833 lines
34 KiB
Python
833 lines
34 KiB
Python
import inspect
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import json
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from typing import Any, Dict, Iterable, Mapping, Optional, Protocol
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from fastapi import Depends, HTTPException
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from sqlalchemy.orm import Session
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from app.core.config import settings
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from app.db import get_db_session
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from app.repositories.conversation_repository import ConversationRepository
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from app.repositories.message_repository import MessageRepository
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from app.services.contract_content_normalizer import normalize_contract_content
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from shared_ai_platform_sdk import RequestContext as SharedAIRequestContext
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from shared_ai_platform_sdk import SharedAIPlatformClient as SharedAIPlatformSdkClient
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from shared_ai_platform_sdk import SharedAIPlatformError
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REMOTE_CHAT_TEMPLATE_KEYS = {
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"general-assistant.chat",
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"internal-knowledge.chat",
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"site-chat.customer-service",
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}
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class SharedAIPlatformClient(Protocol):
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def stream_answer(
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self,
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current_user: Dict[str, Any],
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conversation_id: Optional[str],
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message: str,
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review_context: Optional[Any] = None,
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template_key: Optional[str] = None,
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) -> Iterable[str]: ...
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def list_knowledge_bases(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict: ...
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def list_conversations(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict: ...
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def get_conversation_detail(self, current_user: Dict[str, Any], conversation_id: str) -> dict: ...
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def run_legal_review(self, current_user: Dict[str, Any], payload: Dict[str, Any]) -> dict: ...
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def extract_document_text(self, current_user: Dict[str, Any], *, file_name: str, mime_type: Optional[str], content: bytes) -> dict: ...
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def classify_pdf_source(self, current_user: Dict[str, Any], *, content: bytes) -> dict: ...
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def create_knowledge_base(self, current_user: Dict[str, Any], name: str, description: Optional[str]) -> dict: ...
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def list_knowledge_base_versions(self, current_user: Dict[str, Any], knowledge_base_id: str) -> list[dict]: ...
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def publish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict: ...
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def unpublish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict: ...
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def rollback_knowledge_base(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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target_version_label: str,
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change_summary: Optional[str] = None,
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) -> dict: ...
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def list_documents(self, current_user: Dict[str, Any], knowledge_base_id: str, page: int, page_size: int) -> dict: ...
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def upload_document(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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file_name: str,
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mime_type: Optional[str],
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content: bytes,
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) -> dict: ...
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def retry_document(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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document_id: str,
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file_name: Optional[str] = None,
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mime_type: Optional[str] = None,
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content: Optional[bytes] = None,
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) -> dict: ...
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def enhance_contract_generation(
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self,
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current_user: Dict[str, Any],
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*,
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prompt_runtime: Optional[Dict[str, Any]],
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prompt: str,
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draft_content: str,
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metadata: Optional[Dict[str, Any]] = None,
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) -> dict: ...
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class RemoteSharedAIPlatformClient:
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def __init__(self, base_url: str, app_id: str, api_key: str, timeout_seconds: float, db: Optional[Session] = None):
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self.base_url = base_url.rstrip("/")
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self.app_id = app_id
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self.api_key = api_key
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self.timeout_seconds = timeout_seconds
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self.db = db
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self.sdk = SharedAIPlatformSdkClient(
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base_url=self.base_url,
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api_key=self.api_key,
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app_id=self.app_id,
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timeout_seconds=self.timeout_seconds,
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api_prefix=settings.shared_ai_platform_api_prefix,
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)
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def _context(self, current_user: Dict[str, Any]) -> SharedAIRequestContext:
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return SharedAIRequestContext(
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tenant_id=current_user.get("tenant_id", ""),
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user_id=current_user.get("id", ""),
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user_role=current_user.get("role", "admin"),
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)
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def stream_answer(
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self,
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current_user: Dict[str, Any],
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conversation_id: Optional[str],
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message: str,
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review_context: Optional[Any] = None,
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template_key: Optional[str] = None,
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) -> Iterable[str]:
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review_context_payload = self._normalize_review_context(review_context)
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remote_template_key = self._resolve_remote_chat_template_key(template_key)
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def _event_stream():
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attempt_template_keys = [remote_template_key]
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if remote_template_key:
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# Some shared-ai deployments only have generic chat templates.
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# If the template-key-specific stream dies before sending any
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# payload, retry once without the explicit template key.
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attempt_template_keys.append(None)
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for attempt_index, active_template_key in enumerate(attempt_template_keys):
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emitted_payload = False
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try:
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for event in self.sdk.stream_conversation(
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self._context(current_user),
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message=message,
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chat_context=review_context_payload or {},
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conversation_id=conversation_id,
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template_key=active_template_key,
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):
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if event.event_type in {"delta", "text"}:
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emitted_payload = True
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yield self._format_event({"type": "text", "content": event.payload.get("content", "")})
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elif event.event_type == "sources":
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emitted_payload = True
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yield self._format_event({"type": "sources", "sources": event.payload.get("sources", [])})
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elif event.event_type == "end":
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emitted_payload = True
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yield self._format_event(
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{
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"type": "end",
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"conversation_id": event.payload.get("conversation_id"),
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}
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)
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elif event.event_type == "error":
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if attempt_index == 0 and template_key and not emitted_payload:
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break
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yield self._format_event(
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{
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"type": "error",
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"message": event.payload.get("message", "shared ai platform request failed"),
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}
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)
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return
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elif event.event_type in {"start", "usage"}:
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continue
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else:
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return
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except SharedAIPlatformError as exc:
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if attempt_index == 0 and remote_template_key and not emitted_payload:
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continue
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yield self._format_event({"type": "error", "message": self._build_stream_error_message(exc)})
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return
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except Exception as exc: # pragma: no cover - protects remote stream regressions
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if attempt_index == 0 and remote_template_key and not emitted_payload:
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continue
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yield self._format_event({"type": "error", "message": self._build_stream_error_message(exc)})
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return
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yield self._format_event(
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{
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"type": "error",
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"message": "共享 AI 问答暂时不可用，请稍后重试。",
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}
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)
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return _event_stream()
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@staticmethod
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def _build_stream_error_message(exc: Exception) -> str:
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detail = str(exc).strip()
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if detail:
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return f"共享 AI 问答暂时不可用，请稍后重试。{detail}"
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return "共享 AI 问答暂时不可用，请稍后重试。"
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@staticmethod
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def _resolve_remote_chat_template_key(template_key: Optional[str]) -> Optional[str]:
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normalized = str(template_key or "").strip()
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if normalized in REMOTE_CHAT_TEMPLATE_KEYS:
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return normalized
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return None
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def list_knowledge_bases(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict:
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context = self._context(current_user)
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method = self.sdk.list_knowledge_bases
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normalized_page = max(int(page or 1), 1)
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normalized_page_size = max(min(int(page_size or 20), 100), 1)
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try:
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signature = inspect.signature(method)
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accepts_pagination = (
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"page" in signature.parameters
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or "page_size" in signature.parameters
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or any(parameter.kind == inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())
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)
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except (TypeError, ValueError):
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accepts_pagination = True
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if accepts_pagination:
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try:
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payload = method(context, page=normalized_page, page_size=normalized_page_size)
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except TypeError as exc:
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if "unexpected keyword argument" not in str(exc):
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raise
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payload = method(context)
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else:
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payload = method(context)
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return self._paginate_remote_knowledge_bases_payload(
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self._apply_remote_knowledge_defaults(payload),
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normalized_page,
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normalized_page_size,
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)
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def list_conversations(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict:
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try:
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return self.sdk.list_conversations(self._context(current_user), page=page, page_size=page_size)
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except Exception as exc:
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return self._fallback_list_conversations(current_user, page, page_size, exc)
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def get_conversation_detail(self, current_user: Dict[str, Any], conversation_id: str) -> dict:
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try:
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return self.sdk.get_conversation_detail(self._context(current_user), conversation_id)
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except Exception as exc:
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return self._fallback_get_conversation_detail(current_user, conversation_id, exc)
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def run_legal_review(self, current_user: Dict[str, Any], payload: Dict[str, Any]) -> dict:
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return self.sdk.run_legal_review(
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self._context(current_user),
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title=payload.get("title") or "文本输入合同",
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text=payload.get("text") or "",
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contract_type=payload.get("contract_type"),
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review_as=payload.get("review_as") or "party_a",
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provider=payload.get("provider"),
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)
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def extract_document_text(self, current_user: Dict[str, Any], *, file_name: str, mime_type: Optional[str], content: bytes) -> dict:
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return self.sdk.extract_document_text(
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self._context(current_user),
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file_name=file_name,
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mime_type=mime_type,
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content=content,
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)
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def classify_pdf_source(self, current_user: Dict[str, Any], *, content: bytes) -> dict:
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return self.sdk.classify_pdf_source(
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self._context(current_user),
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content=content,
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)
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def create_knowledge_base(self, current_user: Dict[str, Any], name: str, description: Optional[str]) -> dict:
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payload = self.sdk.create_knowledge_base(
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self._context(current_user),
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name=name,
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description=description,
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retrieval_mode="hybrid",
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)
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if "retrieval_mode" not in payload:
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payload["retrieval_mode"] = "hybrid"
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return payload
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def list_knowledge_base_versions(self, current_user: Dict[str, Any], knowledge_base_id: str) -> list[dict]:
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try:
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return self.sdk.list_knowledge_base_versions(self._context(current_user), knowledge_base_id)
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except SharedAIPlatformError as exc:
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if exc.status_code in (401, 403):
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raise
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return self._fallback_knowledge_base_versions(current_user, knowledge_base_id, exc)
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except Exception as exc:
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return self._fallback_knowledge_base_versions(current_user, knowledge_base_id, exc)
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def publish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict:
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payload = self.sdk.publish_knowledge_base(self._context(current_user), knowledge_base_id)
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if "retrieval_mode" not in payload:
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payload["retrieval_mode"] = "hybrid"
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return payload
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def unpublish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict:
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payload = self.sdk.unpublish_knowledge_base(self._context(current_user), knowledge_base_id)
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if "retrieval_mode" not in payload:
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payload["retrieval_mode"] = "hybrid"
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return payload
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def rollback_knowledge_base(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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target_version_label: str,
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change_summary: Optional[str] = None,
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) -> dict:
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payload = self.sdk.rollback_knowledge_base(
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self._context(current_user),
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knowledge_base_id,
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target_version_label=target_version_label,
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change_summary=change_summary,
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)
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if "retrieval_mode" not in payload:
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payload["retrieval_mode"] = "hybrid"
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return payload
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def list_documents(self, current_user: Dict[str, Any], knowledge_base_id: str, page: int, page_size: int) -> dict:
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payload = self.sdk.list_documents(self._context(current_user), knowledge_base_id, page=page, page_size=page_size)
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return self._normalize_remote_knowledge_documents_payload(payload)
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def upload_document(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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file_name: str,
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mime_type: Optional[str],
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content: bytes,
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) -> dict:
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payload = self.sdk.upload_document(
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self._context(current_user),
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knowledge_base_id,
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file_name=file_name,
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mime_type=mime_type,
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content=content,
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)
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return self._normalize_remote_knowledge_document_item(payload)
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def retry_document(
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self,
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current_user: Dict[str, Any],
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knowledge_base_id: str,
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document_id: str,
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file_name: Optional[str] = None,
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mime_type: Optional[str] = None,
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content: Optional[bytes] = None,
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) -> dict:
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payload = self.sdk.retry_document(
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self._context(current_user),
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knowledge_base_id,
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document_id,
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file_name=file_name,
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mime_type=mime_type,
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content=content,
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)
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return self._normalize_remote_knowledge_document_item(payload)
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def enhance_contract_generation(
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self,
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current_user: Dict[str, Any],
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*,
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prompt_runtime: Optional[Dict[str, Any]],
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prompt: str,
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draft_content: str,
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metadata: Optional[Dict[str, Any]] = None,
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) -> dict:
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template_key = str((prompt_runtime or {}).get("template_key") or "").strip() or None
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payload = dict(metadata or {})
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payload["draft_content"] = draft_content
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payload["prompt_version"] = (prompt_runtime or {}).get("prompt_version")
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payload["prompt_key"] = (prompt_runtime or {}).get("prompt_key")
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payload["prompt_type"] = (prompt_runtime or {}).get("prompt_type")
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stream = self.stream_answer(
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current_user,
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None,
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prompt,
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review_context=payload,
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template_key=template_key,
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)
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text_parts: list[str] = []
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for chunk in stream:
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if not isinstance(chunk, str):
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continue
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for line in chunk.splitlines():
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if not line.startswith("data:"):
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continue
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raw = line[5:].strip()
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if not raw:
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continue
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try:
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event = json.loads(raw)
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except json.JSONDecodeError:
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continue
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if not isinstance(event, Mapping):
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continue
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if event.get("type") == "text":
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text_parts.append(str(event.get("content") or ""))
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elif event.get("type") == "error":
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raise RuntimeError(str(event.get("message") or "shared ai enhancement failed"))
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raw_content = "".join(text_parts).strip()
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if not raw_content:
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raise RuntimeError("shared ai enhancement returned empty content")
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structured_output = self._extract_structured_output(raw_content)
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content = self._extract_enhanced_contract_content(structured_output, raw_content)
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return {
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"content": content,
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"raw_content": raw_content,
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"structured_output": structured_output,
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"provider": "shared-ai-platform",
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"model": (prompt_runtime or {}).get("model"),
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"prompt_key": (prompt_runtime or {}).get("prompt_key"),
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"prompt_version": (prompt_runtime or {}).get("prompt_version"),
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}
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@staticmethod
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def _extract_enhanced_contract_content(structured_output: Optional[Dict[str, Any]], raw_content: str) -> str:
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if not isinstance(structured_output, Mapping):
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return normalize_contract_content(raw_content)
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for key in ("html", "content", "text", "body", "markdown", "document"):
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value = structured_output.get(key)
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if isinstance(value, str) and value.strip():
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return normalize_contract_content(value)
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return normalize_contract_content(raw_content)
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@staticmethod
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def _extract_structured_output(raw_content: str) -> Optional[Dict[str, Any]]:
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cleaned = str(raw_content or "").strip()
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if not cleaned:
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return None
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if cleaned.startswith("```"):
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cleaned = cleaned.removeprefix("```json").removeprefix("```").strip()
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if cleaned.endswith("```"):
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cleaned = cleaned[:-3].strip()
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try:
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parsed = json.loads(cleaned)
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except json.JSONDecodeError:
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return None
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return parsed if isinstance(parsed, dict) else None
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def _format_event(self, payload: Dict[str, object]) -> str:
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return f"data: {json.dumps(payload, ensure_ascii=False)}\n\n"
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def _apply_remote_knowledge_defaults(self, payload: dict) -> dict:
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items = payload.get("items")
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if not isinstance(items, list):
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return payload
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for item in items:
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if isinstance(item, dict) and not item.get("retrieval_mode"):
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item["retrieval_mode"] = "hybrid"
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items.sort(key=self._knowledge_base_sort_key, reverse=True)
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return payload
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def _paginate_remote_knowledge_bases_payload(self, payload: dict, page: int, page_size: int) -> dict:
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items = payload.get("items") if isinstance(payload, Mapping) else None
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if not isinstance(items, list):
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return payload
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normalized = dict(payload)
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total = int(normalized.get("total") or len(items))
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source_page_size = int(normalized.get("page_size") or len(items) or page_size)
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source_page = int(normalized.get("page") or 1)
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if source_page == page and source_page_size == page_size:
|
|
normalized["total"] = total
|
|
normalized["page"] = page
|
|
normalized["page_size"] = page_size
|
|
return normalized
|
|
|
|
if total == len(items):
|
|
start = (page - 1) * page_size
|
|
normalized["items"] = items[start : start + page_size]
|
|
normalized["total"] = total
|
|
normalized["page"] = page
|
|
normalized["page_size"] = page_size
|
|
return normalized
|
|
|
|
@staticmethod
|
|
def _knowledge_base_sort_key(item: Any) -> str:
|
|
if not isinstance(item, Mapping):
|
|
return ""
|
|
return str(item.get("updated_at") or item.get("created_at") or "")
|
|
|
|
def _fallback_knowledge_base_versions(self, current_user: Dict[str, Any], knowledge_base_id: str, exc: Exception) -> list[dict]:
|
|
try:
|
|
payload = self.list_knowledge_bases(current_user, 1, 100)
|
|
except Exception as list_exc:
|
|
raise HTTPException(status_code=503, detail=self._build_knowledge_base_versions_error_message(exc)) from list_exc
|
|
|
|
items = payload.get("items") if isinstance(payload, Mapping) else []
|
|
knowledge_base = next((item for item in items if isinstance(item, Mapping) and item.get("id") == knowledge_base_id), None)
|
|
if not knowledge_base:
|
|
raise HTTPException(status_code=404, detail="知识库不存在或无权访问")
|
|
|
|
version_label = str(knowledge_base.get("current_version_label") or "current")
|
|
timestamp = knowledge_base.get("published_at") or knowledge_base.get("updated_at") or knowledge_base.get("created_at")
|
|
return [
|
|
{
|
|
"id": f"{knowledge_base_id}-{version_label}",
|
|
"knowledge_base_id": knowledge_base_id,
|
|
"version_label": version_label,
|
|
"name": knowledge_base.get("name") or "",
|
|
"description": knowledge_base.get("description"),
|
|
"retrieval_mode": knowledge_base.get("retrieval_mode") or "hybrid",
|
|
"status": knowledge_base.get("status") or "active",
|
|
"published_at": knowledge_base.get("published_at"),
|
|
"published_by": knowledge_base.get("published_by"),
|
|
"change_summary": self._build_knowledge_base_versions_error_message(exc),
|
|
"created_at": timestamp,
|
|
}
|
|
]
|
|
|
|
def _normalize_remote_knowledge_documents_payload(self, payload: dict) -> dict:
|
|
items = payload.get("items")
|
|
if not isinstance(items, list):
|
|
return payload
|
|
|
|
payload["items"] = [self._normalize_remote_knowledge_document_item(item) for item in items]
|
|
return payload
|
|
|
|
def _normalize_remote_knowledge_document_item(self, payload: dict) -> dict:
|
|
metadata = payload.get("metadata_json")
|
|
if not isinstance(metadata, Mapping):
|
|
metadata = payload.get("metadata")
|
|
metadata = metadata if isinstance(metadata, Mapping) else {}
|
|
|
|
normalized = dict(payload)
|
|
source_type = normalized.get("source_type") or metadata.get("source_type")
|
|
authority = normalized.get("authority") or metadata.get("authority") or metadata.get("issuer")
|
|
effective_date = normalized.get("effective_date") or metadata.get("effective_date")
|
|
region = normalized.get("region") or metadata.get("region") or metadata.get("jurisdiction")
|
|
tags = normalized.get("tags")
|
|
if tags is None:
|
|
tags = normalized.get("tags_json")
|
|
if tags is None:
|
|
tags = metadata.get("tags")
|
|
|
|
normalized["source_type"] = source_type
|
|
normalized["authority"] = authority
|
|
normalized["effective_date"] = effective_date
|
|
normalized["region"] = region
|
|
normalized["tags"] = list(tags) if isinstance(tags, list) else None
|
|
if normalized["tags"] is not None and normalized.get("tags_json") is None:
|
|
normalized["tags_json"] = normalized["tags"]
|
|
if metadata and normalized.get("metadata_json") is None:
|
|
normalized["metadata_json"] = dict(metadata)
|
|
return normalized
|
|
|
|
def _normalize_review_context(self, review_context: Any) -> Optional[Dict[str, Any]]:
|
|
if review_context is None:
|
|
return None
|
|
if isinstance(review_context, Mapping):
|
|
return dict(review_context)
|
|
if hasattr(review_context, "model_dump"):
|
|
return review_context.model_dump(mode="json", by_alias=True, exclude_none=True)
|
|
return review_context
|
|
|
|
def _fallback_list_conversations(self, current_user: Dict[str, Any], page: int, page_size: int, exc: Exception) -> dict:
|
|
if self.db is None:
|
|
raise HTTPException(status_code=503, detail=self._build_history_error_message(exc)) from exc
|
|
normalized_page = max(int(page or 1), 1)
|
|
normalized_page_size = max(min(int(page_size or 20), 100), 1)
|
|
repository = ConversationRepository(self.db)
|
|
tenant_id = str(current_user.get("tenant_id") or "")
|
|
user_id = str(current_user.get("id") or "")
|
|
items = repository.list_paginated(tenant_id, user_id, normalized_page, normalized_page_size)
|
|
return {
|
|
"items": [
|
|
{
|
|
"id": item.id,
|
|
"title": item.title,
|
|
"message_count": item.message_count,
|
|
"last_message_at": item.last_message_at.isoformat() if item.last_message_at else None,
|
|
}
|
|
for item in items
|
|
],
|
|
"page": normalized_page,
|
|
"page_size": normalized_page_size,
|
|
"total": repository.count(tenant_id, user_id),
|
|
"source": "local_fallback",
|
|
"warning": self._build_history_error_message(exc),
|
|
}
|
|
|
|
def _fallback_get_conversation_detail(self, current_user: Dict[str, Any], conversation_id: str, exc: Exception) -> dict:
|
|
if self.db is None:
|
|
raise HTTPException(status_code=503, detail=self._build_history_error_message(exc)) from exc
|
|
tenant_id = str(current_user.get("tenant_id") or "")
|
|
user_id = str(current_user.get("id") or "")
|
|
conversation = ConversationRepository(self.db).get_by_id_for_user(conversation_id, tenant_id, user_id)
|
|
if conversation is None:
|
|
raise HTTPException(status_code=503, detail=self._build_history_error_message(exc)) from exc
|
|
messages = MessageRepository(self.db).list_by_conversation(conversation.id)
|
|
return {
|
|
"id": conversation.id,
|
|
"title": conversation.title,
|
|
"messages": [
|
|
{
|
|
"id": message.id,
|
|
"role": message.role,
|
|
"content": message.content,
|
|
"sources": message.sources_json or [],
|
|
"created_at": message.created_at.isoformat(),
|
|
}
|
|
for message in messages
|
|
if message.tenant_id == tenant_id
|
|
],
|
|
"source": "local_fallback",
|
|
"warning": self._build_history_error_message(exc),
|
|
}
|
|
|
|
@staticmethod
|
|
def _build_history_error_message(exc: Exception) -> str:
|
|
detail = str(exc).strip()
|
|
if detail:
|
|
return f"共享 AI 会话历史暂时不可用，已切换为本地历史记录。原因：{detail[:200]}"
|
|
return "共享 AI 会话历史暂时不可用，已切换为本地历史记录。"
|
|
|
|
@staticmethod
|
|
def _build_knowledge_base_versions_error_message(exc: Exception) -> str:
|
|
detail = str(exc).strip()
|
|
if detail:
|
|
return f"共享 AI 版本历史暂时不可用，已展示当前知识库快照。原因：{detail[:200]}"
|
|
return "共享 AI 版本历史暂时不可用，已展示当前知识库快照。"
|
|
|
|
|
|
|
|
class UnavailableSharedAIPlatformClient:
|
|
def __init__(self, reason: str, db: Optional[Session] = None):
|
|
self.reason = reason
|
|
self.db = db
|
|
|
|
def stream_answer(
|
|
self,
|
|
current_user: Dict[str, Any],
|
|
conversation_id: Optional[str],
|
|
message: str,
|
|
review_context: Optional[Any] = None,
|
|
template_key: Optional[str] = None,
|
|
) -> Iterable[str]:
|
|
yield self._format_event(
|
|
{
|
|
"type": "error",
|
|
"message": f"模型服务未配置或暂不可用：{self.reason}。请管理员到“大模型设置”核对参数，并完成后端/共享 AI 服务配置后重试。",
|
|
}
|
|
)
|
|
|
|
def list_conversations(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict:
|
|
if self.db is None:
|
|
return self._empty_conversations(page, page_size)
|
|
normalized_page = max(int(page or 1), 1)
|
|
normalized_page_size = max(min(int(page_size or 20), 100), 1)
|
|
repository = ConversationRepository(self.db)
|
|
tenant_id = str(current_user.get("tenant_id") or "")
|
|
user_id = str(current_user.get("id") or "")
|
|
items = repository.list_paginated(tenant_id, user_id, normalized_page, normalized_page_size)
|
|
return {
|
|
"items": [
|
|
{
|
|
"id": item.id,
|
|
"title": item.title,
|
|
"message_count": item.message_count,
|
|
"last_message_at": item.last_message_at.isoformat() if item.last_message_at else None,
|
|
}
|
|
for item in items
|
|
],
|
|
"page": normalized_page,
|
|
"page_size": normalized_page_size,
|
|
"total": repository.count(tenant_id, user_id),
|
|
"source": "local_fallback",
|
|
"warning": self._history_warning(),
|
|
}
|
|
|
|
def get_conversation_detail(self, current_user: Dict[str, Any], conversation_id: str) -> dict:
|
|
if self.db is None:
|
|
raise HTTPException(status_code=503, detail=self._history_warning())
|
|
tenant_id = str(current_user.get("tenant_id") or "")
|
|
user_id = str(current_user.get("id") or "")
|
|
conversation = ConversationRepository(self.db).get_by_id_for_user(conversation_id, tenant_id, user_id)
|
|
if conversation is None:
|
|
raise HTTPException(status_code=404, detail="conversation not found")
|
|
messages = MessageRepository(self.db).list_by_conversation(conversation.id)
|
|
return {
|
|
"id": conversation.id,
|
|
"title": conversation.title,
|
|
"messages": [
|
|
{
|
|
"id": message.id,
|
|
"role": message.role,
|
|
"content": message.content,
|
|
"sources": message.sources_json or [],
|
|
"created_at": message.created_at.isoformat(),
|
|
}
|
|
for message in messages
|
|
if message.tenant_id == tenant_id
|
|
],
|
|
"source": "local_fallback",
|
|
"warning": self._history_warning(),
|
|
}
|
|
|
|
def list_knowledge_bases(self, current_user: Dict[str, Any], page: int, page_size: int) -> dict:
|
|
return {
|
|
"items": [],
|
|
"page": max(int(page or 1), 1),
|
|
"page_size": max(min(int(page_size or 20), 100), 1),
|
|
"total": 0,
|
|
"warning": self._unavailable_message(),
|
|
}
|
|
|
|
def list_knowledge_base_versions(self, current_user: Dict[str, Any], knowledge_base_id: str) -> list[dict]:
|
|
return []
|
|
|
|
def list_documents(self, current_user: Dict[str, Any], knowledge_base_id: str, page: int, page_size: int) -> dict:
|
|
return {
|
|
"items": [],
|
|
"page": max(int(page or 1), 1),
|
|
"page_size": max(min(int(page_size or 20), 100), 1),
|
|
"total": 0,
|
|
"warning": self._unavailable_message(),
|
|
}
|
|
|
|
def create_knowledge_base(self, current_user: Dict[str, Any], name: str, description: Optional[str]) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def publish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def unpublish_knowledge_base(self, current_user: Dict[str, Any], knowledge_base_id: str) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def rollback_knowledge_base(
|
|
self,
|
|
current_user: Dict[str, Any],
|
|
knowledge_base_id: str,
|
|
target_version_label: str,
|
|
change_summary: Optional[str] = None,
|
|
) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def upload_document(
|
|
self,
|
|
current_user: Dict[str, Any],
|
|
knowledge_base_id: str,
|
|
file_name: str,
|
|
mime_type: Optional[str],
|
|
content: bytes,
|
|
) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def retry_document(
|
|
self,
|
|
current_user: Dict[str, Any],
|
|
knowledge_base_id: str,
|
|
document_id: str,
|
|
file_name: Optional[str] = None,
|
|
mime_type: Optional[str] = None,
|
|
content: Optional[bytes] = None,
|
|
) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def run_legal_review(self, current_user: Dict[str, Any], payload: Dict[str, Any]) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def extract_document_text(self, current_user: Dict[str, Any], *, file_name: str, mime_type: Optional[str], content: bytes) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def classify_pdf_source(self, current_user: Dict[str, Any], *, content: bytes) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def enhance_contract_generation(
|
|
self,
|
|
current_user: Dict[str, Any],
|
|
*,
|
|
prompt_runtime: Optional[Dict[str, Any]],
|
|
prompt: str,
|
|
draft_content: str,
|
|
metadata: Optional[Dict[str, Any]] = None,
|
|
) -> dict:
|
|
self._raise_unavailable()
|
|
|
|
def _empty_conversations(self, page: int, page_size: int) -> dict:
|
|
return {
|
|
"items": [],
|
|
"page": max(int(page or 1), 1),
|
|
"page_size": max(min(int(page_size or 20), 100), 1),
|
|
"total": 0,
|
|
"source": "local_fallback",
|
|
"warning": self._history_warning(),
|
|
}
|
|
|
|
def _history_warning(self) -> str:
|
|
return f"共享 AI 会话历史暂不可用，已切换为本地历史记录。原因：{self.reason}"
|
|
|
|
def _unavailable_message(self) -> str:
|
|
return f"共享 AI 服务未配置或暂不可用：{self.reason}"
|
|
|
|
def _raise_unavailable(self):
|
|
raise HTTPException(status_code=503, detail=self._unavailable_message())
|
|
|
|
@staticmethod
|
|
def _format_event(payload: Dict[str, object]) -> str:
|
|
return f"data: {json.dumps(payload, ensure_ascii=False)}\n\n"
|
|
|
|
|
|
def get_shared_ai_platform_client(db: Session = Depends(get_db_session)) -> SharedAIPlatformClient:
|
|
return build_shared_ai_platform_client(db)
|
|
|
|
|
|
|
|
def build_shared_ai_platform_client(db: Session) -> SharedAIPlatformClient:
|
|
base_url = settings.shared_ai_platform_base_url.strip()
|
|
api_key = settings.shared_ai_platform_api_key.strip()
|
|
missing_parts = []
|
|
if not base_url:
|
|
missing_parts.append("SHARED_AI_PLATFORM_BASE_URL")
|
|
if not api_key:
|
|
missing_parts.append("SHARED_AI_PLATFORM_API_KEY")
|
|
if missing_parts:
|
|
return UnavailableSharedAIPlatformClient(f"缺少 {', '.join(missing_parts)}", db=db)
|
|
|
|
return RemoteSharedAIPlatformClient(
|
|
base_url=base_url,
|
|
app_id=settings.shared_ai_platform_app_id,
|
|
api_key=api_key,
|
|
timeout_seconds=settings.shared_ai_platform_timeout_seconds,
|
|
db=db,
|
|
)
|