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Create app.py
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app.py
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import json
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import os
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import time
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import uuid
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import tempfile
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from PIL import Image
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import gradio as gr
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import base64
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import mimetypes
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from google import genai
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from google.genai import types
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def save_binary_file(file_name, data):
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with open(file_name, "wb") as f:
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f.write(data)
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def generate(text, file_name, api_key, model="gemini-2.0-flash-exp"):
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# Initialize client using provided api_key (or fallback to env variable)
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client = genai.Client(api_key=(api_key.strip() if api_key and api_key.strip() != ""
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else os.environ.get("GEMINI_API_KEY")))
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files = [
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client.files.upload(file=file_name),
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]
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contents = [
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types.Content(
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role="user",
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parts=[
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types.Part.from_uri(
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file_uri=files[0].uri,
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mime_type=files[0].mime_type,
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),
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types.Part.from_text(text=text),
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],
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),
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]
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generate_content_config = types.GenerateContentConfig(
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temperature=1,
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top_p=0.95,
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top_k=40,
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max_output_tokens=8192,
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response_modalities=[
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"image",
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"text",
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],
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response_mime_type="text/plain",
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)
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
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temp_path = tmp.name
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for chunk in client.models.generate_content_stream(
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model=model,
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contents=contents,
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config=generate_content_config,
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):
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if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
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continue
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inline_data = chunk.candidates[0].content.parts[0].inline_data
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if inline_data:
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save_binary_file(temp_path, inline_data.data)
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print(
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"File of mime type "
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f"{inline_data.mime_type} saved to: {temp_path}"
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)
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else:
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print(chunk.text)
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del files
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return temp_path
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def process_image_and_prompt(composite_pil, prompt, gemini_api_key):
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# Save the composite image to a temporary file.
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
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composite_path = tmp.name
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composite_pil.save(composite_path)
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file_name = composite_path
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input_text = prompt
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model = "gemini-2.0-flash-exp"
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gemma_edited_image_path = generate(text=input_text, file_name=file_name, api_key=gemini_api_key, model=model)
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print("image_path ", gemma_edited_image_path)
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result_img = Image.open(gemma_edited_image_path)
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if result_img.mode == "RGBA":
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result_img = result_img.convert("RGB")
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return [result_img]
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# Build a Blocks-based interface to include the custom HTML header.
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with gr.Blocks() as demo:
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# HTML Header for the application.
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gr.HTML(
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"""
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<div style='display: flex; align-items: center; justify-content: center; gap: 20px'>
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<div style="background-color: var(--block-background-fill); border-radius: 8px">
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<img src="https://www.gstatic.com/lamda/images/gemini_favicon_f069958c85030456e93de685481c559f160ea06b.png" style="width: 100px; height: 100px;">
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</div>
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<div>
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<h1>Gen AI Image Editing</h1>
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<p>Gemini using for Image Editing</p>
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<p>Powered by <a href="https://gradio.app/">Gradio</a> ⚡️</p>
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<p>Get an API Key <a href="https://aistudio.google.com/apikey">here</a></p>
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<p>Follow me on Twitter: <a href="https://x.com/Ameerazam18">Ameerazam18</a></p>
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</div>
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</div>
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"""
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)
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# Title and description.
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# Define examples to be shown within the Gradio interface
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examples = [
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# Each example is a list corresponding to the inputs:
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# [Input Image, Prompt, Guidance Scale, Number of Steps, LoRA Name]
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["data/1.webp", 'change text to "AMEER"'],
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["data/2.webp", "remove the spoon from hand only"],
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["data/3.webp", 'change text to "Make it "'],
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["data/1.jpg", "add joker style only on face"],
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["data/1777043.jpg", "add joker style only on face"],
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["data/2807615.jpg","add lipstick on lip only "],
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["data/76860.jpg", "add lipstick on lip only "],
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["data/2807615.jpg", "make it happy looking face only"],
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]
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gr.Markdown("Upload an image and enter a prompt to generate outputs in the gallery. Do not Use NFSW Images")
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with gr.Row():
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with gr.Column():
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image_input = gr.Image(
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type="pil",
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label="Upload Image",
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image_mode="RGBA"
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)
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gemini_api_key = gr.Textbox(
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lines=1,
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placeholder="Enter Gemini API Key (optional)",
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label="Gemini API Key (optional) Generate and fill here"
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)
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prompt_input = gr.Textbox(
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lines=2,
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placeholder="Enter prompt here...",
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label="Prompt"
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)
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submit_btn = gr.Button("Generate")
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with gr.Column():
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output_gallery = gr.Gallery(label="Generated Outputs")
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# Set up the interaction.
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submit_btn.click(
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fn=process_image_and_prompt,
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inputs=[image_input, prompt_input, gemini_api_key],
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outputs=output_gallery,
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)
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gr.Examples(
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examples=examples,
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inputs=[image_input, prompt_input, gemini_api_key],
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label="Try these examples"
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)
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demo.launch(share=True)
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