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Browse files- app.py +54 -0
- requirements.txt +4 -0
app.py
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from dotenv import load_dotenv
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load_dotenv()
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import streamlit as st
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import os
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import google.generativeai as genai
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain.prompts import PromptTemplate
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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model = ChatGoogleGenerativeAI(model="gemini-pro")
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def gemini_model(input_text,no_of_words,blog_style):
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# here we are creating a template for the prompt
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template = """
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Write a blog on the topic of {input_text} for {blog_style} audience.
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The blog should be {no_of_words} words long.
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"""
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# here we are creating a prompt using the template and the input variables
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prompt = PromptTemplate(input_variables=["input_text","blog_style","no_of_words"],template=template)
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# here we are generating the blog
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response = model.invoke(prompt.format(input_text=input_text,blog_style=blog_style,no_of_words=no_of_words))
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print(response)
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return response.content
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st.set_page_config(page_title="Blog Generator", initial_sidebar_state="collapsed", layout="centered")
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# Header
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st.title("π Generate Blog")
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# Input Section
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input_text = st.text_input("π Enter the topic of the blog you want to generate")
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# Creating 2 columns for additional 2 fields
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col1, col2 = st.columns([2, 2])
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# Number of words input
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with col1:
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no_of_words = st.text_input("π Number of Words", value="500")
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# Blog style selection
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with col2:
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blog_style = st.selectbox("π Writing the blog for", ("Researchers or Professionals", "General Audience"), index=0)
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# Generate Button
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submit_button = st.button("Generate Blog π")
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# Display the generated blog on button click
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if submit_button:
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st.success("π **Generated Blog:**")
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generated_blog = gemini_model(input_text, no_of_words, blog_style)
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st.write(generated_blog)
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requirements.txt
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@@ -0,0 +1,4 @@
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google-generativeai
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streamlit
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python-dotenv
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langchain
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