app.py

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, api_key, model="gemini-2.0-flash-exp-image-generation"):
    logger.debug(f"Starting generate function with text: '{text}', model: '{model}'")

    files = None  # Initialize 'files' to None
    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.")

        try:
            client = genai.Client(api_key=effective_api_key)
            logger.debug("Gemini client initialized.")
        except Exception as e:
            logger.error(f"Error initializing Gemini client: {e}")
            return None  # Return None if client initialization fails

        contents = [
            types.Content(
                role="user",
                parts=[
                    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)

                # Log the raw chunk for deeper inspection
                logger.debug(f"Raw chunk: {chunk}")

        logger.debug("Uploaded files deleted.")
        return temp_path

    except Exception as e:
        logger.exception("An error occurred during generation:")
        return None  # Return None when error happens


def generate_image_from_prompt(prompt, gemini_api_key):
    logger.debug(f"Starting generate_image_from_prompt with prompt: '{prompt}'")
    try:

        input_text = prompt
        model = "gemini-2.0-flash-exp-image-generation"

        gemma_generated_image_path = generate(text=input_text, api_key=gemini_api_key, model=model)

        if gemma_generated_image_path:
            logger.debug(f"Image generated at path: {gemma_generated_image_path}")
            result_img = Image.open(gemma_generated_image_path)
            if result_img.mode == "RGBA":
                result_img = result_img.convert("RGB")
            return [result_img]
        else:
            logger.error("generate function returned None.")
            return []

    except Exception as e:
        logger.exception("Error occurred in generate_image_from_prompt")
        return []


# --- 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>စာသားမှပုံသို့ပြောင်းပါ</p>
            <p>API Key ကို <a href="https://aistudio.google.com/apikey">ဤနေရာ</a> တွင် ဖန်တီးပါ</p>
        </div>
        </div>
        """
    )
    gr.Markdown("သင်လိုချင်တဲ့ပုံအတွက် စာသား prompt ကိုထည့်ပါ။")

    with gr.Row():
        with gr.Column():
            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=generate_image_from_prompt,
        inputs=[prompt_input, gemini_api_key],
        outputs=output_gallery,
    )

try:
    demo.launch()
except Exception as e:
    logger.error(f"Failed to launch Gradio app: {e}")
    print(f"Failed to launch Gradio app: {e}")