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,