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Python: [BREAKING] update context provider APIs, middleware, and per-service-call history persistence (#4992)

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* Rename provider base APIs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Allow provider-added chat and function middleware

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Simulate service-stored history per model call

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix typing regressions in CI

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix response ID suppression review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Rename per-service-call history persistence APIs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address context persistence review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Stabilize markdown sample docs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Persist service continuation state per call

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Eduard van Valkenburg
2026-04-01 18:13:11 +02:00
committed by GitHub
Unverified
parent 38de991481
commit b065a4ce51
37 changed files with 1836 additions and 396 deletions
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python/samples/05-end-to-end/hosted_agents/README.md
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@@ -7,7 +7,7 @@ These samples demonstrate how to build and host AI agents in Python using the [A
| Sample | Description |
| ----------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- |
| [`agent_with_hosted_mcp`](./agent_with_hosted_mcp/) | Hosted MCP tool that connects to Microsoft Learn via `https://learn.microsoft.com/api/mcp` |
| [`agent_with_text_search_rag`](./agent_with_text_search_rag/) | Retrieval-augmented generation using a custom `BaseContextProvider` with Contoso Outdoors sample data |
| [`agent_with_text_search_rag`](./agent_with_text_search_rag/) | Retrieval-augmented generation using a custom `ContextProvider` with Contoso Outdoors sample data |
| [`agents_in_workflow`](./agents_in_workflow/) | Concurrent workflow that combines researcher, marketer, and legal specialist agents |
| [`agent_with_local_tools`](./agent_with_local_tools/) | Local Python tool execution for Seattle hotel search |
| [`writer_reviewer_agents_in_workflow`](./writer_reviewer_agents_in_workflow/) | Writer/Reviewer workflow using `FoundryChatClient` |
python/samples/05-end-to-end/hosted_agents/agent_with_text_search_rag/main.py
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@@ -5,7 +5,7 @@ import sys
from dataclasses import dataclass
from typing import Any
from agent_framework import Agent, AgentSession, BaseContextProvider, Message, SessionContext
from agent_framework import Agent, AgentSession, ContextProvider, Message, SessionContext
from agent_framework.foundry import FoundryChatClient
from azure.ai.agentserver.agentframework import from_agent_framework # pyright: ignore[reportUnknownVariableType]
from azure.identity import DefaultAzureCredential
@@ -28,7 +28,7 @@ class TextSearchResult:
text: str
class TextSearchContextProvider(BaseContextProvider):
class TextSearchContextProvider(ContextProvider):
"""A simple context provider that simulates text search results based on keywords in the user's message."""
def __init__(self):
python/samples/05-end-to-end/m365-agent/README.md
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@@ -7,7 +7,7 @@ This sample demonstrates a simple Weather Forecast Agent built with the Python M
- Python 3.11+
- [uv](https://github.com/astral-sh/uv) for fast dependency management
- [devtunnel](https://learn.microsoft.com/azure/developer/dev-tunnels/get-started?tabs=windows)
- [Microsoft 365 Agents Toolkit](https://github.com/OfficeDev/microsoft-365-agents-toolkit) for playground/testing
- `agentsplayground` for playground/testing
- Access to OpenAI or Azure OpenAI with a model like `gpt-4o-mini`
## Configuration