app.py

import asyncio
import functools
import hashlib
import importlib
import json
import os
import shutil
import tempfile
import sys
import traceback
import uuid
import subprocess
import threading
from contextlib import asynccontextmanager
from copy import deepcopy
from datetime import datetime
from typing import Optional, Tuple
import time
from concurrent.futures import ThreadPoolExecutor

import gradio as gr
from pdf2image import convert_from_path
from pptx import Presentation as PptxPresentation

sys.path.append("./")
import pptagent.induct as induct
import pptagent.pptgen as pptgen
from pptagent.document import Document
from pptagent.model_utils import ModelManager, parse_pdf
from pptagent.multimodal import ImageLabler
from pptagent.presentation import Presentation
from pptagent.utils import Config, get_logger, package_join, pjoin, ppt_to_images_async


async def run_blocking(func, *args, **kw):
    loop = asyncio.get_running_loop()
    return await loop.run_in_executor(None, functools.partial(func, *args, **kw))


async def run_cmd(cmd: list[str]):
    proc = await asyncio.create_subprocess_exec(
        *cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
    )
    stdout, stderr = await proc.communicate()
    if proc.returncode != 0:
        raise RuntimeError(f"{' '.join(cmd)}\n{stderr.decode()}")
    return stdout


# Constants
DEBUG = True if len(sys.argv) == 1 else False
RUNS_DIR = package_join("runs")
STAGES = ["PPT Parsing", "PDF Parsing", "PPT Analysis", "PPT Generation", "Success!"]

# Create a temp directory for Gradio outputs
GRADIO_TEMP_DIR = os.path.join(tempfile.gettempdir(), "gradio_ppt_agent")
os.makedirs(GRADIO_TEMP_DIR, exist_ok=True)

# Global variables
ppt_video_progress_store: dict[str, dict] = {}
progress_store: dict[str, dict] = {}
models = None  # Initialize as None, will be set in main thread
logger = get_logger(__name__)
executor = ThreadPoolExecutor(max_workers=2)

# 在文件顶部添加默认模板配置
DEFAULT_TEMPLATES = [
    {
        "name": "Template1",
        "path": "templates/Template1.pptx",
        "preview": "templates/previews/Template1.jpg"
    },
    {
        "name": "Template2",
        "path": "templates/Template2.pptx",
        "preview": "templates/previews/Template2.jpg"
    },
    {
        "name": "Template3",
        "path": "templates/Template3.pptx",
        "preview": "templates/previews/Template3.jpg"
    },
]


# 新增函数：获取默认模板列表
def get_default_templates():
    """获取可用的默认模板"""
    available_templates = []
    base_dir = os.path.dirname(__file__)

    for template in DEFAULT_TEMPLATES:
        template_path = os.path.join(base_dir, template["path"])
        preview_path = os.path.join(base_dir, template["preview"])

        if os.path.exists(template_path) and os.path.exists(preview_path):
            available_templates.append({
                "name": template["name"],
                "path": template_path,
                "preview": preview_path
            })

    return available_templates


# 新增函数：模板选择回调
def select_template(selected_template_name):
    """选择默认模板"""
    if selected_template_name == "Upload Custom":
        return gr.update(visible=True), gr.update(visible=False), None
    else:
        templates = get_default_templates()
        for template in templates:
            if template["name"] == selected_template_name:
                return gr.update(visible=False), gr.update(visible=True), template["path"]
        return gr.update(visible=True), gr.update(visible=False), None


# 新增函数：创建模板选择界面
def create_template_selection():
    """创建模板选择界面"""
    templates = get_default_templates()

    with gr.Row():
        with gr.Column():
            gr.Markdown("### Choose Template")

            # 创建模板选择按钮
            template_choices = [template["name"] for template in templates] + ["Upload Custom"]
            template_radio = gr.Radio(
                choices=template_choices,
                value="Upload Custom",
                label="Select Template Type"
            )

            # 默认模板预览
            template_preview = gr.Gallery(
                value=[[template["preview"], template["name"]] for template in templates],
                label="Template Previews",
                columns=2,
                rows=2,
                height="auto",
                visible=True
            )

            # 自定义上传区域
            custom_upload = gr.File(
                label="Upload Custom PPT Template",
                file_types=[".pptx"],
                type="filepath",
                visible=True
            )

            # 显示选中的模板
            selected_template_display = gr.Textbox(
                label="Selected Template",
                interactive=False,
                visible=False
            )

    return template_radio, template_preview, custom_upload, selected_template_display


def copy_to_gradio_safe_path(source_path: str, filename: str = None) -> str:
    """

    Copy file to a Gradio-safe location (temp directory)



    Args:

        source_path: Path to source file

        filename: Optional custom filename, defaults to original filename



    Returns:

        Path to copied file in temp directory

    """
    if not os.path.exists(source_path):
        raise FileNotFoundError(f"Source file not found: {source_path}")

    if filename is None:
        filename = os.path.basename(source_path)

    # Create unique filename to avoid conflicts
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    name, ext = os.path.splitext(filename)
    safe_filename = f"{name}_{timestamp}{ext}"

    safe_path = os.path.join(GRADIO_TEMP_DIR, safe_filename)
    shutil.copy2(source_path, safe_path)

    return safe_path


# Initialize models with custom configuration
def init_models(api_key: str = None, api_base: str = None, language_model: str = None,

                vision_model: str = None, text_model: str = None):
    """Initialize models with custom configuration"""
    global models
    try:
        # Set environment variables if provided
        if api_key:
            os.environ["OPENAI_API_KEY"] = api_key
        if api_base:
            os.environ["API_BASE"] = api_base
        if language_model:
            os.environ["LANGUAGE_MODEL"] = language_model
        if vision_model:
            os.environ["VISION_MODEL"] = vision_model
        if text_model:
            os.environ["TEXT_MODEL"] = text_model

        # Initialize models
        models = ModelManager(
            api_base=api_base,
            api_key=api_key,
            language_model_name=language_model,
            vision_model_name=vision_model,
            text_model_name=text_model
        )

        # Test connections in main thread
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)

        result = loop.run_until_complete(models.test_connections())
        assert result, "Model connection test failed"

        logger.info("Models initialized successfully")
        return "✅ Models initialized successfully"
    except Exception as e:
        error_msg = f"❌ Model initialization failed: {e}"
        logger.error(error_msg)
        return error_msg


class GradioProgressManager:
    def __init__(self, task_id: str, stages: list[str], progress_callback=None):
        self.task_id = task_id
        self.stages = stages
        self.progress_callback = progress_callback
        self.failed = False
        self.current_stage = 0
        self.total_stages = len(stages)

    async def report_progress(self):
        self.current_stage += 1
        progress = int((self.current_stage / self.total_stages) * 100)
        status = f"Stage: {self.stages[self.current_stage - 1]}"
        if self.progress_callback:
            self.progress_callback(progress, status)
        return progress, status

    async def fail_stage(self, error_message: str):
        error_status = f"{self.stages[self.current_stage]} Error: {error_message}"
        if self.progress_callback:
            self.progress_callback(100, error_status)
        self.failed = True
        logger.error(f"{self.task_id}: {error_status}")
        return error_status


def generate_ppt(pptx_file, pdf_file, num_pages, progress=gr.Progress()):
    """Generate PPT from template and PDF"""
    try:
        # Make sure models are initialized
        if models is None:
            return None, "❌ Please initialize models first in the Configuration tab"

        # Create task ID
        task_id = datetime.now().strftime("20%y-%m-%d") + "/" + str(uuid.uuid4())
        logger.info(f"PPT generation task created: {task_id}")

        # Create directories
        os.makedirs(pjoin(RUNS_DIR, task_id), exist_ok=True)

        task = {
            "numberOfPages": num_pages,
            "pptx": "default_template",
        }

        # Handle PPT template
        if pptx_file is not None:
            pptx_blob = open(pptx_file, "rb").read()
            pptx_md5 = hashlib.md5(pptx_blob).hexdigest()
            task["pptx"] = pptx_md5
            pptx_dir = pjoin(RUNS_DIR, "pptx", pptx_md5)
            if not os.path.exists(pptx_dir):
                os.makedirs(pptx_dir, exist_ok=True)
                with open(pjoin(pptx_dir, "source.pptx"), "wb") as f:
                    f.write(pptx_blob)

        # Handle PDF
        if pdf_file is not None:
            pdf_blob = open(pdf_file, "rb").read()
            pdf_md5 = hashlib.md5(pdf_blob).hexdigest()
            task["pdf"] = pdf_md5
            pdf_dir = pjoin(RUNS_DIR, "pdf", pdf_md5)
            if not os.path.exists(pdf_dir):
                os.makedirs(pdf_dir, exist_ok=True)
                with open(pjoin(pdf_dir, "source.pdf"), "wb") as f:
                    f.write(pdf_blob)

        else:
            return None, "❌ Please provide a PDF file"

        progress_store[task_id] = task

        # Progress callback
        def update_progress(prog, status):
            progress(prog / 100, desc=status)

        # Run PPT generation directly in main thread event loop
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)

        final_ppt_path = loop.run_until_complete(ppt_gen_async(task_id, update_progress))

        if final_ppt_path and os.path.exists(final_ppt_path):
            # Copy to Gradio-safe location
            safe_path = copy_to_gradio_safe_path(final_ppt_path, "generated_presentation.pptx")
            return safe_path, f"✅ PPT generated successfully! Task ID: {task_id}"
        else:
            return None, "❌ PPT generation failed"

    except Exception as e:
        logger.error(f"PPT generation error: {str(e)}")
        traceback.print_exc()
        return None, f"❌ Error: {str(e)}"

def generate_ppt_with_template_selection(selected_template_name, custom_pptx_file, pdf_file, num_pages, progress=gr.Progress()):
    """Generate PPT with template selection"""
    try:
        # Make sure models are initialized
        if models is None:
            return None, "❌ Please initialize models first in the Configuration tab"

        # 确定使用的模板文件
        pptx_file = None
        if selected_template_name and selected_template_name != "Upload Custom":
            # 使用默认模板
            templates = get_default_templates()
            for template in templates:
                if template["name"] == selected_template_name:
                    pptx_file = template["path"]
                    break
        else:
            # 使用上传的自定义模板
            pptx_file = custom_pptx_file

        # 调用原有的generate_ppt函数
        return generate_ppt(pptx_file, pdf_file, num_pages, progress)

    except Exception as e:
        logger.error(f"PPT generation with template selection error: {str(e)}")
        return None, f"❌ Error: {str(e)}"


async def ppt_gen_async(task_id: str, progress_callback=None):
    """Async PPT generation function"""
    try:
        if DEBUG:
            importlib.reload(induct)
            importlib.reload(pptgen)

        task = progress_store[task_id]
        pptx_md5 = task["pptx"]
        pdf_md5 = task["pdf"]
        generation_config = Config(pjoin(RUNS_DIR, task_id))
        pptx_config = Config(pjoin(RUNS_DIR, "pptx", pptx_md5))
        json.dump(task, open(pjoin(generation_config.RUN_DIR, "task.json"), "w"))

        progress_manager = GradioProgressManager(task_id, STAGES, progress_callback)
        parsedpdf_dir = pjoin(RUNS_DIR, "pdf", pdf_md5)
        ppt_image_folder = pjoin(pptx_config.RUN_DIR, "slide_images")

        if progress_callback:
            progress_callback(10, "Task initialized successfully")

        # PPT parsing
        presentation = Presentation.from_file(
            pjoin(pptx_config.RUN_DIR, "source.pptx"), pptx_config
        )

        if not os.path.exists(ppt_image_folder) or len(os.listdir(ppt_image_folder)) != len(presentation):
            await ppt_to_images_async(
                pjoin(pptx_config.RUN_DIR, "source.pptx"), ppt_image_folder
            )

            # Handle error slides
            for err_idx, _ in presentation.error_history:
                error_file = pjoin(ppt_image_folder, f"slide_{err_idx:04d}.jpg")
                if os.path.exists(error_file):
                    os.remove(error_file)

            # Rename slides
            for i, slide in enumerate(presentation.slides, 1):
                slide.slide_idx = i
                old_path = pjoin(ppt_image_folder, f"slide_{slide.real_idx:04d}.jpg")
                new_path = pjoin(ppt_image_folder, f"slide_{slide.slide_idx:04d}.jpg")
                if os.path.exists(old_path):
                    os.rename(old_path, new_path)

        # Image labeling
        labler = ImageLabler(presentation, pptx_config)
        stats_file = pjoin(pptx_config.RUN_DIR, "image_stats.json")
        if os.path.exists(stats_file):
            image_stats = json.load(open(stats_file, encoding="utf-8"))
            labler.apply_stats(image_stats)
        else:
            await labler.caption_images_async(models.vision_model)
            json.dump(
                labler.image_stats,
                open(stats_file, "w", encoding="utf-8"),
                ensure_ascii=False,
                indent=4,
            )
        await progress_manager.report_progress()

        # PDF parsing
        source_md_path = pjoin(parsedpdf_dir, "source.md")
        if not os.path.exists(source_md_path):
            # Check if we have a PDF file
            pdf_file_path = pjoin(RUNS_DIR, "pdf", pdf_md5, "source.pdf")
            if os.path.exists(pdf_file_path):
                text_content = parse_pdf(
                    pdf_file_path,
                    parsedpdf_dir,
                    models.marker_model,
                )
            else:
                raise ValueError("No PDF file found")
        else:
            text_content = open(source_md_path, encoding="utf-8").read()
        await progress_manager.report_progress()

        # Document refine
        refined_doc_path = pjoin(parsedpdf_dir, "refined_doc.json")
        if not os.path.exists(refined_doc_path):
            source_doc = await Document.from_markdown_async(
                text_content,
                models.language_model,
                models.vision_model,
                parsedpdf_dir,
            )
            json.dump(
                source_doc.to_dict(),
                open(refined_doc_path, "w"),
                ensure_ascii=False,
                indent=4,
            )
        else:
            source_doc_dict = json.load(open(refined_doc_path))
            source_doc = Document.from_dict(source_doc_dict, parsedpdf_dir)
        await progress_manager.report_progress()

        # Slide Induction
        slide_induction_path = pjoin(pptx_config.RUN_DIR, "slide_induction.json")
        if not os.path.exists(slide_induction_path):
            deepcopy(presentation).save(
                pjoin(pptx_config.RUN_DIR, "template.pptx"), layout_only=True
            )
            await ppt_to_images_async(
                pjoin(pptx_config.RUN_DIR, "template.pptx"),
                pjoin(pptx_config.RUN_DIR, "template_images"),
            )
            slide_inducter = induct.SlideInducterAsync(
                presentation,
                ppt_image_folder,
                pjoin(pptx_config.RUN_DIR, "template_images"),
                pptx_config,
                models.image_model,
                models.language_model,
                models.vision_model,
            )
            layout_induction = await slide_inducter.layout_induct()
            slide_induction = await slide_inducter.content_induct(layout_induction)
            json.dump(
                slide_induction,
                open(slide_induction_path, "w", encoding="utf-8"),
                ensure_ascii=False,
                indent=4,
            )
        else:
            slide_induction = json.load(open(slide_induction_path, encoding="utf-8"))
        await progress_manager.report_progress()

        # PPT Generation
        ppt_agent = pptgen.PPTAgentAsync(
            models.text_model,
            models.language_model,
            models.vision_model,
            error_exit=False,
            retry_times=5,
        )
        ppt_agent.set_reference(
            config=generation_config,
            slide_induction=slide_induction,
            presentation=presentation,
        )

        prs, _ = await ppt_agent.generate_pres(
            source_doc=source_doc,
            num_slides=task["numberOfPages"],
        )

        final_path = pjoin(generation_config.RUN_DIR, "final.pptx")
        prs.save(final_path)
        logger.info(f"{task_id}: generation finished")
        await progress_manager.report_progress()

        return final_path

    except Exception as e:
        logger.error(f"PPT generation failed: {str(e)}")
        traceback.print_exc()
        return None


def ppt_to_video(ppt_file, progress=gr.Progress()):
    """Convert PPT to video presentation"""
    try:
        task_id = str(uuid.uuid4())
        logger.info(f"PPT2Video task created: {task_id}")

        task_dir = pjoin(RUNS_DIR, "ppt_video", task_id)
        os.makedirs(task_dir, exist_ok=True)

        # Copy PPT file
        ppt_blob = open(ppt_file, "rb").read()
        ppt_path = pjoin(task_dir, "source.pptx")
        with open(ppt_path, "wb") as f:
            f.write(ppt_blob)

        # Initialize progress
        ppt_video_progress_store[task_id] = {
            "status": "processing",
            "current_step": 1,
            "current_slide": 0,
            "total_slides": 0,
            "progress_percentage": 0,
            "task_dir": task_dir,
            "ppt_path": ppt_path
        }

        # Progress callback
        def update_progress(prog, status):
            progress(prog, desc=status)

        # Run PPT to video conversion directly in main thread event loop
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)

        video_path = loop.run_until_complete(process_ppt_to_video_async(task_id, update_progress))

        if video_path and os.path.exists(video_path):
            # Copy to Gradio-safe location
            safe_path = copy_to_gradio_safe_path(video_path, "generated_video.mp4")
            return safe_path, f"✅ Video generated successfully! Task ID: {task_id}"
        else:
            return None, "❌ Video generation failed"

    except Exception as e:
        logger.error(f"PPT to video error: {str(e)}")
        return None, f"❌ Error: {str(e)}"


async def process_ppt_to_video_async(task_id: str, progress_callback):
    """Process PPT to video asynchronously"""
    try:
        task_dir = ppt_video_progress_store[task_id]["task_dir"]
        ppt_path = ppt_video_progress_store[task_id]["ppt_path"]

        progress_callback(0.1, "Converting PPT to PDF...")

        # Convert PPT to PDF
        pdf_path = pjoin(task_dir, "source.pdf")
        await run_cmd([
            "libreoffice", "--headless", "--convert-to", "pdf",
            ppt_path, "--outdir", task_dir
        ])

        # Convert PDF to images
        images_from_path = await run_blocking(convert_from_path, pdf_path)
        prs = await run_blocking(PptxPresentation, ppt_path)

        if len(images_from_path) != len(prs.slides):
            raise Exception("PPT页数与生成的图片数量不匹配")

        progress_callback(0.2, "Extracting slides...")

        # Generate video segments
        video_segments = []
        with tempfile.TemporaryDirectory() as temp_path:
            total_slides = len(prs.slides)
            for i, (slide, image) in enumerate(zip(prs.slides, images_from_path)):
                slide_progress = 0.3 + (i / total_slides) * 0.4
                progress_callback(slide_progress, f"Processing slide {i + 1}/{total_slides}")

                # Get notes
                notes = ""
                if slide.has_notes_slide:
                    notes = slide.notes_slide.notes_text_frame.text
                if not notes.strip():
                    notes = f"This is slide {i + 1}"

                # Save image
                image_path = pjoin(temp_path, f"frame_{i}.jpg")
                image.save(image_path)

                # Generate audio
                audio_path = pjoin(temp_path, f"frame_{i}.wav")
                await generate_tts_audio(notes, audio_path)

                # Create video segment
                video_segment_path = await create_video_segment(
                    image_path, audio_path, temp_path, i
                )
                video_segments.append(video_segment_path)

            progress_callback(0.8, "Merging video segments...")

            # Merge video segments
            output_video_path = pjoin(task_dir, "output.mp4")
            await merge_video_segments(video_segments, output_video_path)

        progress_callback(1.0, "Video generation completed!")

        ppt_video_progress_store[task_id]["status"] = "completed"
        return output_video_path

    except Exception as e:
        logger.error(f"PPT2Video processing failed {task_id}: {e}")
        ppt_video_progress_store[task_id]["status"] = "failed"
        return None


async def generate_tts_audio(text: str, output_path: str):
    """Generate TTS audio"""
    try:
        # Try to use MegaTTS3 if available
        sys.path.append(pjoin(os.path.dirname(__file__), "MegaTTS3"))
        from tts.infer_cli import MegaTTS3DiTInfer
        from tts.utils.audio_utils.io import save_wav

        infer = MegaTTS3DiTInfer(ckpt_root=pjoin(os.path.dirname(__file__), "MegaTTS3", "checkpoints"))

        prompt_audio_path = pjoin(os.path.dirname(__file__), "MegaTTS3", "assets", "English_prompt.wav")

        with open(prompt_audio_path, 'rb') as f:
            audio_bytes = f.read()
        latent_file = None
        potential_npy = os.path.splitext(prompt_audio_path)[0] + '.npy'
        if os.path.isfile(potential_npy):
            latent_file = potential_npy
        resource_context = infer.preprocess(audio_bytes, latent_file)

        wav_bytes = infer.forward(
            resource_context,
            text,
            time_step=32,
            p_w=1.6,
            t_w=2.5
        )

        save_wav(wav_bytes, output_path)

    except Exception as e:
        logger.error(f"TTS failed: {str(e)}")
        # Fallback: create silent audio
        import numpy as np
        import wave

        sample_rate = 22050
        duration = 3.0
        samples = np.zeros(int(sample_rate * duration), dtype=np.int16)

        with wave.open(output_path, 'w') as wav_file:
            wav_file.setnchannels(1)
            wav_file.setsampwidth(2)
            wav_file.setframerate(sample_rate)
            wav_file.writeframes(samples.tobytes())


async def create_video_segment(image_path: str, audio_path: str, temp_path: str, index: int):
    """Create video segment from image and audio"""
    output_path = pjoin(temp_path, f"segment_{index}.mp4")
    await run_cmd([
        "ffmpeg", "-y", "-loop", "1", "-i", image_path, "-i", audio_path,
        "-vf", "scale=1920:1080", "-c:v", "libx264", "-tune", "stillimage",
        "-c:a", "aac", "-b:a", "192k", "-pix_fmt", "yuv420p", "-shortest",
        output_path
    ])
    return output_path


async def merge_video_segments(video_segments: list[str], output_path: str):
    """Merge video segments"""
    list_file_path = output_path.replace('.mp4', '_list.txt')
    with open(list_file_path, "w") as f:
        for seg in video_segments:
            f.write(f"file '{seg}'\n")

    await run_cmd([
        "ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", list_file_path,
        "-c", "copy", output_path
    ])
    os.remove(list_file_path)


def cleanup_temp_files():
    """Clean up old temporary files"""
    try:
        import glob
        import time

        # Remove files older than 1 hour
        cutoff_time = time.time() - 3600
        for file_path in glob.glob(os.path.join(GRADIO_TEMP_DIR, "*")):
            if os.path.getctime(file_path) < cutoff_time:
                try:
                    os.remove(file_path)
                    logger.info(f"Cleaned up old temp file: {file_path}")
                except Exception as e:
                    logger.warning(f"Failed to remove temp file {file_path}: {e}")
    except Exception as e:
        logger.warning(f"Cleanup failed: {e}")


# Gradio interface
def create_gradio_interface():
    """Create Gradio interface"""

    with gr.Blocks(title="PresentAgent", theme=gr.themes.Soft()) as demo:
        gr.Markdown("# PresentAgent - PowerPoint Generation and Presentation Creation")

        with gr.Tabs():
            # Model Configuration Tab
            with gr.TabItem("🔧 Configuration"):
                gr.Markdown("## Model Configuration")
                gr.Markdown(
                    "Configure your API settings and model parameters before using the PPT generation features.")

                with gr.Row():
                    with gr.Column():
                        api_key_input = gr.Textbox(
                            label="API Key",
                            type="password",
                            placeholder="Enter your OpenAI API key",
                            value=""
                        )
                        api_base_input = gr.Textbox(
                            label="API Base URL",
                            placeholder="https://api.openai.com/v1",
                            value=""
                        )

                        with gr.Row():
                            language_model_input = gr.Textbox(
                                label="Language Model",
                                placeholder="Model for text generation",
                                value="gpt-4o"
                            )
                            vision_model_input = gr.Textbox(
                                label="Vision Model",
                                placeholder="Model for image processing",
                                value="gpt-4o"
                            )
                            text_model_input = gr.Textbox(
                                label="Text Embedding Model",
                                placeholder="Model for text embeddings",
                                value="text-embedding-3-small"
                            )

                        init_btn = gr.Button("Initialize Models", variant="primary", size="lg")

                    with gr.Column():
                        init_status = gr.Textbox(
                            label="Initialization Status",
                            interactive=False,
                            lines=3
                        )

                        gr.Markdown("""

                        ### Instructions:

                        1. Enter your API key and base URL

                        2. Configure model names (defaults are recommended)

                        3. Click "Initialize Models" to test the connection

                        4. Once initialized, you can use the PPT generation features

                        """)

                init_btn.click(
                    fn=init_models,
                    inputs=[api_key_input, api_base_input, language_model_input, vision_model_input, text_model_input],
                    outputs=[init_status]
                )

            with gr.TabItem("📊 PPT Generation"):
                gr.Markdown("## Generate PowerPoint from Template and PDF")

                with gr.Row():
                    with gr.Column():
                        # 模板选择区域
                        template_radio, template_preview, custom_upload, selected_template_display = create_template_selection()

                        # PDF输入
                        pdf_input = gr.File(
                            label="PDF Document",
                            file_types=[".pdf"],
                            type="filepath"
                        )

                        # 页数选择
                        num_pages_input = gr.Slider(
                            minimum=1,
                            maximum=50,
                            value=10,
                            step=1,
                            label="Number of Slides"
                        )

                        generate_btn = gr.Button("Generate PPT", variant="primary", size="lg")

                    with gr.Column():
                        ppt_output = gr.File(label="Generated PPT")
                        ppt_status = gr.Textbox(label="Status", interactive=False, lines=3)

                # 绑定模板选择事件
                template_radio.change(
                    fn=select_template,
                    inputs=[template_radio],
                    outputs=[custom_upload, selected_template_display, gr.State()]
                )

                # 绑定生成按钮
                generate_btn.click(
                    fn=generate_ppt_with_template_selection,
                    inputs=[template_radio, custom_upload, pdf_input, num_pages_input],
                    outputs=[ppt_output, ppt_status]
                )

            # PPT to Video Tab
            with gr.TabItem("🎬 PPT to Presentation"):
                gr.Markdown("## Convert PowerPoint to Video Presentation")

                with gr.Row():
                    with gr.Column():
                        ppt_video_input = gr.File(
                            label="PowerPoint File",
                            file_types=[".pptx"],
                            type="filepath"
                        )

                        video_btn = gr.Button("Convert to Video", variant="primary", size="lg")

                    with gr.Column():
                        video_output = gr.File(label="Generated Video")
                        video_status = gr.Textbox(label="Status", interactive=False, lines=3)

                video_btn.click(
                    fn=ppt_to_video,
                    inputs=[ppt_video_input],
                    outputs=[video_output, video_status]
                )

    return demo


def setup_template_directories():
    """设置模板目录结构"""
    base_dir = os.path.dirname(__file__)
    template_dir = os.path.join(base_dir, "templates")
    preview_dir = os.path.join(template_dir, "previews")

    os.makedirs(template_dir, exist_ok=True)
    os.makedirs(preview_dir, exist_ok=True)

    logger.info(f"Template directories created at: {template_dir}")
    logger.info("Please place your default template files in the templates directory")
    logger.info("Please place corresponding preview images in the templates/previews directory")


# Main function
if __name__ == "__main__":
    # Create runs directory
    os.makedirs(RUNS_DIR, exist_ok=True)
    os.makedirs(pjoin(RUNS_DIR, "feedback"), exist_ok=True)

    setup_template_directories()

    # Clean up old temp files
    cleanup_temp_files()

    # Create and launch Gradio interface
    demo = create_gradio_interface()

    # Launch with allowed paths
    demo.queue().launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True,
        show_error=True,
        allowed_paths=[RUNS_DIR]
    )