shinalok
7f50333bdb
- app.py: image_input gr.Image component, respond() accepts image_path, all yields updated to 7 outputs - api_client.py: chat(image_path=None), base64-encodes image for API - services/chat.py: chat(image_path=None) passes through to api_client Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
380 lines
14 KiB
Python
380 lines
14 KiB
Python
"""율봇 WebUI — youlbot REST API를 호출하는 Gradio 프론트엔드.
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실행:
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python app.py
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환경변수 (.env):
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YOULBOT_API_URL=http://localhost:8000
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YOULBOT_API_TOKEN= ← api.py에 API_TOKEN 설정 시 동일 값
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"""
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import html as _html
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import logging
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import os
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import gradio as gr
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from dotenv import load_dotenv
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load_dotenv()
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logging.basicConfig(
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level=os.getenv("LOG_LEVEL", "INFO").upper(),
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format="%(asctime)s %(levelname)-8s %(name)s — %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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logger = logging.getLogger(__name__)
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from container import Container
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container = Container()
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USER_LABELS = ["아록", "근혜", "도율", "하율"]
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DEFAULT_USER = "아록"
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# ── STT (Whisper) — 로컬 실행 유지 ──────────────────────────────
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_whisper_model = None
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def _get_whisper():
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global _whisper_model
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if _whisper_model is None:
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import whisper
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_whisper_model = whisper.load_model(container.config().whisper_model_size)
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return _whisper_model
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def transcribe_audio(filepath: str) -> str:
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if not filepath:
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return ""
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model = _get_whisper()
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result = model.transcribe(filepath, language="ko")
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return result["text"].strip()
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# ── 채팅 ─────────────────────────────────────────────────────────
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async def respond(message, history, show_thinking, user_id, use_tts, run_ids, image_path):
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if not message.strip() and not image_path:
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yield history, "", None, run_ids, "", "", None
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return
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history = list(history)
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run_ids = list(run_ids)
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display_msg = message
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if image_path:
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display_msg = f"🖼️ [이미지 첨부]\n{message}" if message.strip() else "🖼️ [이미지 첨부]"
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history.append({"role": "user", "content": display_msg})
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history.append({"role": "assistant", "content": ""})
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yield history, "", None, run_ids, "", "", None # boxes 초기화 + 이미지 초기화
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collected_run_id: str | None = None
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tts_text = ""
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thinking_acc = ""
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thinking_text = ""
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thinking_finalized = False
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source_box_html = ""
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try:
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async for token, run_id in container.chat_service().chat(
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message or "이 이미지를 분석해줘.", user_id, show_thinking, image_path=image_path
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):
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if run_id is not None:
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collected_run_id = run_id
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break
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# 즉시 상태 — thinking_acc에 누적 안 함
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if isinstance(token, dict) and "__status" in token:
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if not thinking_acc:
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yield history, "", None, run_ids, _status_html(token["__status"]), gr.update(), gr.update()
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continue
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# 사고 과정(LLM thinking) — 현재 줄만 live_html로 표시
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if isinstance(token, dict) and "__thinking" in token:
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thinking_text += token["__thinking"]
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thinking_acc += token["__thinking"]
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yield history, "", None, run_ids, _live_html(_last_line(thinking_text)), gr.update(), gr.update()
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continue
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# 진행 로그(LangGraph, 검색 등) — 메시지 전체를 live_html로 표시
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if isinstance(token, dict) and "__meta" in token:
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thinking_acc += token["__meta"]
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live = token["__meta"].strip()
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if live:
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yield history, "", None, run_ids, _live_html(live), gr.update(), gr.update()
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continue
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# RAG 출처 — 별도 source_box로 표시
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if isinstance(token, dict) and "__sources" in token:
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source_box_html = _sources_html(token["__sources"])
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yield history, "", None, run_ids, gr.update(), source_box_html, gr.update()
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continue
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# 첫 답변 토큰 도착 — 전체를 details로 전환 (접힌 상태)
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if thinking_acc and not thinking_finalized:
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thinking_finalized = True
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yield history, "", None, run_ids, _thinking_html(thinking_acc), gr.update(), gr.update()
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tts_text += token
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history[-1]["content"] += token
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yield history, "", None, run_ids, gr.update(), gr.update(), gr.update()
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except Exception as e:
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history[-1]["content"] += f"\n\n[오류: {e}]"
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yield history, "", None, run_ids, gr.update(), gr.update(), gr.update()
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return
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run_ids.append(collected_run_id)
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if use_tts:
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audio_path = await container.tts_service().speak(tts_text)
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yield history, "", audio_path, run_ids, gr.update(), gr.update(), gr.update()
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else:
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yield history, "", None, run_ids, gr.update(), gr.update(), gr.update()
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async def handle_feedback(like_data: gr.LikeData, history, run_ids, user_id):
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idx = like_data.index
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if isinstance(idx, (list, tuple)):
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idx = idx[0]
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if not isinstance(idx, int) or idx < 0 or idx >= len(history):
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return
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if history[idx].get("role") != "assistant":
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return
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asst_turn = sum(1 for m in history[:idx] if m.get("role") == "assistant")
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run_id = run_ids[asst_turn] if run_ids and asst_turn < len(run_ids) else None
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user_msg = str(history[idx - 1]["content"]) if idx > 0 else ""
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asst_msg = str(history[idx]["content"])
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rating = 1 if like_data.liked else -1
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try:
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await container.chat_service().save_feedback(user_id, user_msg, asst_msg, rating, run_id)
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except Exception as e:
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logger.error("피드백 저장 실패: %s", e)
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def switch_user(user_id):
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return [], []
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async def reset_chat(user_id):
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try:
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await container.chat_service().reset(user_id)
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except Exception as e:
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logger.error("대화 초기화 실패: %s", e)
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return [], []
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# ── 문서 관리 ─────────────────────────────────────────────────────
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async def ingest_files(files):
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if not files:
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return "파일을 선택해주세요."
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paths = [f if isinstance(f, str) else f.name for f in files]
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results = []
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for path in paths:
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try:
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result = await container.document_service().ingest(path)
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name = os.path.basename(path)
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results.append(f"{name} → {result.get('chunks', '?')}개 청크")
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except Exception as e:
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results.append(f"{os.path.basename(path)} 오류: {e}")
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return "\n".join(results)
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async def list_docs():
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try:
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sources = await container.document_service().list_documents()
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return [[os.path.basename(s), s] for s in sources]
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except Exception as e:
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return [[f"오류: {e}", ""]]
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async def delete_doc(source):
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if not source.strip():
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return "삭제할 파일 경로를 입력하세요.", await list_docs()
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try:
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await container.document_service().delete_document(source.strip())
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return f"삭제 완료: {os.path.basename(source.strip())}", await list_docs()
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except Exception as e:
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return f"오류: {e}", await list_docs()
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# ── UI 구성 ──────────────────────────────────────────────────────
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_BOX_STYLE = (
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"background:#f9f9f9;border-left:3px solid #bbb;border-radius:6px;"
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"padding:8px 14px;margin-bottom:6px;"
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)
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_CONTENT_STYLE = (
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"margin-top:6px;white-space:pre-wrap;font-size:0.85em;"
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"color:#555;max-height:160px;overflow-y:auto;"
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)
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def _last_line(text: str) -> str:
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"""현재 진행 중인 마지막 비어있지 않은 줄 반환."""
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lines = [l for l in text.split("\n") if l.strip()]
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return lines[-1] if lines else text.strip()
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def _live_html(text: str) -> str:
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"""스트리밍 중 현재 줄만 보여주는 단순 div (details 미사용 → 닫힘 현상 없음)."""
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return (
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f'<div style="{_BOX_STYLE}">'
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f'<strong>🤔 분석 중...</strong>'
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f'<div style="{_CONTENT_STYLE}">{_html.escape(text)} ▌</div>'
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f'</div>'
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)
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def _thinking_html(text: str) -> str:
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"""완료 후 전체 내용을 접기/펼치기로 표시."""
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return (
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f'<details style="{_BOX_STYLE}">'
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f'<summary style="cursor:pointer;font-weight:bold;">💭 분석 완료</summary>'
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f'<div style="{_CONTENT_STYLE}">{_html.escape(text)}</div>'
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f'</details>'
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)
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def _status_html(status: str) -> str:
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"""내용 없이 상태만 표시하는 단순 헤더."""
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return (
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f'<div style="{_BOX_STYLE}">'
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f'<strong>🤔 {_html.escape(status)}</strong>'
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f'</div>'
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)
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def _sources_html(sources: list) -> str:
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"""RAG 출처 목록을 접기/펼치기로 표시."""
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items = "".join(
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f"<li>{_html.escape(s['filename'])}"
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+ (f" — {s['page']}페이지" if "page" in s else "")
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+ "</li>"
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for s in sources
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)
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return (
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f'<details style="{_BOX_STYLE}">'
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f'<summary style="cursor:pointer;font-weight:bold;">📄 출처 ({len(sources)}개)</summary>'
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f'<ul style="margin:6px 0;padding-left:18px;font-size:0.85em;color:#555;">{items}</ul>'
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f'</details>'
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)
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with gr.Blocks(title="율봇") as demo:
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gr.Markdown("# 율봇\n육아·금융 전문 AI 상담 도우미")
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user_state = gr.State(DEFAULT_USER)
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run_ids_state = gr.State([])
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with gr.Tab("대화"):
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with gr.Row():
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user_selector = gr.Dropdown(
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choices=USER_LABELS,
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value=DEFAULT_USER,
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label="사용자",
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scale=1,
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)
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thinking_box = gr.HTML(value="")
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chatbot = gr.Chatbot(label="율봇", height=500)
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source_box = gr.HTML(value="")
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with gr.Row(equal_height=True):
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image_input = gr.Image(
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type="filepath",
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label="이미지 첨부 (선택)",
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sources=["upload", "clipboard"],
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scale=1,
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height=120,
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)
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with gr.Column(scale=5):
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msg_box = gr.Textbox(
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placeholder="질문을 입력하세요... (Enter로 전송)",
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label="",
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lines=2,
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autofocus=True,
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)
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send_btn = gr.Button("전송", variant="primary")
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with gr.Row():
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audio_input = gr.Audio(
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sources=["microphone"],
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type="filepath",
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label="음성으로 질문하기",
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scale=4,
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)
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transcribe_btn = gr.Button("음성 → 텍스트 변환", scale=1)
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with gr.Row():
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show_thinking = gr.Checkbox(label="사고 과정 표시", value=True)
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use_tts = gr.Checkbox(label="음성으로 답변 읽기 (TTS)", value=False)
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reset_btn = gr.Button("대화 초기화", size="sm")
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tts_output = gr.Audio(label="음성 답변", autoplay=True, visible=False)
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use_tts.change(lambda v: gr.Audio(visible=v), inputs=[use_tts], outputs=[tts_output])
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user_selector.change(
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switch_user,
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inputs=[user_selector],
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outputs=[chatbot, run_ids_state],
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).then(
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lambda u: u, inputs=[user_selector], outputs=[user_state]
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)
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transcribe_btn.click(transcribe_audio, inputs=[audio_input], outputs=[msg_box])
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_respond_inputs = [msg_box, chatbot, show_thinking, user_state, use_tts, run_ids_state, image_input]
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_respond_outputs = [chatbot, msg_box, tts_output, run_ids_state, thinking_box, source_box, image_input]
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send_btn.click(respond, inputs=_respond_inputs, outputs=_respond_outputs)
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msg_box.submit(respond, inputs=_respond_inputs, outputs=_respond_outputs)
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reset_btn.click(reset_chat, inputs=[user_state], outputs=[chatbot, run_ids_state])
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chatbot.like(
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handle_feedback,
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inputs=[chatbot, run_ids_state, user_state],
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outputs=[],
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)
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with gr.Tab("문서 등록"):
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gr.Markdown("PDF 또는 TXT 파일을 업로드하면 율봇이 내용을 참고해 답변합니다.")
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file_input = gr.File(
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file_types=[".pdf", ".txt"],
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file_count="multiple",
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label="파일 선택",
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)
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ingest_btn = gr.Button("문서 수집", variant="primary")
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ingest_status = gr.Textbox(label="결과", interactive=False)
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ingest_btn.click(ingest_files, inputs=[file_input], outputs=[ingest_status])
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with gr.Tab("문서 관리"):
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gr.Markdown("Qdrant에 등록된 문서 목록입니다. 불필요한 문서를 삭제할 수 있습니다.")
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doc_table = gr.Dataframe(
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headers=["파일명", "전체 경로"],
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label="등록된 문서",
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interactive=False,
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)
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refresh_btn = gr.Button("새로고침")
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gr.Markdown("---")
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with gr.Row():
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delete_source = gr.Textbox(
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label="삭제할 파일 경로",
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placeholder="위 표에서 전체 경로를 복사해 붙여넣으세요",
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scale=4,
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)
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delete_btn = gr.Button("삭제", variant="stop", scale=1)
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delete_status = gr.Textbox(label="결과", interactive=False)
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refresh_btn.click(list_docs, outputs=[doc_table])
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delete_btn.click(delete_doc, inputs=[delete_source], outputs=[delete_status, doc_table])
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demo.load(list_docs, outputs=[doc_table])
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if __name__ == "__main__":
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demo.launch(
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server_name=container.config().server_host,
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server_port=container.config().server_port,
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theme=gr.themes.Soft(),
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)
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