davideuler
commited on
Commit
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Parent(s):
79d1413
记录调用语言模型的错误日志;PDF文件可以下载,优化下载的PDF文件大小
Browse files- .gitignore +2 -0
- README.md +19 -0
- deep_translator/openai_compatible.py +39 -0
- pdf_translator_web.py +185 -36
.gitignore
CHANGED
@@ -23,6 +23,8 @@ var/
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.idea/
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.idea
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.cached
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wheels/
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*.egg-info/
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.installed.cfg
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.idea/
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.idea
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.cached
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*.pdf
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*.log
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wheels/
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*.egg-info/
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.installed.cfg
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README.md
CHANGED
@@ -73,6 +73,25 @@ cmake --build build --config Release -j 12
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```
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### Options 3. Local inference service by ollama/vLLM and other application such as LMStudio
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Please read the official guide for you LLM inferencing tool.
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```
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## Note on using OpenAI Compatible LLM service provider
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For example, run the following command before start the streamlit application to enable translation by deepseek :
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``` bash
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export OPENAI_MODEL=deepseek-chat
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export OPENAI_API_BASE=https://api.deepseek.com/v1
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export OPENAI_API_KEY=sk-xxxx
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```
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Run the following command before start the streamlit application to enable translation by moonshot :
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``` bash
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export OPENAI_MODEL=moonshot-v1-8k
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export OPENAI_API_BASE=https://api.moonshot.cn/v1
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export OPENAI_API_KEY=sk-xxxx
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```
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### Options 3. Local inference service by ollama/vLLM and other application such as LMStudio
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Please read the official guide for you LLM inferencing tool.
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deep_translator/openai_compatible.py
ADDED
@@ -0,0 +1,39 @@
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import json
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import time
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import os,logging
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import streamlit as st
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from .chatgpt import ChatGptTranslator
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logging.basicConfig(filename='application.log', level=logging.INFO, format='%(asctime)s - %(levelname)-5s %(lineno)d %(filename)s:%(funcName)s - %(message)s')
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class OpenAICompatibleTranslator(ChatGptTranslator):
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"""Translator that handles OpenAI compatible APIs with better error handling"""
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def __init__(self, source="en", target="zh-CN", **kwargs):
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super().__init__(source=source, target=target, **kwargs)
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self.retry_count = 3
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self.retry_delay = 1 # seconds
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def translate(self, text: str, **kwargs) -> str:
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"""
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Translate text with retry mechanism and error handling
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"""
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if not text.strip():
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return text
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for attempt in range(self.retry_count):
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try:
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api_base = os.environ["OPENAI_API_BASE"]
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logging.info(f"Request OpenAI compatible api, base_url: {api_base}")
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return super().translate(text, **kwargs)
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except json.JSONDecodeError:
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logging.warn(f"Translation API response JSONDecodeError, will retry later...")
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if attempt == self.retry_count - 1:
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logging.error(f"Translation API response error, using original text")
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st.warning(f"Translation API response error, using original text")
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return text
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time.sleep(self.retry_delay)
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except Exception as e:
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logging.error(f"Translation error: {str(e)}")
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st.error(f"Translation error: {str(e)}")
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return text
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pdf_translator_web.py
CHANGED
@@ -6,8 +6,9 @@ import streamlit as st
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import pymupdf
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from deep_translator import (
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GoogleTranslator,
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ChatGptTranslator,
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)
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# Constants
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DEFAULT_PAGES_PER_LOAD = 2
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# Supported translators
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TRANSLATORS = {
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'google': GoogleTranslator,
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'chatgpt': ChatGptTranslator,
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}
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# Color options
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cache_dir.mkdir(exist_ok=True)
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return cache_dir
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def get_cache_key(
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"""Generate cache key for a specific page translation"""
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#
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-
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def get_cached_translation(cache_key: str) -> pymupdf.Document:
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"""Get cached translation if exists"""
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cache_path = get_cache_dir() / cache_key
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if cache_path.exists():
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-
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return None
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def save_translation_cache(doc: pymupdf.Document, cache_key: str):
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"""Save translation to cache"""
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cache_path = get_cache_dir() / cache_key
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doc.save(str(cache_path))
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def translate_pdf_pages(doc, doc_bytes, start_page, num_pages, translator, text_color, translator_name, target_lang):
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"""Translate specific pages of a PDF document with progress and caching"""
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@@ -84,6 +92,8 @@ def translate_pdf_pages(doc, doc_bytes, start_page, num_pages, translator, text_
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rgb_color = COLOR_MAP.get(text_color.lower(), COLOR_MAP["darkred"])
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translated_pages = []
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# Create a progress bar
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progress_bar = st.progress(0)
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for i, page_num in enumerate(range(start_page, min(start_page + num_pages, doc.page_count))):
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status_text.text(f"Translating page {page_num + 1}...")
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#
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-
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cached_doc = get_cached_translation(cache_key)
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if cached_doc is not None:
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translated_pages.append(cached_doc)
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else:
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# Create a new PDF document for this page
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new_doc = pymupdf.open()
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new_doc.insert_pdf(doc, from_page=page_num, to_page=page_num)
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for block in blocks:
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bbox = block[:4]
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text = block[4]
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-
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# Translate the text
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translated = translator.translate(text)
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# Cover original text with white and add translation in color
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# Save to cache
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save_translation_cache(new_doc, cache_key)
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translated_pages.append(new_doc)
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# Update progress
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progress = (i + 1) /
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progress_bar.progress(progress)
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# Clear progress indicators
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progress_bar.empty()
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-
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return translated_pages
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def get_page_image(page, scale=2
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"""Get high quality image from PDF page"""
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# 计算缩放后的尺寸
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zoom = scale
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mat = pymupdf.Matrix(zoom, zoom)
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#
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pix = page.get_pixmap(
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return pix
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def main():
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st.set_page_config(layout="wide", page_title="PDF Translator for Human: with Local-LLM/GPT")
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st.title("PDF Translator for Human: with Local-LLM/GPT")
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index=0
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)
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#
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if translator_name
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st.subheader("
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target_lang = st.selectbox(
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"Target Language",
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options=list(LANGUAGE_OPTIONS.keys()),
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index=0
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)
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-
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-
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-
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-
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api_base = st.text_input(
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"API Base URL",
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value=os.getenv("OPENAI_API_BASE",
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)
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model = st.text_input(
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"Model Name",
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value=os.getenv("OPENAI_MODEL",
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)
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# Update environment variables
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os.environ["OPENAI_API_KEY"] = api_key
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os.environ["OPENAI_API_BASE"] = api_base
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os.environ["OPENAI_MODEL"] = model
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target_lang = LANGUAGE_OPTIONS[target_lang]
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else:
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# For Google Translator,
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target_lang_name = st.selectbox(
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"Target Language",
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options=list(SOURCE_LANGUAGE_OPTIONS.keys())[:-1], # Remove "Auto" option
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st.session_state.current_page = 0
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st.session_state.translation_started = True # 自动开始翻译
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# Display original pages immediately
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with col1:
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st.header("Original")
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pix = get_page_image(page)
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st.image(pix.tobytes(), caption=f"Page {st.session_state.current_page + i + 1}", use_container_width=True)
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-
# Navigation buttons
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-
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-
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if st.session_state.current_page > 0:
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-
if st.button("Previous Pages"):
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st.session_state.current_page = max(0, st.session_state.current_page - pages_per_load)
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st.rerun()
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-
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if st.session_state.current_page + pages_per_load < doc.page_count:
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-
if st.button("Next Pages"):
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st.session_state.current_page = min(
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doc.page_count - 1,
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st.session_state.current_page + pages_per_load
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)
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st.rerun()
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else:
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st.info("Please upload a PDF file to begin translation")
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import pymupdf
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from deep_translator import (
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GoogleTranslator,
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)
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from deep_translator.openai_compatible import OpenAICompatibleTranslator
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import logging
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# Constants
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DEFAULT_PAGES_PER_LOAD = 2
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# Supported translators
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TRANSLATORS = {
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'OpenAI': OpenAICompatibleTranslator,
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'OpenAI Compatible': OpenAICompatibleTranslator,
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'google': GoogleTranslator,
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}
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# Color options
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cache_dir.mkdir(exist_ok=True)
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return cache_dir
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def get_cache_key(doc_info: dict, page_num: int, translator_name: str, target_lang: str, text_content: str):
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"""Generate cache key for a specific page translation"""
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+
# 使用文档信息和页面内容的组合生成唯一标识
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content_hash = hashlib.md5(text_content.encode('utf-8')).hexdigest()[:8]
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doc_id = f"{doc_info.get('title', '')}_{doc_info.get('author', '')}_{doc_info.get('pagecount', '')}"
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doc_hash = hashlib.md5(doc_id.encode('utf-8')).hexdigest()[:8]
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return f"{doc_hash}_{content_hash}_page{page_num}_{translator_name}_{target_lang}.pdf"
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def get_cached_translation(cache_key: str) -> pymupdf.Document:
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"""Get cached translation if exists"""
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cache_path = get_cache_dir() / cache_key
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if cache_path.exists():
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try:
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return pymupdf.open(str(cache_path))
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except Exception as e:
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logging.error(f"Error loading cache: {str(e)}")
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return None
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return None
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def save_translation_cache(doc: pymupdf.Document, cache_key: str):
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"""Save translation to cache"""
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cache_path = get_cache_dir() / cache_key
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+
doc.save(str(cache_path)) # 确保提供文件路径字符串
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def translate_pdf_pages(doc, doc_bytes, start_page, num_pages, translator, text_color, translator_name, target_lang):
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"""Translate specific pages of a PDF document with progress and caching"""
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92 |
rgb_color = COLOR_MAP.get(text_color.lower(), COLOR_MAP["darkred"])
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translated_pages = []
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+
total_pages = min(start_page + num_pages, doc.page_count) - start_page
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cache_hits = 0
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# Create a progress bar
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progress_bar = st.progress(0)
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for i, page_num in enumerate(range(start_page, min(start_page + num_pages, doc.page_count))):
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status_text.text(f"Translating page {page_num + 1}...")
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# Extract text content for cache key
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page = doc[page_num]
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text_content = page.get_text("text")
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# Check cache first using text content
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cache_key = get_cache_key(
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doc.metadata,
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+
page_num,
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+
translator_name,
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+
target_lang,
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+
text_content
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)
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+
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cached_doc = get_cached_translation(cache_key)
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120 |
if cached_doc is not None:
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translated_pages.append(cached_doc)
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+
cache_hits += 1
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+
logging.info(f"Cache hit: Using cached translation for page {page_num + 1}")
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124 |
+
status_text.text(f"Using cached translation for page {page_num + 1}")
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125 |
else:
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126 |
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logging.info(f"Cache miss: Translating page {page_num + 1}")
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status_text.text(f"Translating page {page_num + 1} (not in cache)")
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+
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# Create a new PDF document for this page
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130 |
new_doc = pymupdf.open()
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131 |
new_doc.insert_pdf(doc, from_page=page_num, to_page=page_num)
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137 |
for block in blocks:
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bbox = block[:4]
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139 |
text = block[4]
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translated = translator.translate(text)
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141 |
|
142 |
# Cover original text with white and add translation in color
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150 |
# Save to cache
|
151 |
save_translation_cache(new_doc, cache_key)
|
152 |
translated_pages.append(new_doc)
|
153 |
+
logging.info(f"Cached new translation for page {page_num + 1}")
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154 |
|
155 |
# Update progress
|
156 |
+
progress = (i + 1) / total_pages
|
157 |
progress_bar.progress(progress)
|
158 |
|
159 |
+
# Clear progress indicators and show summary
|
160 |
progress_bar.empty()
|
161 |
+
if cache_hits > 0:
|
162 |
+
st.info(f"Used cache for {cache_hits} out of {total_pages} pages")
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163 |
|
164 |
return translated_pages
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165 |
|
166 |
+
def get_page_image(page, scale=2):
|
167 |
"""Get high quality image from PDF page"""
|
168 |
# 计算缩放后的尺寸
|
169 |
zoom = scale
|
170 |
mat = pymupdf.Matrix(zoom, zoom)
|
171 |
|
172 |
+
# 使用较低分辨率渲染页面,但保持清晰度
|
173 |
+
pix = page.get_pixmap(
|
174 |
+
matrix=mat,
|
175 |
+
alpha=False,
|
176 |
+
colorspace="rgb", # Use RGB instead of RGBA
|
177 |
+
)
|
178 |
|
179 |
return pix
|
180 |
|
181 |
+
def translate_all_pages(
|
182 |
+
input_doc,
|
183 |
+
output_doc,
|
184 |
+
translator,
|
185 |
+
progress_bar,
|
186 |
+
batch_size=1,
|
187 |
+
**kwargs
|
188 |
+
):
|
189 |
+
"""Translate all pages of the PDF document"""
|
190 |
+
# Define colors
|
191 |
+
WHITE = pymupdf.pdfcolor["white"]
|
192 |
+
rgb_color = COLOR_MAP.get(kwargs.get('text_color', 'darkred').lower(), COLOR_MAP["darkred"])
|
193 |
+
|
194 |
+
total_pages = input_doc.page_count
|
195 |
+
|
196 |
+
# Create a progress bar for overall progress
|
197 |
+
status_text = st.empty()
|
198 |
+
|
199 |
+
# Translate all pages using translate_pdf_pages
|
200 |
+
translated_pages = translate_pdf_pages(
|
201 |
+
input_doc,
|
202 |
+
None, # doc_bytes not needed as we're using text content for cache
|
203 |
+
0, # start from first page
|
204 |
+
total_pages, # translate all pages
|
205 |
+
translator,
|
206 |
+
kwargs.get('text_color', 'darkred'),
|
207 |
+
kwargs.get('translator_name', 'google'),
|
208 |
+
kwargs.get('target_lang', 'zh-CN')
|
209 |
+
)
|
210 |
+
|
211 |
+
# Combine all pages into one PDF with compression
|
212 |
+
output_path = kwargs.get('output_path', 'output.pdf')
|
213 |
+
for trans_doc in translated_pages:
|
214 |
+
output_doc.insert_pdf(trans_doc)
|
215 |
+
|
216 |
+
# Save with compression options
|
217 |
+
output_doc.save(
|
218 |
+
output_path,
|
219 |
+
garbage=4,
|
220 |
+
deflate=True,
|
221 |
+
clean=True,
|
222 |
+
linear=True
|
223 |
+
)
|
224 |
+
|
225 |
+
return output_doc
|
226 |
+
|
227 |
def main():
|
228 |
st.set_page_config(layout="wide", page_title="PDF Translator for Human: with Local-LLM/GPT")
|
229 |
st.title("PDF Translator for Human: with Local-LLM/GPT")
|
|
|
261 |
index=0
|
262 |
)
|
263 |
|
264 |
+
# OpenAI specific settings
|
265 |
+
if translator_name in ['OpenAI', 'OpenAI Compatible']:
|
266 |
+
st.subheader(f"{translator_name} Settings")
|
267 |
target_lang = st.selectbox(
|
268 |
"Target Language",
|
269 |
options=list(LANGUAGE_OPTIONS.keys()),
|
270 |
index=0
|
271 |
)
|
272 |
+
|
273 |
+
# Only show API key input if not set in environment
|
274 |
+
if not os.getenv("OPENAI_API_KEY"):
|
275 |
+
api_key = st.text_input(
|
276 |
+
"API Key",
|
277 |
+
value="",
|
278 |
+
type="password"
|
279 |
+
)
|
280 |
+
os.environ["OPENAI_API_KEY"] = api_key
|
281 |
+
|
282 |
+
# Different default API base for OpenAI and OpenAI Compatible
|
283 |
+
default_base = "https://api.openai.com/v1" if translator_name == 'OpenAI' else DEFAULT_API_BASE
|
284 |
api_base = st.text_input(
|
285 |
"API Base URL",
|
286 |
+
value=os.getenv("OPENAI_API_BASE", default_base)
|
287 |
)
|
288 |
+
|
289 |
+
# Different default model for OpenAI and OpenAI Compatible
|
290 |
+
default_model = "gpt-4o-mini" if translator_name == 'OpenAI' else DEFAULT_MODEL
|
291 |
model = st.text_input(
|
292 |
"Model Name",
|
293 |
+
value=os.getenv("OPENAI_MODEL", default_model)
|
294 |
)
|
295 |
|
296 |
# Update environment variables
|
|
|
297 |
os.environ["OPENAI_API_BASE"] = api_base
|
298 |
os.environ["OPENAI_MODEL"] = model
|
299 |
target_lang = LANGUAGE_OPTIONS[target_lang]
|
300 |
else:
|
301 |
+
# For Google Translator, show target language selection
|
302 |
target_lang_name = st.selectbox(
|
303 |
"Target Language",
|
304 |
options=list(SOURCE_LANGUAGE_OPTIONS.keys())[:-1], # Remove "Auto" option
|
|
|
319 |
st.session_state.current_page = 0
|
320 |
st.session_state.translation_started = True # 自动开始翻译
|
321 |
|
322 |
+
# Initialize translation status
|
323 |
+
if 'all_translated' not in st.session_state:
|
324 |
+
st.session_state.all_translated = False
|
325 |
+
if 'translated_doc' not in st.session_state:
|
326 |
+
st.session_state.translated_doc = None
|
327 |
+
|
328 |
# Display original pages immediately
|
329 |
with col1:
|
330 |
st.header("Original")
|
|
|
360 |
pix = get_page_image(page)
|
361 |
st.image(pix.tobytes(), caption=f"Page {st.session_state.current_page + i + 1}", use_container_width=True)
|
362 |
|
363 |
+
# Navigation and action buttons in one row
|
364 |
+
st.markdown("---") # Add a separator
|
365 |
+
button_col1, button_col2, button_col3, button_col4 = st.columns(4)
|
366 |
+
|
367 |
+
# Previous Pages button
|
368 |
+
with button_col1:
|
369 |
if st.session_state.current_page > 0:
|
370 |
+
if st.button("Previous Pages", use_container_width=True):
|
371 |
st.session_state.current_page = max(0, st.session_state.current_page - pages_per_load)
|
372 |
st.rerun()
|
373 |
+
else:
|
374 |
+
st.button("Previous Pages", disabled=True, use_container_width=True)
|
375 |
|
376 |
+
# Next Pages button
|
377 |
+
with button_col2:
|
378 |
if st.session_state.current_page + pages_per_load < doc.page_count:
|
379 |
+
if st.button("Next Pages", use_container_width=True):
|
380 |
st.session_state.current_page = min(
|
381 |
doc.page_count - 1,
|
382 |
st.session_state.current_page + pages_per_load
|
383 |
)
|
384 |
st.rerun()
|
385 |
+
else:
|
386 |
+
st.button("Next Pages", disabled=True, use_container_width=True)
|
387 |
+
|
388 |
+
# Translate All button
|
389 |
+
with button_col3:
|
390 |
+
if st.button("Translate All",
|
391 |
+
disabled=st.session_state.all_translated,
|
392 |
+
use_container_width=True):
|
393 |
+
# Configure translator
|
394 |
+
TranslatorClass = TRANSLATORS[translator_name]
|
395 |
+
translator = TranslatorClass(source=source_lang, target=target_lang)
|
396 |
+
|
397 |
+
# Translate all pages
|
398 |
+
output_doc = pymupdf.open()
|
399 |
+
output_path = f"translated_{uploaded_file.name}"
|
400 |
+
output_doc = translate_all_pages(
|
401 |
+
doc,
|
402 |
+
output_doc,
|
403 |
+
translator,
|
404 |
+
st.empty(),
|
405 |
+
pages_per_load,
|
406 |
+
text_color=text_color,
|
407 |
+
translator_name=translator_name,
|
408 |
+
target_lang=target_lang,
|
409 |
+
output_path=output_path # 提供输出路径
|
410 |
+
)
|
411 |
+
|
412 |
+
st.session_state.all_translated = True
|
413 |
+
st.session_state.translated_doc = output_path
|
414 |
+
st.rerun()
|
415 |
+
|
416 |
+
# Download button
|
417 |
+
with button_col4:
|
418 |
+
if not st.session_state.all_translated:
|
419 |
+
st.markdown(
|
420 |
+
"""
|
421 |
+
<div title="You can download the translated file after all content has been translated">
|
422 |
+
<button style="width: 100%" disabled>Download</button>
|
423 |
+
</div>
|
424 |
+
""",
|
425 |
+
unsafe_allow_html=True
|
426 |
+
)
|
427 |
+
else:
|
428 |
+
with open(st.session_state.translated_doc, "rb") as file:
|
429 |
+
st.download_button(
|
430 |
+
"Download",
|
431 |
+
file,
|
432 |
+
file_name=f"translated_{uploaded_file.name}",
|
433 |
+
mime="application/pdf",
|
434 |
+
use_container_width=True
|
435 |
+
)
|
436 |
else:
|
437 |
st.info("Please upload a PDF file to begin translation")
|
438 |
|