commit2

README.md

@@ -1,5 +1,5 @@
 ---
-title: Basic DAG AI Chatbot With ChatGPT
+title: 9thMLchatGPT
 emoji: 📚
 colorFrom: purple
 colorTo: purple

app.py

@@ -28,17 +28,37 @@ def get_pdf_text(pdf_docs):
 # 과제
 # 아래 텍스트 추출 함수를 작성
 
-def get_text_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(get_text_chunks(text_docs).getvalue())
+    text_loader = TextLoader(temp_filepath)
+    text_doc = text_loader.load()
+    return text_doc
 
-def get_csv_file(docs):
-    pass
 
-def get_json_file(docs):
-    pass
+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(temp_filepath, jq_schema='.messages[].content', text_content=False)
+    json_doc = json_loader.load()
+    return json_doc
+
 
-    
 # 문서들을 처리하여 텍스트 청크로 나누는 함수입니다.
 def get_text_chunks(documents):
     text_splitter = RecursiveCharacterTextSplitter(
@@ -76,6 +96,7 @@ def get_conversation_chain(vectorstore):
     )
     return conversation_chain
 
+
 # 사용자 입력을 처리하는 함수입니다.
 def handle_userinput(user_question):
     # 대화 체인을 사용하여 사용자 질문에 대한 응답을 생성합니다.