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Create app.py
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app.py
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import google.generativeai as genai
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import streamlit as st
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from dotenv import load_dotenv
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import os
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@st.cache_resource
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def get_llm():
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load_dotenv()
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api_key = os.environ.get('API_KEY')
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genai.configure(api_key=api_key)
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model = genai.GenerativeModel(
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'gemini-pro', generation_config={"temperature": temperature})
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return model
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st.title("Medium.com Blog Generator π§π»βπ»!!!")
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def get_genai_response(prompt, question):
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response = model.generate_content([prompt, question])
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# print(response.text)
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return response.text
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prompt = """
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Imagine you're a friendly expert at a local library. Tailor your explanation to a general audience who might have some curiosity about the topic but no prior in-depth knowledge. Make the information engaging and informative, and keep in mind the best practices for writing on Medium.com"""
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topic = st.text_input("Topic")
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creativity_arr = ["High Accuracy",
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"Balanced Accuracy & Creativity", "High Creativity "]
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creativity = st.selectbox("Choose creativity level:", creativity_arr)
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if creativity == "High Accuracy":
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temperature = 0.1
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elif creativity == "Balanced Accuracy & Creativity":
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temperature = 0.5
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else:
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temperature = 0.8
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submit_button = st.button("Submit")
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model = get_llm()
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if submit_button:
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st.header("Response")
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with st.spinner(text="Fetching response from LLM..."):
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text = get_genai_response(
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prompt, topic)
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st.write(text)
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