minimax-use
# 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)
标签
skill
ai
