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import json
import os
import time
import uuid
import tempfile
from PIL import Image
import gradio as gr
import base64
import mimetypes
import logging
from google import genai
from google.genai import types
# Configure logging
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def save_binary_file(file_name, data):
logger.debug(f"Saving binary data to file: {file_name}")
with open(file_name, "wb") as f:
f.write(data)
logger.debug(f"File saved successfully: {file_name}")
def generate(text, file_name, api_key, model="gemini-2.0-flash-exp-image-generation"):
logger.debug(f"Starting generate function with text: '{text}', file_name: '{file_name}', model: '{model}'")
try:
# Initialize client
effective_api_key = api_key.strip() if api_key and api_key.strip() != "" else os.environ.get("GEMINI_API_KEY")
logger.debug(f"Using API Key: {'Provided' if api_key.strip() else 'From Environment Variable'}")
if not effective_api_key:
logger.error("No API key provided or found in environment variable.")
raise ValueError("API key is required.")
client = genai.Client(api_key=effective_api_key)
logger.debug("Gemini client initialized.")
files = [
client.files.upload(file=file_name),
]
logger.debug(f"File uploaded. URI: {files[0].uri}, MIME Type: {files[0].mime_type}")
contents = [
types.Content(
role="user",
parts=[
types.Part.from_uri(
file_uri=files[0].uri,
mime_type=files[0].mime_type,
),
types.Part.from_text(text=text),
],
),
]
logger.debug(f"Content object created: {contents}")
generate_content_config = types.GenerateContentConfig(
temperature=1,
top_p=0.95,
top_k=40,
max_output_tokens=8192,
response_modalities=[
"image",
"text",
],
response_mime_type="text/plain",
)
logger.debug(f"Generate content config: {generate_content_config}")
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
temp_path = tmp.name
logger.debug(f"Temporary file created: {temp_path}")
response_stream = client.models.generate_content_stream(
model=model,
contents=contents,
config=generate_content_config,
)
logger.debug("Starting to process response stream...")
for chunk in response_stream:
if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
logger.warning("Chunk has no candidates, content, or parts. Skipping.")
continue
inline_data = chunk.candidates[0].content.parts[0].inline_data
if inline_data:
save_binary_file(temp_path, inline_data.data)
logger.info(f"File of mime type {inline_data.mime_type} saved to: {temp_path} and prompt input :{text}")
else:
logger.info(f"Received text: {chunk.text}")
print(chunk.text) # Keep the print for immediate console output
# Log the raw chunk for deeper inspection
logger.debug(f"Raw chunk: {chunk}")
del files
logger.debug("Uploaded files deleted.")
return temp_path
except Exception as e:
logger.exception("An error occurred during generation:") # This will log the full traceback
return None # Return None when error happens
def process_image_and_prompt(composite_pil, prompt, gemini_api_key):
logger.debug(f"Starting process_image_and_prompt with prompt: '{prompt}'")
try:
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
composite_path = tmp.name
composite_pil.save(composite_path)
logger.debug(f"Composite image saved to: {composite_path}")
file_name = composite_path
input_text = prompt
model = "gemini-2.0-flash-exp-image-generation" # Consider changing this to "gemini-pro-vision"
gemma_edited_image_path = generate(text=input_text, file_name=file_name, api_key=gemini_api_key, model=model)
if gemma_edited_image_path: # Check none or not
logger.debug(f"Image generated at path: {gemma_edited_image_path}")
result_img = Image.open(gemma_edited_image_path)
if result_img.mode == "RGBA":
result_img = result_img.convert("RGB")
return [result_img]
else:
logger.error("generate function returned None.")
return [] # Return empty when error
except Exception as e:
logger.exception("Error occurred in process_image_and_prompt")
return [] # Return empty when error
# --- Gradio Interface ---
with gr.Blocks() as demo:
gr.HTML(
"""
<div style='display: flex; align-items: center; justify-content: center; gap: 20px'>
<div style="background-color: var(--block-background-fill); border-radius: 8px">
<img src="https://www.gstatic.com/lamda/images/gemini_favicon_f069958c85030456e93de685481c559f160ea06b.png" style="width: 100px; height: 100px;">
</div>
<div>
<h1></h1>
<p>ပုံရိပ်တည်းဖြတ်ရန် Gemini</p>
<p>API Key ကို <a href="https://aistudio.google.com/apikey">ဤနေရာ</a> တွင် ဖန်တီးပါ</p>
</div>
</div>
"""
)
gr.Markdown("ပုံတစ်ပုံ တင်ပြီး ပုံကိုတည်းဖြတ်ရန် သင်လိုချင်တာကို ရိုက်ထည့်ပါ။")
with gr.Row():
with gr.Column():
image_input = gr.Image(type="pil", label="ပုံတင်ရန်", image_mode="RGBA")
gemini_api_key = gr.Textbox(
lines=1,
placeholder="Gemini API Key ထည့်ပါ",
label="Gemini API Key",
type="password"
)
prompt_input = gr.Textbox(
lines=2,
placeholder="သင်လိုချင်တာကို ဤနေရာတွင် ရိုက်ထည့်ပါ...",
label="သင်လိုချင်တာ"
)
submit_btn = gr.Button("ထုတ်လုပ်ပါ")
with gr.Column():
output_gallery = gr.Gallery(label="ထုတ်လုပ်ပြီးရလဒ်များ")
submit_btn.click(
fn=process_image_and_prompt,
inputs=[image_input, prompt_input, gemini_api_key],
outputs=output_gallery,
)
# --- Test Code ---
# Create a dummy image (replace with your actual image if needed)
dummy_image = Image.new("RGBA", (100, 100), color="red")
dummy_prompt = "Make the image blue"
dummy_api_key = os.environ.get("GEMINI_API_KEY") # Or put a placeholder key here for testing
# Call the function directly
logger.info("Calling process_image_and_prompt directly...")
result = process_image_and_prompt(dummy_image, dummy_prompt, dummy_api_key)
if result:
logger.info(f"Direct call successful. Result: {result}")
# result[0].show() # Uncomment to display image if running locally
else:
logger.error("Direct call failed.")
demo.launch(share=True) # gradio launch last |