gns3-server/gns3server/schemas/controller/llm_model_configs.py
YueGuobin f4723cd083 docs: restructure LLM model configs API documentation for nested config object
Update API documentation to reflect new nested `config` object structure in LLM model configurations endpoints. The response format now encapsulates provider-specific fields (provider, base_url, model, temperature, api_key, max_tokens) within a `config` object, while moving ownership metadata (user_id, group_id, is_default, version, created_at, updated_at) to the top level. This aligns the user-facing endpoints with the group configuration structure and improves API consistency.
2026-03-03 22:47:36 +08:00

133 lines
4.6 KiB
Python

#
# Copyright (C) 2026 GNS3 Technologies Inc.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from typing import Optional, List, Literal
from pydantic import BaseModel, Field, ConfigDict
from uuid import UUID
from .base import DateTimeModelMixin
# Valid model types
ModelType = Literal['text', 'vision', 'stt', 'tts', 'multimodal', 'embedding', 'reranking', 'other']
# Core model config schema (stored in config JSONB field)
class LLMModelConfigData(BaseModel):
"""
LLM model configuration data.
Stored in the config JSONB column (provider, base_url, model, etc.).
"""
provider: str = Field(..., description="LLM provider (e.g., 'openai', 'anthropic', 'ollama')")
base_url: str = Field(..., description="API base URL")
model: str = Field(..., description="Model name")
temperature: float = Field(default=0.7, ge=0.0, le=2.0, description="Temperature parameter")
api_key: Optional[str] = Field(None, description="API key (will be encrypted)")
max_tokens: Optional[int] = Field(None, gt=0, description="Max tokens for generation")
# Allow extra fields for extensibility
model_config = ConfigDict(extra="allow")
# Request schemas
class LLMModelConfigCreate(BaseModel):
"""Request to create a new LLM model configuration."""
name: str = Field(..., min_length=1, max_length=100, description="Configuration name")
model_type: ModelType = Field(..., description="Model type")
is_default: Optional[bool] = Field(False, description="Set as default configuration")
# Config fields
provider: str = Field(..., description="LLM provider")
base_url: str = Field(..., description="API base URL")
model: str = Field(..., description="Model name")
temperature: float = Field(default=0.7, ge=0.0, le=2.0)
api_key: Optional[str] = None
max_tokens: Optional[int] = Field(None, gt=0)
# Allow extra config fields
model_config = ConfigDict(extra="allow")
class LLMModelConfigUpdate(BaseModel):
"""Request to update an existing LLM model configuration."""
# Table-level fields
name: Optional[str] = Field(None, min_length=1, max_length=100)
model_type: Optional[ModelType] = None
is_default: Optional[bool] = None
expected_version: Optional[int] = Field(None, description="Expected version for optimistic locking")
# Config fields
provider: Optional[str] = None
base_url: Optional[str] = None
model: Optional[str] = None
temperature: Optional[float] = Field(None, ge=0.0, le=2.0)
api_key: Optional[str] = None
max_tokens: Optional[int] = Field(None, gt=0)
# Allow extra config fields
model_config = ConfigDict(extra="allow")
# Response schemas
class LLMModelConfigResponse(DateTimeModelMixin):
"""LLM model configuration response."""
config_id: UUID
name: str
model_type: ModelType
config: LLMModelConfigData
user_id: Optional[UUID] = None
group_id: Optional[UUID] = None
is_default: bool
version: int = Field(..., description="Optimistic locking version")
model_config = ConfigDict(from_attributes=True)
class LLMModelConfigWithSource(DateTimeModelMixin):
"""Model configuration with source information (for inheritance)."""
config_id: UUID
name: str
model_type: ModelType
config: LLMModelConfigData
user_id: Optional[UUID] = None
group_id: Optional[UUID] = None
is_default: bool
version: int
source: str = Field(..., description="Source: 'user' or 'group'")
group_name: Optional[str] = Field(None, description="Group name if source is 'group'")
model_config = ConfigDict(from_attributes=True, extra="allow")
class LLMModelConfigInheritedResponse(BaseModel):
"""Response containing user's effective configs (own + inherited from groups)."""
configs: list[LLMModelConfigWithSource]
default_config: Optional[LLMModelConfigWithSource] = None
total: int
class LLMModelConfigListResponse(BaseModel):
"""Response containing a list of model configurations with default."""
configs: list[LLMModelConfigResponse]
default_config: Optional[LLMModelConfigResponse] = None
total: int