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from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.llms import HuggingFaceEndpoint
import streamlit as st
# prepare Falcon Huggingface API
llm = HuggingFaceEndpoint(
endpoint_url= f"https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta",
huggingfacehub_api_token='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',
task="text-generation",
model_kwargs = {
"min_length": 8192,
"max_length":8192,
"temperature":0.1,
"max_new_tokens":4000,
"num_return_sequences":1
}
)
topics_template = PromptTemplate(
input_variables = ['keyword'],
template = """
I want you to Write a comprehensive article about "{keyword}" covering the following aspects:
Introduction: Provide an engaging introduction to the topic, highlighting its relevance and significance.
History and Background: Explain the historical context and background of {keyword}.
Key Concepts and Terminology: Define important terms and concepts related to {keyword}.
Current State of {keyword}: Discuss the current trends, developments, and challenges in the field of {keyword}.
Use Cases and Applications: Explore practical applications and use cases of {keyword} in various industries.
Benefits and Drawbacks: Highlight the advantages and disadvantages of {keyword}.
Future Outlook: Predict the future trends and potential advancements in {keyword}.
Conclusion: Summarize the key points and reiterate the importance of {keyword}.
Ensure that the article is well-structured, informative, and at least 1500 words long. Use SEO best practices for content optimization.
""")
st.title("Blog Writer")
keyword = st.text_input("Input the keyword you wish to write about")
topic_writing_chain = LLMChain(llm= llm, prompt=topics_template, verbose = True)
with st.spinner('Wait for it...'):
if keyword:
topics = topic_writing_chain(keyword)
st.write(topics)
st.success('') |