metorial-openai-compatible 1.0.5

OpenAI-compatible provider base for Metorial

metorial-openai-compatible

OpenAI-compatible provider integration for Metorial. Works with any API that follows the OpenAI chat completions format.

Installation

pip install metorial openai

Quick Start

import asyncio
from metorial import Metorial, MetorialOpenAICompatible
from openai import AsyncOpenAI

metorial = Metorial(api_key="your-metorial-api-key")

# Works with any OpenAI-compatible API
client = AsyncOpenAI(
    api_key="your-api-key",
    base_url="https://your-api-endpoint.com/v1"
)

async def main():
    async def session_handler(session):
        messages = [{"role": "user", "content": "What's the latest news?"}]

        for _ in range(10):
            response = await client.chat.completions.create(
                model="your-model",
                messages=messages,
                tools=session["tools"]
            )

            choice = response.choices[0]
            tool_calls = choice.message.tool_calls

            if not tool_calls:
                print(choice.message.content)
                break

            tool_responses = await session["callTools"](tool_calls)
            messages.append({"role": "assistant", "tool_calls": tool_calls})
            messages.extend(tool_responses)

        await session["closeSession"]()

    await metorial.with_provider_session(
        MetorialOpenAICompatible.chat_completions,
        {"serverDeployments": [{"serverDeploymentId": "your-server-deployment-id"}]},
        session_handler
    )

asyncio.run(main())

Streaming

import asyncio
from metorial import Metorial, MetorialOpenAICompatible
from openai import AsyncOpenAI

metorial = Metorial(api_key="your-metorial-api-key")
client = AsyncOpenAI(
    api_key="your-api-key",
    base_url="https://your-api-endpoint.com/v1"
)

async def main():
    async def session_handler(session):
        messages = [{"role": "user", "content": "What's the latest news?"}]

        stream = await client.chat.completions.create(
            model="your-model",
            messages=messages,
            tools=session["tools"],
            stream=True
        )

        async for chunk in stream:
            if chunk.choices[0].delta.content:
                print(chunk.choices[0].delta.content, end="", flush=True)

        await session["closeSession"]()

    await metorial.with_provider_session(
        MetorialOpenAICompatible.chat_completions,
        {
            "serverDeployments": [{"serverDeploymentId": "your-server-deployment-id"}],
            "streaming": True,  # Required for streaming with tool calls
        },
        session_handler
    )

asyncio.run(main())

Compatible Providers

Any provider with an OpenAI-compatible API:

• DeepSeek (https://api.deepseek.com)
• Together AI (https://api.together.xyz/v1)
• XAI (https://api.x.ai/v1)
• Groq (https://api.groq.com/openai/v1)
• And many more...

Session Object

async def session_handler(session):
    tools = session["tools"]           # Tool definitions in OpenAI format
    call_tools = session["callTools"]  # Execute tools and get responses
    close_session = session["closeSession"]  # Close the session when done

Error Handling

from metorial import MetorialAPIError

try:
    await metorial.with_provider_session(...)
except MetorialAPIError as e:
    print(f"API Error: {e.message} (Status: {e.status})")
except Exception as e:
    print(f"Unexpected error: {e}")

License

MIT License - see LICENSE file for details.