export TOKENFAB_API_KEY="your-api-key"

$env:TOKENFAB_API_KEY="your-api-key"

pip install openai

from openai import OpenAI

client = OpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

resp = client.chat.completions.create(model="glm-5.2", messages=[{"role":"user","content":"Introduce the TokenFab platform"}])
print(resp.choices[0].message.content)

pip install openai

from openai import OpenAI
client = OpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

try:
    r = client.chat.completions.create(model="glm-5.2", messages=[{"role":"user","content":"Hello"}])
except Exception as e:
    print(f"Error: {e}")

from openai import OpenAI

client = OpenAI(base_url="https://api.tokenfab.cn/v1", api_key="your-api-key")
resp = client.responses.create(
    model="glm-5.2",
    input="Hello, TokenFab",
    instructions="Answer in English.")
print(resp.output_text)

import anthropic

client = anthropic.Anthropic(
    api_key="your-api-key",
    base_url="https://api.tokenfab.cn/anthropic",
)

message = client.messages.create(
    model="glm-5.2",
    max_tokens=1024,
    messages=[{"role": "user", "content": "hello"}],
    thinking={"type": "disabled"},
)
print(message.content[0].text)

with client.messages.stream(
    model="glm-5.2",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Tell me a story"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

export ANTHROPIC_BASE_URL="https://api.tokenfab.cn/anthropic"
export ANTHROPIC_AUTH_TOKEN="your-api-key"
export ANTHROPIC_DEFAULT_MODEL="glm-5.2"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="glm-5.2"
export ANTHROPIC_SMALL_FAST_MODEL="glm-5.2"
export CLAUDE_CODE_DEFAULT_HAIKU_MODEL="glm-5.2"
export CLAUDE_CODE_SUBAGENT_MODEL="glm-5.2"

$env:ANTHROPIC_BASE_URL="https://api.tokenfab.cn/anthropic"
$env:ANTHROPIC_AUTH_TOKEN="your-api-key"
$env:ANTHROPIC_DEFAULT_MODEL="glm-5.2"
$env:ANTHROPIC_DEFAULT_HAIKU_MODEL="glm-5.2"
$env:ANTHROPIC_SMALL_FAST_MODEL="glm-5.2"
$env:CLAUDE_CODE_DEFAULT_HAIKU_MODEL="glm-5.2"
$env:CLAUDE_CODE_SUBAGENT_MODEL="glm-5.2"

cd /path/to/my-project
claude

openclaw onboard --install-daemon

curl -fsSL https://openclaw.ai/install.sh | bash

iwr -useb https://openclaw.ai/install.ps1 | iex

openclaw dashboard

openclaw terminal

openclaw terminal --model glm-5.2

curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash

{
  "models": [
    {
      "id": "deepseek-v4-pro",
      "name": "DeepSeek V4 Pro",
      "vendor": "TokenFab",
      "url": "https://api.tokenfab.cn/v1/chat/completions",
      "apiKey": "${{API_KEY}}",
      "maxInputTokens": 128000,
      "maxOutputTokens": 8192,
      "supportsToolCall": true,
      "supportsImages": false,
      "relatedModels": {
        "lite": "deepseek-v4-flash",
        "reasoning": "deepseek-v4-pro"
      }
    },
    {
      "id": "deepseek-v4-flash",
      "name": "DeepSeek V4 Flash",
      "vendor": "TokenFab",
      "url": "https://api.tokenfab.cn/v1/chat/completions",
      "apiKey": "${{API_KEY}}",
      "maxInputTokens": 128000,
      "maxOutputTokens": 8192,
      "supportsToolCall": true,
      "supportsImages": false
    }
  ],
  "availableModels": [
    "deepseek-v4-pro",
    "deepseek-v4-flash"
  ]
}

from openai import OpenAI

client = OpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

stream = client.chat.completions.create(model="glm-5.2", messages=[{"role":"user","content":"Tell me a story"}], stream=True)
for chunk in stream:
    if chunk.choices:
        if chunk.choices[0].delta.content:
            print(chunk.choices[0].delta.content, end="", flush=True)

data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1784950000,"model":"glm-5.2","choices":[{"index":0,"delta":{"role":"assistant","content":"Today"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1784950000,"model":"glm-5.2","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}
data: [DONE]

from openai import OpenAI

client = OpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

response = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[{"role": "user", "content": "What are the latest AI industry trends in 2026?"}],
    extra_body={"enable_thinking":True}
)

print(response.choices[0].message.reasoning)

tools = [{"type":"function","function":{"name":"get_weather","description":"Check weather","parameters":{"type":"object","properties":{"city":{"type":"string"}},"required":["city"]}}}]
messages = [{"role":"user","content":"What is the weather like in Beijing?"}]
r1 = client.chat.completions.create(model="glm-5.2", messages=messages, tools=tools)
tc = r1.choices[0].message.tool_calls[0]
result = "Beijing is sunny today, 25°C"
messages.append(r1.choices[0].message)
messages.append({"role":"tool","tool_call_id":tc.id,"content":result})
r2 = client.chat.completions.create(model="glm-5.2", messages=messages)
print(r2.choices[0].message.content)

messages = [{"role":"user","content":"What is the weather like in Beijing?"}]
r1 = client.chat.completions.create(model="glm-5.2", messages=messages)
messages.append({"role":"assistant","content":r1.choices[0].message.content})
messages.append({"role":"user","content":"What about Shanghai?"})
r2 = client.chat.completions.create(model="glm-5.2", messages=messages)

r = client.chat.completions.create(model="glm-5.2", messages=[{"role":"user","content":"List 3 fruits and their prices"}],
    response_format={"type":"json_schema","json_schema":{"name":"fruits","schema":{"type":"object","properties":{"fruits":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string"},"price":{"type":"number"}},"required":["name","price"]}}},"required":["fruits"]}}})
print(r.choices[0].message.content)

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

async def ask(q):
    r = await client.chat.completions.create(model="glm-5.2", messages=[{"role":"user","content":q}])
    print(r.choices[0].message.content)

async def main():
    tasks = [ask(q) for q in ["Summarize AI", "Translate Hello", "Recommend 3 books"]]
    await asyncio.gather(*tasks)

asyncio.run(main())

from openai import OpenAI

client = OpenAI(api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")

response = client.chat.completions.create(
    model="glm-5.2",
    messages=[{"role": "user", "content": "What are the latest trends in AI in 2026?"}],
    extra_body={"enable_web_search": True}
)

print(response.choices[0].message.content)

curl -X POST https://api.tokenfab.cn/v1/responses \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "input": "What are today's top tech headlines?",
    "tools": [{"type": "web_search"}]
  }'

curl -X POST https://api.tokenfab.cn/v1/responses \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.7-plus",
    "input": "Count the days in February 2026 and compute 3 to the power of 20 exactly.",
    "tools": [{"type": "code_interpreter"}]
  }'

curl -X POST https://api.tokenfab.cn/v1/responses \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "input": "Summarize the key points of this page: https://example.com",
    "tools": [{"type": "web_extractor"}]
  }'

curl -X POST https://api.tokenfab.cn/v1/chat/completions \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "messages": [{"role": "user", "content": "What are today's top tech headlines?"}],
    "enable_web_search": true
  }'

curl -X POST https://api.tokenfab.cn/v1/chat/completions \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "messages": [
      {"role": "system", "content": "You are a translation assistant"},
      {"role": "user", "content": "Translate the following English to Chinese: Hello World"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "glm-5.2",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Hello World"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 28,
    "completion_tokens": 5,
    "total_tokens": 33
  }
}

curl -X POST https://api.tokenfab.cn/v1/responses \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "input": "Describe the weather in Beijing today and cite the sources.",
    "instructions": "Answer in English.",
    "stream": false,
    "max_output_tokens": 16384,
    "temperature": 0.7,
    "top_p": 0.9,
    "tools": [{"type": "web_search"}],
    "tool_choice": {"type": "web_search"},
    "reasoning": {"effort": "low"},
    "store": false
  }'

curl -X POST https://api.tokenfab.cn/v1/responses \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "input": "Explain what an async task is.",
    "stream": true
  }'

{
  "id": "021793159464483fc7…",
  "object": "response",
  "created_at": 1793159467,
  "completed_at": null,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "max_tool_calls": null,
  "model": "glm-5.2",
  "output": [
    {
      "id": "ws_8faf6e80-b67b-4c74-9ad0-02e17b3f737f",
      "type": "web_search_call",
      "status": "completed",
      "action": {
        "type": "search",
        "query": "Beijing weather today",
        "sources": [
          { "type": "url", "url": "https://m.tianqi.com/tongzhou/", "title": "北京通州天气" },
          { "type": "url", "url": "http://tj.weather.com.cn/tqyw/10/4837553.shtml", "title": "今日天气" }
        ]
      }
    },
    {
      "id": "rs_231c7e38ea2eb8bd…",
      "type": "reasoning",
      "role": "assistant",
      "content": [{ "type": "reasoning_text", "text": "Based on the search results…" }]
    },
    {
      "id": "msg_006e4808292cb3ba…",
      "type": "message",
      "status": "completed",
      "role": "assistant",
      "content": [{
        "type": "output_text",
        "text": "Today in Beijing the weather is clear (sunny) with temperatures around 1–15°C…",
        "annotations": [],
        "logprobs": []
      }]
    }
  ],
  "previous_response_id": null,
  "prompt_cache_key": null,
  "reasoning": null,
  "safety_identifier": null,
  "service_tier": null,
  "status": "completed",
  "stop_reason": "stop",
  "tools": null,
  "usage": {
    "input_tokens": 2511,
    "input_tokens_details": { "cached_read_tokens": 0, "cached_write_tokens": 0, "cached_tokens": 0 },
    "output_tokens": 134,
    "output_tokens_details": { "reasoning_tokens": 10, "num_search_queries": 1 },
    "total_tokens": 2645
  },
  "extra_fields": {
    "request_type": "responses",
    "original_model_requested": "glm-5.2",
    "latency": 3184,
    "chunk_index": 0
  }
}

curl https://api.tokenfab.cn/v1/models \
  -H "Authorization: Bearer your-api-key"

{"object":"list","data":[
  {"id":"aicc-doubao-seedance-2-0","object":"model","owned_by":"tokenfab"},
  {"id":"deepseek-v4-flash","object":"model","owned_by":"tokenfab"},
  {"id":"deepseek-v4-pro","object":"model","owned_by":"tokenfab"},
  {"id":"glm-5.2","object":"model","owned_by":"tokenfab"},
  {"id":"glm-5.3","object":"model","owned_by":"tokenfab"},
  {"id":"happyhorse-1.1-i2v","object":"model","owned_by":"tokenfab"},
  {"id":"happyhorse-1.1-r2v","object":"model","owned_by":"tokenfab"},
  {"id":"happyhorse-1.1-t2v","object":"model","owned_by":"tokenfab"},
  {"id":"kimi-k2.6","object":"model","owned_by":"tokenfab"},
  {"id":"kimi-k2.7-code","object":"model","owned_by":"tokenfab"},
  {"id":"kimi-k3","object":"model","owned_by":"tokenfab"},
  {"id":"occupancy-hold","object":"model","owned_by":"tokenfab"},
  {"id":"qwen3.7-max","object":"model","owned_by":"tokenfab"},
  {"id":"qwen3.7-max-2026-06-08","object":"model","owned_by":"tokenfab"},
  {"id":"qwen3.7-plus","object":"model","owned_by":"tokenfab"},
  {"id":"viduq3-pro","object":"model","owned_by":"tokenfab"},
  {"id":"viduq3-turbo","object":"model","owned_by":"tokenfab"}
]}

{"error":{"code":"invalid_api_key","message":"Authentication failed, please check your API Key"}}

from langchain_openai import ChatOpenAI
llm = ChatOpenAI(model="glm-5.2", api_key="your-api-key", base_url="https://api.tokenfab.cn/v1")
response = llm.invoke("Introduce deep learning")

curl -X POST https://api.tokenfab.cn/v1/videos \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.1-t2v",
    "prompt": "A golden puppy running on the grass, sunny, camera following",
    "seconds": "5",
    "size": "1080P"
  }'

# Response Example
# {"id":"vid-abc123","status":"queued","created_at":"2026-07-01T12:00:00Z"}

# Query task status
curl https://api.tokenfab.cn/v1/videos/vid-abc123 \
  -H "Authorization: Bearer your-api-key"

# Response Example (in progress, may carry progress)
# {"id":"vid-abc123","status":"in_progress","progress":45}

# Response Example (failed)
# {"id":"vid-abc123","status":"failed","error":{"message":"..."}}

# Response Example (completed)
# {"id":"vid-abc123","status":"completed","videos":[{"url":"https://cdn.tokenfab.cn/...mp4"}],"url":"https://cdn.tokenfab.cn/...mp4"}

# Download video (url from the completed response above; no API key required)
curl -o video.mp4 "https://cdn.tokenfab.cn/...mp4"

curl -X POST https://api.tokenfab.cn/v1/videos \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.1-i2v",
    "prompt": "Camera slowly pushes in, a girl slightly turns her head and smiles",
    "input_reference": "https://example.com/photo.jpg",
    "seconds": "5",
    "size": "1080P"
  }'

curl -X POST https://api.tokenfab.cn/v1/videos \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "viduq3-turbo",
    "prompt": "City skyline transitioning from day to night, lights gradually turning on",
    "input_reference": "https://example.com/first_frame.jpg",
    "last_frame": "https://example.com/last_frame.jpg",
    "seconds": "5",
    "size": "1080P"
  }'

curl -X POST https://api.tokenfab.cn/v1/videos \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "happyhorse-1.1-r2v",
    "prompt": "The person in [Image 1] walks down the street, keeping the outfit style consistent",
    "reference_images": [
      "https://example.com/ref1.jpg",
      "https://example.com/ref2.jpg"
    ],
    "seconds": "5",
    "size": "1080P"
  }'