Projeto do Agent Contas ORACLE

2026-08-19 09:35:50 -03:00
commit 950a2bcd33
1366 changed files with 177217 additions and 0 deletions
--- a/app/agents/suporte_contas_agent.py
+++ b/app/agents/suporte_contas_agent.py
@@ -0,0 +1,138 @@
+from app.agents.prompting import apply_agent_profile_prompt
+from app.agents.contas_prompting import load_domain_prompt
+from app.agents.runtime import AgentRuntimeMixin
+from app.domain.contas.informational_context import infer_informational_context
+
+
+class SuporteContasAgent(AgentRuntimeMixin):
+    name = "suporte_contas_agent"
+
+    def __init__(
+        self,
+        llm,
+        telemetry=None,
+        tool_router=None,
+        rag_service=None,
+        cache=None,
+        settings=None,
+        observer=None,
+        memory=None,
+        summary_memory=None,
+        guardrail_pipeline=None,
+    ):
+        self.llm = llm
+        self.telemetry = telemetry
+        self.tool_router = tool_router
+        self.rag_service = rag_service
+        self.cache = cache
+        self.settings = settings
+        self.observer = observer
+        self.memory = memory
+        self.summary_memory = summary_memory
+        self.guardrail_pipeline = guardrail_pipeline
+
+    async def run(self, state):
+        await self._emit_ic(
+            "IC.SUPORTE_CONTAS_AGENT_STARTED",
+            state,
+            {"business_component": "suporte"},
+            component="agent.suporte_contas.start",
+        )
+
+        tool_context = await self._collect_tool_context(state)
+        if tool_context:
+            await self._emit_ic(
+                "IC.SUPORTE_CONTAS_MCP_CONTEXT_COLLECTED",
+                state,
+                {"tool_result_count": len(tool_context)},
+                component="agent.suporte_contas.mcp",
+            )
+
+        state["mcp_results"] = tool_context
+        clarification_message = self.transaction_clarification_message(state)
+        if clarification_message:
+            return {
+                "answer": f"[{self.__class__.__name__}] {clarification_message}",
+                "next_state": state.get("next_state") or "COLLECTING_PARAMETERS",
+                "mcp_results": tool_context,
+                **self.transaction_state_patch(state),
+            }
+
+        confirmation_message = self.transaction_confirmation_message(state)
+        if confirmation_message:
+            result = {
+                "answer": f"[{self.__class__.__name__}] {confirmation_message}",
+                "next_state": state.get("next_state"),
+                "mcp_results": tool_context,
+                **self.transaction_state_patch(state),
+            }
+            return result
+
+        direct_answer = self.build_direct_mcp_answer(state, tool_context, agent_label="SuporteContasAgent")
+        if direct_answer:
+            return {
+                "answer": direct_answer,
+                "next_state": state.get("next_state") or "ACTIVE",
+                "mcp_results": tool_context,
+                "rag": {"enabled": False, "skipped": True, "reason": "direct_mcp_answer"},
+                **self.transaction_state_patch(state),
+            }
+
+        rag_context, rag_metadata = await self._retrieve_rag_context(state)
+        informational_patch = infer_informational_context(
+            str(rag_metadata.get("query") or state.get("sanitized_input") or state.get("user_text") or ""),
+            state.get("invoice_detail"),
+        ) if rag_metadata.get("enabled") else {}
+        if rag_metadata.get("enabled"):
+            await self._emit_ic(
+                "IC.SUPORTE_CONTAS_RAG_CONTEXT_RETRIEVED",
+                state,
+                {
+                    "document_count": rag_metadata.get("document_count"),
+                    "graph_neighbors": rag_metadata.get("graph_neighbors"),
+                    "latency_ms": rag_metadata.get("latency_ms"),
+                },
+                component="agent.suporte_contas.rag",
+            )
+
+        # Prepara ConversationSummaryMemory antes de montar o prompt.
+        # O build_messages() do framework injeta resumo + últimas mensagens quando habilitado.
+        await self.prepare_memory_context(state)
+
+        messages = self.build_messages(
+            state,
+            system_prompt=apply_agent_profile_prompt(
+                state,
+                load_domain_prompt("support"),
+            ),
+            mcp_results=tool_context,
+            rag_context=rag_context,
+            rag_metadata=rag_metadata,
+        )
+
+        answer = await self._invoke_llm_cached(state, "SuporteContasAgent", messages)
+        result = {
+            "answer": f"[SuporteContasAgent] {answer}",
+            "next_state": "SUPORTE_CONTAS_ACTIVE",
+            "mcp_results": tool_context,
+            "rag": rag_metadata,
+            "memory_context_metadata": state.get("memory_context_metadata"),
+            **informational_patch,
+            **self.transaction_state_patch(state),
+        }
+
+        await self._emit_ic(
+            "IC.SUPORTE_CONTAS_AGENT_COMPLETED",
+            state,
+            {
+                "answer_chars": len(result.get("answer") or ""),
+                "has_mcp_results": bool(tool_context),
+                "rag_enabled": bool(rag_metadata.get("enabled")),
+                "memory_context": state.get("memory_context_metadata"),
+            },
+            component="agent.suporte_contas.completed",
+        )
+        return result
+
+    async def _collect_tool_context(self, state):
+        return await self._collect_mcp_context(state)