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 doesweb_searchSearch the web using MiniMax's search APIunderstand_imageAnalyze images using MiniMax's vision modelchatHave a conversation with MiniMax LLMsstream_chatStream chat with real-time response chunkstranslateTranslate text between languagesmodelsShow 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"
}

Learn More#

• Full API documentation: references/API.md
• Available models: assets/models.json