Skill: cnlangzi/minimax-use (version 0.1.0)

--- name: minimax-use description: "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." metadata: openclaw: requires: env: - MINIMAX_API_KEY primaryEnv: MINIMAX_API_KEY os: - linux - darwin - win32 author: OpenClaw version: "0.1.0" compatibility: Requires Python 3.8+ and the requests library. Requires MINIMAX_API_KEY from https://platform.minimaxi.com --- # 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 | 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 ```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](references/API.md) - Available models: [assets/models.json](assets/models.json)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)