feat(memory-config): Add V1 memory config management API endpoints
-Add full CRUD endpoints for memory config via API Key auth (/v1/memory_config) -Add V1 request schemas: ConfigCreateRequest, ConfigUpdateRequest, ConfigUpdateExtractedRequest, ConfigUpdateForgettingRequest -Add config-workspace ownership verification -Add scenes/simple, read_all_config, read_config_extracted query endpoints -Add create_config, update_config, update_config_extracted, update_config_forgetting, delete_config mutation endpoints -Reuse management-side controllers with pre-validation ownership checks
This commit is contained in:
miao
@@ -108,8 +108,9 @@ async def create_end_user(
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workspace_id=workspace_id,
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other_id=payload.other_id,
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memory_config_id=memory_config_id,
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other_name=payload.other_name,
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)
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end_user.other_name = payload.other_name
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logger.info(f"End user ready: {end_user.id}")
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result = {
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@@ -1,20 +1,84 @@
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"""Memory Config 服务接口 - 基于 API Key 认证"""
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from fastapi import APIRouter, Depends, Request
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from typing import Optional
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import uuid
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from fastapi import APIRouter, Body, Depends, Header, Query, Request
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from fastapi.encoders import jsonable_encoder
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from sqlalchemy.orm import Session
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from app.controllers import memory_storage_controller
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from app.controllers import memory_forget_controller
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from app.controllers import ontology_controller
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from app.schemas.memory_storage_schema import ForgettingConfigUpdateRequest
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from app.core.api_key_auth import require_api_key
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from app.core.error_codes import BizCode
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from app.core.exceptions import BusinessException
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from app.core.logging_config import get_business_logger
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from app.core.response_utils import success
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from app.db import get_db
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from app.repositories.memory_config_repository import MemoryConfigRepository
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from app.schemas.api_key_schema import ApiKeyAuth
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from app.schemas.memory_api_schema import ListConfigsResponse
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from app.schemas.memory_api_schema import (
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ConfigUpdateExtractedRequest,
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ConfigUpdateRequest,
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ListConfigsResponse,
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ConfigCreateRequest,
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ConfigUpdateForgettingRequest,
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)
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from app.schemas.memory_storage_schema import (
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ConfigUpdate,
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ConfigUpdateExtracted,
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ConfigParamsCreate,
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)
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from app.services import api_key_service
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from app.services.memory_api_service import MemoryAPIService
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from app.utils.config_utils import resolve_config_id
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router = APIRouter(prefix="/memory_config", tags=["V1 - Memory Config API"])
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logger = get_business_logger()
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def _get_current_user(api_key_auth: ApiKeyAuth, db: Session):
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"""Build a current_user object from API key auth
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Args:
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api_key_auth: Validated API key auth info
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db: Database session
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Returns:
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User object with current_workspace_id set
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"""
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api_key = api_key_service.ApiKeyService.get_api_key(db, api_key_auth.api_key_id, api_key_auth.workspace_id)
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current_user = api_key.creator
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current_user.current_workspace_id = api_key_auth.workspace_id
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return current_user
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def _verify_config_ownership(config_id:str, workspace_id:uuid.UUID, db:Session):
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"""Verify that the config belongs to the workspace.
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Args:
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config_id: The ID of the config to verify
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workspace_id: The workspace ID tocheck against
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db: Database session for querying
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Raises:
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BusinessException: If the config does not exist or does not belong to the workspace
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"""
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try:
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resolved_id = resolve_config_id(config_id, db)
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except ValueError as e:
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raise BusinessException(
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message=f"Invalid config_id: {e}",
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code=BizCode.INVALID_PARAMETER,
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)
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config = MemoryConfigRepository.get_by_id(db, resolved_id)
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if not config or config.workspace_id != workspace_id:
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raise BusinessException(
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message="Config not found or access denied",
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code=BizCode.MEMORY_CONFIG_NOT_FOUND,
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)
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@router.get("/configs")
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@require_api_key(scopes=["memory"])
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async def list_memory_configs(
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@@ -37,3 +101,245 @@ async def list_memory_configs(
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logger.info(f"Listed {result['total']} configs for workspace: {api_key_auth.workspace_id}")
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return success(data=ListConfigsResponse(**result).model_dump(), msg="Configs listed successfully")
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@router.get("/read_all_config")
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@require_api_key(scopes=["memory"])
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async def read_all_config(
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request:Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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):
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"""
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List all memory configs with full details (enhanced version).
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Returns complete config fields for the authorized workspace.
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No config_id ownership check needed — results are filtered by workspace.
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"""
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logger.info(f"V1 get all configs (full) - workspace: {api_key_auth.workspace_id}")
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current_user = _get_current_user(api_key_auth, db)
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return memory_storage_controller.read_all_config(
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current_user=current_user,
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db=db,
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)
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@router.get("/scenes/simple")
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@require_api_key(scopes=["memory"])
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async def get_ontology_scenes(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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):
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"""
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Get available ontology scenes for the workspace.
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Returns a simple list of scene_id and scene_name for dropdown selection.
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Used before creating a memory config to choose which ontology scene to associate.
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"""
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logger.info(f"V1 get scenes - workspace: {api_key_auth.workspace_id}")
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current_user = _get_current_user(api_key_auth, db)
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return await ontology_controller.get_scenes_simple(
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db=db,
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current_user=current_user,
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)
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@router.get("/read_config_extracted")
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@require_api_key(scopes=["memory"])
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async def read_config_extracted(
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request: Request,
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config_id: str = Query(..., description="config_id"),
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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):
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"""
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Get extraction engine config details for a specific config.
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Only configs belonging to the authorized workspace can be queried.
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"""
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logger.info(f"V1 read extracted config - config_id: {config_id}, workspace: {api_key_auth.workspace_id}")
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_verify_config_ownership(config_id, api_key_auth.workspace_id, db)
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current_user = _get_current_user(api_key_auth, db)
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return memory_storage_controller.read_config_extracted(
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config_id = config_id,
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current_user = current_user,
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db = db,
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)
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@router.post("/create_config")
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@require_api_key(scopes=["memory"])
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async def create_memory_config(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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message: str = Body(None, description="Request body"),
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x_language_type: Optional[str] = Header(None, alias="X-Language-Type"),
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):
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"""
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Create a new memory config for the workspace.
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The config will be associated with the workspace of the API Key.
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config_name is required, other fields are optional.
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"""
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body = await request.json()
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payload = ConfigCreateRequest(**body)
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logger.info(f"V1 create config - workspace: {api_key_auth.workspace_id}, config_name: {payload.config_name}")
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# 构造管理端 Schema，workspace_id 从 API Key 注入
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current_user = _get_current_user(api_key_auth, db)
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mgmt_payload = ConfigParamsCreate(
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config_name=payload.config_name,
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config_desc=payload.config_desc or "",
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scene_id=payload.scene_id,
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llm_id=payload.llm_id,
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embedding_id=payload.embedding_id,
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rerank_id=payload.rerank_id,
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reflection_model_id=payload.reflection_model_id,
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emotion_model_id=payload.emotion_model_id,
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)
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#将返回数据中UUID序列化处理
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result =memory_storage_controller.create_config(
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payload=mgmt_payload,
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current_user=current_user,
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db=db,
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x_language_type=x_language_type,
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)
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return jsonable_encoder(result)
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@router.put("/update_config")
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@require_api_key(scopes=["memory"])
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async def update_memory_config(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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message: str = Body(None, description="Request body"),
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):
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"""
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Update memory config basic info (name, description, scene).
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Requires API Key with 'memory' scope
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Only configs belonging to the authorized workspace can be updated.
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"""
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body = await request.json()
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payload = ConfigUpdateRequest(**body)
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logger.info(f"V1 update config - config_id: {payload.config_id}, workspace: {api_key_auth.workspace_id}")
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_verify_config_ownership(payload.config_id, api_key_auth.workspace_id, db)
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current_user = _get_current_user(api_key_auth, db)
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mgmt_payload = ConfigUpdate(
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config_id = payload.config_id,
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config_name = payload.config_name,
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config_desc = payload.config_desc,
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scene_id = payload.scene_id,
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)
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return memory_storage_controller.update_config(
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payload = mgmt_payload,
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current_user = current_user,
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db = db,
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)
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@router.put("/update_config_extracted")
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@require_api_key(scopes=["memory"])
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async def update_memory_config_extracted(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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message: str = Body(None, description="Request body"),
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):
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"""
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update memory config extraction engine config (models, thresholds, chunking, pruning, etc.).
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Requires API Key with 'memory' scope.
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Only configs belonging to the authorized workspace can be updated.
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"""
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body = await request.json()
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payload = ConfigUpdateExtractedRequest(**body)
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logger.info(f"V1 update extracted config - config_id: {payload.config_id}, workspace: {api_key_auth.workspace_id}")
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#校验权限
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_verify_config_ownership(payload.config_id, api_key_auth.workspace_id, db)
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current_user = _get_current_user(api_key_auth, db)
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update_fields = payload.model_dump(exclude_unset=True)
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mgmt_payload = ConfigUpdateExtracted(**update_fields)
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return memory_storage_controller.update_config_extracted(
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payload = mgmt_payload,
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current_user = current_user,
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db = db,
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)
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@router.put("/update_config_forgetting")
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@require_api_key(scopes=["memory"])
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async def update_memory_config_forgetting(
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request: Request,
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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message: str = Body(None, description="Request body"),
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):
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"""
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update memory config forgetting settings (forgetting strategy, parameters, etc.).
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Requires API Key with 'memory' scope.
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Only configs belonging to the authorized workspace can be updated.
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"""
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body = await request.json()
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payload = ConfigUpdateForgettingRequest(**body)
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logger.info(f"V1 update forgetting config - config_id: {payload.config_id}, workspace: {api_key_auth.workspace_id}")
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#校验权限
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_verify_config_ownership(payload.config_id, api_key_auth.workspace_id, db)
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current_user = _get_current_user(api_key_auth, db)
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update_fields = payload.model_dump(exclude_unset=True)
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mgmt_payload = ForgettingConfigUpdateRequest(**update_fields)
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#将返回数据中UUID序列化处理
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result = await memory_forget_controller.update_forgetting_config(
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payload = mgmt_payload,
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current_user = current_user,
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db = db,
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)
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return jsonable_encoder(result)
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@router.delete("/delete_config")
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@require_api_key(scopes=["memory"])
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async def delete_memory_config(
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config_id: str,
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request: Request,
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force: bool = Query(False, description="是否强制删除（即使有终端用户正在使用）"),
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api_key_auth: ApiKeyAuth = None,
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db: Session = Depends(get_db),
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):
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"""
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Delete a memory config.
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- Default configs cannot be deleted.
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- If end users are connected and force=False, returns a warning.
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- If force=True, clears end user references and deletes the config.
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Only configs belonging to the authorized workspace can be deleted.
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"""
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logger.info(f"V1 delete config - config_id: {config_id}, force: {force}, workspace: {api_key_auth.workspace_id}")
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_verify_config_ownership(config_id, api_key_auth.workspace_id, db)
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current_user = _get_current_user(api_key_auth, db)
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return memory_storage_controller.delete_config(
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config_id=config_id,
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force=force,
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current_user=current_user,
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db=db,
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)
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@@ -4,9 +4,10 @@ This module defines Pydantic schemas for the Memory API Service endpoints,
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including request validation and response structures for read and write operations.
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"""
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from typing import Any, Dict, List, Optional
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from typing import Any, Dict, List, Literal, Optional
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import uuid
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from pydantic import BaseModel, Field, field_validator
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from pydantic import BaseModel, ConfigDict, Field, field_validator
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class MemoryWriteRequest(BaseModel):
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@@ -231,6 +232,7 @@ class MemoryConfigItem(BaseModel):
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created_at: Optional[str] = Field(None, description="Creation timestamp")
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updated_at: Optional[str] = Field(None, description="Last update timestamp")
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# ========== V1 记忆配置管理接口 Schema ==========
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class ListConfigsResponse(BaseModel):
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"""Response schema for listing memory configs.
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@@ -241,3 +243,149 @@ class ListConfigsResponse(BaseModel):
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"""
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configs: List[MemoryConfigItem] = Field(default_factory=list, description="List of configs")
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total: int = Field(0, description="Total number of configs")
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class ConfigCreateRequest(BaseModel):
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"""Request schema for creating a new memory config."""
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config_name: str = Field(..., description="Configuration name")
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config_desc: Optional[str] = Field("", description="Configuration description")
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scene_id: uuid.UUID = Field(..., description="Associated ontology scene ID (UUID, required)")
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llm_id: Optional[str] = Field(None, description="LLM model configuration ID")
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embedding_id: Optional[str] = Field(None, description="Embedding model configuration ID")
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rerank_id: Optional[str] = Field(None, description="Reranking model configuration ID")
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reflection_model_id: Optional[str] = Field(None, description="Reflection model ID")
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emotion_model_id: Optional[str] = Field(None, description="Emotion analysis model ID")
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@field_validator("config_name")
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@classmethod
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def validate_config_name(cls, v: str) -> str:
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if not v or not v.strip():
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raise ValueError("config_name is required and cannot be empty")
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return v.strip()
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class ConfigUpdateRequest(BaseModel):
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"""Request schema for updating memory config basic info.
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Attributes:
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config_id: Configuration UUID to update (required)
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config_name: New configuration name
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config_desc: New configuration description
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scene_id: New associated ontology scene ID
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"""
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config_id: str = Field(..., description="Configuration ID to update")
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config_name: Optional[str] = Field(None, description="Configuration name")
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config_desc: Optional[str] = Field(None, description="Configuration description")
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scene_id: Optional[uuid.UUID] = Field(None, description="Associated ontology scene ID")
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@field_validator("config_id")
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@classmethod
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def validate_config_id(cls, v: str) -> str:
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"""Validate that config_id is not empty."""
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if not v or not v.strip():
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raise ValueError("config_id is required and cannot be empty")
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return v.strip()
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class ConfigUpdateExtractedRequest(BaseModel):
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"""Request schema for updating memory config extracted parameters.
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Attributes:
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config_id: Configuration UUID to update (required)
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llm_id: Optional LLM model configuration ID
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audio_id: Optional audio model configuration ID
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vision_id: Optional vision model configuration ID
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video_id: Optional video model configuration ID
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embedding_id: Optional embedding model configuration ID
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rerank_id: Optional reranking model configuration ID
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enable_llm_dedup_blockwise: Optional toggle for LLM decision deduplication
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enable_llm_disambiguation: Optional toggle for LLM decision disambiguation
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deep_retrieval: Optional toggle for deep retrieval
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t_type_strict: Optional float (0-1) for type strictness threshold
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t_name_strict: Optional float (0-1) for name strictness threshold
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t_overall: Optional float (0-1) for overall strictness threshold
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state: Optional boolean for config active state
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chunker_strategy: Optional string for memory chunking strategy
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statement_granularity: Optional int (1-3) for statement extraction granularity
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include_dialogue_context: Optional boolean for including dialogue context in retrieval
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max_context: Optional int for maximum dialogue context length in characters
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pruning_enabled: Optional boolean to enable intelligent semantic pruning
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pruning_scene: Optional string for semantic pruning scene
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pruning_threshold: Optional float (0-0.9) for semantic pruning threshold
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enable_self_reflexion: Optional boolean to enable self-reflexion
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iteration_period: Optional string for reflexion iteration period in hours (1, 3, 6, 12, 24)
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reflexion_range: Optional string for reflexion range (partial or all)
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baseline: Optional string for baseline (TIME/FACT/TIME-FACT)
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"""
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config_id: str = Field(..., description="Configuration ID (UUID)")
|
||||
llm_id: Optional[str] = Field(None, description="LLM model configuration ID")
|
||||
audio_id: Optional[str] = Field(None, description="Audio model ID")
|
||||
vision_id: Optional[str] = Field(None, description="Vision model ID")
|
||||
video_id: Optional[str] = Field(None, description="Video model ID")
|
||||
embedding_id: Optional[str] = Field(None, description="Embedding model configuration ID")
|
||||
rerank_id: Optional[str] = Field(None, description="Reranking model configuration ID")
|
||||
enable_llm_dedup_blockwise: Optional[bool] = Field(None, description="Enable LLM decision deduplication")
|
||||
enable_llm_disambiguation: Optional[bool] = Field(None, description="Enable LLM decision disambiguation")
|
||||
deep_retrieval: Optional[bool] = Field(None, description="Deep retrieval toggle")
|
||||
|
||||
t_type_strict: Optional[float] = Field(None, ge=0.0, le=1.0, description="type strictness threshold")
|
||||
t_name_strict: Optional[float] = Field(None, ge=0.0, le=1.0, description="name strictness threshold")
|
||||
t_overall: Optional[float] = Field(None, ge=0.0, le=1.0, description="overall strictness threshold")
|
||||
state: Optional[bool] = Field(None, description="config active state")
|
||||
# 句子提取
|
||||
chunker_strategy: Optional[str] = Field(None, description="memory chunking strategy")
|
||||
statement_granularity: Optional[int] = Field(None, ge=1, le=3, description="statement extraction granularity")
|
||||
include_dialogue_context: Optional[bool] = Field(None, description="whether to include dialogue context in retrieval")
|
||||
max_context: Optional[int] = Field(None, gt=100, description="maximum dialogue context length in characters")
|
||||
# 剪枝配置：与 runtime.json 中 pruning 段对应
|
||||
pruning_enabled: Optional[bool] = Field(None, description="whether to enable intelligent semantic pruning")
|
||||
pruning_scene: Optional[str] = Field(None, description="semantic pruning scene")
|
||||
pruning_threshold: Optional[float] = Field(None, ge=0.0, le=0.9, description="semantic pruning threshold (0-0.9)")
|
||||
enable_self_reflexion: Optional[bool] = Field(None, description="whether to enable self-reflexion")
|
||||
iteration_period: Optional[Literal["1", "3", "6", "12", "24"]] = Field(None, description="reflexion iteration period in hours (1, 3, 6, 12, 24)")
|
||||
reflexion_range: Optional[Literal["partial", "all"]] = Field(None, description="reflexion range: partial/all")
|
||||
baseline: Optional[Literal["TIME", "FACT", "TIME-FACT"]] = Field(None, description="baseline: TIME/FACT/TIME-FACT")
|
||||
|
||||
@field_validator("config_id")
|
||||
@classmethod
|
||||
def validate_config_id(cls, v: str) -> str:
|
||||
if not v or not v.strip():
|
||||
raise ValueError("config_id is required and cannot be empty")
|
||||
return v.strip()
|
||||
|
||||
class ConfigUpdateForgettingRequest(BaseModel):
|
||||
"""Request schema for updating memory config forgetting parameters.
|
||||
|
||||
Attributes:
|
||||
config_id: Configuration UUID to update (required)
|
||||
decay_constant: Decay constant for forgetting
|
||||
lambda_time: Time decay parameter
|
||||
lambda_mem: Memory decay parameter
|
||||
offset: Offset for forgetting curve
|
||||
max_history_length: Maximum history length to consider for forgetting
|
||||
forgetting_threshold: Threshold for forgetting
|
||||
min_days_since_access: Minimum days since last access to trigger forgetting
|
||||
enable_llm_summary: Whether to use LLM-generated summaries for forgetting
|
||||
max_merge_batch_size: Maximum batch size for merging nodes during forgetting
|
||||
forgetting_interval_hours: Interval in hours for periodic forgetting
|
||||
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True, extra="forbid")
|
||||
config_id: str = Field(..., description="Configuration ID (UUID)")
|
||||
decay_constant: Optional[float] = Field(None, ge=0.0, le=1.0, description="Decay constant for forgetting")
|
||||
lambda_time: Optional[float] = Field(None, ge=0.0, le=1.0, description="Time decay parameter")
|
||||
lambda_mem: Optional[float] = Field(None, ge=0.0, le=1.0, description="Memory decay parameter")
|
||||
offset: Optional[float] = Field(None, ge=0.0, le=1.0, description="Offset for forgetting curve")
|
||||
max_history_length: Optional[int] = Field(None, ge=10, le=1000, description="Maximum history length to consider for forgetting")
|
||||
forgetting_threshold: Optional[float] = Field(None, ge=0.0, le=1.0, description="Forgetting threshold")
|
||||
min_days_since_access: Optional[int] = Field(None, ge=1, le=365, description="Minimum days since last access to trigger forgetting")
|
||||
enable_llm_summary: Optional[bool] = Field(None, description="Whether to use LLM-generated summaries for forgetting")
|
||||
max_merge_batch_size: Optional[int] = Field(None, ge=1, le=1000, description="Maximum batch size for merging nodes during forgetting")
|
||||
forgetting_interval_hours: Optional[int] = Field(None, ge=1, le=168, description="Interval in hours for periodic forgetting")
|
||||
|
||||
@field_validator("config_id")
|
||||
@classmethod
|
||||
def validate_config_id(cls, v: str) -> str:
|
||||
if not v or not v.strip():
|
||||
raise ValueError("config_id is required and cannot be empty")
|
||||
return v.strip()
|
||||
Reference in New Issue
Block a user