"""FlovyService — AI orkestratör. Router → RAG → Memory → Prompt → LLM → Parser. ARCHITECTURE §14: GemmaClient yalnız buradan çağrılır. Bu servis sohbet DB yazımı YAPMAZ; AIResult döner, persistans ChatService'tedir. NOT: Tool-use loop (search/cart/pay) Adım 8'de bağlanır; şimdilik marker'lar + düz LLM metni + RAG/memory context. """ import logging from dataclasses import dataclass, field from fastapi import Depends from app.config import settings from app.models.chat import ChatSession from app.repositories.chat_repo import ChatRepository from app.repositories.tenant_repo import TenantRepository from app.repositories.visitor_repo import VisitorRepository from app.repositories.widget_repo import WidgetRepository from app.services.ai.gemma_client import GemmaClient, get_gemma_client from app.services.ai.intent_router import IntentRouter from app.services.ai.prompt_builder import PromptBuilder from app.services.ai.response_parser import ResponseParser from app.services.product_service import ProductService from app.services.rag.knowledge_retriever import KnowledgeRetriever from app.services.visitor.memory_builder import MemoryBuilder from app.utils.exceptions import ExternalServiceError logger = logging.getLogger("flovy") _HISTORY_LIMIT = 10 _FALLBACK = ( "Şu anda yapay zekâ ile yanıt veremiyorum, " "dilerseniz sizi bir temsilciye bağlayabilirim." ) @dataclass class AIResult: reply_text: str | None = None ui_blocks: list[dict] = field(default_factory=list) escalate: bool = False clear_cart: bool = False intent: str | None = None layer: str = "llm" model: str | None = None def _carousel(products: list[dict]) -> dict: items = [] for p in products: images = p.get("images") or [] items.append( { "id": p["id"], "title": p["title"], "price": p["price"], "compare_at_price": p.get("compare_at_price"), "stock_status": p.get("stock_status"), "stock_quantity": p.get("stock_quantity"), "image": images[0] if images else None, "has_variants": bool(p.get("variants")), "variants": p.get("variants") or [], } ) return {"type": "product_carousel", "products": items} class FlovyService: def __init__( self, intent_router: IntentRouter = Depends(), retriever: KnowledgeRetriever = Depends(), product_service: ProductService = Depends(), widget_repo: WidgetRepository = Depends(), visitor_repo: VisitorRepository = Depends(), tenant_repo: TenantRepository = Depends(), chat_repo: ChatRepository = Depends(), gemma: GemmaClient = Depends(get_gemma_client), prompt_builder: PromptBuilder = Depends(), response_parser: ResponseParser = Depends(), ): self.intent_router = intent_router self.retriever = retriever self.product_service = product_service self.widget_repo = widget_repo self.visitor_repo = visitor_repo self.tenant_repo = tenant_repo self.chat_repo = chat_repo self.gemma = gemma self.prompt_builder = prompt_builder self.response_parser = response_parser async def respond(self, session: ChatSession, user_message: str) -> AIResult: tenant_id = session.tenant_id widget = await self.widget_repo.get(session.widget_id, tenant_id) decision = await self.intent_router.decide(user_message) if decision.reply is not None: result = await self._handle_marker_or_text( decision.reply, tenant_id, user_message, widget ) result.intent = decision.intent result.layer = decision.layer return result return await self._handle_llm(session, user_message, widget, tenant_id) # ---------------- rule/semantic ---------------- async def _handle_marker_or_text( self, reply: str, tenant_id: str, user_message: str, widget ) -> AIResult: if reply == "__CATALOG__": return await self._catalog(tenant_id, query=None) if reply == "__SEARCH_PRODUCTS__": return await self._catalog(tenant_id, query=user_message) if reply == "__ESCALATE__": return AIResult( reply_text="Sizi bir müşteri temsilcisine bağlıyorum, lütfen bekleyin.", escalate=True, ) if reply == "__CART_CLEAR__": return AIResult(reply_text="Sepetiniz temizlendi.", clear_cart=True) if reply == "__INTRO__": brand = self._brand_name(widget) return AIResult( reply_text=f"Ben {brand} dijital satış asistanıyım. Ürün önerebilir, " "sorularınızı yanıtlayabilir ve sipariş vermenize yardımcı olabilirim." ) # düz hazır cevap return AIResult(reply_text=reply) async def _catalog(self, tenant_id: str, query: str | None) -> AIResult: products = await self.product_service.search_products( tenant_id, query=query, limit=8 ) if not products: return AIResult(reply_text="Bu kritere uygun ürün bulamadım.") return AIResult( reply_text="İşte size uygun ürünler:", ui_blocks=[_carousel(products)], ) # ---------------- llm ---------------- async def _handle_llm( self, session: ChatSession, user_message: str, widget, tenant_id: str ) -> AIResult: if widget is None or not widget.ai_enabled: return AIResult(reply_text=_FALLBACK, escalate=True) tenant = await self.tenant_repo.get_by_id(tenant_id) if tenant and tenant.monthly_message_used >= tenant.monthly_message_quota: return AIResult( reply_text="Aylık yanıt kotamız doldu, sizi bir temsilciye bağlayabilirim.", escalate=True, ) try: rag_context = await self._rag_context(tenant_id, user_message) memory_context = await self._memory_context(session) history = await self.chat_repo.list_messages( session.id, tenant_id, limit=_HISTORY_LIMIT ) system = self.prompt_builder.build_system( self._brand_name(widget), widget.persona, memory_context=memory_context, rag_context=rag_context, ) contents = self.prompt_builder.build_contents(history, user_message) raw = await self.gemma.generate(contents, system_instruction=system) parsed = self.response_parser.parse(raw) except ExternalServiceError as e: logger.warning("LLM yanıt veremedi: %s", e.code) return AIResult(reply_text=_FALLBACK) if tenant: await self.tenant_repo.update( tenant, monthly_message_used=tenant.monthly_message_used + 1 ) text = parsed.text or "Bu konuda size nasıl yardımcı olabilirim?" # TODO(Adım8): parsed.tool_calls → ToolRegistry.execute (search/cart/pay/lead) return AIResult(reply_text=text, model=settings.gemma_model, layer="llm") # ---------------- helpers ---------------- async def _rag_context(self, tenant_id: str, query: str) -> str: results = await self.retriever.top_k(tenant_id, query, k=5) snippets = [r["content"] for r in results if r.get("score", 0) > 0.3] return "\n---\n".join(snippets[:5]) async def _memory_context(self, session: ChatSession) -> str: if not session.visitor_id: return "" visitor = await self.visitor_repo.get(session.visitor_id, session.tenant_id) return MemoryBuilder().build(visitor) def _brand_name(self, widget) -> str: if widget and widget.settings: return widget.settings.get("brand_name") or widget.name return widget.name if widget else "mağaza"