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import streamlit as st
import os
from streamlit_chat import message
from langchain.prompts import PromptTemplate
from langchain import LLMChain
from langchain_community.llms.huggingface_hub import HuggingFaceHub
llm = HuggingFaceHub(repo_id="suriya7/MaxMini-Instruct-248M",
task ='text2text-generation',
huggingfacehub_api_token=os.getenv('HF_TOKEN'),
model_kwargs={
"do_sample":True,
"max_new_tokens":250
})
template = """
Please Answer the Question:
previous chat: {previous_history}
Human:{question}
chatbot:
"""
prompt = PromptTemplate(template=template,input_variables=['question','previous_history'])
llm_chain = LLMChain(
llm=llm,
prompt=prompt,
verbose=True,
)
previous_response = ""
def conversational_chat(user_query):
previous_response = "".join([f"Human: {i[0]}\nChatbot: {i[1]}" for i in st.session_state['history'] if i is not None])
result = llm_chain.predict(
question=user_query,
previous_history = previous_response
)
st.session_state['history'].append((user_query, result))
return result
st.title('MaxMini')
st.info("MaxMini-Instruct-248M is a T5 (Text-To-Text Transfer Transformer) model fine-tuned on a variety of tasks. This model is designed to perform a range of instructional tasks, enabling users to generate instructions for various inputs.")
st.session_state['history'] = []
if 'message' not in st.session_state:
st.session_state['message'] = ['Hey There! How Can I Assist You']
st.session_state['past'] = []
# Create containers for chat history and user input
response_container = st.container()
container = st.container()
# User input form
user_input = st.chat_input("Ask Your Questions 👉..")
with container:
if user_input:
output = conversational_chat(user_input)
# answer = response_generator(output)
st.session_state['past'].append(user_input)
st.session_state['message'].append(output)
# Display chat history
if st.session_state['message']:
with response_container:
for i in range(len(st.session_state['message'])):
if i != 0:
message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="adventurer")
message(st.session_state["message"][i], key=str(i), avatar_style="bottts") |