserInfo.model_validate(kwargs)
else:
self.user_info = UserInfo()
async def invoked(
self,
request_messages: Message | Sequence[Message],
response_messages: Message | Sequence[Message] | None = None,
invoke_exception: Exception | None = None,
**kwargs: Any,
) -> None:
"""Extract user information from messages after each agent call."""
# Check if we need to extract user info from user messages
user_messages = [msg for msg in request_messages if hasattr(msg, "role") and msg.role == "user"] # type: ignore
if (self.user_info.name is None or self.user_info.age is None) and user_messages:
try:
# Use the chat client to extract structured information
result = await self._chat_client.get_response(
messages=request_messages, # type: ignore
instructions="Extract the user's name and age from the message if present. "
"If not present return nulls.",
options={"response_format": UserInfo},
)
# Update user info with extracted data
try:
extracted = result.value
if self.user_info.name is None and extracted.name:
self.user_info.name = extracted.name
if self.user_info.age is None and extracted.age:
self.user_info.age = extracted.age
except Exception:
pass # Failed to extract, continue without updating
except Exception:
pass # Failed to extract, continue without updating
async def invoking(self, messages: Message | MutableSequence[Message], **kwargs: Any) -> Context:
"""Provide user information context before each agent call."""
instructions: list[str] = []
if self.user_info.name is None:
instructions.append(
"Ask the user for their name and politely decline to answer any questions until they provide it."
)
else:
instructions.append(f"The user's name is {self.user_info.name}.")
if self.user_info.age is None:
instructions.append(
"Ask the user for their age and politely decline to answer any questions until they provide it."
)
else:
instructions.append(f"The user's age is {self.user_info.age}.")
# Return context with additional instructions
return Context(instructions=" ".join(instructions))
def serialize(self) -> str:
"""Serialize the user info for thread persistence."""
return self.user_info.model_dump_json()
async def main():
async with AzureCliCredential() as credential:
client = AzureAIClient(credential=credential)
# Create the memory provider
memory_provider = UserInfoMemory(client)
# Create the agent with memory
async with Agent(
client=client,
instructions="You are a friendly assistant. Always address the user by their name.",
context_provider=memory_provider,
) as agent:
# Create a new thread for the conversation
thread = agent.get_new_thread()
print(await agent.run("Hello, what is the square root of 9?", thread=thread))
print(await agent.run("My name is Ruaidhrí", thread=thread))
print(await agent.run("I am 20 years old", thread=thread))
# Access the memory component via the thread's get_service method and inspect the memories
user_info_memory = thread.context_provider.providers[0] # type: ignore
if user_info_memory:
print()
print(f"MEMORY - User Name: {user_info_memory.user_info.name}") # type: ignore
print(f"MEMORY - User Age: {user_info_memory.user_info.age}") # type: ignore
if __name__ == "__main__":
asyncio.run(main())