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* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
96 lines
3.1 KiB
Python
96 lines
3.1 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Run a deterministic local streamable HTTP MCP server for integration tests."""
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from __future__ import annotations
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import argparse
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import asyncio
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from collections.abc import Sequence
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from mcp.server.fastmcp import FastMCP
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from starlette.requests import Request
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from starlette.responses import JSONResponse, Response
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DEFAULT_HOST = "127.0.0.1"
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DEFAULT_PORT = 8011
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DEFAULT_MOUNT_PATH = "/mcp"
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SERVER_NAME = "agent-framework-local-ci-mcp"
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AGENT_FRAMEWORK_DESCRIPTION = (
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"Microsoft Agent Framework is a multi-language framework for building, orchestrating, and deploying AI agents."
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)
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def _normalize_mount_path(path: str) -> str:
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"""Normalize a configured mount path for the streamable HTTP endpoint."""
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normalized = path.strip() or DEFAULT_MOUNT_PATH
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if not normalized.startswith("/"):
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normalized = f"/{normalized}"
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return normalized.rstrip("/") or "/"
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def create_server(*, host: str, port: int, mount_path: str) -> FastMCP:
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"""Create the local MCP integration test server."""
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server = FastMCP(
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name=SERVER_NAME,
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instructions="Deterministic local MCP server used by Agent Framework integration tests.",
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host=host,
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port=port,
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streamable_http_path=mount_path,
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log_level="INFO",
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)
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@server.custom_route("/healthz", methods=["GET"], include_in_schema=False)
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async def healthz(_request: Request) -> Response:
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"""Return a simple readiness response for CI health checks."""
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await asyncio.sleep(0)
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return JSONResponse(
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{
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"status": "ok",
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"name": SERVER_NAME,
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"mcp_path": mount_path,
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}
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)
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@server.tool(
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name="search_agent_framework_docs",
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description="Return deterministic Agent Framework documentation text for MCP integration tests.",
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)
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def search_agent_framework_docs(query: str) -> str:
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"""Return a deterministic response for the MCP integration tests."""
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return (
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f"{AGENT_FRAMEWORK_DESCRIPTION}\n\n"
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f"Query: {query}\n"
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"This response came from the local streamable HTTP MCP integration test server."
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)
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return server
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def parse_args(argv: Sequence[str] | None = None) -> argparse.Namespace:
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"""Parse CLI arguments for the local MCP server."""
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--host", default=DEFAULT_HOST, help="Host interface to bind.")
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parser.add_argument("--port", type=int, default=DEFAULT_PORT, help="Port to bind.")
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parser.add_argument(
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"--mount-path",
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default=DEFAULT_MOUNT_PATH,
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help="Mount path for the streamable HTTP MCP endpoint.",
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)
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return parser.parse_args(list(argv) if argv is not None else None)
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def main(argv: Sequence[str] | None = None) -> None:
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"""Start the local MCP streamable HTTP server."""
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args = parse_args(argv)
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server = create_server(
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host=args.host,
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port=args.port,
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mount_path=_normalize_mount_path(args.mount_path),
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)
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server.run(transport="streamable-http")
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if __name__ == "__main__":
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main()
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