app.py

from langchain.llms import HuggingFaceHub
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
import os
import gradio as gr

model_id = "distilgpt2"
HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
hf = HuggingFaceHub( 
                     repo_id=model_id,
                     huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
                     model_kwargs={"temperature":0.7,"max_new_tokens":50})



# hf = HuggingFacePipeline.from_model_id(
#     model_id=model_id,
#     task="text-generation",
#     huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
#     pipeline_kwargs={"max_new_tokens": 100}
# )

from langchain.memory import ConversationBufferWindowMemory



template = """
You are Abi, a useful AI assistant and answer for user questions.
{chat_history}
Question: {question}
Answer:
"""
# prompt = PromptTemplate.from_template(template)
promt = PromptTemplate(template = template, input_variables=['chat_history','question'])

memory = ConversationBufferMemory(memory_key="chat_history")
history =[]

llm_chain = LLMChain(llm=hf, prompt=promt, memory= memory,verbose = False)

def ask_bot(query,hist = history):
    result = llm_chain({"question": query, "chat_history": history})
    history.append((query,result))
    return result['text']
    
demo = gr.ChatInterface(ask_bot,
                        examples=['How are you doing?','What can you do?','Tell me a story','Tell me a joke','Who is prime minister of India?'],
                        title="Abi - An AI Assistant",
                        description="This is an AI Chatbot Assistant that uses Falcon 7b-instruct LLM to generate the output for the user queries.\n You can further know more from my GitHub Repo👉 https://github.com/abishekbabuofficial/AI-Assistant-Chatbot.\n♥️♥️♥️Application developed by Abishek B♥️♥️♥️")

demo.launch(debug=True)