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.
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:
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:
export MINIMAX_API_HOST="https://api.minimaxi.com/anthropic"
CLI Commands
# 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
| Command | What it does |
|---|---|
web_search | Search the web using MiniMax's search API |
understand_image | Analyze images using MiniMax's vision model |
chat | Have a conversation with MiniMax LLMs |
stream_chat | Stream chat with real-time response chunks |
translate | Translate text between languages |
models | Show all available MiniMax models |
CLI Examples
# 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
from scripts import web_search
result = web_search("Python best practices", count=10)
print(result)
Image Analysis
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
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 messagesystem(str, optional): System promptmodel(str, default: "MiniMax-M2.7"): Model nametemperature(float, default: 1.0): Temperature parameter, range (0.0, 1.0]max_tokens(int, default: 4096): Max tokens to generatestream(bool, default: False): Enable streaming responsehistory(list, optional): History list for multi-turn conversation, each message{"role": "user"/"assistant", "content": "..."}
Streaming Chat
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
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 translatetarget_lang(str, default: "English"): Target language, e.g., "English", "Chinese", "Japanese"source_lang(str, default: "auto"): Source language, "auto" for auto-detectmodel(str, default: "MiniMax-M2.7"): Model nametemperature(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:
{
"success": true,
"result": {...}
}
Error:
{
"success": false,
"error": "error message"
}
Learn More
- Full API documentation: references/API.md
- Available models: assets/models.json
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