import streamlit as st
from PIL import Image
from google import genai
import json
from io import BytesIO
def edit_image_with_ai(image, description):
with open('app_config.json') as config_file:
config = json.load(config_file)
api_key = config["nano-banana"]["api_key"]
client = genai.Client(api_key=api_key)
prompt = description
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview",
contents=[prompt, image],
)
text_response = None
image_response = None
for part in response.candidates[0].content.parts:
if part.text is not None:
text_response = part.text
if part.inline_data is not None:
image_response = Image.open(BytesIO(part.inline_data.data))
return text_response, image_response
def ai_image_editor():
st.markdown("
AI Image Editor🖼️
", unsafe_allow_html=True)
st.markdown(" Edit and enhance your images with the power of AI! 🎨 ", unsafe_allow_html=True)
st.info("Powered by the online [Gemini Image Generation](https://ai.google.dev/gemini-api/docs/image-generation) API!")
# user upload an image and provide a description of the edit they want
uploaded_image = st.file_uploader("Upload an image to edit", type=["png", "jpg", "jpeg"])
if uploaded_image is not None:
with st.spinner("Loading image..."):
# display the uploaded image
image = Image.open(uploaded_image)
st.image(image, width= 300)
st.success("Image uploaded successfully!")
edit_description = st.text_area("Describe the edits you want to make to the image")
if st.button("AI Editing"):
if edit_description.strip() == "":
st.error("Please provide a description of the edits you want to make.")
else:
with st.spinner("Editing image..."):
# Call the AI image editing function (to be implemented)
text_response, image_response = edit_image_with_ai(image, edit_description)
if text_response:
st.info(text_response)
if image_response:
st.image(image_response, width=300)