Skip to main content

metorial-mistral

Mistral AI provider integration for Metorial.

Installation

pip install metorial mistralai

Quick Start

import asyncio
from metorial import Metorial, MetorialMistral
from mistralai import AsyncMistral

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

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

        for _ in range(10):
            response = await mistral.chat.complete_async(
                model="mistral-large-latest",
                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(
        MetorialMistral,
        {"serverDeployments": [{"serverDeploymentId": "your-server-deployment-id"}]},
        session_handler
    )

asyncio.run(main())

Streaming

import asyncio
from metorial import Metorial, MetorialMistral
from mistralai import AsyncMistral

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

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

        stream = await mistral.chat.stream_async(
            model="mistral-large-latest",
            messages=messages,
            tools=session["tools"]
        )

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

        await session["closeSession"]()

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

asyncio.run(main())

Supported Models

  • mistral-large-latest: Most capable Mistral model
  • codestral-latest: Code-focused Mistral model

Session Object

async def session_handler(session):
    tools = session["tools"]           # Tool definitions in Mistral 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.

Metadata

Release files for metorial-mistral 1.0.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for metorial-mistral 1.0.5
File Size Uploaded
metorial_mistral-1.0.5.tar.gz 6.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for metorial-mistral 1.0.5
File Interpreter ABI Platform
metorial_mistral-1.0.5-py3-none-any.whl Python 3 none any Details

Total release size: 11.0 kB

Release files / metorial_mistral-1.0.5.tar.gz

Download URL metorial_mistral-1.0.5.tar.gz
Size 6.0 kB
Tags Source
SHA-256 checksum
How to use checksums
8f5559eb24060b07cf7b273a4d264b5f58a85d0142edf0b3ae8449595249d4de
BLAKE2b-256 checksum
How to use checksums
58d099012c6edc4ca424e789b48fba0afbbc0e5f896192a7e453c376bfd0394d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 23, 2025.

Transparency log

Release files / metorial_mistral-1.0.5-py3-none-any.whl

Download URL metorial_mistral-1.0.5-py3-none-any.whl
Size 4.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
15b50c114f20900e64063ae60dd96cb785cd2eb065d1475c805a31598d48a2f3
BLAKE2b-256 checksum
How to use checksums
a2d378c4314de82e1888990b4ab77d0b55a2b39dc0c51753adba9d9741dbc180
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 23, 2025.

Transparency log
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page