请见下（由于字符限制，仅提供部分，完整内容请参考原始文档）
name: cn-llm
description: "中国LLM网关 - 统一接口，支持Qwen、DeepSeek、GLM、Baichuan等，OpenAI兼容，一个API Key即可访问所有模型。"
homepage: https://openclaw.ai
metadata: {"openclaw":{"emoji":"🐉","requires":{"bins":["curl","python3"],"env":["AISA_API_KEY"]},"primaryEnv":"AISA_API_KEY"}}
# OpenClaw CN-LLM 🐉
中国LLM统一网关。由AIsa驱动。
一个API Key即可访问所有中国LLM。OpenAI兼容接口。支持Qwen、DeepSeek、GLM、Baichuan、Moonshot等模型的统一API访问。
# OpenClaw CN-LLM 🐉
China LLM Unified Gateway. Powered by AIsa.
One API Key to access all Chinese LLMs. OpenAI compatible interface.
Qwen, DeepSeek, GLM, Baichuan, Moonshot, and more - unified API access.
🔥 What You Can Do
Intelligent Chat
``
"Use Qwen to answer Chinese questions, use DeepSeek for coding"
`
Deep Reasoning
`
"Use DeepSeek-R1 for complex reasoning tasks"
`
Code Generation
`
"Use DeepSeek-Coder to generate Python code with explanations"
`
Long Text Processing
`
"Use Qwen-Long for ultra-long document summarization"
`
Model Comparison
`
"Compare response quality between Qwen-Max and DeepSeek-V3"
`
Supported Models
Qwen (Alibaba)
| Model | Input Price | Output Price | Features |
|-----|---------|---------|------|
| qwen3-max | $1.37/M | $5.48/M | Most powerful general model |
| qwen3-max-2026-01-23 | $1.37/M | $5.48/M | Latest version |
| qwen3-coder-plus | $2.86/M | $28.60/M | Enhanced code generation |
| qwen3-coder-flash | $0.72/M | $3.60/M | Fast code generation |
| qwen3-coder-480b-a35b-instruct | $2.15/M | $8.60/M | 480B large model |
| qwen3-vl-plus | $0.43/M | $4.30/M | Vision-language model |
| qwen3-vl-flash | $0.86/M | $0.86/M | Fast vision model |
| qwen3-omni-flash | $4.00/M | $16.00/M | Multimodal model |
| qwen-vl-max | $0.23/M | $0.57/M | Vision-language |
| qwen-plus-2025-12-01 | $1.26/M | $12.60/M | Plus version |
| qwen-mt-flash | $0.168/M | $0.514/M | Fast machine translation |
| qwen-mt-lite | $0.13/M | $0.39/M | Lite machine translation |
DeepSeek
| Model | Input Price | Output Price | Features |
|-----|---------|---------|------|
| deepseek-r1 | $2.00/M | $8.00/M | Reasoning model, supports Tools |
| deepseek-v3 | $1.00/M | $4.00/M | General chat, 671B parameters |
| deepseek-v3-0324 | $1.20/M | $4.80/M | V3 stable version |
| deepseek-v3.1 | $4.00/M | $12.00/M | Latest Terminus version |
Note: Prices are in M (million tokens). Model availability may change, see marketplace.aisa.one/pricing for the latest list.
Quick Start
`
bash
export AISA_API_KEY="your-key"
`
API Endpoints
OpenAI Compatible Interface
`
POST https://api.aisa.one/v1/chat/completions
`
Qwen Example
`
bash
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-max",
"messages": [
{"role": "system", "content": "You are a professional Chinese assistant."},
{"role": "user", "content": "Please explain what a large language model is?"}
],
"temperature": 0.7,
"max_tokens": 1000
}'
`
DeepSeek Example
`
bash
# DeepSeek-V3 general chat (671B parameters)
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v3",
"messages": [{"role": "user", "content": "Write a quicksort algorithm in Python"}],
"temperature": 0.3
}'
# DeepSeek-R1 deep reasoning (supports Tools)
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-r1",
"messages": [{"role": "user", "content": "A farmer needs to cross a river with a wolf, a sheep, and a cabbage. The boat can only carry the farmer and one item at a time. If the farmer is not present, the wolf will eat the sheep, and the sheep will eat the cabbage. How can the farmer safely cross?"}]
}'
# DeepSeek-V3.1 Terminus latest version
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v3.1",
"messages": [{"role": "user", "content": "Implement an LRU cache with get and put operations"}]
}'
`
Qwen3 Code Generation Example
`
bash
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-coder-plus",
"messages": [{"role": "user", "content": "Implement a thread-safe Map in Go"}]
}'
`
Parameter Reference
| Parameter | Type | Required | Description |
|-----|------|-----|------|
| model
| string | Yes | Model identifier |
| messages
| array | Yes | Message list |
| temperature
| number | No | Randomness (0-2, default 1) |
| max_tokens
| integer | No | Maximum tokens to generate |
| stream
| boolean | No | Stream output (default false) |
| top_p
| number | No | Nucleus sampling parameter (0-1) |
Response Format
`
json
{
"id": "chatcmpl-xxx",
"object": "chat.completion",
"created": 1234567890,
"model": "qwen-max",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "A large language model (LLM) is a deep learning-based..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 30,
"completion_tokens": 150,
"total_tokens": 180,
"cost": 0.001
}
}
`
Streaming Output
`
bash
curl -X POST "https://api.aisa.one/v1/chat/completions" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-plus",
"messages": [{"role": "user", "content": "Tell a Chinese folk story"}],
"stream": true
}'
`
Returns Server-Sent Events (SSE) format:
`
data: {"id":"chatcmpl-xxx","choices":[{"delta":{"content":"Once"}}]}
data: {"id":"chatcmpl-xxx","choices":[{"delta":{"content":" upon"}}]}
...
data: [DONE]
`
Python Client
CLI Usage
`
bash
# Qwen chat
python3 {baseDir}/scripts/cn_llm_client.py chat --model qwen3-max --message "Hello, please introduce yourself"
# Qwen3 code generation
python3 {baseDir}/scripts/cn_llm_client.py chat --model qwen3-coder-plus --message "Write a binary search algorithm"
# DeepSeek-R1 reasoning
python3 {baseDir}/scripts/cn_llm_client.py chat --model deepseek-r1 --message "Which is larger, 9.9 or 9.11? Please reason in detail"
# DeepSeek-V3 chat
python3 {baseDir}/scripts/cn_llm_client.py chat --model deepseek-v3 --message "Tell a story" --stream
# With system prompt
python3 {baseDir}/scripts/cn_llm_client.py chat --model qwen3-max --system "You are a classical poetry expert" --message "Write a poem about plum blossoms"
# Model comparison
python3 {baseDir}/scripts/cn_llm_client.py compare --models "qwen3-max,deepseek-v3" --message "What is quantum computing?"
# List supported models
python3 {baseDir}/scripts/cn_llm_client.py models
`
Python SDK Usage
`
python
from cn_llm_client import CNLLMClient
client = CNLLMClient() # Uses AISA_API_KEY environment variable
# Qwen chat
response = client.chat(
model="qwen3-max",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response["choices"][0]["message"]["content"])
# Qwen3 code generation
response = client.chat(
model="qwen3-coder-plus",
messages=[
{"role": "system", "content": "You are a professional programmer."},
{"role": "user", "content": "Implement a singleton pattern in Python"}
],
temperature=0.3
)
# Streaming output
for chunk in client.chat_stream(
model="deepseek-v3",
messages=[{"role": "user", "content": "Tell a story about an idiom"}]
):
print(chunk, end="", flush=True)
# Model comparison
results = client.compare_models(
models=["qwen3-max", "deepseek-v3", "deepseek-r1"],
message="Explain what machine learning is"
)
for model, result in results.items():
print(f"{model}: {result['response'][:100]}...")
`
Use Cases
1. Chinese Content Generation
`
python
# Copywriting
response = client.chat(
model="qwen3-max",
messages=[
{"role": "system", "content": "You are a professional copywriter."},
{"role": "user", "content": "Write a product introduction for a smart watch"}
]
)
`
2. Code Development
`
python
# Code generation and explanation
response = client.chat(
model="qwen3-coder-plus",
messages=[{"role": "user", "content": "Implement a thread-safe Map in Go"}]
)
`
3. Complex Reasoning
`
python
# Mathematical reasoning
response = client.chat(
model="deepseek-r1",
messages=[{"role": "user", "content": "Prove: For any positive integer n, n³-n is divisible by 6"}]
)
`
4. Visual Understanding
`
python
# Image understanding
response = client.chat(
model="qwen3-vl-plus",
messages=[
{"role": "user", "content": [
{"type": "text", "text": "Describe the content of this image"},
{"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}}
]}
]
)
`
5. Model Routing Strategy
`
python
MODEL_MAP = {
"chat": "qwen3-max", # General chat
"code": "qwen3-coder-plus", # Code generation
"reasoning": "deepseek-r1", # Complex reasoning
"vision": "qwen3-vl-plus", # Visual understanding
"fast": "qwen3-coder-flash", # Fast response
"translate": "qwen-mt-flash" # Machine translation
}
def route_by_task(task_type: str, message: str) -> str:
model = MODEL_MAP.get(task_type, "qwen3-max")
return client.chat(model=model, messages=[{"role": "user", "content": message}])
`
Error Handling
Errors return JSON with error
field:
`
json
{
"error": {
"code": "model_not_found",
"message": "Model 'xxx' is not available"
}
}
`
Common error codes:
401
- Invalid or missing API Key
402
- Insufficient balance
404
- Model not found
429
- Rate limit exceeded
500
- Server error
Pricing
| Model | Input ($/M) | Output ($/M) |
|-----|-----------|-----------|
| qwen3-max | $1.37 | $5.48 |
| qwen3-coder-plus | $2.86 | $28.60 |
| qwen3-coder-flash | $0.72 | $3.60 |
| qwen3-vl-plus | $0.43 | $4.30 |
| deepseek-v3 | $1.00 | $4.00 |
| deepseek-r1 | $2.00 | $8.00 |
| deepseek-v3.1 | $4.00 | $12.00 |
Price unit: $ per Million tokens. Each response includes
usage.cost
and usage.credits_remaining
.
Get Started
- Register at aisa.one
- Get API Key
- Top up (pay-as-you-go)
- Set environment variable:
export AISA_API_KEY="your-key"`
Full API Reference
See
API Reference for complete endpoint documentation.
by