refactor: separa composição OCI e inicialização do DeepAgents

src/voice_assistant/agent/deep_agent.py

@@ -2,10 +2,11 @@
 Deep Agents implementation of the AgentVoice Agent port.
 
 Responsibilities:
-- OCI Generative AI inference through LangChain.
+- Translate a prepared DeepAgents graph to the Agent streaming contract.
 - Contextual memory per session.
 - Text streaming compatible with VoicePipeline.
-- Asynchronous resource cleanup.
+- Explicit closure of consumed event streams.
+- Model/client ownership belongs to the composition that supplies the graph.
 
 Does not manage:
 - WebSocket connections.
@@ -21,27 +22,22 @@ from collections.abc import AsyncGenerator, Iterator
 from typing import Any
 from contextlib import aclosing
 
-from deepagents import create_deep_agent
 from langchain_core.messages import HumanMessage
 from langchain_core.runnables import RunnableConfig
-from langchain_oci import ChatOCIGenAI
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.graph.state import CompiledStateGraph
 
 from voice_assistant.agent.adapter import StreamingAgentAdapter
 
-DEFAULT_SYSTEM_PROMPT = """
-Você é o AgentVoice, um assistente pessoal por voz. Que responde pelo nome de Roberta.
 
-Responda em português brasileiro, de forma natural,
-objetiva e adequada para reprodução por voz.
-
-Mantenha o contexto das mensagens anteriores.
-Interprete correções e complementos do usuário
-considerando o histórico da conversa.
-
-Não invente informações atuais ou resultados
-de ferramentas que não foram executadas.
-"""
+def positive_timeout(value: float, name: str) -> float:
+    if (
+        isinstance(value, bool)
+        or not isinstance(value, (int, float))
+        or not math.isfinite(value)
+        or value <= 0
+    ):
+        raise ValueError(f"{name} must be finite and positive.")
+    return float(value)
 
 
 def _text_fragments(content: str | list[str | dict[str, Any]]) -> Iterator[str]:
@@ -62,64 +58,11 @@ def _text_fragments(content: str | list[str | dict[str, Any]]) -> Iterator[str]:
 
 
 class DeepAgentsAdapter(StreamingAgentAdapter):
-    def __init__(
-        self,
-        region: str,
-        compartment_id: str,
-        model_id: str,
-        temperature: float,
-        max_completion_tokens: int,
-        timeout_seconds: float,
-        system_prompt: str = DEFAULT_SYSTEM_PROMPT,
-        *,
-        auth_type: str = "INSTANCE_PRINCIPAL",
-        auth_profile: str = "DEFAULT",
-        auth_file_location: str = "~/.oci/config",
-    ) -> None:
-        if not region:
-            raise ValueError("OCI region is required.")
-
-        if not compartment_id:
-            raise ValueError("OCI compartment_id is required.")
-
-        if not model_id:
-            raise ValueError("OCI model_id is required.")
-
-        if (
-            isinstance(timeout_seconds, bool)
-            or not isinstance(timeout_seconds, (int, float))
-            or not math.isfinite(timeout_seconds)
-            or timeout_seconds <= 0
-        ):
-            raise ValueError("timeout_seconds must be finite and positive.")
-
-        self._stream_event_timeout = float(timeout_seconds)
-
-        self._model = ChatOCIGenAI(
-            model_id=model_id,
-            compartment_id=compartment_id,
-            service_endpoint=(
-                f"https://inference.generativeai.{region}.oci.oraclecloud.com"
-            ),
-            auth_type=auth_type,
-            auth_profile=auth_profile,
-            auth_file_location=auth_file_location,
-            is_stream=True,
-            model_kwargs={
-                "temperature": temperature,
-                "max_tokens": max_completion_tokens,
-            },
+    def __init__(self, graph: CompiledStateGraph, timeout_seconds: float) -> None:
+        self._stream_event_timeout = positive_timeout(
+            timeout_seconds, "timeout_seconds"
         )
-
-        self._checkpointer = MemorySaver()
-
-        self._graph = create_deep_agent(
-            model=self._model,
-            tools=[],
-            system_prompt=system_prompt,
-            checkpointer=self._checkpointer,
-        )
-
+        self._graph = graph
         self._closed = False
 
     @staticmethod
@@ -176,5 +119,4 @@ class DeepAgentsAdapter(StreamingAgentAdapter):
         if self._closed:
             return
 
-        await self._model.aclose()
         self._closed = True