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from flask import Flask, request, jsonify | |
from langchain_community.document_loaders import TextLoader | |
from langchain.text_splitter import CharacterTextSplitter | |
from langchain_community.embeddings import HuggingFaceEmbeddings | |
from langchain_community.vectorstores import FAISS | |
from langchain.chains.question_answering import load_qa_chain | |
from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint | |
# To comment in production usage | |
# import Constants | |
import os | |
key = "hf_" + "TFQcwtpWpItqrR" +"kKazmgBASKDIsTnGDeqM" | |
os.environ["HUGGINGFACEHUB_API_TOKEN"] = key | |
app = Flask(__name__) | |
# try: | |
loader = TextLoader("./data/app.txt") | |
document = loader.load() | |
# Split the document into chunks | |
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | |
docs = text_splitter.split_documents(document) | |
# Create embeddings | |
embedding = HuggingFaceEmbeddings(model_name = "sentence-transformers/all-mpnet-base-v2") | |
db = FAISS.from_documents(docs, embedding) | |
# Load the Question-Answering chain | |
llm = HuggingFaceEndpoint(repo_id="google/flan-t5-xxl", temperature=0.8, model_kwargs={"max_length": 512}) | |
chain = load_qa_chain(llm, chain_type="stuff") | |
# except Exception as e: | |
# print("Recived Setup error: ", e) | |
def process_query(query): | |
# os.system("cls") | |
# try: | |
querySimilarDocs = db.similarity_search(query) | |
res = chain.run(input_documents = querySimilarDocs, question = query) | |
return res | |
# except Exception as e: | |
# print("Received process error: ", e) | |
# # return "An Error occurred!!" | |
# return e | |
def process_request(): | |
# Debugging... | |
for name, value in os.environ.items(): | |
print("{0}: {1}".format(name, value)) | |
# try: | |
data = request.get_json() | |
user_input = data['query'] | |
response = process_query(user_input) | |
return jsonify({"response": response}) | |
# except Exception as e: | |
# print("Received Process request error: ", e) | |
# return jsonify({"response": str(e)}) | |
## Development phase use case only | |
# if __name__ == '__main__': | |
# app.run(debug=True) | |