Spaces:
Sleeping
Sleeping
File size: 2,420 Bytes
0b8d329 26bd2c9 0b8d329 26bd2c9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
from flask import Flask, request, jsonify
from dotenv import load_dotenv
from PyPDF2 import PdfReader
from langchain.text_splitter import CharacterTextSplitter
from langchain.embeddings import OpenAIEmbeddings
from langchain.vectorstores import FAISS
from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationBufferMemory
from langchain.chains import ConversationalRetrievalChain
import os
app = Flask(__name__)
load_dotenv()
OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
def get_pdf_text(pdf_docs):
text = ""
for pdf in pdf_docs:
pdf_reader = PdfReader(pdf)
for page in pdf_reader.pages:
text += page.extract_text()
return text
def get_text_chunks(text):
text_splitter = CharacterTextSplitter(
separator="\n",
chunk_size=1000,
chunk_overlap=200,
length_function=len
)
chunks = text_splitter.split_text(text)
return chunks
def get_vectorstore(text_chunks):
embeddings = OpenAIEmbeddings()
vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
return vectorstore
def get_conversation_chain(vectorstore):
llm = ChatOpenAI()
memory = ConversationBufferMemory(
memory_key='chat_history', return_messages=True)
conversation_chain = ConversationalRetrievalChain.from_llm(
llm=llm,
retriever=vectorstore.as_retriever(),
memory=memory
)
return conversation_chain
@app.route('/upload', methods=['POST'])
def upload_files():
if 'files' not in request.files:
return jsonify({"error": "No file part in the request"}), 400
files = request.files.getlist('files')
raw_text = get_pdf_text(files)
text_chunks = get_text_chunks(raw_text)
vectorstore = get_vectorstore(text_chunks)
global conversation_chain
conversation_chain = get_conversation_chain(vectorstore)
return jsonify({"status": "Files processed successfully"}), 200
@app.route('/query', methods=['POST'])
def query():
if 'question' not in request.json:
return jsonify({"error": "No question provided"}), 400
question = request.json['question']
if 'conversation_chain' not in globals():
return jsonify({"error": "No conversation chain initialized. Please upload documents first."}), 400
response = conversation_chain({'question': question})
return jsonify({"response": response['answer']})
|