Skip to main content

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agent_framework_ep-0.1.1.tar.gz (37.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agent_framework_ep-0.1.1-py3-none-any.whl (18.5 kB view details)

Uploaded Python 3

File details

Details for the file agent_framework_ep-0.1.1.tar.gz.

File metadata

  • Download URL: agent_framework_ep-0.1.1.tar.gz
  • Upload date:
  • Size: 37.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.15

File hashes

Hashes for agent_framework_ep-0.1.1.tar.gz
Algorithm Hash digest
SHA256 e40eae5cd84e796d0e65c2d2ad6f2469bfc3edd1f42bfeabaae9bd51fdd3a11a
MD5 a43c7208f803d639a1e5ddd2e59ee51c
BLAKE2b-256 7737a19c0fca03a6e253ae61c67c41d991a6bac9501126440409039682238571

See more details on using hashes here.

File details

Details for the file agent_framework_ep-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for agent_framework_ep-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9061810fb4b7f9d05343d608b1a543582f3001ea9155a7b080683dfbea4874ab
MD5 0b84beba45953163efff35b55b080c4c
BLAKE2b-256 7700ab49210b0da57e66ad522c5c8583b9ac2c5faea20ba351161615d1f8c38b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page