Spaces:
Running
Running
File size: 2,491 Bytes
c701e36 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
import streamlit as st
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain_community.llms import HuggingFaceHub
from huggingface_hub import login
from dotenv import load_dotenv
import os
load_dotenv()
# Authenticate with Hugging Face Hub
hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
login(hf_token)
# Initialize LLM using HuggingFaceHub
llm = HuggingFaceHub(
repo_id="caffsean/t5-base-finetuned-keyword-to-text-generation",
model_kwargs={
"temperature": 0.7, # Adjust for creativity
"max_length": 512, # Adjust for desired output length
}
)
# Define a function to generate responses
def get_blog_response(keywords: str, no_words: str, blog_style: str) -> str:
# Define a prompt template
template = "Generate a blog for {blog_style} job profile based on the keywords '{keywords}' within {no_words} words."
prompt = PromptTemplate(
input_variables=["keywords", "no_words", "blog_style"],
template=template
)
# Use LangChain LLMChain for structured interaction
chain = LLMChain(llm=llm, prompt=prompt)
response = chain.run(keywords=keywords, no_words=no_words, blog_style=blog_style)
return response
# Streamlit UI
st.set_page_config(
page_title="Blog Generation Using LangChain and Hugging Face",
layout="centered",
initial_sidebar_state="collapsed"
)
st.header("Blog Generation App :earth_americas:")
st.write("This app uses LangChain and a fine-tuned T5 model for generating blogs. Please provide your inputs below:")
# Input fields
keywords = st.text_input("Enter the Blog Keywords")
col1, col2 = st.columns([5, 5])
with col1:
no_words = st.text_input("Number of Words")
with col2:
blog_style = st.selectbox(
"Writing the blog for",
["Researchers", "Engineers", "Doctors", "Content Creators", "Sportsman", "Businessman", "Common People"],
index=0
)
submit = st.button("Generate Blog")
# Generate response
if submit:
if keywords and no_words.isdigit() and int(no_words) > 0:
try:
st.write("Generating blog...")
response = get_blog_response(keywords, no_words, blog_style)
st.markdown(f"### Generated Blog:\n\n{response}")
except Exception as e:
st.error(f"An error occurred: {e}")
else:
st.warning("Please provide valid inputs for all fields.")
|