Update app.py

app.py

@@ -0,0 +1,47 @@
+import streamlit as st
+from langchain.prompts import PromptTemplate
+from langchain_google_genai import ChatGoogleGenerativeAI
+import os, spaces
+
+os.environ['GOOGLE_API_KEY'] = os.getenv('geminiapi')
+
+# Function for LLM response
+def llm_response(user_text, number_of_words, blog_audience):
+    # define llm
+    llm = ChatGoogleGenerativeAI(model="gemini-pro")
+    # define prompt template
+    ptemplate = ''' 
+    You are an Expert Blog Writer. For the topic {user_text},
+    write a Blog in {number_of_words} words for an audience of {blog_audience}.
+    '''
+    prompt = PromptTemplate(template=ptemplate,input_variables=['user_text','number_of_words','blog_audience'])
+    final_prompt = prompt.format(user_text=user_text, number_of_words=number_of_words, blog_audience=blog_audience)
+    # invoke llm to get result
+    result = llm.invoke(final_prompt)
+    # print result on screen
+    st.write(result.content)
+
+# define page config
+st.set_page_config(
+    page_title="Blog Generation",
+    page_icon="🧊",
+    layout="centered",
+    initial_sidebar_state="collapsed",
+)
+
+st.header("Blog Generation App🧊")
+user_text = st.text_input("Enter title for blog")
+col1,col2 = st.columns([6,6])
+
+with col1:
+    number_of_words = st.text_input("Number of words in Blog")
+
+with col2:
+    blog_audience = st.selectbox("Select the audience for the Blog",
+                                  ['Data Scientist', 'Researcher', 'Common People'],
+                                  index=2)
+
+submit_btn = st.button("Submit")
+
+if submit_btn:
+    llm_response(user_text, number_of_words, blog_audience) # function call for printing results