import os
import shutil
from pathlib import Path
from pdf2zh import __version__
from pdf2zh.pdf2zh import extract_text
import gradio as gr
import numpy as np
import pymupdf
import tqdm
import requests
import cgi
# Map service names to pdf2zh service options
service_map = {
#"Google": ("google", None, None),
#"DeepL": ("deepl", "DEEPL_AUTH_KEY", None),
#"DeepLX": ("deeplx", "DEEPLX_AUTH_KEY", None),
#"Ollama": ("ollama", None, "gemma2"),
"OpenAI": ("openai", "OPENAI_API_KEY", "gpt-4o"),
#"Azure": ("azure", "AZURE_APIKEY", None),
#"Tencent": ("tencent", "TENCENT_SECRET_KEY", None),
}
lang_map = {
"Chinese": "zh",
"English": "en",
"French": "fr",
"German": "de",
"Japanese": "ja",
"Korean": "ko",
"Russian": "ru",
"Spanish": "es",
"Italian": "it",
}
page_map = {
"All": None,
"First": [0],
"First 5 pages": list(range(0, 5)),
}
flag_demo = False
if os.environ.get("PDF2ZH_DEMO"):
flag_demo = True
service_map = {
"Google": ("google", None, None),
}
page_map = {
"First": [0],
"First 20 pages": list(range(0, 20)),
}
client_key = os.environ.get("PDF2ZH_CLIENT_KEY")
server_key = os.environ.get("PDF2ZH_SERVER_KEY")
def verify_recaptcha(response):
recaptcha_url = "https://www.google.com/recaptcha/api/siteverify"
print("reCAPTCHA", server_key, response)
data = {"secret": server_key, "response": response}
result = requests.post(recaptcha_url, data=data).json()
print("reCAPTCHA", result.get("success"))
return result.get("success")
def pdf_preview(file):
doc = pymupdf.open(file)
page = doc[0]
pix = page.get_pixmap()
image = np.frombuffer(pix.samples, np.uint8).reshape(pix.height, pix.width, 3)
return image
def upload_file(file, service, progress=gr.Progress()):
"""Handle file upload, validation, and initial preview."""
if not file or not os.path.exists(file):
return None, None
try:
# Convert first page for preview
preview_image = pdf_preview(file)
return file, preview_image
except Exception as e:
print(f"Error converting PDF: {e}")
return None, None
def download_with_limit(url, save_path, size_limit):
chunk_size = 1024
total_size = 0
with requests.get(url, stream=True, timeout=10) as response:
response.raise_for_status()
content = response.headers.get("Content-Disposition")
try:
_, params = cgi.parse_header(content)
filename = params["filename"]
except Exception:
filename = os.path.basename(url)
with open(save_path / filename, "wb") as file:
for chunk in response.iter_content(chunk_size=chunk_size):
total_size += len(chunk)
if size_limit and total_size > size_limit:
raise gr.Error("Exceeds file size limit")
file.write(chunk)
return save_path / filename
def translate(
file_type,
file_input,
link_input,
service,
apikey,
model_id,
lang_from,
lang_to,
page_range,
recaptcha_response,
progress=gr.Progress(),
):
"""Translate PDF content using selected service."""
if flag_demo and not verify_recaptcha(recaptcha_response):
raise gr.Error("reCAPTCHA fail")
progress(0, desc="Starting translation...")
output = Path("pdf2zh_files")
output.mkdir(parents=True, exist_ok=True)
if file_type == "File":
if not file_input:
raise gr.Error("No input")
file_path = shutil.copy(file_input, output)
else:
if not link_input:
raise gr.Error("No input")
file_path = download_with_limit(
link_input,
output,
5 * 1024 * 1024 if flag_demo else None,
)
filename = os.path.splitext(os.path.basename(file_path))[0]
file_en = output / f"{filename}.pdf"
file_zh = output / f"{filename}-zh.pdf"
file_dual = output / f"{filename}-dual.pdf"
selected_service = service_map[service][0]
if service_map[service][1]:
os.environ.setdefault(service_map[service][1], apikey)
selected_page = page_map[page_range]
lang_from = lang_map[lang_from]
lang_to = lang_map[lang_to]
if selected_service == "google":
lang_from = "zh-CN" if lang_from == "zh" else lang_from
lang_to = "zh-CN" if lang_to == "zh" else lang_to
print(f"Files before translation: {os.listdir(output)}")
def progress_bar(t: tqdm.tqdm):
progress(t.n / t.total, desc="Translating...")
param = {
"files": [file_en],
"pages": selected_page,
"lang_in": lang_from,
"lang_out": lang_to,
"service": f"{selected_service}:{model_id}",
"output": output,
"thread": 4,
"callback": progress_bar,
}
print(param)
extract_text(**param)
print(f"Files after translation: {os.listdir(output)}")
if not file_zh.exists() or not file_dual.exists():
raise gr.Error("No output")
try:
translated_preview = pdf_preview(str(file_zh))
except Exception:
raise gr.Error("No preview")
progress(1.0, desc="Translation complete!")
return (
str(file_zh),
translated_preview,
str(file_dual),
gr.update(visible=True),
gr.update(visible=True),
gr.update(visible=True),
)
# Global setup
custom_blue = gr.themes.Color(
c50="#E8F3FF",
c100="#BEDAFF",
c200="#94BFFF",
c300="#6AA1FF",
c400="#4080FF",
c500="#165DFF", # Primary color
c600="#0E42D2",
c700="#0A2BA6",
c800="#061D79",
c900="#03114D",
c950="#020B33",
)
with gr.Blocks(
title="PDFBestTranslate - PDF Translation with preserved formats",
theme=gr.themes.Default(
primary_hue=custom_blue, spacing_size="md", radius_size="lg"
),
css="""
.secondary-text {color: #999 !important;}
footer {visibility: hidden}
.env-warning {color: #dd5500 !important;}
.env-success {color: #559900 !important;}
/* Add dashed border to input-file class */
.input-file {
border: 1.2px dashed #165DFF !important;
border-radius: 6px !important;
# background-color: #ffffff !important;
transition: background-color 0.4s ease-out;
}
.input-file:hover {
border: 1.2px dashed #165DFF !important;
border-radius: 6px !important;
color: #165DFF !important;
background-color: #E8F3FF !important;
transition: background-color 0.2s ease-in;
}
.progress-bar-wrap {
border-radius: 8px !important;
}
.progress-bar {
border-radius: 8px !important;
}
# .input-file label {
# color: #165DFF !important;
# border: 1.2px dashed #165DFF !important;
# border-left: none !important;
# border-top: none !important;
# }
# .input-file .wrap {
# color: #165DFF !important;
# }
# .input-file .or {
# color: #165DFF !important;
# }
""",
head=(
"""
"""
if flag_demo
else ""
),
) as demo:
gr.Markdown(
#"# [PDFMathTranslate @ GitHub](https://github.com/Byaidu/PDFMathTranslate)"
"# [PDFMathTranslate——科研之心免费提供(更多科研AI智能体请点击)](https://ai.linkagi.top)"
)
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("## File | < 5 MB" if flag_demo else "## File")
file_type = gr.Radio(
choices=["File", "Link"],
label="Type",
value="File",
)
file_input = gr.File(
label="File",
file_count="single",
file_types=[".pdf"],
type="filepath",
elem_classes=["input-file"],
)
link_input = gr.Textbox(
label="Link",
visible=False,
interactive=True,
)
gr.Markdown("## Option(请先选择翻译模型)")
with gr.Row():
service = gr.Dropdown(
label="Service",
choices=service_map.keys(),
value="Google",
)
apikey = gr.Textbox(
label="API Key",
max_lines=1,
visible=False,
)
with gr.Row():
lang_from = gr.Dropdown(
label="Translate from",
choices=lang_map.keys(),
value="English",
)
lang_to = gr.Dropdown(
label="Translate to",
choices=lang_map.keys(),
value="Chinese",
)
page_range = gr.Radio(
choices=page_map.keys(),
label="Pages",
value=list(page_map.keys())[0],
)
model_id = gr.Textbox(
label="Model ID",
visible=False,
interactive=True,
)
envs_status = "- Properly configured.
"
def details_wrapper(text_markdown):
text = f"""
- GUI by: Rongxin
- Version: {__version__}
"""
return text
def env_var_checker(env_var_name: str) -> str:
if env_var_name:
if not os.environ.get(env_var_name):
envs_status = (
f"- Warning: environmental not found or error ({env_var_name})."
+ "
- Please make sure that the environment variables are properly configured "
+ "(guide).
"
)
else:
value = str(os.environ.get(env_var_name))
envs_status = "- Properly configured.
"
envs_status += (
f"- {env_var_name}: {value[:13]}***
"
)
else:
envs_status = (
"- Properly configured.
"
)
return details_wrapper(envs_status)
def on_select_service(service, evt: gr.EventData):
if service_map[service][1]:
apikey_content = gr.update(
visible=False, value=os.environ.get(service_map[service][1])
)
else:
apikey_content = gr.update(visible=False)
if service_map[service][2]:
model_visibility = gr.update(
visible=True, value=service_map[service][2]
)
else:
model_visibility = gr.update(visible=False)
return (
env_var_checker(service_map[service][1]),
model_visibility,
apikey_content,
)
def on_select_filetype(file_type):
return (
gr.update(visible=file_type == "File"),
gr.update(visible=file_type == "Link"),
)
output_title = gr.Markdown("## Translated", visible=False)
output_file = gr.File(label="Download Translation", visible=False)
output_file_dual = gr.File(
label="Download Translation (Dual)", visible=False
)
recaptcha_response = gr.Textbox(
label="reCAPTCHA Response", elem_id="verify", visible=False
)
recaptcha_box = gr.HTML('