Create app.py

app.py

@@ -0,0 +1,52 @@
+import google.generativeai as genai
+import streamlit as st
+from dotenv import load_dotenv
+import os
+
+
+@st.cache_resource
+def get_llm():
+    load_dotenv()
+    api_key = os.environ.get('API_KEY')
+    genai.configure(api_key=api_key)
+    model = genai.GenerativeModel(
+        'gemini-pro', generation_config={"temperature": temperature})
+    return model
+
+
+st.title("Medium.com Blog Generator 🧑🏻‍💻!!!")
+
+
+def get_genai_response(prompt, question):
+    response = model.generate_content([prompt, question])
+    # print(response.text)
+    return response.text
+
+
+prompt = """
+      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"""
+
+
+topic = st.text_input("Topic")
+
+creativity_arr = ["High Accuracy",
+                  "Balanced Accuracy & Creativity", "High Creativity "]
+creativity = st.selectbox("Choose creativity level:", creativity_arr)
+
+if creativity == "High Accuracy":
+    temperature = 0.1
+elif creativity == "Balanced Accuracy & Creativity":
+    temperature = 0.5
+else:
+    temperature = 0.8
+
+submit_button = st.button("Submit")
+
+model = get_llm()
+
+if submit_button:
+    st.header("Response")
+    with st.spinner(text="Fetching response from LLM..."):
+        text = get_genai_response(
+            prompt, topic)
+    st.write(text)