catalog-agent/utils/api_models.py
2025-10-18 09:20:59 +08:00

292 lines
8.6 KiB
Python

#!/usr/bin/env python3
"""
API data models and response schemas.
"""
from typing import Dict, List, Optional, Any, AsyncGenerator
from pydantic import BaseModel, Field, field_validator, ConfigDict
class Message(BaseModel):
role: str
content: str
class DatasetRequest(BaseModel):
system_prompt: Optional[str] = None
mcp_settings: Optional[List[Dict]] = None
files: Optional[Dict[str, List[str]]] = Field(default=None, description="Files organized by key groups. Each key maps to a list of file paths (supports zip files)")
unique_id: Optional[str] = None
@field_validator('files', mode='before')
@classmethod
def validate_files(cls, v):
"""Validate dict format with key-grouped files"""
if v is None:
return None
if isinstance(v, dict):
# Validate dict format
for key, value in v.items():
if not isinstance(key, str):
raise ValueError(f"Key in files dict must be string, got {type(key)}")
if not isinstance(value, list):
raise ValueError(f"Value in files dict must be list, got {type(value)} for key '{key}'")
for item in value:
if not isinstance(item, str):
raise ValueError(f"File paths must be strings, got {type(item)} in key '{key}'")
return v
else:
raise ValueError(f"Files must be a dict with key groups, got {type(v)}")
class ChatRequest(BaseModel):
messages: List[Message]
model: str = "qwen3-next"
model_server: str = ""
unique_id: Optional[str] = None
stream: Optional[bool] = False
class FileProcessRequest(BaseModel):
unique_id: str
files: Optional[Dict[str, List[str]]] = Field(default=None, description="Files organized by key groups. Each key maps to a list of file paths (supports zip files)")
system_prompt: Optional[str] = None
mcp_settings: Optional[List[Dict]] = None
model_config = ConfigDict(extra='allow')
@field_validator('files', mode='before')
@classmethod
def validate_files(cls, v):
"""Validate dict format with key-grouped files"""
if v is None:
return None
if isinstance(v, dict):
# Validate dict format
for key, value in v.items():
if not isinstance(key, str):
raise ValueError(f"Key in files dict must be string, got {type(key)}")
if not isinstance(value, list):
raise ValueError(f"Value in files dict must be list, got {type(value)} for key '{key}'")
for item in value:
if not isinstance(item, str):
raise ValueError(f"File paths must be strings, got {type(item)} in key '{key}'")
return v
else:
raise ValueError(f"Files must be a dict with key groups, got {type(v)}")
class DatasetResponse(BaseModel):
success: bool
message: str
unique_id: Optional[str] = None
dataset_structure: Optional[str] = None
class ChatCompletionResponse(BaseModel):
id: str
object: str = "chat.completion"
created: int
model: str
choices: List[Dict[str, Any]]
usage: Optional[Dict[str, int]] = None
class ChatResponse(BaseModel):
choices: List[Dict]
usage: Optional[Dict] = None
class FileProcessResponse(BaseModel):
success: bool
message: str
unique_id: str
processed_files: List[str]
class ErrorResponse(BaseModel):
error: Dict[str, Any]
@classmethod
def create(cls, message: str, error_type: str = "invalid_request_error", code: Optional[str] = None):
error_data = {
"message": message,
"type": error_type
}
if code:
error_data["code"] = code
return cls(error=error_data)
class HealthCheckResponse(BaseModel):
status: str = "healthy"
timestamp: str
version: str = "1.0.0"
class SystemStatusResponse(BaseModel):
status: str
projects_count: int
total_projects: List[str]
active_projects: List[str]
system_info: Dict[str, Any]
class CacheStatusResponse(BaseModel):
cached_projects: List[str]
cache_info: Dict[str, Any]
class ProjectStatusResponse(BaseModel):
unique_id: str
project_exists: bool
project_path: Optional[str] = None
processed_files_count: int
processed_files: Dict[str, Dict]
document_files_count: int
document_files: List[str]
has_system_prompt: bool
has_mcp_settings: bool
readme_exists: bool
log_file_exists: bool
dataset_structure: Optional[str] = None
error: Optional[str] = None
class ProjectListResponse(BaseModel):
projects: List[str]
count: int
class ProjectStatsResponse(BaseModel):
unique_id: str
total_processed_files: int
total_document_files: int
total_document_size: int
total_document_size_mb: float
has_system_prompt: bool
has_mcp_settings: bool
has_readme: bool
document_files_detail: List[Dict[str, Any]]
embedding_files_count: int
embedding_files_detail: List[Dict[str, Any]]
class ProjectActionResponse(BaseModel):
success: bool
message: str
unique_id: str
action: str
# Utility functions for creating responses
def create_success_response(message: str, **kwargs) -> Dict[str, Any]:
"""Create a standardized success response"""
return {
"success": True,
"message": message,
**kwargs
}
def create_error_response(message: str, error_type: str = "error", **kwargs) -> Dict[str, Any]:
"""Create a standardized error response"""
return {
"success": False,
"error": error_type,
"message": message,
**kwargs
}
class QueueTaskRequest(BaseModel):
"""队列任务请求模型"""
unique_id: str
files: Optional[Dict[str, List[str]]] = Field(default=None, description="Files organized by key groups. Each key maps to a list of file paths (supports zip files)")
system_prompt: Optional[str] = None
mcp_settings: Optional[List[Dict]] = None
priority: Optional[int] = Field(default=0, description="Task priority (higher number = higher priority)")
delay: Optional[int] = Field(default=0, description="Delay execution by N seconds")
model_config = ConfigDict(extra='allow')
@field_validator('files', mode='before')
@classmethod
def validate_files(cls, v):
"""Validate dict format with key-grouped files"""
if v is None:
return None
if isinstance(v, dict):
# Validate dict format
for key, value in v.items():
if not isinstance(key, str):
raise ValueError(f"Key in files dict must be string, got {type(key)}")
if not isinstance(value, list):
raise ValueError(f"Value in files dict must be list, got {type(value)} for key '{key}'")
for item in value:
if not isinstance(item, str):
raise ValueError(f"File paths must be strings, got {type(item)} in key '{key}'")
return v
else:
raise ValueError(f"Files must be a dict with key groups, got {type(v)}")
class QueueTaskResponse(BaseModel):
"""队列任务响应模型"""
success: bool
message: str
unique_id: str
task_id: Optional[str] = None
task_status: Optional[str] = None
estimated_processing_time: Optional[int] = None # seconds
class QueueStatusResponse(BaseModel):
"""队列状态响应模型"""
success: bool
message: str
queue_stats: Dict[str, Any]
pending_tasks: List[Dict[str, Any]]
class TaskStatusResponse(BaseModel):
"""任务状态响应模型"""
success: bool
message: str
task_id: str
task_status: Optional[str] = None
task_result: Optional[Dict[str, Any]] = None
error: Optional[str] = None
def create_chat_response(
messages: List[Message],
model: str,
content: str,
usage: Optional[Dict[str, int]] = None
) -> Dict[str, Any]:
"""Create a chat completion response"""
import time
import uuid
return {
"id": f"chatcmpl-{uuid.uuid4().hex[:8]}",
"object": "chat.completion",
"created": int(time.time()),
"model": model,
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": content
},
"finish_reason": "stop"
}
],
"usage": usage or {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
}
}