234 lines
12 KiB
Python
234 lines
12 KiB
Python
import os, sys, subprocess
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from urllib.request import urlopen
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from urllib.parse import quote
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if sys.stdout is None: sys.stdout = open(os.devnull, "w")
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if sys.stderr is None: sys.stderr = open(os.devnull, "w")
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try: sys.stdout.reconfigure(errors='replace')
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except: pass
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try: sys.stderr.reconfigure(errors='replace')
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except: pass
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script_dir = os.path.dirname(__file__)
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sys.path.append(os.path.abspath(os.path.join(script_dir, '..')))
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sys.path.append(os.path.abspath(script_dir))
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import streamlit as st
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import time, json, re, threading, queue
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from agentmain import GeneraticAgent
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import chatapp_common # activate /continue command (monkey patches GeneraticAgent)
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from continue_cmd import handle_frontend_command, reset_conversation, list_sessions, extract_ui_messages
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st.set_page_config(page_title="Cowork", layout="wide")
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@st.cache_resource
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def init():
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agent = GeneraticAgent()
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if agent.llmclient is None:
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st.error("⚠️ 사용 가능한 LLM 인터페이스가 구성되지 않았습니다. mykey.py를 설정하세요.")
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st.stop()
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else: threading.Thread(target=agent.run, daemon=True).start()
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return agent
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agent = init()
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st.title("🖥️ Cowork")
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if 'autonomous_enabled' not in st.session_state: st.session_state.autonomous_enabled = False
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@st.fragment
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def render_sidebar():
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current_idx = agent.llm_no
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st.caption(f"LLM Core: {current_idx}: {agent.get_llm_name()}", help="백업 링크 전환하려면 클릭하세요")
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last_reply_time = st.session_state.get('last_reply_time', 0)
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if last_reply_time > 0:
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st.caption(f"대기 시간：{int(time.time()) - last_reply_time}초", help="30분 이상 응답이 없으면 시스템이 자동으로 작업을 시작합니다")
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if st.button("백업 링크 전환"):
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agent.next_llm(); st.rerun(scope="fragment")
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if st.button("작업 강제 중지"):
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agent.abort(); st.toast("중지 신호가 전송되었습니다"); st.rerun()
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if st.button("도구 재주입"):
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agent.llmclient.last_tools = ''
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try:
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hist_path = os.path.join(script_dir, '..', 'assets', 'tool_usable_history.json')
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with open(hist_path, 'r', encoding='utf-8') as f: tool_hist = json.load(f)
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agent.llmclient.backend.history.extend(tool_hist)
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st.toast(f"도구가 재주입되었습니다. {len(tool_hist)}개의 예시 기록이 추가되었습니다")
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except Exception as e: st.toast(f"도구 예시 주입 실패: {e}")
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if st.button("🐱 데스크톱 펫"):
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kwargs = {'creationflags': 0x08} if sys.platform == 'win32' else {}
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pet_script = os.path.join(script_dir, 'desktop_pet_v2.pyw')
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if not os.path.exists(pet_script): pet_script = os.path.join(script_dir, 'desktop_pet.pyw')
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subprocess.Popen([sys.executable, pet_script], **kwargs)
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def _pet_req(q):
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def _do():
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try: urlopen(f'http://127.0.0.1:41983/?{q}', timeout=2)
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except Exception: pass
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threading.Thread(target=_do, daemon=True).start()
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agent._pet_req = _pet_req
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if not hasattr(agent, '_turn_end_hooks'): agent._turn_end_hooks = {}
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def _pet_hook(ctx):
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parts = [f"Turn {ctx.get('turn','?')}"]
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if ctx.get('summary'): parts.append(ctx['summary'])
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if ctx.get('exit_reason'): parts.append('작업 완료')
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_pet_req(f'msg={quote(chr(10).join(parts))}')
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if ctx.get('exit_reason'): _pet_req('state=idle')
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agent._turn_end_hooks['pet'] = _pet_hook
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st.toast("데스크톱 펫이 시작되었습니다")
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st.divider()
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if st.button("대기 중 자율 행동 시작"):
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st.session_state.last_reply_time = int(time.time()) - 1800
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st.toast("마지막 응답 시간을 1800초 전으로 설정했습니다"); st.rerun()
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if st.session_state.autonomous_enabled:
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if st.button("⏸️ 자율 행동 금지"):
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st.session_state.autonomous_enabled = False
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st.toast("⏸️ 자율 행동이 금지되었습니다"); st.rerun()
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st.caption("🟢 자율 행동이 실행 중입니다. 30분 후 자동으로 진행됩니다")
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else:
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if st.button("▶️ 자율 행동 허용", type="primary"):
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st.session_state.autonomous_enabled = True
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st.toast("✅ 자율 행동이 허용되었습니다"); st.rerun()
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st.caption("🔴 자율 행동이 중지되었습니다")
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with st.sidebar: render_sidebar()
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def fold_turns(text):
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"""Return list of segments: [{'type':'text','content':...}, {'type':'fold','title':...,'content':...}]"""
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# 먼저 4개 이상의 백틱 블록을 플레이스홀더로 교체하여 하위 에이전트 중첩 LLM Running이 잘못 잘리는 것을 방지합니다.
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_ph = []
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safe = re.sub(r'`{4,}.*?`{4,}', lambda m: (_ph.append(m.group(0)), f'\x00PH{len(_ph)-1}\x00')[1], text, flags=re.DOTALL)
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parts = re.split(r'(\**LLM Running \(Turn \d+\) \.\.\.\*\**)', safe)
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parts = [re.sub(r'\x00PH(\d+)\x00', lambda m: _ph[int(m.group(1))], p) for p in parts]
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if len(parts) < 4: return [{'type': 'text', 'content': text}]
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segments = []
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if parts[0].strip(): segments.append({'type': 'text', 'content': parts[0]})
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turns = []
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for i in range(1, len(parts), 2):
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marker = parts[i]
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content = parts[i+1] if i+1 < len(parts) else ''
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turns.append((marker, content))
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for idx, (marker, content) in enumerate(turns):
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if idx < len(turns) - 1:
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_c = re.sub(r'`{3,}.*?`{3,}|<thinking>.*?</thinking>', '', content, flags=re.DOTALL)
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matches = re.findall(r'<summary>\s*((?:(?!<summary>).)*?)\s*</summary>', _c, re.DOTALL)
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if matches:
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title = matches[0].strip()
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title = title.split('\n')[0]
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if len(title) > 50: title = title[:50] + '...'
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else: title = marker.strip('*')
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segments.append({'type': 'fold', 'title': title, 'content': content})
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else: segments.append({'type': 'text', 'content': marker + content})
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return segments
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def render_segments(segments, suffix=''):
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# 전체 다시 그리기: 호출자가 slot.container()로 감싸서 DOM 경로가 안정적이고 rerun 간 정렬이 보장되도록 함 ("회색 잔상" 제거).
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# heartbeat 대기 시 segments 변경 없음 → Streamlit 백엔드 diff 변화 없음 → 프론트엔드 깜빡임 제로;
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# 단 container/markdown 자체는 API 호출이므로 StopException은 여전히 발생함 (abort는 정상 작동).
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for seg in segments:
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if seg['type'] == 'fold':
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with st.expander(seg['title'], expanded=False): st.markdown(seg['content'])
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else:
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st.markdown(seg['content'] + suffix)
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def agent_backend_stream(prompt):
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display_queue = agent.put_task(prompt, source="user")
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response = ''
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try:
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while True:
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try: item = display_queue.get(timeout=1)
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except queue.Empty:
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yield response # heartbeat: let outer st.markdown() run → Streamlit checks StopException
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continue
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if 'next' in item:
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response = item['next']; yield response
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if 'done' in item:
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yield item['done']; break
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finally: agent.abort()
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if "messages" not in st.session_state: st.session_state.messages = []
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for msg in st.session_state.messages:
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with st.chat_message(msg["role"]):
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# slot=st.empty() + with slot.container(): ... 외부 껍질을 사용하여 DOM 경로와 스트리밍 렌더링이 완전히 일치하고 rerun 간 정렬됨
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slot = st.empty()
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with slot.container():
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if msg["role"] == "assistant": render_segments(fold_turns(msg["content"]))
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else: st.markdown(msg["content"])
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# Scroll-height ghost fix: during streaming, expander open/close mid-animation can leave
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# phantom height → scrollbar long but can't scroll to bottom. Periodically detect & reflow.
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try:
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from streamlit import iframe as _st_iframe # 1.56+
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_embed_html = lambda html, **kw: _st_iframe(html, **{k: max(v, 1) if isinstance(v, int) else v for k, v in kw.items()})
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except (ImportError, AttributeError):
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from streamlit.components.v1 import html as _embed_html # ≤1.55
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_js_scroll_fix = ("!function(){var p=window.parent;if(p.__sfx)return;p.__sfx=1;"
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"var d=p.document;setInterval(function(){"
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"var m=d.querySelector('section.main');if(!m)return;"
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"var b=m.querySelector('.block-container');if(!b)return;"
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"if(m.scrollHeight>b.scrollHeight+150){"
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"m.style.overflow='hidden';void m.offsetHeight;m.style.overflow=''}"
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"},3000)}()")
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# IME composition fix (macOS only) - prevents Enter from submitting during CJK input
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_js_ime_fix = ("" if os.name == 'nt' else
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"!function(){if(window.parent.__imeFix)return;window.parent.__imeFix=1;"
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"var d=window.parent.document,c=0;"
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"d.addEventListener('compositionstart',()=>c=1,!0);"
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"d.addEventListener('compositionend',()=>c=0,!0);"
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"function f(){d.querySelectorAll('textarea[data-testid=stChatInputTextArea]')"
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".forEach(t=>{t.__imeFix||(t.__imeFix=1,t.addEventListener('keydown',e=>{"
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"e.key==='Enter'&&!e.shiftKey&&(e.isComposing||c||e.keyCode===229)&&"
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"(e.stopImmediatePropagation(),e.preventDefault())},!0))})}"
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"f();new MutationObserver(f).observe(d.body,{childList:1,subtree:1})}()")
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_embed_html(f'<script>{_js_scroll_fix};{_js_ime_fix}</script>', height=0)
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if prompt := st.chat_input("any task?"):
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ts = time.strftime("%Y-%m-%d %H:%M:%S")
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cmd = (prompt or "").strip()
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def _reset_and_rerun():
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st.session_state.streaming = False
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st.session_state.stopping = False
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st.session_state.display_queue = None
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st.session_state.partial_response = ""
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st.session_state.reply_ts = ""
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st.session_state.current_prompt = ""
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st.session_state.last_reply_time = int(time.time())
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st.rerun()
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if cmd == "/new":
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st.session_state.messages = [{"role": "assistant", "content": reset_conversation(agent), "time": ts}]
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_reset_and_rerun()
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if cmd.startswith("/continue"):
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m = re.match(r'/continue\s+(\d+)\s*$', cmd.strip())
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sessions = list_sessions(exclude_pid=os.getpid()) if m else []
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idx = int(m.group(1)) - 1 if m else -1
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# Resolve target path BEFORE handle (which snapshots current log, shifting indices).
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target = sessions[idx][0] if 0 <= idx < len(sessions) else None
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result = handle_frontend_command(agent, cmd)
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history = extract_ui_messages(target) if target and result.startswith('✅') else None
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tail = [{"role": "assistant", "content": result, "time": ts}]
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if history:
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st.session_state.messages = history + tail
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else:
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st.session_state.messages = list(st.session_state.messages) + \
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[{"role": "user", "content": cmd, "time": ts}] + tail
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_reset_and_rerun()
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st.session_state.messages.append({"role": "user", "content": prompt})
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if hasattr(agent, '_pet_req') and not prompt.startswith('/'): agent._pet_req('state=walk')
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with st.chat_message("user"): st.markdown(prompt)
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with st.chat_message("assistant"):
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frozen = 0; live = st.empty(); response = ''
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CURSOR = ' ▌'
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for response in agent_backend_stream(prompt):
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segs = fold_turns(response)
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n_done = max(0, len(segs) - 1)
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while frozen < n_done:
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with live.container(): render_segments([segs[frozen]])
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live = st.empty(); frozen += 1
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with live.container(): render_segments([segs[-1]], suffix=CURSOR) # 라이브 영역
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segs = fold_turns(response)
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for i in range(frozen, len(segs)):
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with live.container(): render_segments([segs[i]])
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if i < len(segs) - 1: live = st.empty()
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st.session_state.messages.append({"role": "assistant", "content": response})
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st.session_state.last_reply_time = int(time.time())
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if st.session_state.autonomous_enabled:
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st.markdown(f"""<div id="last-reply-time" style="display:none">{st.session_state.get('last_reply_time', int(time.time()))}</div>""", unsafe_allow_html=True)
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