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from dotenv import load_dotenv
import streamlit as st
import os
import google.generativeai as genai
from PIL import Image
load_dotenv()
GOOGLE_API_KEY = os.getenv("GOOGLE_API")
genai.configure(api_key=GOOGLE_API_KEY)
model = genai.GenerativeModel('gemini-pro')
model_vision = genai.GenerativeModel('gemini-pro-vision')
def gemini_response(question):
try:
response1 = model.generate_content(question)
return response1.text
except Exception as e:
raise e
def gemini_response_vision(input_texts, image):
try:
if input_texts != "":
response2 = model_vision.generate_content([input_texts, image])
else:
response2 = model_vision.generate_content(image)
return response2.text
except Exception as e:
raise e
# streamlit_analytics.start_tracking()
tab1, tab2 = st.tabs(["TAB_1:Gemini LLM App Q & A:sunglasses:", "TAB_2:Gemini-Pro-Vision Image To Text:rocket:"])
with tab1:
st.title('Generative Question And Answer :blue[Gemini LLM App] :sunglasses:')
input_1 = st.text_input("Ask Question:")
submit1 = st.button("Generate Response")
if submit1:
if input_1 is not None:
st.write('Your Query Response')
response = gemini_response(input_1)
st.write(response)
else:
st.write("Enter The Text")
with tab2:
st.title('Generative Image Description :blue[Gemini-Pro-Vision LLM App] :sunglasses:')
uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
input_2 = st.text_input("Text for Image: Ask question related to uploaded image")
if uploaded_image is not None:
img = Image.open(uploaded_image)
st.image(img, caption="upload images", use_column_width=True)
submit2 = st.button("Generate Text from Image ")
if submit2:
st.subheader("Response:")
res = gemini_response_vision(input_texts=input_2, image=img)
st.write(res)
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