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.env

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+GOOGLE_API_KEY = "AIzaSyDUgfjwgH9lMEfxe_dQQMN-MH4syGlmifM"

app.py

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+from dotenv import load_dotenv
+
+load_dotenv()  # take environment variables from .env.
+
+import streamlit as st
+import os
+import pathlib
+import textwrap
+
+import google.generativeai as genai
+
+from IPython.display import display
+from IPython.display import Markdown
+
+
+def to_markdown(text):
+    text = text.replace('•', '  *')
+    return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))
+
+
+os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+
+## Function to load OpenAI model and get respones
+
+def get_gemini_response(question):
+    model = genai.GenerativeModel('gemini-pro')
+    response = model.generate_content(question)
+    return response.text
+
+
+##initialize our streamlit app
+
+st.set_page_config(page_title="Q&A Demo")
+
+st.header("Sujatha Pro")
+
+input = st.text_input("Input: ", key="input")
+
+submit = st.button("Ask the question")
+
+## If ask button is clicked
+
+if submit:
+    response = get_gemini_response(input)
+    st.subheader("The Response is")
+    st.write(response)

chat.py

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+from dotenv import load_dotenv
+
+load_dotenv()  # take environment variables from .env.
+
+import streamlit as st
+import os
+import pathlib
+import textwrap
+
+import google.generativeai as genai
+
+from IPython.display import display
+from IPython.display import Markdown
+
+os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+## Function to load OpenAI model and get respones
+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 Application")
+
+input = st.text_input("Input: ", key="input")
+
+submit = st.button("Ask the question")
+
+## If ask button is clicked
+
+if submit:
+
+    response = get_gemini_response(input)
+    st.subheader("The Response is")
+    for chunk in response:
+        print(st.write(chunk.text))
+        print("_" * 80)
+
+    st.write(chat.history)

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv

vision.py

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+from dotenv import load_dotenv
+
+load_dotenv()  # take environment variables from .env.
+
+import streamlit as st
+import os
+import pathlib
+import textwrap
+from PIL import Image
+
+import google.generativeai as genai
+
+os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+
+## Function to load OpenAI model and get respones
+
+def get_gemini_response(input, image):
+    model = genai.GenerativeModel('gemini-pro-vision')
+    if input != "":
+        response = model.generate_content([input, image])
+    else:
+        response = model.generate_content(image)
+    return response.text
+
+
+##initialize our streamlit app
+
+st.set_page_config(page_title="Gemini Image Demo")
+
+st.header("Gemini Application")
+input = st.text_input("Input Prompt: ", key="input")
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+image = ""
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image.", use_column_width=True)
+
+submit = st.button("Tell me about the image")
+
+## If ask button is clicked
+
+if submit:
+    response = get_gemini_response(input, image)
+    st.subheader("The Response is")
+    st.write(response)