refactor: get function

app.py

@@ -28,17 +28,39 @@ def get_pdf_text(pdf_docs):
 # 과제
 # 아래 텍스트 추출 함수를 작성
 
-def get_text_file(docs):
-    pass
-
-
-def get_csv_file(docs):
-    pass
+def get_text_file(text_docs):
+    temp_dir = tempfile.TemporaryDirectory()
+    temp_filepath = os.path.join(temp_dir.name, text_docs.name)
+    with open(temp_filepath, "wb") as f:
+        f.write(text_docs.getvalue())
+    text_loader = TextLoader(temp_filepath)
+    text_doc = text_loader.load()
+    return text_doc
+
+
+def get_csv_file(csv_docs):
+    temp_dir = tempfile.TemporaryDirectory()
+    temp_filepath = os.path.join(temp_dir.name, csv_docs.name)
+    with open(temp_filepath, "wb") as f:
+        f.write(csv_docs.getvalue())
+    csv_loader = CSVLoader(temp_filepath)
+    csv_doc = csv_loader.load()
+    return csv_doc
+
+def get_json_file(json_docs):
+    temp_dir = tempfile.TemporaryDirectory()
+    temp_filepath = os.path.join(temp_dir.name, json_docs.name)
+    with open(temp_filepath, "wb") as f:
+        f.write(json_docs.getvalue())
+    json_loader = JSONLoader(
+        file_path=temp_filepath,
+        jq_schema='.messages[].content',
+        text_content=False
+    )
+    json_doc = json_loader.load()
+    return json_doc
 
-def get_json_file(docs):
-    pass
 
-    
 # 문서들을 처리하여 텍스트 청크로 나누는 함수입니다.
 def get_text_chunks(documents):
     text_splitter = RecursiveCharacterTextSplitter(
@@ -64,7 +86,7 @@ def get_vectorstore(text_chunks):
 def get_conversation_chain(vectorstore):
     gpt_model_name = 'gpt-3.5-turbo'
     llm = ChatOpenAI(model_name = gpt_model_name) #gpt-3.5 모델 로드
-    
+
     # 대화 기록을 저장하기 위한 메모리를 생성합니다.
     memory = ConversationBufferMemory(
         memory_key='chat_history', return_messages=True)