wehub-resource-sync
113 lines
6.1 KiB
Python
113 lines
6.1 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import os
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from pathlib import Path
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from semantic_kernel.agents import ChatCompletionAgent, ChatHistoryAgentThread
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from semantic_kernel.connectors.ai import FunctionChoiceBehavior
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from semantic_kernel.connectors.ai.ollama import OllamaChatCompletion
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from semantic_kernel.connectors.mcp import MCPStdioPlugin
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from semantic_kernel.functions import KernelArguments
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"""
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The following sample demonstrates how to create a chat completion agent that
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answers questions about Github using a Local Agent with two local MCP Servers.
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It uses a Ollama Chat Completion to create a agent, so make sure to
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set the required environment variables for the Azure AI Foundry service:
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- OLLAMA_CHAT_MODEL_ID
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"""
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USER_INPUTS = [
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"list the latest 10 issues that have the label: triage and python and are open",
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"""generate release notes with this list:
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* Python: Add ChatCompletionAgent integration tests by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11430
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* Python: Update Doc Gen demo based on latest agent invocation api pattern by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11426
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* Python: Update Python min version in README by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11428
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* Python: Fix `TypeError` when required is missing in MCP tool’s inputSchema by @KanchiShimono in https://github.com/microsoft/semantic-kernel/pull/11458
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* Python: Update chromadb requirement from <0.7,>=0.5 to >=0.5,<1.1 in /python by @dependabot in https://github.com/microsoft/semantic-kernel/pull/11420
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* Python: Bump google-cloud-aiplatform from 1.86.0 to 1.87.0 in /python by @dependabot in https://github.com/microsoft/semantic-kernel/pull/11423
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* Python: Support Auto Function Invocation Filter for AzureAIAgent and OpenAIAssistantAgent by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11460
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* Python: Improve agent integration tests by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11475
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* Python: Allow Kernel Functions from Prompt for image and audio content by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11403
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* Python: Introducing SK as a MCP Server by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11362
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* Python: sample using GitHub MCP Server and Azure AI Agent by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11465
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* Python: allow settings to be created directly by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11468
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* Python: Bug fix for azure ai agent truncate strategy. Add sample. by @moonbox3 in https://github.com/microsoft/semantic-kernel/pull/11503
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* Python: small code improvements in code of call automation sample by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11477
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* Added missing import asyncio to agent with plugin python by @sphenry in https://github.com/microsoft/semantic-kernel/pull/11472
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* Python: version updated to 1.28.0 by @eavanvalkenburg in https://github.com/microsoft/semantic-kernel/pull/11504""",
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]
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async def main():
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# Load the MCP Servers as Plugins
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async with (
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MCPStdioPlugin(
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name="Github",
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description="Github Plugin",
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command="docker",
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args=["run", "-i", "--rm", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"],
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env={"GITHUB_PERSONAL_ACCESS_TOKEN": os.getenv("GITHUB_PERSONAL_ACCESS_TOKEN")},
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) as github_plugin,
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MCPStdioPlugin(
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name="ReleaseNotes",
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description="SK Release Notes Plugin",
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command="uv",
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args=[
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f"--directory={str(Path(os.path.dirname(__file__)).parent.parent.joinpath('demos', 'mcp_server'))}",
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"run",
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"mcp_server_with_prompts.py",
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],
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) as release_notes_plugin,
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):
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# Create the agent
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agent = ChatCompletionAgent(
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# Using the OllamaChatCompletion service
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service=OllamaChatCompletion(),
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name="GithubAgent",
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instructions="You interact with the user to help them with the Microsoft semantic-kernel github project. "
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"You have dedicated tools for this, including one to write release notes, "
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"make sure to use that when needed. The repo is always semantic-kernel (aka SK) with owner Microsoft. "
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"and when doing lists, always return 5 items and sort descending by created or updated"
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"You are specialized in Python, so always include label, python, in addition to the other labels.",
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plugins=[github_plugin, release_notes_plugin],
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function_choice_behavior=FunctionChoiceBehavior.Auto(
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filters={
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# exclude a bunch of functions because the local models have trouble with too many functions
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"included_functions": [
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"Github-list_issues",
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"ReleaseNotes-release_notes_prompt",
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]
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}
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),
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)
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print(f"Agent uses Ollama with the {agent.service.ai_model_id} model")
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# Create a thread to hold the conversation
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# If no thread is provided, a new thread will be
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# created and returned with the initial response
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thread: ChatHistoryAgentThread | None = None
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for user_input in USER_INPUTS:
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print(f"# User: {user_input}", end="\n\n")
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first_chunk = True
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async for response in agent.invoke_stream(
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messages=user_input,
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thread=thread,
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arguments=KernelArguments(owner="microsoft", repo="semantic-kernel"),
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):
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if first_chunk:
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print(f"# {response.name}: ", end="", flush=True)
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first_chunk = False
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print(response.content, end="", flush=True)
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thread = response.thread
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print()
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# Cleanup: Clear the thread
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await thread.delete() if thread else None
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if __name__ == "__main__":
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asyncio.run(main())
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