refactor: ChatOpenAI의 인스턴스는 openai_api_key는 환경변수에서 불러옴

#41

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/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, MODEL_NAME
+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(
@@ -144,9 +144,7 @@
     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")
 
@@ -176,9 +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}
 
@@ -201,7 +197,7 @@
     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']
     #################

pages/3_gene_question_no_resume.py

@@ -27,7 +27,7 @@
 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, MODEL_NAME
+from config import DATA_DIR, IMG_PATH, CSS_PATH, MODEL_NAME
 
 st.session_state["FAV_IMAGE_PATH"] = os.path.join(IMG_PATH, "favicon.png")
 st.set_page_config(
@@ -135,9 +135,7 @@
     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")
 
@@ -155,7 +153,7 @@
     st.session_state.logger.info("create no resume prompt question template")
     st.session_state.prompt_question = create_prompt_with_no_resume(prompt_noResume_question_template)
 
-    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.run({"jd": st.session_state.job_description})
     #################

pages/4_show_questions_hint.py

@@ -12,7 +12,7 @@
 from src.generate_question import (create_prompt_feedback,  # 추가
                                    create_prompt_hint)
 from src.util import read_prompt_from_txt
-from config import DATA_DIR, IMG_PATH, OPENAI_API_KEY, MODEL_NAME
+from config import DATA_DIR, IMG_PATH, MODEL_NAME
 
 st.session_state["FAV_IMAGE_PATH"] = os.path.join(IMG_PATH, "favicon.png")
 st.set_page_config(
@@ -80,7 +80,7 @@
                 st.session_state.logger.info("create prompt_Feedback object")
 
                 ### 모델 세팅 그대로
-                llm = ChatOpenAI(temperature=0.0, model_name=MODEL_NAME, openai_api_key=OPENAI_API_KEY)
+                llm = ChatOpenAI(temperature=0.0, model_name=MODEL_NAME)
 
                 st.session_state.logger.info("create llm object")
 
@@ -115,7 +115,7 @@
             st.session_state.logger.info("create prompt_Hint object")
 
             ### 모델 세팅
-            llm = ChatOpenAI(temperature=0.0, model_name=MODEL_NAME, openai_api_key=OPENAI_API_KEY)
+            llm = ChatOpenAI(temperature=0.0, model_name=MODEL_NAME)
 
             st.session_state.logger.info("create llm object")
 

src/gene_question_2chain_ver.py

@@ -20,10 +20,10 @@
 from streamlit_extras.switch_page_button import switch_page
 from util import local_css, read_prompt_from_txt
 
-from config import OPENAI_API_KEY, MODEL_NAME
+from config import MODEL_NAME, PATH
 
 DATA_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), "data")
-st.session_state["FAV_IMAGE_PATH"] = os.path.join(DATA_DIR, "images/favicon.png")
+st.session_state["FAV_IMAGE_PATH"] = os.path.join(DATA_DIR, "images", "favicon.png")
 st.set_page_config(
     page_title="Hello Jobits",  # 브라우저탭에 뜰 제목
     page_icon=Image.open(
@@ -36,14 +36,12 @@
 st.session_state.logger.info("start")
 NEXT_PAGE = "show_questions_hint"
 
-MY_PATH = os.path.dirname(os.path.dirname(__file__))
-
 #### style css ####
 MAIN_IMG = st.session_state.MAIN_IMG
 LOGO_IMG = st.session_state.LOGO_IMG
 
-local_css(MY_PATH + "/css/background.css")
-local_css(MY_PATH + "/css/2_generate_question.css")
+local_css(PATH + "/css/background.css")
+local_css(PATH + "/css/2_generate_question.css")
 st.markdown(f"""
             <style>
                 /* 로딩이미지 */
@@ -181,7 +179,7 @@
             ### JD 사용하여 JD 추출용 프롬프트 만들기
             st.session_state.logger.info("prompt JD start")
 
-            prompt_template = read_prompt_from_txt(MY_PATH + "/data/test/prompt_JD_template.txt")
+            prompt_template = read_prompt_from_txt(PATH + "data", "test", "prompt_JD_template.txt")
 
             prompt_JD = create_prompt_with_jd(prompt_template)
             # prompt_JD 생성완료
@@ -211,7 +209,7 @@
 
             st.session_state.logger.info("prompt QA start")
 
-            prompt_template = read_prompt_from_txt(MY_PATH + "/data/test/prompt_qa_template")
+            prompt_template = read_prompt_from_txt(PATH + "/data/test/prompt_qa_template")
 
             st.session_state.logger.info("create prompt QA template")
 
@@ -225,7 +223,7 @@
 
             ### 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)
 
             chain_type_kwargs = {"prompt": prompt_qa}
 

src/semantic_search.py

@@ -15,7 +15,7 @@ def faiss_inference(query):
     output으로는 (4 * 키워드 줄 개수 - 중복된 문장)개의 질문이 반환됩니다
     '''
     embeddings = HuggingFaceEmbeddings(
-            model_name = "BM-K/KoSimCSE-roberta-multitask",
+            model_name = "jhgan/ko-sroberta-multitask",
             model_kwargs = {'device': 'cuda'}
         )
     store_name="./FAISS_INDEX_TAG"

src/util.py

@@ -201,9 +201,6 @@ def save_uploaded_jd_as_filepath(uploaded_jd, save_directory, filename="uploaded
     return file_path
 
 
-os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
-
-
 @st.cache_resource
 def load_chain(question):
     """