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Separate thinking tokens from meta — use __thinking key for display

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stream_response() now yields {"__thinking": str} for thinking content
instead of {"__meta": str}. Removed [사고 과정]/[/사고 과정] marker
yields; consumers handle thinking display independently.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
sal
2026-06-01 10:33:06 +09:00
parent 67821250fd
commit c061aef220
1 changed files with 8 additions and 22 deletions
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services/agent/agent_service.py
+8 -22
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@@ -257,9 +257,7 @@ class AgentService:
if isinstance(data, dict) and "__thinking" in data:
# thinking 첫 토큰 도착 시 agent 레이블 + prev_node 갱신
if "agent" != prev_node:
if thinking_open:
yield {"__meta": "\n[/사고 과정]\n"}
thinking_open = False
thinking_open = False
content_started = False
if lg:
elapsed = time.perf_counter() - start_time
@@ -267,10 +265,8 @@ class AgentService:
yield {"__meta": f"\n[LangGraph → {label}] ({elapsed:.2f}s)\n"}
prev_node = "agent"
if _think_verbose:
if not thinking_open:
yield {"__meta": "\n[사고 과정]\n"}
thinking_open = True
yield {"__meta": data["__thinking"]}
thinking_open = True
yield {"__thinking": data["__thinking"]}
continue
# ── messages 이벤트 ──────────────────────────────────────
@@ -280,9 +276,7 @@ class AgentService:
# ── 노드 전환 시 플래그 리셋 + 레이블 출력 ──────────────
# (agent 레이블은 custom 이벤트 핸들러에서 이미 처리될 수 있으므로 중복 방지)
if node != prev_node:
if thinking_open:
yield {"__meta": "\n[/사고 과정]\n"}
thinking_open = False
thinking_open = False
content_started = False
if lg:
elapsed = time.perf_counter() - start_time
@@ -298,9 +292,7 @@ class AgentService:
# ── agent 노드 — AIMessageChunk만 처리 (중복 방지) ──────
if node == "agent" and isinstance(chunk, AIMessageChunk):
if chunk.tool_calls:
if thinking_open:
yield {"__meta": "\n[/사고 과정]\n"}
thinking_open = False
thinking_open = False
for tc in chunk.tool_calls:
pending_tool_calls[tc["id"]] = tc
if tc.get("name") == "search_documents":
@@ -314,9 +306,7 @@ class AgentService:
yield {"__meta": f" [tool_call: {tc['name']}({args_str})]\n"}
elif chunk.content:
if thinking_open:
yield {"__meta": "\n[/사고 과정]\n"}
thinking_open = False
thinking_open = False
if lg and not content_started:
yield {"__meta": "\n[LangGraph → agent: 최종 답변 생성]\n\n"}
content_started = True
@@ -329,9 +319,7 @@ class AgentService:
if not content_started and not thinking_open:
thinking = chunk.additional_kwargs.get("thinking", "")
if thinking and _think_verbose:
yield {"__meta": "\n[사고 과정]\n"}
yield {"__meta": thinking}
yield {"__meta": "\n[/사고 과정]\n"}
yield {"__thinking": thinking}
if chunk.content:
if lg:
yield {"__meta": "\n[LangGraph → agent: 최종 답변 생성]\n\n"}
@@ -359,9 +347,7 @@ class AgentService:
result_lines = [b for b in chunk.content.split("\n\n") if b.strip()]
yield {"__meta": f" [웹 검색 결과: {len(result_lines)}건 → agent 복귀]\n"}
if thinking_open:
yield {"__meta": "\n[/사고 과정]\n"}
thinking_open = False
self._last_run_id = str(run_id)
# 대화 내용을 MySQL에 저장