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#this is one is using FALCON-7B
from langchain import HuggingFaceHub, LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.document_loaders.csv_loader import CSVLoader
from langchain.vectorstores import FAISS
import tempfile
from streamlit_chat import message
import streamlit as st
import os
import re
import sys
import pandas as pd
def extract_text_from_html(html):
cleanr = re.compile('<.*?>')
cleantext = re.sub(cleanr, '', html)
return cleantext.strip()
def conversational_chat(query):
output = llm_chain.predict(human_input=query)
return extract_text_from_html(output)
user_api_key = st.sidebar.text_input(
label="#### Your HuggingFace API key 👇",
placeholder="Paste your HuggingGace API key, sk-",
type="password")
if user_api_key is not None and user_api_key.strip() != "":
# huggingfacehub_api_token = os.environ[user_api_key]
#setting up the LLM
repo_id = "tiiuae/falcon-7b-instruct"
template = """
Your custon promp
{history}
Me:{human_input}
Jack:
"""
prompt = PromptTemplate(
input_variables=["history", "human_input"],
template=template
)
llm_chain = LLMChain(
llm=HuggingFaceHub(huggingfacehub_api_token=user_api_key, repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature": 0.2}),
prompt=prompt,
verbose=True,
memory=ConversationBufferWindowMemory(k=2)
)
if 'history' not in st.session_state:
st.session_state['history'] = []
if 'generated' not in st.session_state:
st.session_state['generated'] = ["Hello ! Ask me anything about " + " 🤗"]
if 'past' not in st.session_state:
st.session_state['past'] = ["Hey ! 👋"]
#container for the chat history
response_container = st.container()
#container for the user's text input
container = st.container()
with container:
with st.form(key='my_form', clear_on_submit=True):
user_input = st.text_input("Query:", placeholder="Lets talk about something General", key='input')
submit_button = st.form_submit_button(label='Send')
if submit_button and user_input:
output = conversational_chat(user_input)
st.session_state['past'].append(user_input)
st.session_state['generated'].append(output)
if st.session_state['generated']:
with response_container:
for i in range(len(st.session_state['generated'])):
message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")
else:
st.text("Please enter your HuggingFace API key above.")
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