Update app.py

app.py

@@ -1,16 +1,31 @@
 import gradio as gr
 import os
-from langchain_community.chat_models import ChatOpenAI
+
 from langchain_community.document_loaders import TextLoader
+from langchain_openai import ChatOpenAI
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import FAISS
+from langchain.chains import RetrievalQA
+from langchain.chains import ConversationalRetrievalChain
 
 OpenAIModel = "gpt-3.5-turbo"
 OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]
 llm = ChatOpenAI(model=OpenAIModel, temperature=0.1, openai_api_key=OPENAI_API_KEY)
 
-def greet(name):
-    return "Hello " + name + "!!"
+def ask(text):
+  answer = qa.run(text)
+  return answer
     
 loader = TextLoader("test.txt")
 data = loader.load()
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+
+embeddings = OpenAIEmbeddings(openai_api_key=OPENAI_API_KEY)
+
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=50)
+all_splits = text_splitter.split_documents(data)
+db2 = FAISS.from_documents(all_splits, embeddings)
+
+qa = RetrievalQA.from_chain_type(llm=llm, retriever=db2.as_retriever())
+
+iface = gr.Interface(ask,gr.Textbox(label="Question"),gr.Textbox(label="Answer"), title="BiMah Customer Service Chatbot",description="A chatbot that can answer things related to BiMah (Bimbel Mahasiswa)", examples=["How BiMah can enforce students to be better?","Siapa CEO BiMah?", "Bagaimana langkah-langkah pendaftaran di BiMah?"])
 iface.launch()