Files
deer-flow/backend/src/gateway/routers/models.py
hetaoBackend 8434cf4c60 feat: add MCP API endpoint and enhance API documentation
Add new MCP configuration management endpoint and enhance API documentation
with detailed descriptions, examples, and OpenAPI support for better
developer experience.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-20 13:20:50 +08:00

111 lines
3.1 KiB
Python

from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from src.config import get_app_config
router = APIRouter(prefix="/api", tags=["models"])
class ModelResponse(BaseModel):
"""Response model for model information."""
name: str = Field(..., description="Unique identifier for the model")
display_name: str | None = Field(None, description="Human-readable name")
description: str | None = Field(None, description="Model description")
supports_thinking: bool = Field(default=False, description="Whether model supports thinking mode")
class ModelsListResponse(BaseModel):
"""Response model for listing all models."""
models: list[ModelResponse]
@router.get(
"/models",
response_model=ModelsListResponse,
summary="List All Models",
description="Retrieve a list of all available AI models configured in the system.",
)
async def list_models() -> ModelsListResponse:
"""List all available models from configuration.
Returns model information suitable for frontend display,
excluding sensitive fields like API keys and internal configuration.
Returns:
A list of all configured models with their metadata.
Example Response:
```json
{
"models": [
{
"name": "gpt-4",
"display_name": "GPT-4",
"description": "OpenAI GPT-4 model",
"supports_thinking": false
},
{
"name": "claude-3-opus",
"display_name": "Claude 3 Opus",
"description": "Anthropic Claude 3 Opus model",
"supports_thinking": true
}
]
}
```
"""
config = get_app_config()
models = [
ModelResponse(
name=model.name,
display_name=model.display_name,
description=model.description,
supports_thinking=model.supports_thinking,
)
for model in config.models
]
return ModelsListResponse(models=models)
@router.get(
"/models/{model_name}",
response_model=ModelResponse,
summary="Get Model Details",
description="Retrieve detailed information about a specific AI model by its name.",
)
async def get_model(model_name: str) -> ModelResponse:
"""Get a specific model by name.
Args:
model_name: The unique name of the model to retrieve.
Returns:
Model information if found.
Raises:
HTTPException: 404 if model not found.
Example Response:
```json
{
"name": "gpt-4",
"display_name": "GPT-4",
"description": "OpenAI GPT-4 model",
"supports_thinking": false
}
```
"""
config = get_app_config()
model = config.get_model_config(model_name)
if model is None:
raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
return ModelResponse(
name=model.name,
display_name=model.display_name,
description=model.description,
supports_thinking=model.supports_thinking,
)