Use DeepAgents model resolver in reviewer graph

agent_reviewer/builder.py

@@ -7,11 +7,11 @@ typed :class:`ReviewReport` through the ``submit_review_report`` tool.
 from __future__ import annotations
 
 from dataclasses import dataclass
+from types import SimpleNamespace
 from typing import Any
 
 from a2a_pack import GiteaBackend
-from deepagents import create_deep_agent
-from langchain_openai import ChatOpenAI
+from a2a_pack.deepagents import create_a2a_deep_agent
 
 from .config import Settings, load_settings
 from .tools import ReviewReport, ToolContext, build_tools
@@ -132,22 +132,19 @@ def build_reviewer_graph(
             + ", ".join(missing_llm_fields)
         )
 
-    model_kwargs: dict[str, Any] = {
-        "model": ctx.llm_model,
-        "base_url": ctx.llm_base_url,
-        "api_key": ctx.llm_api_key,
-        "stream_usage": True,
-    }
-    if ctx.llm_temperature_mode != "omit":
-        model_kwargs["temperature"] = (
-            ctx.llm_temperature if ctx.llm_temperature is not None else 0.0
-        )
-    if ctx.llm_extra_body:
-        model_kwargs["extra_body"] = dict(ctx.llm_extra_body)
-    model = ChatOpenAI(**model_kwargs)
+    llm_creds = SimpleNamespace(
+        model=ctx.llm_model,
+        base_url=ctx.llm_base_url,
+        api_key=ctx.llm_api_key,
+        temperature_mode=ctx.llm_temperature_mode or "default",
+        temperature=ctx.llm_temperature,
+        extra_body=dict(ctx.llm_extra_body or {}),
+    )
 
-    return create_deep_agent(
-        model=model,
+    return create_a2a_deep_agent(
+        ctx,
+        creds=llm_creds,
+        default_temperature=0.0,
         tools=tools,
         system_prompt=SYSTEM_PROMPT,
         backend=backend,

tests/test_agent.py

@@ -84,16 +84,13 @@ def test_reviewer_graph_uses_forwarded_llm_credentials(
 ) -> None:
     captured: dict = {}
 
-    class FakeChatOpenAI:
-        def __init__(self, **kwargs: object) -> None:
-            captured["model_kwargs"] = kwargs
-
-    def fake_create_deep_agent(**kwargs: object) -> dict[str, object]:
+    def fake_create_a2a_deep_agent(ctx, *, creds, default_temperature=None, **kwargs) -> dict[str, object]:
+        captured["creds"] = creds
+        captured["default_temperature"] = default_temperature
         captured["graph_kwargs"] = kwargs
         return kwargs
 
-    monkeypatch.setattr(reviewer_builder, "ChatOpenAI", FakeChatOpenAI)
-    monkeypatch.setattr(reviewer_builder, "create_deep_agent", fake_create_deep_agent)
+    monkeypatch.setattr(reviewer_builder, "create_a2a_deep_agent", fake_create_a2a_deep_agent)
 
     graph = build_reviewer_graph(
         ReviewerContext(
@@ -111,13 +108,13 @@ def test_reviewer_graph_uses_forwarded_llm_credentials(
     )
 
     assert graph is captured["graph_kwargs"]
-    assert captured["model_kwargs"] == {
-        "model": "platform-model",
-        "base_url": "http://litellm.test/v1",
-        "api_key": "scoped-grant-token",
-        "stream_usage": True,
-        "extra_body": {"extra_body": {"thinking": {"type": "disabled"}}},
-    }
+    creds = captured["creds"]
+    assert getattr(creds, "model") == "platform-model"
+    assert getattr(creds, "base_url") == "http://litellm.test/v1"
+    assert getattr(creds, "api_key") == "scoped-grant-token"
+    assert getattr(creds, "temperature_mode") == "omit"
+    assert getattr(creds, "extra_body") == {"extra_body": {"thinking": {"type": "disabled"}}}
+    assert captured["default_temperature"] == 0.0
 
 
 def test_reviewer_graph_rejects_missing_forwarded_llm_credentials(