talktosayno

Runtime error

App Files Files Community

talktosayno / app.py

Ridealist

refactor: Add Comments for explainig codes and adjust linting

6a11f08 12 months ago

raw history blame contribute delete

No virus

4.53 kB

	import gradio as gr
	import openai
	import os

	from langchain.chat_models import ChatOpenAI
	from langchain.document_loaders import PyPDFLoader
	from langchain.embeddings.openai import OpenAIEmbeddings
	from langchain.text_splitter import CharacterTextSplitter
	from langchain.vectorstores import Chroma
	from dotenv import load_dotenv

	from langchain.embeddings.cohere import CohereEmbeddings
	from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch
	from PyPDF2 import PdfWriter

	load_dotenv()
	os.environ["OPENAI_API_KEY"] = os.getenv('my_secret')
	openai.api_key = os.getenv('my_secret')

	## Load PDF file
	loader = PyPDFLoader("docs.pdf")
	documents = loader.load()

	## Split Document
	text_splitter = CharacterTextSplitter(chunk_size=800, chunk_overlap=0)
	texts = text_splitter.split_documents(documents)

	## token -> Vector Embedding
	embeddings = OpenAIEmbeddings()
	vector_store = Chroma.from_documents(texts, embeddings)
	retriever = vector_store.as_retriever(search_kwargs={"k": 2})

	from langchain.chat_models import ChatOpenAI
	from langchain.chains import RetrievalQAWithSourcesChain
	from langchain.prompts.chat import (
	ChatPromptTemplate,
	SystemMessagePromptTemplate,
	HumanMessagePromptTemplate,
	)

	## Build LLM Chain
	llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0) # Modify model_name if you have access to GPT-4

	chain = RetrievalQAWithSourcesChain.from_chain_type(
	llm=llm,
	chain_type="stuff",
	retriever = retriever,
	return_source_documents=True)

	system_template="""Use the following pieces of context to answer the users question shortly.
	Given the following summaries of a long document and a question, create a final answer with references ("SOURCES"), use "SOURCES" in capital letters regardless of the number of sources.
	If you don't know the answer, just say that "I don't know", don't try to make up an answer.
	----------------
	{summaries}

	You MUST answer in Korean and in Markdown format:"""

	messages = [
	SystemMessagePromptTemplate.from_template(system_template),
	HumanMessagePromptTemplate.from_template("{question}")
	]

	prompt = ChatPromptTemplate.from_messages(messages)

	############################
	## Local 에서 잘 되는지 확인
	chain_type_kwargs = {"prompt": prompt}

	llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0) # Modify model_name if you have access to GPT-4

	chain = RetrievalQAWithSourcesChain.from_chain_type(
	llm=llm,
	chain_type="stuff",
	retriever = retriever,
	return_source_documents=True,
	chain_type_kwargs=chain_type_kwargs
	)

	query = "행복한 인생이란?"
	result = chain(query)


	for doc in result['source_documents']:
	print('내용 : ' + doc.page_content[0:100].replace('\n', ' '))
	print('파일 : ' + doc.metadata['source'])
	print('페이지 : ' + str(doc.metadata['page']))
	##############################

	## Define response method
	def respond(message, chat_history): # 채팅봇의 응답을 처리하는 함수를 정의합니다.

	result = chain(message)
	bot_message = result['answer']

	for i, doc in enumerate(result['source_documents']):
	bot_message += '[' + str(i+1) + '] ' + doc.metadata['source'] + '(' + str(doc.metadata['page']) + ') '
	chat_history.append((message, bot_message)) # 채팅 기록에 사용자의 메시지와 봇의 응답을 추가합니다.

	return "", chat_history # 수정된 채팅 기록을 반환합니다.

	## Build Gradio App
	with gr.Blocks(theme='gstaff/sketch') as demo: # gr.Blocks()를 사용하여 인터페이스를 생성합니다.
	gr.Markdown("# 안녕하세요. 세이노와 대화해보세요.")
	chatbot = gr.Chatbot(label="채팅창") # '채팅창'이라는 레이블을 가진 채팅봇 컴포넌트를 생성합니다.
	msg = gr.Textbox(label="입력") # '입력'이라는 레이블을 가진 텍스트박스를 생성합니다.
	clear = gr.Button("초기화") # '초기화'라는 레이블을 가진 버튼을 생성합니다.

	msg.submit(respond, [msg, chatbot], [msg, chatbot]) # 텍스트박스에 메시지를 입력하고 제출하면 respond 함수가 호출되도록 합니다.
	clear.click(lambda: None, None, chatbot, queue=False) # '초기화' 버튼을 클릭하면 채팅 기록을 초기화합니다.
	demo.launch(debug=True) # 인터페이스를 실행합니다. 실행하면 사용자는 '입력' 텍스트박스에 메시지를 작성하고 제출할 수 있으며, '초기화' 버튼을 통해 채팅 기록을 초기화 할 수 있습니다.