Files
DATA 6de0bf9f5b Initial commit: hardened DeerFlow factory
Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection
hardening:

- New deerflow.security package: content_delimiter, html_cleaner,
  sanitizer (8 layers — invisible chars, control chars, symbols, NFC,
  PUA, tag chars, horizontal whitespace collapse with newline/tab
  preservation, length cap)
- New deerflow.community.searx package: web_search, web_fetch,
  image_search backed by a private SearX instance, every external
  string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>>
  delimiters
- All native community web providers (ddg_search, tavily, exa,
  firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail
  stubs that raise NativeWebToolDisabledError at import time, so a
  misconfigured tool.use path fails loud rather than silently falling
  back to unsanitized output
- Native client back-doors (jina_client.py, infoquest_client.py)
  stubbed too
- Native-tool tests quarantined under tests/_disabled_native/
  (collect_ignore_glob via local conftest.py)
- Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve
  newlines and tabs so list/table structure survives
- Hardened runtime config.yaml references only the searx-backed tools
- Factory overlay (backend/) kept in sync with deer-flow tree as a
  reference / source

See HARDENING.md for the full audit trail and verification steps.
2026-04-12 14:23:57 +02:00

117 lines
3.5 KiB
Python

from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from deerflow.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")
model: str = Field(..., description="Actual provider model identifier")
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")
supports_reasoning_effort: bool = Field(default=False, description="Whether model supports reasoning effort")
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,
model=model.model,
display_name=model.display_name,
description=model.description,
supports_thinking=model.supports_thinking,
supports_reasoning_effort=model.supports_reasoning_effort,
)
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,
model=model.model,
display_name=model.display_name,
description=model.description,
supports_thinking=model.supports_thinking,
supports_reasoning_effort=model.supports_reasoning_effort,
)