diff --git a/book_maker/translator/chatgptapi_translator.py b/book_maker/translator/chatgptapi_translator.py
index 02332ce..67c6239 100644
--- a/book_maker/translator/chatgptapi_translator.py
+++ b/book_maker/translator/chatgptapi_translator.py
@@ -361,106 +361,110 @@ class ChatGPTAPI(Base):
def translate_list(self, plist):
plist_len = len(plist)
- # Format input with explicit paragraph numbering
- formatted_paragraphs = []
+ # 创建原始文本列表，并为每个段落添加明确的编号标记
+ formatted_text = ""
for i, p in enumerate(plist, 1):
temp_p = copy(p)
for sup in temp_p.find_all("sup"):
sup.extract()
- formatted_paragraphs.append(f"{temp_p.get_text().strip()}")
-
- # Join with single newlines for cleaner input
- new_str = "\n".join(formatted_paragraphs)
+ para_text = temp_p.get_text().strip()
+ # 使用特殊的分隔符和明确的编号
+ formatted_text += f"PARAGRAPH {i}:\n{para_text}\n\n"
print(f"plist len = {plist_len}")
- # Save original prompt template
+ # 保存原始提示模板
original_prompt_template = self.prompt_template
- # Create a structured prompt that forces exact paragraph count and prevents merging
+ # 创建明确要求保持段落结构的提示
structured_prompt = (
f"Translate the following {plist_len} paragraphs to {{language}}. "
- f"CRUCIAL: Your output MUST contain EXACTLY {plist_len} paragraphs. "
- f"Each paragraph is wrapped in numbered tags like text. "
- f"DO NOT merge paragraphs. Keep each paragraph separate. "
- f"DO NOT combine multiple paragraphs into one. "
- f"Preserve numbers at the beginning of paragraphs like '17' or '10x'. "
- f"Each original paragraph should become exactly one translated paragraph. "
- f"Example output format: translated text for paragraph 1\ntranslated text for paragraph 2\n...\ntranslated text for paragraph {plist_len}"
+ f"CRUCIAL INSTRUCTION: Format your response using EXACTLY this structure:\n\n"
+ f"TRANSLATION OF PARAGRAPH 1:\n[Your translation of paragraph 1 here]\n\n"
+ f"TRANSLATION OF PARAGRAPH 2:\n[Your translation of paragraph 2 here]\n\n"
+ f"... and so on for all {plist_len} paragraphs.\n\n"
+ f"You MUST provide EXACTLY {plist_len} translated paragraphs. "
+ f"Do not merge, split, or rearrange paragraphs. "
+ f"Translate each paragraph independently but consistently. "
+ f"Keep all numbers and special formatting in your translation. "
+ f"Each original paragraph must correspond to exactly one translated paragraph."
)
- self.prompt_template = structured_prompt + " `{text}`"
+ self.prompt_template = structured_prompt + " ```{text}```"
- # First translation attempt
- translated_text = self.translate(new_str, False)
+ # 翻译
+ translated_text = self.translate(formatted_text, False)
- # Extract paragraphs using the tags
- result_list = self.extract_tagged_paragraphs(translated_text, plist_len)
-
- # If we still don't have the right number, try the retry approach
- start_time = time.time()
- if len(result_list) != plist_len:
- result_list, retry_count = self.get_best_result_list(
- plist_len,
- new_str,
- 6,
- result_list,
+ # 从结构化输出中提取翻译
+ translated_paragraphs = []
+ for i in range(1, plist_len + 1):
+ pattern = (
+ r"TRANSLATION OF PARAGRAPH "
+ + str(i)
+ + r":(.*?)(?=TRANSLATION OF PARAGRAPH \d+:|\Z)"
)
- else:
- retry_count = 0
+ matches = re.findall(pattern, translated_text, re.DOTALL)
- end_time = time.time()
+ if matches:
+ translated_paragraph = matches[0].strip()
+ translated_paragraphs.append(translated_paragraph)
+ else:
+ print(f"Warning: Could not find translation for paragraph {i}")
+ # 尝试更宽松的匹配
+ loose_pattern = (
+ r"(?:TRANSLATION|PARAGRAPH|PARA).*?"
+ + str(i)
+ + r".*?:(.*?)(?=(?:TRANSLATION|PARAGRAPH|PARA).*?\d+.*?:|\Z)"
+ )
+ loose_matches = re.findall(loose_pattern, translated_text, re.DOTALL)
+ if loose_matches:
+ translated_paragraphs.append(loose_matches[0].strip())
+ else:
+ translated_paragraphs.append("")
- # Restore original prompt
+ # 恢复原始提示
self.prompt_template = original_prompt_template
- # Clean up the results - strip any XML tags from the final output
- cleaned_result_list = []
- for paragraph in result_list:
- # Remove any XML tags that might be in the output
- cleaned_text = re.sub(r"(.*?)", r"\1", paragraph)
- # Also clean any partial tags
- cleaned_text = re.sub(r"", "", cleaned_text).strip()
- cleaned_result_list.append(cleaned_text)
-
- # Check for merged paragraphs and attempt to split them
- final_result_list = []
- for paragraph in cleaned_result_list:
- # If this is potentially a merged paragraph, try to split it
- if len(paragraph) > 200 and ". " in paragraph:
- # Look for sentence patterns that might indicate paragraph breaks
- potential_paragraphs = re.split(r"(?<=[.!?])\s+(?=[A-Z0-9])", paragraph)
- # Only split if it would help us get closer to the target paragraph count
- if (
- len(potential_paragraphs) > 1
- and len(final_result_list) + len(potential_paragraphs) <= plist_len
- ):
- final_result_list.extend(potential_paragraphs)
- continue
- final_result_list.append(paragraph)
-
- # Ensure we have exactly plist_len paragraphs
- if len(final_result_list) > plist_len:
- final_result_list = final_result_list[:plist_len]
- elif len(final_result_list) < plist_len:
- final_result_list.extend([""] * (plist_len - len(final_result_list)))
-
- # Log results
- state = "fail" if len(result_list) != plist_len else "success"
- log_path = "log/buglog.txt"
-
- self.log_retry(state, retry_count, end_time - start_time, log_path)
- if state == "fail":
- self.log_translation_mismatch(
- plist_len, result_list, new_str, "\n", log_path
+ # 如果提取到的段落数不正确，尝试备用提取方法
+ if len(translated_paragraphs) != plist_len:
+ print(
+ f"Warning: Extracted {len(translated_paragraphs)}/{plist_len} paragraphs. Using fallback extraction."
)
+ # 提取所有可能的段落标记
+ all_para_pattern = r"(?:TRANSLATION|PARAGRAPH|PARA).*?(\d+).*?:(.*?)(?=(?:TRANSLATION|PARAGRAPH|PARA).*?\d+.*?:|\Z)"
+ all_matches = re.findall(all_para_pattern, translated_text, re.DOTALL)
- # Remove ONLY the paragraph numbering formats, not all numbers at the start
- final_result_list = [
- re.sub(r"^(\(\d+\)|\d+\.)\s*", "", s) for s in final_result_list
- ]
+ if all_matches:
+ # 创建一个字典，根据段落编号映射翻译内容
+ para_dict = {}
+ for num_str, content in all_matches:
+ try:
+ num = int(num_str)
+ if 1 <= num <= plist_len:
+ para_dict[num] = content.strip()
+ except ValueError:
+ continue
- return final_result_list
+ # 按原始顺序重建翻译列表
+ new_translated_paragraphs = []
+ for i in range(1, plist_len + 1):
+ if i in para_dict:
+ new_translated_paragraphs.append(para_dict[i])
+ else:
+ new_translated_paragraphs.append("")
+
+ if len(new_translated_paragraphs) == plist_len:
+ translated_paragraphs = new_translated_paragraphs
+
+ # 确保最终有正确数量的段落
+ if len(translated_paragraphs) < plist_len:
+ translated_paragraphs.extend(
+ [""] * (plist_len - len(translated_paragraphs))
+ )
+ elif len(translated_paragraphs) > plist_len:
+ translated_paragraphs = translated_paragraphs[:plist_len]
+
+ return translated_paragraphs
def extract_tagged_paragraphs(self, text, plist_len):
"""Extract paragraphs from text with ... tags."""