vamsigutta

from sentence_transformers import SentenceTransformer, util
import torch

if __name__ == "__main__":
  questions = ["hi", "What is the product", "what is the cost of the product"]
  answers = ["Hi there, How can I help you", "The product is an QA chatbot", "The product is available for free"]
  
  ## Load the pretrained model
  model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
  model.max_seq_length = 512

vamsigutta

from langchain.document_loaders import DirectoryLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import HuggingFaceInstructEmbeddings
from langchain.vectorstores import FAISS
from transformers import T5Tokenizer, T5ForConditionalGeneration
import speech_recognition as sr
import sys

def get_context_faiss(query):
    search_results = db.similarity_search(query)