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Microsoft Agent Framework extensions for mainstream open-source LLMs

Project description

agent-framework-ep

Microsoft Agent Framework extensions for mainstream open-source LLMs, including structured output support for GLM, Kimi, Qwen, and DeepSeek, along with reasoning_content support. Plus a local containerized code interpreter environment. 'ep' stands for enterprise-level applications.

Features

  • OpenAI-like Client Extensions (openai_like)

    • Structured output parsing with JSON fallback (dirtyjson, json-repair)
    • Reasoning content support for DeepSeek-R1 style models
    • Compatible with Microsoft Agent Framework's OpenAIChatClient
  • Code Executor (code_executor)

    • Docker-based code execution environment
    • Supports Python, bash, and shell scripts
    • Timeout and cancellation support
    • Isolated execution for security
  • Dynamic Skills Provider (skills_provider)

    • Async skill updates before each agent run
    • Extendable skills from external sources

Installation

pip install agent-framework-ep

Or with uv:

uv add agent-framework-ep

Prerequisites

  • Python 3.12+
  • Docker (for code execution features)

Quick Start

OpenAI-like Client with Structured Output

from pydantic import BaseModel
from agent_framework import Agent
from agent_framework_ep import OpenAILikeChatClient

class Response(BaseModel):
    answer: str
    confidence: float

# Create client with structured output support
client = OpenAILikeChatClient(
    model="deepseek-chat",
    api_key="your-api-key"
)

# Use with Agent framework
agent = Agent(client=client)
response = await agent.run(
    "What is the capital of France?",
    response_format=Response
)
print(response.result)  # Parsed Response object

Code Execution

import asyncio
from agent_framework_ep import DockerCommandLineCodeExecutor, CodeBlock, CancellationToken

async def main():
    async with DockerCommandLineCodeExecutor(
        image="python-code-sandbox"
    ) as executor:
        result = await executor.execute_code_blocks(
            [CodeBlock(code="print('Hello, World!')", language="python")],
            CancellationToken()
        )
        print(result.output)  # Hello, World!
        print(result.exit_code)  # 0

asyncio.run(main())

Dynamic Skills Provider

from agent_framework_ep import UpdatableSkillsProvider
from agent_framework import Skill

async def fetch_dynamic_skills():
    # Fetch skills from external source
    return [
        Skill(name="web-search", description="Search the web", content="..."),
    ]

provider = UpdatableSkillsProvider(
    skill_paths="./skills",
    skills_updater=fetch_dynamic_skills
)

Development

# Clone the repository
git clone https://github.com/qianpeng/agent-framework-ep.git
cd agent-framework-ep

# Install dependencies
uv sync

# Run tests
uv run pytest

# Run tests with Docker (requires Docker)
uv run pytest -m docker

# Lint and format
uv run ruff check --fix .
uv run ruff format .

# Type check
uv run mypy src/agent_framework_ep

License

MIT License - see LICENSE for details.

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