feat: playwrite mcp に変更

backend/README.md

@@ -37,6 +37,27 @@ docker-compose exec app uv run alembic upgrade head
 docker-compose exec app uv run alembic history
 ```
 
+## デプロイ手順
+
+Backend と Worker の変更を反映する手順です。
+
+### Backend (FastAPI) の再起動
+```bash
+cd backend
+docker compose restart app
+```
+
+### Worker イメージの再ビルド・K8s ロード
+```bash
+# 1. イメージをビルド
+docker build -t ui-recommender-worker:latest -f docker/worker.Dockerfile .
+
+# 2. Docker Desktop の組み込み K8s にロード
+docker save ui-recommender-worker:latest | docker exec -i desktop-control-plane ctr -n k8s.io images import -
+```
+
+> **Note:** Worker Pod は `imagePullPolicy: Never` で運用しているため、レジストリへの push は不要です。
+
 ## 技術スタック
 - Python 3.13
 - FastAPI 0.129.0

backend/app/infra/k8s_client.py

@@ -49,6 +49,7 @@ def _build_worker_container(
                 ),
             ),
             client.V1EnvVar(name="TERM", value="dumb"),
+            client.V1EnvVar(name="CLAUDE_CODE_MAX_OUTPUT_TOKENS", value="128000"),
         ]
         return client.V1Container(
             name="worker",
@@ -292,6 +293,7 @@ def _build_session_worker_container(
                 ),
             ),
             client.V1EnvVar(name="TERM", value="dumb"),
+            client.V1EnvVar(name="CLAUDE_CODE_MAX_OUTPUT_TOKENS", value="128000"),
         ] + self._build_s3_env_vars()
         return client.V1Container(
             name="worker",
@@ -461,7 +463,7 @@ def create_session_pr_job(
         return job_name
 
     async def stream_pod_logs(
-        self, job_name: str, tail_lines: int = 100, since_seconds: int | None = None
+        self, job_name: str, tail_lines: int = 1000, since_seconds: int | None = None
     ) -> AsyncIterator[str]:
         """Stream logs from a job's pod. Yields log lines as they arrive.
 

backend/app/infra/s3_client.py

@@ -129,15 +129,6 @@ def generate_presigned_url(self, key: str, expires_in: int = 3600) -> str | None
 
     # ── High-level artifact accessors ──
 
-    def get_proposals(self, session_id: str, iteration_index: int) -> list[dict[str, Any]] | None:
-        data = self.download_json(self.proposals_json_key(session_id, iteration_index))
-        if isinstance(data, dict) and "proposals" in data:
-            result: list[dict[str, Any]] = data["proposals"]
-            return result
-        if isinstance(data, list):
-            return data
-        return None
-
     def get_diff(self, session_id: str, iteration_index: int, proposal_index: int) -> str | None:
         return self.download_text(self.diff_key(session_id, iteration_index, proposal_index))
 

backend/app/usecase/session_usecase.py

@@ -308,10 +308,12 @@ async def _run_session_analysis(
                 "error": None,
                 "proposals": None,
                 "before_screenshot_key": None,
+                "device_type": None,
             }
         )
 
         if result.get("proposals"):
+            device_type = result.get("device_type", "desktop")
             proposals = []
             for i, prop in enumerate(result["proposals"]):
                 p = Proposal(
@@ -333,10 +335,11 @@ async def _run_session_analysis(
                 before_screenshot_key=result.get("before_screenshot_key"),
             )
             logger.info(
-                "Session %s iter %d analysis done: %d proposals",
+                "Session %s iter %d analysis done: %d proposals (device: %s)",
                 session_id,
                 iteration_index,
                 len(proposals),
+                device_type,
             )
 
             # Auto-trigger implementation for ALL proposals
@@ -355,6 +358,7 @@ async def _run_session_analysis(
                         proposal_id=str(proposal.id),
                         plan_json=str(proposal.plan),
                         selected_proposal_index=selected_proposal_index,
+                        device_type=device_type,
                     )
                 )
         else:
@@ -394,6 +398,7 @@ async def _run_session_implementation(
     proposal_id: str,
     plan_json: str,
     selected_proposal_index: int | None,
+    device_type: str = "desktop",
 ) -> None:
     """Background: run one session-based implementation workflow."""
     db = SessionLocal()
@@ -417,6 +422,7 @@ async def _run_session_implementation(
                 "branch": branch,
                 "proposal_index": proposal_index,
                 "proposal_plan": plan_json,
+                "device_type": device_type,
                 "selected_proposal_index": selected_proposal_index,
                 "k8s_job_name": None,
                 "status": "pending",

backend/app/workflow/session_analyzer_graph.py

@@ -57,17 +57,24 @@ async def extract_results(state: SessionAnalyzerState) -> dict:
     session_id = state["session_id"]
     iteration_index = state["iteration_index"]
 
-    proposals = s3.get_proposals(session_id, iteration_index)
-    before_key = s3.before_screenshot_key(session_id, iteration_index)
-    has_before = s3.exists(before_key)
-
-    if proposals is None:
+    data = s3.download_json(s3.proposals_json_key(session_id, iteration_index))
+    if isinstance(data, dict) and "proposals" in data:
+        proposals = data["proposals"]
+        device_type = data.get("device_type", "desktop")
+    elif isinstance(data, list):
+        proposals = data
+        device_type = "desktop"
+    else:
         return {"error": "Failed to read proposals from S3", "status": "failed"}
+
     if len(proposals) == 0:
-        return {"error": "No proposals generated by analyzer", "status": "failed"}
+        return {"error": "No proposals generated", "status": "failed"}
+
+    before_key = s3.before_screenshot_key(session_id, iteration_index)
     return {
         "proposals": proposals,
-        "before_screenshot_key": before_key if has_before else None,
+        "device_type": device_type,
+        "before_screenshot_key": before_key if s3.exists(before_key) else None,
     }
 
 

backend/app/workflow/session_implementation_graph.py

@@ -1,3 +1,4 @@
+import json as _json
 import logging
 from typing import Any
 
@@ -15,9 +16,16 @@ async def create_k8s_job(state: SessionImplementationState) -> dict:
     k8s = K8sClient()
     s3 = S3Client()
 
-    # Write proposal plan to S3 for the worker to read
+    # Write proposal plan to S3 for the worker to read (includes device_type)
     plan_key = s3.plan_key(state["session_id"], state["iteration_index"], state["proposal_index"])
-    s3.upload_text(plan_key, state["proposal_plan"])
+    plan_with_device = _json.dumps(
+        {
+            "plan": state["proposal_plan"],
+            "device_type": state.get("device_type", "desktop"),
+        },
+        ensure_ascii=False,
+    )
+    s3.upload_text(plan_key, plan_with_device)
 
     job_name = k8s.create_session_implementation_job(
         session_id=state["session_id"],

backend/app/workflow/state.py

@@ -23,6 +23,7 @@ class SessionAnalyzerState(TypedDict):
     # Output
     proposals: list[dict] | None
     before_screenshot_key: str | None
+    device_type: str | None
 
 
 class SessionImplementationState(TypedDict):
@@ -35,6 +36,7 @@ class SessionImplementationState(TypedDict):
     branch: str
     proposal_index: int
     proposal_plan: str
+    device_type: str
 
     # Patch context (for iter > 0)
     selected_proposal_index: int | None