app.py

import gradio as gr 
import subprocess, shutil, os, zipfile, datetime
from pathlib import Path

ROOT = Path(__file__).resolve().parent
OUTPUT_DIR = ROOT / "output"
INPUT_DIR = ROOT / "input"
LOGO_DIR = INPUT_DIR / "logo"
POSTER_LATEX_DIR = ROOT / "posterbuilder" / "latex_proj"
ZIP_PATH = ROOT / "output.zip"
LOG_PATH = ROOT / "last_run.log"

def run_pipeline(arxiv_url, pdf_file, openai_key, logo_files):
    start_time = datetime.datetime.now()
    logs = [f"🚀 Starting pipeline at {start_time.strftime('%Y-%m-%d %H:%M:%S')}\n"]

    # ====== 目录准备 ======
    for d in [OUTPUT_DIR, LOGO_DIR, POSTER_LATEX_DIR, INPUT_DIR]:
        d.mkdir(parents=True, exist_ok=True)

    # 清理旧输出
    for item in OUTPUT_DIR.iterdir():
        if item.is_dir():
            shutil.rmtree(item)
        else:
            item.unlink()
    if ZIP_PATH.exists():
        ZIP_PATH.unlink()
    logs.append("🧹 Cleaned previous output.\n")

    # ====== 校验：必须上传 LOGO ======
    # Gradio 可能返回单个文件对象或列表，这里统一成列表处理
    if logo_files is None:
        logo_files = []
    if not isinstance(logo_files, (list, tuple)):
        logo_files = [logo_files]
    logo_files = [f for f in logo_files if f]  # 过滤掉 None

    if len(logo_files) == 0:
        msg = "❌ 必须上传作者所属机构 Logo（可多张）。"
        logs.append(msg)
        _write_logs(logs)
        return "\n".join(logs), None

    # 清空 input/logo 后再保存
    for item in LOGO_DIR.iterdir():
        if item.is_file():
            item.unlink()
    saved_logo_paths = []
    for lf in logo_files:
        p = LOGO_DIR / Path(lf.name).name
        shutil.copy(lf.name, p)
        saved_logo_paths.append(p)
    logs.append(f"🏷️ Saved {len(saved_logo_paths)} logo file(s) to: {LOGO_DIR}\n")

    # ====== 处理上传 PDF（可选） ======
    pdf_path = None
    if pdf_file:
        pdf_dir = INPUT_DIR / "pdf"
        pdf_dir.mkdir(parents=True, exist_ok=True)
        pdf_path = pdf_dir / Path(pdf_file.name).name
        shutil.copy(pdf_file.name, pdf_path)
        logs.append(f"📄 Uploaded PDF saved to: {pdf_path}\n")

        # 为 pipeline 的 Step 1.5 兼容：额外复制到 input/paper.pdf
        canonical_pdf = INPUT_DIR / "paper.pdf"
        shutil.copy(pdf_file.name, canonical_pdf)
        logs.append(f"🔁 Also copied PDF to: {canonical_pdf}\n")

    # ====== 校验输入来源 ======
    if not arxiv_url and not pdf_file:
        msg = "❌ 请提供 arXiv 链接或上传 PDF 文件（二选一）。"
        logs.append(msg)
        _write_logs(logs)
        return "\n".join(logs), None

    # ====== 构造命令 ======
    cmd = [
        "python", "pipeline.py",
        "--model_name_t", "gpt-5",
        "--model_name_v", "gpt-5",
        "--result_dir", "output",
        "--paper_latex_root", "input/latex_proj",
        "--openai_key", openai_key,
        "--gemini_key", "AIzaSyA1wVVdlYAVs3FULSmCVD1Noulwrq7zqeo",
        "--logo_dir", str(LOGO_DIR)  # 👈 新增：把 logo 目录传入
    ]

    if arxiv_url:
        cmd += ["--arxiv_url", arxiv_url]
    if pdf_path:
        cmd += ["--pdf_path", str(pdf_path)]

    logs.append(f"🧠 Running command:\n{' '.join(cmd)}\n")

    try:
        result = subprocess.run(
            cmd, capture_output=True, text=True, timeout=1800
        )
        logs.append("\n======= STDOUT =======\n")
        logs.append(result.stdout)
        logs.append("\n======= STDERR =======\n")
        logs.append(result.stderr)
    except subprocess.TimeoutExpired:
        msg = "❌ Pipeline timed out (30 min limit)."
        logs.append(msg)
        _write_logs(logs)
        return "\n".join(logs), None
    except Exception as e:
        msg = f"❌ Pipeline error: {e}"
        logs.append(msg)
        _write_logs(logs)
        return "\n".join(logs), None

    # ====== 检查输出 & 打包 ======
    if not any(OUTPUT_DIR.iterdir()):
        msg = "❌ No output generated. Please check logs below."
        logs.append(msg)
        _write_logs(logs)
        return "\n".join(logs), None

    with zipfile.ZipFile(ZIP_PATH, 'w', zipfile.ZIP_DEFLATED) as zipf:
        for root, dirs, files in os.walk(OUTPUT_DIR):
            for file in files:
                file_path = Path(root) / file
                arcname = file_path.relative_to(OUTPUT_DIR)
                zipf.write(file_path, arcname=arcname)
    logs.append(f"✅ Zipped output folder to {ZIP_PATH}\n")

    end_time = datetime.datetime.now()
    logs.append(f"🏁 Completed at {end_time.strftime('%Y-%m-%d %H:%M:%S')} (Duration: {(end_time - start_time).seconds}s)\n")

    _write_logs(logs)
    return "\n".join(logs), ZIP_PATH


def _write_logs(logs):
    with open(LOG_PATH, "w", encoding="utf-8") as f:
        f.write("\n".join(logs))


# ===================== Gradio UI =====================
iface = gr.Interface(
    fn=run_pipeline,
    inputs=[
        gr.Textbox(label="📘 ArXiv URL（二选一）", placeholder="https://arxiv.org/abs/2505.xxxxx"),
        gr.File(label="📄 上传 PDF（二选一）"),
        gr.Textbox(label="🔑 OpenAI API Key", placeholder="sk-...", type="password"),
        gr.File(label="🏷️ 上传作者所属机构 Logo（必选，可多文件）", file_count="multiple", file_types=["image"]),
    ],
    outputs=[
        gr.Textbox(label="🧾 Logs", lines=30, max_lines=50),
        gr.File(label="📦 下载生成结果 (.zip)")
    ],
    title="📄 PaperShow Pipeline",
    description=(
        "必须上传机构 Logo（可多张）。\n"
        "可输入 arXiv 链接或上传 PDF（二选一），系统将生成 Poster 并打包下载。"
    ),
    allow_flagging="never",
)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)