Merge pull request #53 from studio-recoding/feat/email

[feat] 이메일 api 완성

app/database/chroma_db.py

@@ -71,9 +71,7 @@ async def db_daily_schedule(user_data: RecommendationMainRequestDTO):
     month = int(schedule_date.split("-")[1])
     date = int(schedule_date.split("-")[2])
     persona = user_data.user_persona or "hard working"
-    results = schedules.query(
-        query_texts=[persona],
-        n_results=5,
+    results = schedules.get(
         where={"$and":
                [
                    {"member": {"$eq": int(member)}},
@@ -84,7 +82,14 @@ async def db_daily_schedule(user_data: RecommendationMainRequestDTO):
         }
         # where_document={"$contains":"search_string"}  # optional filter
     )
-    return results['documents']
+
+    # documents와 datetime_start 추출
+    results = [(doc, meta['datetime_start']) for doc, meta in zip(results['documents'], results['metadatas'])]
+
+    # 결과 출력
+    print(results)
+
+    return results
 
 # 태그 생성용 스케쥴 반환 - 카테고리에 따라
 async def db_monthly_tag_schedule(user_data: ReportTagsRequestDTO):

app/dto/db_dto.py

@@ -29,3 +29,9 @@ class ReportTagsRequestDTO(BaseModel):
     schedule_datetime_start: str
     schedule_datetime_end: str
 
+class EmailRequestDTO(BaseModel):
+    member_id: int
+    user_persona: str
+    schedule_datetime_start: str
+    schedule_datetime_end: str
+

app/dto/openai_dto.py

@@ -17,4 +17,8 @@ class TagDescription(BaseModel):
     desc: str
 
 class TagsResponse(BaseModel):
-    tagList: List[TagDescription]
+    tagList: List[TagDescription]
+
+class EmailResponse(BaseModel):
+    text: str
+    image: str

app/main.py

@@ -35,6 +35,9 @@
 from app.routers import report
 app.include_router(report.router)
 
+from app.routers import email
+app.include_router(email.router)
+
 # description: prevent CORS error
 origins = [
     "*",

app/prompt/email_prompt.py

@@ -0,0 +1,34 @@
+class Template:
+    daily_email_template = """
+                    {persona}
+                    Construct an email to conclude the user's day. The email should:
+
+                    Acknowledge the user's efforts and achievements throughout the day.
+                    Offer encouragement and suggestions for preparing for tomorrow’s agenda.
+                    Use this information to create a personalized, thoughtful email that reinforces positive feedback and provides motivational insights for the upcoming day.
+                    You should construct the email based solely on the schedule provided, without assuming or extrapolating additional details.
+                    YOU MUST USE {output_language} TO RESPOND. The length of the email should not exceed 2 paragraphs. Do not call user's name.
+
+                    Today's schedule for the user1:
+                    2021-07-19T09:00:00: Zoom meeting attendance
+                    2021-07-19T11:00:00: Review of project report
+                    2021-07-19T13:00:00: Business lunch
+                    2021-07-19T15:00:00: Team meeting
+                    2021-07-19T18:00:00: Workshop preparation
+
+                    Email:
+                    Today's activities show you managed a full and productive schedule.
+
+                    In the morning, your active participation in the Zoom meeting was impressive. Such engagement is crucial for fostering collaborative success.
+                    During your project report review, your attention to detail stood out. This meticulousness will significantly contribute to the project's success.
+                    The business lunch was an important time for building relationships. Such networking will assist in future tasks.
+                    In the afternoon, you effectively led the team meeting, playing a vital role in enhancing team cooperation.
+                    Lastly, thank you for your effort in preparing for the workshop. This preparation will facilitate a smooth running of tomorrow's session.
+
+                    Thank you for your hard work today. Rest well and recharge for another fruitful day tomorrow.
+
+                    Today's schedule for the user2:
+                    {schedule} 
+
+                    Email:
+                    """

app/prompt/openai_config.ini

@@ -16,4 +16,9 @@ MODEL_NAME      = gpt-4
 [NESS_TAGS]
 TEMPERATURE     = 0.5
 MAX_TOKENS      = 2048
+MODEL_NAME      = gpt-4
+
+[NESS_EMAIL]
+TEMPERATURE     = 0.5
+MAX_TOKENS      = 2048
 MODEL_NAME      = gpt-4

app/routers/email.py

@@ -0,0 +1,80 @@
+import configparser
+import os
+
+from openai import OpenAI
+from dotenv import load_dotenv
+from fastapi import APIRouter, Depends, status, HTTPException
+from langchain_community.chat_models import ChatOpenAI
+from langchain_core.prompts import PromptTemplate
+
+from app.dto.db_dto import EmailRequestDTO
+from app.dto.openai_dto import EmailResponse
+from app.prompt import email_prompt, persona_prompt
+import app.database.chroma_db as vectordb
+
+router = APIRouter(
+    prefix="/email",
+    tags=["email"]
+)
+
+# description: load env variables from .env file
+load_dotenv()
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+# description: load config variables from openai_config.ini file
+CONFIG_FILE_PATH = "app/prompt/openai_config.ini"
+config = configparser.ConfigParser()
+config.read(CONFIG_FILE_PATH)
+
+# description: 유저의 하루 스케줄을 기반으로 이메일 내용을 작성한다.
+@router.post("/daily", status_code=status.HTTP_200_OK)
+async def get_daily_email(user_data: EmailRequestDTO) -> EmailResponse:
+    try:
+        # 모델
+        config_recommendation = config['NESS_EMAIL']
+
+        chat_model = ChatOpenAI(temperature=config_recommendation['TEMPERATURE'],  # 창의성 (0.0 ~ 2.0)
+                                max_tokens=config_recommendation['MAX_TOKENS'],  # 최대 토큰수
+                                model_name=config_recommendation['MODEL_NAME'],  # 모델명
+                                openai_api_key=OPENAI_API_KEY  # API 키
+                                )
+
+        # vectordb에서 유저의 정보를 가져온다.
+        schedule = await vectordb.db_daily_schedule(user_data)
+
+        print(schedule)
+
+        # 템플릿
+        email_template = email_prompt.Template.daily_email_template
+
+        # 페르소나
+        persona = user_data.user_persona
+        user_persona_prompt = persona_prompt.Template.from_persona(persona)
+
+        # 이메일 내용
+        prompt = PromptTemplate.from_template(email_template)
+        email_text = chat_model.predict(
+            prompt.format(persona=user_persona_prompt, output_language="Korean", schedule=schedule))
+        print(email_text)
+
+        # \n을 <br>로 변환
+        email_text = email_text.replace("\n", "<br>")
+        print(email_text)
+
+        # 이메일에 들어갈 텍스트
+        client = OpenAI()
+
+        response = client.images.generate(
+            model="dall-e-3",
+            prompt="Relaxing image, Calm and Quiet illustration style",
+            size="1792x1024",
+            quality="standard",
+            n=1,
+        )
+
+        image_url = response.data[0].url
+
+        return EmailResponse(text=email_text, image=image_url)
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

app/routers/recommendation.py

@@ -25,6 +25,7 @@
 config = configparser.ConfigParser()
 config.read(CONFIG_FILE_PATH)
 
+# 유저의 하루 스케줄을 기반으로 한 줄 추천을 생성한다.
 @router.post("/main", status_code=status.HTTP_200_OK)
 async def get_recommendation(user_data: RecommendationMainRequestDTO) -> ChatResponse:
     try: