Feature/15

api/summary.py

@@ -0,0 +1,20 @@
+from fastapi import APIRouter
+from service.summary import call_assistant_summary, AssistantSummary
+from config import settings
+import requests
+import json
+from pydantic import ValidationError
+from fastapi import HTTPException
+
+router = APIRouter(tags=["Summary"])
+
+
+@router.get("/assistant")
+async def call_assistant(userId: int, roomId: str):
+
+    try:
+        message = call_assistant_summary(userId, roomId)
+    except ValidationError as e:
+        raise HTTPException(status_code=500, detail="Internal parsing error")
+
+    return {"message": message}

main.py

@@ -1,7 +1,8 @@
 from fastapi import FastAPI
-from api import health, icebreaking
+from api import health, icebreaking, summary
 
 app = FastAPI(root_path="/ai")
 
 app.include_router(health.router)
 app.include_router(icebreaking.router)
+app.include_router(summary.router)

service/summary.py

@@ -0,0 +1,165 @@
+import requests
+import os
+from config import settings
+from pydantic import BaseModel, Field
+from openai import OpenAI
+from datetime import datetime
+from typing import List
+from dotenv import load_dotenv
+
+
+class Persona(BaseModel):
+    id: int
+    name: str
+    relationship: str | None = ""
+    speech_style: str | None = ""
+    preferences: str | None = ""
+    critical_flags: List[str]
+
+
+class _SummaryPeriod(BaseModel):
+    year: List[str]
+    month: List[str]
+    week: List[str]
+    day: List[str]
+    last_update: datetime
+
+
+class Summaries(BaseModel):
+    health_status: _SummaryPeriod
+    emotional_and_mental_state: _SummaryPeriod
+    hobbies_and_interests: _SummaryPeriod
+    relationship_context: _SummaryPeriod
+    social_activities: _SummaryPeriod
+    intimacy: _SummaryPeriod
+
+
+class Sender(BaseModel):
+    id: int
+    name: str
+
+
+class Message(BaseModel):
+    roomId: str
+    sender: Sender
+    content: str
+    isRead: bool
+    createdAt: datetime
+    updatedAt: datetime
+
+
+class AssistantSummary(BaseModel):
+    roomId: str
+    persona: List[Persona]
+    summaries: Summaries
+    today_messages: List[Message]
+
+
+# 프롬프팅 반환
+def user_prompt(response, userId) -> list[dict]:
+
+    # 현재 대화추천을 요청한 사용자가 누구인지 판단하는 로직
+    id = userId
+    if userId == response.persona[0].id:
+        speaker = response.persona[0].name
+        speaker_speech_style = response.persona[0].speech_style
+    else:
+        speaker = response.persona[1].name
+        speaker_speech_style = response.persona[1].speech_style
+
+    # open ai에 질의 메시지
+    user_content = f"""
+    ### ROLE
+    이번 문장은 {speaker}의 말투({speaker_speech_style})로 작성한다.
+
+    ### CRITICAL_FLAGS
+    {response.persona[0].name}의 {response.persona[0].critical_flags}
+    {response.persona[1].name}의 {response.persona[1].critical_flags}
+
+    ### 요약
+    {response.summaries}
+
+    ### 최근 대화
+    {response.today_messages}
+
+    ### TASK
+    1) 상황 파악 → 사고 단계 기록  
+    2) {speaker} 입장에서 한 문장 작성  
+    3) JSON 만 출력  
+    json
+    {{ "reply": "..." }}
+    """
+    return [
+        {
+            "role": "system",
+            "content": "너는 한국어 어르신 대화 코치이다. 두 어르신의 건강을 고려해 한 문장으로 답한다.",
+        },
+        {"role": "user", "content": user_content},
+    ]
+
+
+### OpenAI 호출
+def get_reply(response, userId) -> str:
+
+    # 프롬프트 생성성
+    messages = user_prompt(response, userId)
+
+    # open 인스턴스 생성
+    load_dotenv()
+    OpenAI.api_key = os.getenv("OPENAI_API_KEY")
+    client = OpenAI(api_key=OpenAI.api_key)
+
+    # gpt에 요청
+    gpt_response = client.chat.completions.create(
+        model="gpt-4o",
+        messages=messages,
+        temperature=0.5,
+    )
+    return gpt_response.choices[0].message.content.strip()
+
+
+# 프론트에서 대답 time out으로 추천대화 get 요청
+def call_assistant_summary(userId: int, roomId: str) -> str:
+
+    # chat 서버에 요약본 요청
+    url = f"{settings.CHAT_SERVER_URL}/summary"
+    response = requests.get(url, params={"roomId": roomId})
+    if response.status_code == 404:
+        # 원하는 대로 처리 (빈 응답, 기본 메시지 반환 등)
+        raise ValueError(f"Summary not found for roomId={roomId}")
+    response.raise_for_status()
+
+    # 파싱 모듈
+    parsing_json_response = AssistantSummary.model_validate(response.json())
+
+    # open ai 호출 -> 추천 대화 반환
+    choice_response = get_reply(parsing_json_response, userId)
+    return choice_response  # open ai content 반환
+
+
+# AssistantSummary(
+#   roomId='6835cbb953943262d4a7e260',
+#   persona=[
+#     Persona(id='1', name='영서', relationship='', speech_style='', preferences='', critical_flags=[]),
+#     Persona(id='2', name='로봇', relationship='', speech_style='', preferences='', critical_flags=[])
+#   ],
+#   summaries=Summaries(
+#     health_status=_SummaryPeriod(year=[], month=[], week=[], day=[], last_update=datetime.datetime(2025, 5, 27, 14, 27, 6, 16)),
+#     emotional_and_mental_state=_SummaryPeriod(...),
+#     hobbies_and_interests=_SummaryPeriod(...),
+#     relationship_context=_SummaryPeriod(...),
+#     social_activities=_SummaryPeriod(...),
+#     intimacy=_SummaryPeriod(...)
+#   ),
+#   today_messages=[
+#     Message(
+#       roomId='6835cbb953943262d4a7e260',
+#       sender=Sender(id='2', name='로봇'),
+#       content='안녕 영서야',
+#       isRead=True,
+#       createdAt=datetime.datetime(2025, 5, 27, 14, 34, 33, 50),
+#       updatedAt=datetime.datetime(2025, 5, 27, 14, 34, 33, 50)
+#     ),
+#     Message(...),
+#   ]
+# )