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https://github.com/bytedance/deer-flow.git
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105db00987
* feat: show token usage per assistant response * fix: align client models response with token usage * fix: address token usage review feedback * docs: clarify token usage config example --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
134 lines
4.1 KiB
Python
134 lines
4.1 KiB
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel, Field
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from deerflow.config import get_app_config
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router = APIRouter(prefix="/api", tags=["models"])
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class ModelResponse(BaseModel):
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"""Response model for model information."""
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name: str = Field(..., description="Unique identifier for the model")
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model: str = Field(..., description="Actual provider model identifier")
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display_name: str | None = Field(None, description="Human-readable name")
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description: str | None = Field(None, description="Model description")
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supports_thinking: bool = Field(default=False, description="Whether model supports thinking mode")
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supports_reasoning_effort: bool = Field(default=False, description="Whether model supports reasoning effort")
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class TokenUsageResponse(BaseModel):
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"""Token usage display configuration."""
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enabled: bool = Field(default=False, description="Whether token usage display is enabled")
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class ModelsListResponse(BaseModel):
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"""Response model for listing all models."""
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models: list[ModelResponse]
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token_usage: TokenUsageResponse
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@router.get(
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"/models",
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response_model=ModelsListResponse,
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summary="List All Models",
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description="Retrieve a list of all available AI models configured in the system.",
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)
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async def list_models() -> ModelsListResponse:
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"""List all available models from configuration.
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Returns model information suitable for frontend display,
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excluding sensitive fields like API keys and internal configuration.
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Returns:
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A list of all configured models with their metadata and token usage display settings.
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Example Response:
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```json
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{
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"models": [
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{
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"name": "gpt-4",
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"model": "gpt-4",
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"display_name": "GPT-4",
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"description": "OpenAI GPT-4 model",
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"supports_thinking": false,
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"supports_reasoning_effort": false
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},
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{
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"name": "claude-3-opus",
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"model": "claude-3-opus",
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"display_name": "Claude 3 Opus",
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"description": "Anthropic Claude 3 Opus model",
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"supports_thinking": true,
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"supports_reasoning_effort": false
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}
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],
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"token_usage": {
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"enabled": true
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}
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}
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```
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"""
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config = get_app_config()
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models = [
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ModelResponse(
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name=model.name,
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model=model.model,
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display_name=model.display_name,
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description=model.description,
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supports_thinking=model.supports_thinking,
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supports_reasoning_effort=model.supports_reasoning_effort,
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)
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for model in config.models
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]
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return ModelsListResponse(
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models=models,
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token_usage=TokenUsageResponse(enabled=config.token_usage.enabled),
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)
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@router.get(
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"/models/{model_name}",
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response_model=ModelResponse,
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summary="Get Model Details",
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description="Retrieve detailed information about a specific AI model by its name.",
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)
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async def get_model(model_name: str) -> ModelResponse:
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"""Get a specific model by name.
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Args:
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model_name: The unique name of the model to retrieve.
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Returns:
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Model information if found.
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Raises:
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HTTPException: 404 if model not found.
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Example Response:
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```json
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{
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"name": "gpt-4",
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"display_name": "GPT-4",
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"description": "OpenAI GPT-4 model",
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"supports_thinking": false
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}
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```
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"""
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config = get_app_config()
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model = config.get_model_config(model_name)
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if model is None:
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raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
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return ModelResponse(
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name=model.name,
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model=model.model,
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display_name=model.display_name,
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description=model.description,
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supports_thinking=model.supports_thinking,
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supports_reasoning_effort=model.supports_reasoning_effort,
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)
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