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feat(audiobook): add turbo mode for project analysis and enhance log streaming with chapter support

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bdim404
2026-03-10 17:01:50 +08:00
parent 11d44fd0be
commit 006aa0c85f
8 changed files with 126 additions and 68 deletions
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65
qwen3-tts-backend/core/audiobook_service.py
View File

@@ -125,25 +125,26 @@ def _split_into_chapters(text: str) -> list[str]:
return chapters
async def analyze_project(project_id: int, user: User, db: Session) -> None:
async def analyze_project(project_id: int, user: User, db: Session, turbo: bool = False) -> None:
project = db.query(AudiobookProject).filter(AudiobookProject.id == project_id).first()
if not project:
return
ps.reset(project_id)
key = str(project_id)
ps.reset(key)
try:
crud.update_audiobook_project_status(db, project_id, "analyzing")
ps.append_line(project_id, f"[分析] 项目「{project.title}」开始角色分析")
ps.append_line(key, f"[分析] 项目「{project.title}」开始角色分析")
llm = _get_llm_service(user)
if project.source_type == "epub" and project.source_path:
ps.append_line(project_id, "[解析] 正在提取 EPUB 章节内容...")
ps.append_line(key, "[解析] 正在提取 EPUB 章节内容...")
epub_chapters = _extract_epub_chapters(project.source_path)
if not epub_chapters:
raise ValueError("No text content extracted from epub.")
text = "\n\n".join(epub_chapters)
ps.append_line(project_id, f"[解析] 提取完成，共 {len(epub_chapters)} 章，{len(text)} 字")
ps.append_line(key, f"[解析] 提取完成，共 {len(epub_chapters)} 章，{len(text)} 字")
project.source_text = text
db.commit()
else:
@@ -154,20 +155,26 @@ async def analyze_project(project_id: int, user: User, db: Session) -> None:
samples = _sample_full_text(text)
n = len(samples)
ps.append_line(project_id, f"\n[LLM] 模型：{user.llm_model}，共 {n} 个采样段，正在分析角色...\n")
ps.append_line(project_id, "")
mode_label = "极速并发" if turbo else "顺序"
ps.append_line(key, f"\n[LLM] 模型：{user.llm_model}，共 {n} 个采样段（{mode_label}模式），正在分析角色...\n")
ps.append_line(key, "")
def on_token(token: str) -> None:
ps.append_token(project_id, token)
ps.append_token(key, token)
def on_sample(i: int, total: int) -> None:
if i < total - 1:
ps.append_line(project_id, f"\n[LLM] 采样段 {i + 1}/{total} 完成，继续分析...\n")
ps.append_line(key, f"\n[LLM] 采样段 {i + 1}/{total} 完成，继续分析...\n")
else:
ps.append_line(project_id, f"\n[LLM] 全部 {total} 个采样段完成，正在合并角色列表...\n")
ps.append_line(project_id, "")
ps.append_line(key, f"\n[LLM] 全部 {total} 个采样段完成，正在合并角色列表...\n")
ps.append_line(key, "")
characters_data = await llm.extract_characters(samples, on_token=on_token, on_sample=on_sample)
characters_data = await llm.extract_characters(
samples,
on_token=on_token,
on_sample=on_sample,
turbo=turbo,
)
has_narrator = any(c.get("name") == "narrator" for c in characters_data)
if not has_narrator:
@@ -177,7 +184,7 @@ async def analyze_project(project_id: int, user: User, db: Session) -> None:
"instruct": "中性声音，语速平稳，叙述感强"
})
ps.append_line(project_id, f"\n\n[完成] 发现 {len(characters_data)} 个角色：{', '.join(c.get('name', '') for c in characters_data)}")
ps.append_line(key, f"\n\n[完成] 发现 {len(characters_data)} 个角色：{', '.join(c.get('name', '') for c in characters_data)}")
crud.delete_audiobook_segments(db, project_id)
crud.delete_audiobook_characters(db, project_id)
@@ -208,13 +215,13 @@ async def analyze_project(project_id: int, user: User, db: Session) -> None:
)
crud.update_audiobook_project_status(db, project_id, "characters_ready")
ps.mark_done(project_id)
ps.mark_done(key)
logger.info(f"Project {project_id} character extraction complete: {len(characters_data)} characters")
except Exception as e:
logger.error(f"Analysis failed for project {project_id}: {e}", exc_info=True)
ps.append_line(project_id, f"\n[错误] {e}")
ps.mark_done(project_id)
ps.append_line(key, f"\n[错误] {e}")
ps.mark_done(key)
crud.update_audiobook_project_status(db, project_id, "error", error_message=str(e))
@@ -246,12 +253,12 @@ def identify_chapters(project_id: int, db, project) -> None:
async def parse_one_chapter(project_id: int, chapter_id: int, user: User, db) -> None:
from db.models import AudiobookChapter as ChapterModel
chapter = crud.get_audiobook_chapter(db, chapter_id)
if not chapter:
return
ps.reset(project_id)
key = f"ch_{chapter_id}"
ps.reset(key)
try:
crud.update_audiobook_chapter_status(db, chapter_id, "parsing")
@@ -264,26 +271,26 @@ async def parse_one_chapter(project_id: int, chapter_id: int, user: User, db) ->
character_names = list(char_map.keys())
label = chapter.title or f"第 {chapter.chapter_index + 1} 章"
ps.append_line(project_id, f"[{label}] 开始解析 ({len(chapter.source_text)} 字)")
ps.append_line(key, f"[{label}] 开始解析 ({len(chapter.source_text)} 字)")
crud.delete_audiobook_segments_for_chapter(db, project_id, chapter.chapter_index)
chunks = _chunk_chapter(chapter.source_text, max_chars=4000)
ps.append_line(project_id, f"共 {len(chunks)} 块\n")
ps.append_line(key, f"共 {len(chunks)} 块\n")
seg_counter = 0
for i, chunk in enumerate(chunks):
ps.append_line(project_id, f"块 {i + 1}/{len(chunks)} → ")
ps.append_line(project_id, "")
ps.append_line(key, f"块 {i + 1}/{len(chunks)} → ")
ps.append_line(key, "")
def on_token(token: str) -> None:
ps.append_token(project_id, token)
ps.append_token(key, token)
try:
segments_data = await llm.parse_chapter_segments(chunk, character_names, on_token=on_token)
except Exception as e:
logger.warning(f"Chapter {chapter_id} chunk {i} failed: {e}")
ps.append_line(project_id, f"\n[回退] {e}")
ps.append_line(key, f"\n[回退] {e}")
narrator = char_map.get("narrator")
if narrator:
crud.create_audiobook_segment(
@@ -308,17 +315,17 @@ async def parse_one_chapter(project_id: int, chapter_id: int, user: User, db) ->
seg_counter += 1
chunk_count += 1
ps.append_line(project_id, f"\n✓ {chunk_count} 段")
ps.append_line(key, f"\n✓ {chunk_count} 段")
ps.append_line(project_id, f"\n[完成] 共 {seg_counter} 段")
ps.append_line(key, f"\n[完成] 共 {seg_counter} 段")
crud.update_audiobook_chapter_status(db, chapter_id, "ready")
ps.mark_done(project_id)
ps.mark_done(key)
logger.info(f"Chapter {chapter_id} parsed: {seg_counter} segments")
except Exception as e:
logger.error(f"parse_one_chapter {chapter_id} failed: {e}", exc_info=True)
ps.append_line(project_id, f"\n[错误] {e}")
ps.mark_done(project_id)
ps.append_line(key, f"\n[错误] {e}")
ps.mark_done(key)
crud.update_audiobook_chapter_status(db, chapter_id, "error", error_message=str(e))

23
qwen3-tts-backend/core/llm_service.py
View File

@@ -1,3 +1,4 @@
import asyncio
import json
import logging
from typing import Any, Dict
@@ -115,7 +116,7 @@ class LLMService:
logger.error(f"JSON parse failed. Raw response (first 500 chars): {raw[:500]}")
raise
async def extract_characters(self, text_samples: list[str], on_token=None, on_sample=None) -> list[Dict]:
async def extract_characters(self, text_samples: list[str], on_token=None, on_sample=None, turbo: bool = False) -> list[Dict]:
system_prompt = (
"你是一个专业的小说分析助手兼声音导演。请分析给定的小说文本，提取所有出现的角色（包括旁白narrator）。\n"
"对每个角色，instruct字段必须是详细的声音导演说明，需覆盖以下六个维度，每个维度单独一句，用换行分隔：\n"
@@ -128,6 +129,26 @@ class LLMService:
"只输出JSON，格式如下，不要有其他文字：\n"
'{"characters": [{"name": "narrator", "description": "第三人称叙述者", "instruct": "音色信息：...\\n身份背景：...\\n年龄设定：...\\n外貌特征：...\\n性格特质：...\\n叙事风格：..."}, ...]}'
)
if turbo and len(text_samples) > 1:
logger.info(f"Extracting characters in turbo mode: {len(text_samples)} samples concurrent")
async def _extract_one(sample: str) -> list[Dict]:
user_message = f"请分析以下小说文本并提取角色：\n\n{sample}"
result = await self.stream_chat_json(system_prompt, user_message, None)
return result.get("characters", [])
results = await asyncio.gather(
*[_extract_one(s) for s in text_samples],
return_exceptions=True,
)
raw_all: list[Dict] = []
for i, r in enumerate(results):
if isinstance(r, Exception):
logger.warning(f"Character extraction failed for sample {i+1}: {r}")
else:
raw_all.extend(r)
return await self.merge_characters(raw_all)
raw_all: list[Dict] = []
for i, sample in enumerate(text_samples):
logger.info(f"Extracting characters from sample {i+1}/{len(text_samples)}")

30
qwen3-tts-backend/core/progress_store.py
View File

@@ -1,38 +1,38 @@
from typing import Dict
_store: Dict[int, dict] = {}
_store: Dict[str, dict] = {}
def _ensure(project_id: int) -> dict:
if project_id not in _store:
_store[project_id] = {"lines": [], "done": False}
return _store[project_id]
def _ensure(key: str) -> dict:
if key not in _store:
_store[key] = {"lines": [], "done": False}
return _store[key]
def reset(project_id: int) -> None:
_store[project_id] = {"lines": [], "done": False}
def reset(key: str) -> None:
_store[key] = {"lines": [], "done": False}
def append_line(project_id: int, text: str) -> None:
s = _ensure(project_id)
def append_line(key: str, text: str) -> None:
s = _ensure(key)
s["lines"].append(text)
def append_token(project_id: int, token: str) -> None:
s = _ensure(project_id)
def append_token(key: str, token: str) -> None:
s = _ensure(key)
if s["lines"]:
s["lines"][-1] += token
else:
s["lines"].append(token)
def mark_done(project_id: int) -> None:
s = _ensure(project_id)
def mark_done(key: str) -> None:
s = _ensure(key)
s["done"] = True
def get_snapshot(project_id: int) -> dict:
s = _store.get(project_id)
def get_snapshot(key: str) -> dict:
s = _store.get(key)
if not s:
return {"lines": [], "done": True}
return {"lines": list(s["lines"]), "done": s["done"]}