Refactor/deploy

.dockerignore

@@ -0,0 +1,97 @@
+# 가상환경
+poetry.lock
+pyproject.toml
+
+# Data
+data/
+
+# Git
+.git
+.github
+.gitignore
+.gitattributes
+*,md
+
+# CI
+.codeclimate.yml
+.travis.yml
+.taskcluster.yml
+
+# Docker
+docker-compose.yml
+Dockerfile
+.docker
+.dockerignore
+
+# Byte-compiled / optimized / DLL files
+**/__pycache__/
+**/*.py[cod]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.cache
+nosetests.xml
+coverage.xml
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Virtual environment
+.env
+.venv/
+venv/
+
+# PyCharm
+.idea
+
+# Python mode for VIM
+.ropeproject
+**/.ropeproject
+
+# Vim swap files
+**/*.swp
+
+# VS Code
+.vscode/

Dockerfile

@@ -0,0 +1,17 @@
+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+# Create a startup script
+RUN echo '#!/bin/bash\n\
+python main.py &\n\
+streamlit run app.py' > start.sh
+
+RUN chmod +x start.sh
+
+CMD ["/bin/bash", "start.sh"]

back/kakao.py

@@ -1,7 +1,7 @@
 import secrets
 from typing import Optional
 
-from config import CLIENT_ID, CLIENT_SECRET, OUTSIDE_IP, PORT, STREAMLIT_PORT
+from config import CLIENT_ID, CLIENT_SECRET, OUTSIDE_IP, PORT
 from fastapi import APIRouter, Depends, Header, HTTPException, status
 from fastapi.responses import RedirectResponse
 from fastapi_oauth_client import OAuthClient

back/managers/mongo_config.py

@@ -1,6 +1,9 @@
 import os
 from pymongo import MongoClient
 from gridfs import GridFSBucket
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
 
 # 환경 변수로부터 MongoDB 설정 읽기
 username = os.getenv("MONGO_USERNAME", "admin")
@@ -11,4 +14,4 @@
 client = MongoClient(MONGO_URL)
 database = client["database"]
 collection = database["users"]
-fs_bucket = GridFSBucket(database)
+fs_bucket = GridFSBucket(database)

config.py

@@ -1,29 +1,42 @@
 import os
-import yaml
+import socket
+import requests
+from dotenv import load_dotenv
+
+def get_public_ip():
+    response = requests.get('https://checkip.amazonaws.com')
+    public_ip = response.text.strip()
+    return public_ip
+
+def get_private_ip():
+    try:
+        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+        s.connect(("8.8.8.8", 80))
+        private_ip = s.getsockname()[0]
+        s.close()
+    except Exception as e:
+        hostname = socket.gethostname()
+        private_ip = socket.gethostbyname(hostname)
+    return private_ip
+
 
 path = os.getcwd()  # 상위 폴더에서 실행된 경우 -> secret_key.yaml이 상위 폴더에 있음
 # path = os.path.dirname(os.path.abspath(__file__)) # 현재 폴더에서 실행된 경우 -> secret_key.yaml이 현재 폴더에 있음
 
-with open(os.path.join(path, "secret_key.yaml"), "r") as yaml_file:
-    cfg = yaml.safe_load(yaml_file)
-
-OPENAI_API_KEY = cfg["OPENAI_API_KEY"]
-COHERE_API_KEY = cfg["COHERE_API_KEY"]
-
-INSIDE_IP = cfg["IP"]["INSIDE_IP"]
-OUTSIDE_IP = cfg["IP"]["OUTSIDE_IP"]
+load_dotenv(override=True)
 
-REST_API_KEY = cfg["Kakaologin"]["REST_API_KEY"]
-REDIRECT_URI = f"http://{OUTSIDE_IP}:{cfg['PORT']}/auth"
+MODEL_NAME = os.getenv("MODEL_NAME", "gpt-4o-mini")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+COHERE_API_KEY = os.getenv("COHERE_API_KEY")
 
-PORT = cfg["PORT"]
-STREAMLIT_PORT = cfg["STREAMLIT"]["PORT"]
+INSIDE_IP = get_private_ip()
+OUTSIDE_IP = get_public_ip()
 
-KEY_FILE = cfg["SSL"]["KEY_FILE"]
-CERT_FILE = cfg["SSL"]["CERT_FILE"]
+PORT = 8001
+STREAMLIT_PORT = 8501
 
-CLIENT_ID = cfg["CLIENT_ID"]
-CLIENT_SECRET = cfg["CLIENT_SECRET"]
+CLIENT_ID = os.getenv("CLIENT_ID")
+CLIENT_SECRET = os.getenv("CLIENT_SECRET")
 
 DATA_DIR = os.path.join(path, "data")
 IMG_PATH = os.path.join(path, "data", "images")

docker-compose.yml

@@ -0,0 +1,56 @@
+version: '3.10'
+
+services:
+  # nginx:
+  #   image: nginx:alpine
+  #   ports:
+  #     - "8080:80"
+  #     - "443:443"
+  #   volumes:
+  #     - /etc/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+  #     - /etc/ssl/merged_certificate.crt:/etc/ssl/merged_certificate.crt:ro
+  #     - /etc/ssl/private/private.key:/etc/ssl/private/private.key:ro
+  #   depends_on:
+  #     - app
+  #   networks:
+  #     - app-network
+
+  app:
+    image: kooqooo/hello-jobits:latest
+    ports:
+      - "8501:8501"
+      - "8001:8001"
+    volumes:
+      - ~/data:/app/data
+    environment:
+      - CLIENT_ID=${CLIENT_ID}
+      - CLIENT_SECRET=${CLIENT_SECRET}
+      - OPENAI_API_KEY=${OPENAI_API_KEY}
+      - COHERE_API_KEY=${COHERE_API_KEY}
+      - MODEL_NAME=${MODEL_NAME}
+      - MONGO_USERNAME=${MONGO_USERNAME}
+      - MONGO_PASSWORD=${MONGO_PASSWORD}
+    depends_on:
+      - mongo
+    networks:
+      - app-network
+
+  mongo:
+    image: mongo:latest
+    ports:
+      - "27017:27017"
+    volumes:
+      - mongo-data:/data/db
+    environment:
+      - MONGO_INITDB_ROOT_USERNAME=${MONGO_USERNAME}
+      - MONGO_INITDB_ROOT_PASSWORD=${MONGO_PASSWORD}
+    networks:
+      - app-network
+
+networks:
+  app-network:
+    driver: bridge
+
+volumes:
+  mongo-data:
+    driver: local

pages/1_home.py

@@ -66,7 +66,6 @@
     print("user_id : ", st.session_state["user_id"])
 
 if "openai_api_key" not in st.session_state:
-    os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
     st.session_state.openai_api_key = OPENAI_API_KEY
 
 if "FAV_IMAGE_PATH" not in st.session_state:

pages/2_user.py

@@ -8,7 +8,7 @@
 sys.path.append("./")
 sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__))))
 
-from config import DATA_DIR, IMG_PATH, path
+from config import DATA_DIR, IMG_PATH, path, CSS_PATH
 from loguru import logger as _logger
 from src.logger import DevConfig
 from src.util import (check_essential, get_image_base64, local_css,
@@ -48,7 +48,7 @@
 
 st.title("안녕하세요, " + st.session_state.nickname + "님!")  # 사용자 이름을 받아서 화면에 출력합니다.
 
-local_css(os.path.join(path, "front", "css", "background.css"))
+local_css(os.path.join(CSS_PATH, "background.css"))
 
 
 # local_css("css/1_user.css")
@@ -237,7 +237,7 @@
 
 
 ## read job info tb
-job_info, JOBS = read_job_info_tb(path + "/data/samples/job_info_tb.parquet")
+job_info, JOBS = read_job_info_tb(os.path.join(DATA_DIR,  "samples", "job_info_tb.parquet"))
 st.session_state.job_info = job_info
 st.session_state.logger.info("read job tb")
 st.session_state.logger.info(f"job info is ... {JOBS}")

pages/3_gene_question.py

@@ -26,7 +26,7 @@
 from src.rule_based import list_extend_questions_based_on_keywords
 from src.util import local_css, read_prompt_from_txt
 from src.semantic_search import faiss_inference, reranker
-from config import OPENAI_API_KEY, DATA_DIR, IMG_PATH, CSS_PATH, PORT
+from config import DATA_DIR, IMG_PATH, CSS_PATH, PORT, MODEL_NAME
 
 st.session_state["FAV_IMAGE_PATH"] = os.path.join(IMG_PATH, "favicon.png")
 st.set_page_config(
@@ -80,8 +80,6 @@
             </style>
             """,unsafe_allow_html=True)
 
-## set variables
-MODEL_NAME = "gpt-3.5-turbo-16k"
 
 ## set save dir
 USER_RESUME_SAVE_DIR = os.path.join(st.session_state["save_dir"], "2_generate_question_user_resume.pdf")
@@ -139,16 +137,14 @@
 
     ### JD 사용하여 JD 추출용 프롬프트 만들기
     st.session_state.logger.info("prompt JD start")
-    prompt_template_jd = read_prompt_from_txt(os.path.join(DATA_DIR, "test/prompt_JD_template.txt"))
+    prompt_template_jd = read_prompt_from_txt(os.path.join(DATA_DIR, "prompts", "prompt_JD_template.txt"))
     st.session_state.prompt_JD = create_prompt_with_jd(prompt_template_jd)
 
     # prompt_JD 생성완료
     st.session_state.logger.info("create prompt JD object")
 
     ### 모델 세팅 그대로
-    llm = ChatOpenAI(temperature=st.session_state.temperature,
-                        model_name=MODEL_NAME,
-                        openai_api_key=OPENAI_API_KEY)
+    llm = ChatOpenAI(temperature=st.session_state.temperature, model_name=MODEL_NAME)
 
     st.session_state.logger.info("create llm object")
 
@@ -167,7 +163,7 @@
     # prompt_qa_template #######################################
 
     st.session_state.logger.info("prompt resume start")
-    prompt_template_resume = read_prompt_from_txt(os.path.join(DATA_DIR, "test/prompt_resume_template.txt"))
+    prompt_template_resume = read_prompt_from_txt(os.path.join(DATA_DIR, "prompts", "prompt_resume_template.txt"))
 
     st.session_state.logger.info("create prompt resume template")
     st.session_state.prompt_resume = create_prompt_with_resume(prompt_template_resume)
@@ -178,9 +174,7 @@
     st.session_state.logger.info("user_resume chunk OpenAIEmbeddings ")
 
     ### STEP 2 를 위한 새 모델 호출
-    llm2 = ChatOpenAI(temperature=0.0, 
-                        model_name=MODEL_NAME, 
-                        openai_api_key=OPENAI_API_KEY)
+    llm2 = ChatOpenAI(temperature=0.0, model_name=MODEL_NAME)
 
     st.session_state.chain_type_kwargs = {"prompt": st.session_state.prompt_resume}
 
@@ -198,12 +192,12 @@
 
     ## step3 :
     st.session_state.logger.info("prompt question start")
-    prompt_template_question = read_prompt_from_txt(os.path.join(DATA_DIR, "test/prompt_question_template.txt"))
+    prompt_template_question = read_prompt_from_txt(os.path.join(DATA_DIR, "prompts", "prompt_question_template.txt"))
 
     st.session_state.logger.info("create prompt question template")
     st.session_state.prompt_question = create_prompt_with_question(prompt_template_question)
 
-    llm3 = ChatOpenAI(temperature=0, model_name=MODEL_NAME, openai_api_key=OPENAI_API_KEY)
+    llm3 = ChatOpenAI(temperature=0, model_name=MODEL_NAME)
     st.session_state.chain = LLMChain(llm=llm3, prompt=st.session_state.prompt_question)
     st.session_state.main_question = st.session_state.chain.invoke({"jd": st.session_state.job_description, "resume": st.session_state.resume})['text']
     #################