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| from transformers import pipeline | |
| import streamlit as st | |
| # Load the text generation pipeline | |
| pipe = pipeline("text-generation", model="meta-llama/Meta-Llama-3-8B") | |
| def generate_blog(topic, no_words): | |
| # Create the prompt | |
| prompt = f"Write a blog on the topic '{topic}' within {no_words} words." | |
| # Generate the blog content | |
| result = pipe(prompt, max_length=int(no_words), num_return_sequences=1) | |
| # Extract the generated text | |
| blog_content = result[0]['generated_text'] | |
| return blog_content | |
| # Streamlit app | |
| st.set_page_config(page_title="Blog Generator", page_icon="📝") | |
| st.title("Blog Content Generator 📝") | |
| # Input fields | |
| topic = st.text_input("Enter the Blog Topic") | |
| no_words = st.number_input("Enter the Number of Words", min_value=50, max_value=1000, value=200, step=50) | |
| if st.button("Generate Blog"): | |
| if topic and no_words: | |
| with st.spinner("Generating blog content..."): | |
| blog_content = generate_blog(topic, no_words) | |
| st.subheader("Generated Blog Content") | |
| st.write(blog_content) | |
| else: | |
| st.error("Please provide both the blog topic and the number of words.") | |
| import streamlit as st | |
| from langchain.prompts import PromptTemplate | |
| from langchain_community.llms import CTransformers | |
| ## Function To get response from LLaMA 2 model | |
| def getLLamaresponse(input_text, no_words, blog_style): | |
| ### LLaMA 2 model | |
| llm = CTransformers( | |
| model='llama-2-7b-chat.ggmlv3.q8_0.bin', | |
| model_type='llama', | |
| config={'max_new_tokens': 256, 'temperature': 0.01} | |
| ) | |
| ## Prompt Template | |
| template = """ | |
| Write a blog for {blog_style} job profile for a topic {input_text} | |
| within {no_words} words. | |
| """ | |
| prompt = PromptTemplate( | |
| input_variables=["blog_style", "input_text", "no_words"], | |
| template=template | |
| ) | |
| ## Generate the response from the LLaMA 2 model | |
| response = llm.invoke(prompt.format(blog_style=blog_style, input_text=input_text, no_words=no_words)) | |
| return response | |
| def main(): | |
| st.set_page_config( | |
| page_title="Generate Blogs", | |
| page_icon='🤖', | |
| layout='centered', | |
| initial_sidebar_state='collapsed' | |
| ) | |
| st.header("Generate Blogs 🤖") | |
| input_text = st.text_input("Enter the Blog Topic") | |
| ## Creating two more columns for additional fields | |
| 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', 'Data Scientist', 'Common People'), index=0) | |
| submit = st.button("Generate") | |
| ## Final response | |
| if submit: | |
| if not input_text or not no_words: | |
| st.error("Please enter both the blog topic and the number of words.") | |
| else: | |
| try: | |
| response = getLLamaresponse(input_text, no_words, blog_style) | |
| st.write(response) | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |
| if __name__ == "__main__": | |
| main() | |