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qachat.py

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+from dotenv import load_dotenv
+load_dotenv()
+
+import streamlit as st
+import os
+import google.generativeai as genai
+
+genai.configure(api_key = os.getenv('GOOGLE_API_KEY'))
+
+# Function to load Gemini Pro model and get response
+model = genai.GenerativeModel('gemini-pro')
+
+chat = model.start_chat(history=[])
+
+def get_gemini_response(question):
+    response = chat.send_message(question,stream=True)
+    return response
+
+
+## initialize our streamlit app
+
+st.set_page_config(page_title='Q&A Demo')
+
+st.header('Gemini LLM Application')
+
+## initialize session state for chat history if does't excit
+if 'chat_history' not in st.session_state:
+    st.session_state['chat_history'] = []
+
+input = st.text_input('Input: ',key='input')
+
+submit = st.button("Ask the question")
+
+if submit and input :
+    response = get_gemini_response(input)
+    # add user query and respinse to session chat history
+    st.session_state['chat_history'].append(('you',input))
+    st.subheader('the response is ')
+    for chunk in response :
+        st.write(chunk.text)
+        st.session_state['chat_history'].append(('Bot',chunk.text))
+
+st.subheader('the chat history is ')
+
+for role,text in st.session_state['chat_history']:
+    st.write(f"{role}:{text}")

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv