feat(demo): 初始化审核智能体演示基线

review_agent/services.py

@@ -0,0 +1,90 @@
+from __future__ import annotations
+
+from django.db.models import Q, QuerySet
+from django.utils import timezone
+
+from .llm import LLMConfigurationError, LLMRequestError, generate_reply
+from .models import Conversation, Message
+
+
+def list_conversations(user, search: str = "") -> QuerySet[Conversation]:
+    """Returns a user's conversations, optionally filtered by title or content."""
+
+    conversations = Conversation.objects.filter(user=user)
+    if not search:
+        return conversations
+
+    return conversations.filter(
+        Q(title__icontains=search) | Q(messages__content__icontains=search)
+    ).distinct()
+
+
+def get_conversation_for_user(user, conversation_id: int | None) -> Conversation | None:
+    """Loads a conversation only when it belongs to the current user."""
+
+    if not conversation_id:
+        return None
+    return Conversation.objects.filter(user=user, pk=conversation_id).first()
+
+
+def create_conversation(user) -> Conversation:
+    """Creates an empty conversation that can immediately accept messages."""
+
+    now = timezone.localtime()
+    return Conversation.objects.create(
+        user=user,
+        title=f"新对话 {now.strftime('%m-%d %H:%M')}",
+    )
+
+
+def append_user_message(conversation: Conversation, content: str) -> Message:
+    """Appends a user message and updates the conversation title from the first prompt."""
+
+    message = Message.objects.create(
+        conversation=conversation,
+        role=Message.Role.USER,
+        content=content.strip(),
+    )
+
+    if conversation.messages.filter(role=Message.Role.USER).count() == 1:
+        conversation.title = build_conversation_title(content)
+        conversation.save(update_fields=["title", "updated_at"])
+
+    return message
+
+
+def append_assistant_message(conversation: Conversation, content: str) -> Message:
+    """Appends the deterministic assistant reply."""
+
+    return Message.objects.create(
+        conversation=conversation,
+        role=Message.Role.ASSISTANT,
+        content=content,
+    )
+
+
+def send_message(conversation: Conversation, content: str) -> tuple[Message, Message]:
+    """Stores one user message and one provider-backed assistant reply."""
+
+    user_message = append_user_message(conversation, content)
+    try:
+        reply_content = generate_reply(conversation, content)
+    except (LLMConfigurationError, LLMRequestError) as exc:
+        reply_content = f"模型调用失败：{exc}"
+
+    assistant_message = append_assistant_message(conversation, reply_content)
+
+    if conversation.title.startswith("新对话"):
+        conversation.title = build_conversation_title(content)
+        conversation.save(update_fields=["title", "updated_at"])
+
+    return user_message, assistant_message
+
+
+def build_conversation_title(content: str) -> str:
+    """Creates a concise title from the first user message."""
+
+    normalized = " ".join(content.strip().split())
+    if not normalized:
+        return "新对话"
+    return normalized[:24]