voxagent 0.2.2

A lightweight, model-agnostic LLM provider abstraction with streaming and tool support

voxagent

A lightweight, model-agnostic LLM provider abstraction with streaming and tool support.

Features

• Multi-Provider: Unified interface for OpenAI, Anthropic, Google, Groq, Ollama
• Streaming: Typed StreamChunk union (TextDelta, ToolUse, MessageEnd, Error)
• Tool System: @tool decorator for easy function-to-tool conversion
• MCP Integration: First-class Model Context Protocol support
• Type Safe: Full type hints with py.typed marker
• Minimal Dependencies: Core requires only pydantic, httpx, anyio

Installation

# Core only (no provider SDKs)
pip install voxagent

# With specific providers
pip install voxagent[openai]
pip install voxagent[anthropic]
pip install voxagent[google]
pip install voxagent[ollama]

# All providers
pip install voxagent[all]

Quick Start

import asyncio
from voxagent import Agent

async def main():
    agent = Agent(model="openai:gpt-4o")
    result = await agent.run("Hello, world!")
    print(result.output)

asyncio.run(main())

Streaming

from voxagent import Agent
from voxagent.providers import TextDeltaChunk

agent = Agent(model="anthropic:claude-3-5-sonnet")

async for chunk in agent.stream("Tell me a story"):
    if isinstance(chunk, TextDeltaChunk):
        print(chunk.delta, end="", flush=True)

Tools

from voxagent import Agent
from voxagent.tools import tool

@tool()
def get_weather(city: str) -> str:
    """Get the current weather for a city."""
    return f"Sunny, 72°F in {city}"

agent = Agent(
    model="openai:gpt-4o",
    tools=[get_weather],
)

result = await agent.run("What's the weather in Paris?")

Supported Providers

Provider	Model Format	Example
OpenAI	openai:model	openai:gpt-4o
Anthropic	anthropic:model	anthropic:claude-3-5-sonnet
Google	google:model	google:gemini-1.5-pro
Groq	groq:model	groq:llama-3.1-70b
Ollama	ollama:model	ollama:llama3.2

API Reference

Agent

from voxagent import Agent

agent = Agent(
    model="provider:model",      # Required: provider:model string
    system_prompt="...",         # Optional: system instructions
    tools=[...],                 # Optional: list of tools
    temperature=0.7,             # Optional: sampling temperature
)

# Single response
result = await agent.run("prompt")

# Streaming
async for chunk in agent.stream("prompt"):
    ...

StreamChunk Types

from voxagent.providers import (
    TextDeltaChunk,    # Text content
    ToolUseChunk,      # Tool invocation
    MessageEndChunk,   # End of message
    ErrorChunk,        # Error occurred
)

Contributing

See CONTRIBUTING.md for development setup and guidelines.

License

MIT License - see LICENSE for details.