Token 計數

概覽

LiteLLM 透過呼叫各提供者特定的 token 計數 API 提供精確的 token 計數。這可讓您在傳送請求前取得準確的 token 數量，協助進行成本估算與上下文視窗管理。

功能	詳細資訊
SDK 方法	litellm.acount_tokens()
Proxy 端點	/v1/messages/count_tokens（Anthropic 格式）、/v1/responses/input_tokens（OpenAI 格式）
備援	對不支援的提供者採用本地 tiktoken 基礎計數

支援的提供者

提供者	Token 計數 API	格式
OpenAI	Responses API /input_tokens	OpenAI Responses
Anthropic	Messages /count_tokens	Anthropic Messages
Vertex AI (Claude)	Vertex AI Partner Models Token Counter	Anthropic Messages
Bedrock (Claude)	AWS Bedrock CountTokens API	Anthropic Messages
Gemini	Google AI Studio countTokens API	Anthropic Messages
Vertex AI (Gemini)	Vertex AI countTokens API	Anthropic Messages
其他提供者	本地 tiktoken 備援	N/A

SDK 使用方式

基本用法

import asyncio
import litellm

async def main():
    # OpenAI
    result = await litellm.acount_tokens(
        model="openai/gpt-4o",
        messages=[{"role": "user", "content": "Hello, how are you?"}],
    )
    print(f"Token count: {result.total_tokens}")
    print(f"Tokenizer: {result.tokenizer_type}")  # "openai_api"

    # Anthropic
    result = await litellm.acount_tokens(
        model="anthropic/claude-3-5-sonnet-20241022",
        messages=[{"role": "user", "content": "Hello, how are you?"}],
    )
    print(f"Token count: {result.total_tokens}")
    print(f"Tokenizer: {result.tokenizer_type}")  # "anthropic_api"

asyncio.run(main())

搭配工具與系統訊息

import asyncio
import litellm

async def main():
    result = await litellm.acount_tokens(
        model="openai/gpt-4o",
        messages=[{"role": "user", "content": "What's the weather in Paris?"}],
        tools=[{
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get weather for a city",
                "parameters": {
                    "type": "object",
                    "properties": {"city": {"type": "string"}},
                },
            },
        }],
        system="You are a helpful weather assistant.",
    )
    print(f"Token count (with tools): {result.total_tokens}")

asyncio.run(main())

回應格式

litellm.acount_tokens() 會回傳一個 TokenCountResponse：

TokenCountResponse(
    total_tokens=15,           # Token count
    request_model="openai/gpt-4o",  # Model requested
    model_used="gpt-4o",      # Model used for counting
    tokenizer_type="openai_api",    # "openai_api", "anthropic_api", "local_tokenizer"
    original_response={"input_tokens": 15},  # Raw API response
    error=False,               # True if counting failed
    error_message=None,        # Error details if failed
)

備援行為

如果提供者不支援 token 計數 API，或 API 金鑰遺失，acount_tokens() 會自動退回到本地 tiktoken 基礎計數：

# Unsupported provider → automatic fallback
result = await litellm.acount_tokens(
    model="together_ai/meta-llama/Llama-3-8b-chat-hf",
    messages=[{"role": "user", "content": "Hello"}],
)
print(result.tokenizer_type)  # "local_tokenizer"

Proxy 使用方式

OpenAI 格式 — /v1/responses/input_tokens

curl

curl -X POST "http://localhost:4000/v1/responses/input_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "gpt-4o",
    "input": "Hello, how are you?"
  }'

Python (httpx)

import httpx

response = httpx.post(
    "http://localhost:4000/v1/responses/input_tokens",
    headers={
        "Content-Type": "application/json",
        "Authorization": "Bearer sk-1234"
    },
    json={
        "model": "gpt-4o",
        "input": "Hello, how are you?"
    }
)

print(response.json())
# {"input_tokens": 7}

回應：

{"input_tokens": 7}

Anthropic 格式 — /v1/messages/count_tokens

請參閱 Anthropic Token Counting 取得完整文件。

curl -X POST "http://localhost:4000/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "claude-3-5-sonnet-20241022",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Proxy 設定

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY

  - model_name: claude-3-5-sonnet
    litellm_params:
      model: anthropic/claude-3-5-sonnet-20241022
      api_key: os.environ/ANTHROPIC_API_KEY