minimax-client 0.3.0

An (unofficial) python native client for easy interaction with MiniMax Open Platform

MiniMax Python Client

An (unofficial) python native client for easy interaction with MiniMax Open Platform

The current implementation includes the following official APIs from MiniMax:

• ChatCompletion v2
• Embeddings
• File

Prerequisites

• Python >= 3.8
• pip
• An API KEY acquired from MiniMax Open Platform

Quick Start

1. Install the package

pip install minimax-client

2. Import the package and invoke the client

2.1 Sync call

from minimax_client import MiniMax


client = MiniMax(api_key="<YOUR_API_KEY>")


response = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "1 + 1 equals: ",
        }
    ]
)


print(response.choices[0].message.content)

2.2 Sync call with streaming

from minimax_client import MiniMax


client = MiniMax(api_key="<YOUR_API_KEY>")


stream = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "What is the term GPT short for?",
        }
    ],
    stream=True,
)


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

2.3 Sync call with tools, stream enabled

from minimax_client import MiniMax


client = MiniMax(api_key="<YOUR_API_KEY>")


stream = client.chat.completions.create(
    model="abab5.5-chat",
    messages=[
        {
            "role": "system",
            "content": "You are a helpful assistant",
        },
        {
            "role": "user",
            "content": "What's the weather like in Log Angeles right now?",
        },
        {
            "role": "assistant",
            "tool_calls": [
                {
                    "id": "call_function_2936815621",
                    "type": "function",
                    "function": {
                        "name": "get_current_weather",
                        "arguments": '{"location": "LogAngeles"}',
                    },
                }
            ],
        },
        {
            "role": "tool",
            "tool_call_id": "call_function_2936815621",
            "content": "LogAngeles / Sunny / 51°F / Wind: East 5 mph",
        },
    ],
    stream=True,
    tool_choice="auto",
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_current_weather",
                "description": "Retrieve the current weather of given location",
                "parameters": '{"type": "object", "properties": {"location": {"type": "string", "description": "Name of a city, eg. Paris, London"}}, "required": ["location"]}',
            },
        }
    ],
)

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

# It's currently sunny in Log Angeles, with a temperature of 51°F and wind from the east at 5 mph.

2.4 Async call

import asyncio

from minimax_client import AsyncMiniMax


async def demo():
    client = AsyncMiniMax(api_key="<YOUR_API_KEY>")

    response = await client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": "1 + 1 equals: ",
            }
        ]
    )

    print(response.choices[0].message.content)


asyncio.run(demo())

2.5 Async call with streaming

import asyncio

from minimax_client import AsyncMiniMax


async def demo():
    client = AsyncMiniMax(api_key="<YOUR_API_KEY>")

    stream = await client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": "What is the term GPT short for?",
            }
        ],
        stream=True,
    )

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


asyncio.run(demo())

2.6 Sync call for embeddings

from minimax_client import MiniMax


client = MiniMax(api_key="<YOUR_API_KEY>")


response = client.embeddings.create(
    input=["Hello world!", "Nice to meet you!"],
    target="db",
)

print(response.vectors[0][:10])
print(response.vectors[1][:10])

2.7 Async call for embeddings

import asyncio

from minimax_client import AsyncMiniMax


async def demo():
    client = AsyncMiniMax(api_key="<YOUR_API_KEY>")

    response = await client.embeddings.create(
        input=["Hello async world!", "Nice to meet you async!"],
        target="query",
    )

    print(response.vectors[0][:10])
    print(response.vectors[1][:10])


asyncio.run(demo())

2.8 Sync call for files

from minimax_client import MiniMax


client = MiniMax(api_key="<YOUR_API_KEY>")


resp = client.files.create(filepath="sample.txt", purpose="retrieval")
print(resp.file.file_id)

resp = client.files.list(purpose="retrieval")
print(resp.files[0].file_id)

resp = client.files.retrieve(file_id=resp.files[0].file_id)
print(resp.file.bytes)

resp = client.files.delete(file_id=resp.file.file_id)
print(resp.file_id)

2.9 Async call for files

import asyncio

from minimax_client import AsyncMiniMax


async def demo():
    client = AsyncMiniMax(api_key="<YOUR_API_KEY>")

    resp = await client.files.create(filepath="sample.txt", purpose="retrieval")
    print(resp.file.file_id)

    resp = await client.files.list(purpose="retrieval")
    print(resp.files[0].file_id)

    resp = await client.files.retrieve(file_id=resp.files[0].file_id)
    print(resp.file.bytes)

    resp = await client.files.delete(file_id=resp.file.file_id)
    print(resp.file_id)

asyncio.run(demo())