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MiniMax工具箱

minimax-use

by cnlangzi

MiniMax AI tools for web search, image analysis, LLM chat, and language translation. Use when you need to search the web, analyze images, generate text with LLMs, or translate between languages.

3.9k内容与创意未扫描2026年3月23日

安装

claude skill add --url github.com/openclaw/skills/tree/main/skills/cnlangzi/minimax-use

必需环境变量

MINIMAX_API_KEY

文档

MiniMax Tools

This skill provides access to MiniMax's AI capabilities, including web search, image analysis, LLM conversations, and text translation.

Setup

First, set up your API key:

bash
export MINIMAX_API_KEY="your-api-key"

To get an API key, sign up at https://platform.minimaxi.com/subscribe/coding-plan

Optionally, you can customize the API endpoint:

bash
export MINIMAX_API_HOST="https://api.minimaxi.com/anthropic"

CLI Commands

bash
# Search the web
python -m scripts web_search "your search query"

# Analyze an image
python -m scripts understand_image "what do you see?" /path/to/image.jpg

# Chat with an LLM
python -m scripts chat "hello, how are you?"

# Stream chat (receive response in chunks)
python -m scripts stream_chat "tell me a story"

# Translate text
python -m scripts translate "hello world" --to Chinese

# List available models
python -m scripts models

Commands Overview

CommandWhat it does
web_searchSearch the web using MiniMax's search API
understand_imageAnalyze images using MiniMax's vision model
chatHave a conversation with MiniMax LLMs
stream_chatStream chat with real-time response chunks
translateTranslate text between languages
modelsShow all available MiniMax models

CLI Examples

bash
# Search the web
python -m scripts web_search "your search query"

# Analyze an image
python -m scripts understand_image "what do you see?" /path/to/image.jpg

# Chat with an LLM
python -m scripts chat "hello, how are you?"

# Stream chat (receive response in chunks)
python -m scripts stream_chat "tell me a story"

# Translate text
python -m scripts translate "hello world" --to Chinese

# List available models
python -m scripts models

Using in Python

Web Search

python
from scripts import web_search

result = web_search("Python best practices", count=10)
print(result)

Image Analysis

python
from scripts import understand_image

# From a local file
result = understand_image("What's in this image?", "/path/to/image.png")

# From a URL
result = understand_image("Describe this image", "https://example.com/image.jpg")

LLM Chat

python
from scripts import chat

result = chat(
    message="Hello, introduce yourself",
    system="You are a helpful AI assistant",
    model="MiniMax-M2.7",
    temperature=1.0,
    max_tokens=4096,
    stream=False,
    history=[
        {"role": "user", "content": "Hi"},
        {"role": "assistant", "content": "Hello! How can I help you?"}
    ]
)

Parameters:

  • message (str): User message
  • system (str, optional): System prompt
  • model (str, default: "MiniMax-M2.7"): Model name
  • temperature (float, default: 1.0): Temperature parameter, range (0.0, 1.0]
  • max_tokens (int, default: 4096): Max tokens to generate
  • stream (bool, default: False): Enable streaming response
  • history (list, optional): History list for multi-turn conversation, each message {"role": "user"/"assistant", "content": "..."}

Streaming Chat

python
from scripts import stream_chat

result = stream_chat(
    message="Tell me a short story",
    system="You are a storyteller",
    model="MiniMax-M2.7",
    temperature=1.0,
    max_tokens=500
)

# Access streaming chunks
if result["success"]:
    chunks = result["result"]["chunks"]
    full_content = result["result"]["content"]
    print(f"Total chunks: {len(chunks)}")
    print(f"Full content: {full_content}")

Translation

python
from scripts import translate

result = translate(
    text="Hello World",
    target_lang="Chinese",
    source_lang="auto",
    model="MiniMax-M2.7",
    temperature=1.0,
    max_tokens=4096
)

Parameters:

  • text (str): Text to translate
  • target_lang (str, default: "English"): Target language, e.g., "English", "Chinese", "Japanese"
  • source_lang (str, default: "auto"): Source language, "auto" for auto-detect
  • model (str, default: "MiniMax-M2.7"): Model name
  • temperature (float, default: 1.0): Temperature parameter, range (0.0, 1.0]
  • max_tokens (int, default: 4096): Max tokens to generate

Response Format

All functions return a consistent response format:

Success:

json
{
  "success": true,
  "result": {...}
}

Error:

json
{
  "success": false,
  "error": "error message"
}

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