feat: improve character preview generation and adjust emotion handling guidelines in LLM service
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@@ -561,6 +561,19 @@ async def generate_project(project_id: int, user: User, db: Session, chapter_ind
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if preview_path.exists():
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ref_audio = str(preview_path)
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if not ref_audio or not Path(ref_audio).exists():
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logger.info(f"No ref audio for char {char.id}, generating preview on-demand...")
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try:
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await generate_character_preview(project_id, char.id, user, db)
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db.refresh(design)
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ref_audio = design.ref_audio_path
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if not ref_audio or not Path(ref_audio).exists():
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preview_path = Path(settings.OUTPUT_DIR) / "audiobook" / str(project_id) / "previews" / f"char_{char.id}.wav"
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if preview_path.exists():
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ref_audio = str(preview_path)
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except Exception as prev_e:
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logger.error(f"On-demand preview generation failed for char {char.id}: {prev_e}")
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if not ref_audio or not Path(ref_audio).exists():
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logger.error(f"No ref audio for char {char.id}, skipping segment {seg.id}")
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crud.update_audiobook_segment_status(db, seg.id, "error")
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@@ -572,7 +585,7 @@ async def generate_project(project_id: int, user: User, db: Session, chapter_ind
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spk_audio_prompt=ref_audio,
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output_path=str(audio_path),
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emo_text=seg.emo_text or None,
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emo_alpha=seg.emo_alpha if seg.emo_alpha is not None else 0.6,
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emo_alpha=seg.emo_alpha if seg.emo_alpha is not None else 0.3,
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)
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with open(audio_path, "wb") as f:
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@@ -654,7 +667,7 @@ async def generate_single_segment(segment_id: int, user: User, db: Session) -> N
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spk_audio_prompt=ref_audio,
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output_path=str(audio_path),
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emo_text=seg.emo_text or None,
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emo_alpha=seg.emo_alpha if seg.emo_alpha is not None else 0.6,
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emo_alpha=seg.emo_alpha if seg.emo_alpha is not None else 0.3,
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)
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with open(audio_path, "wb") as f:
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@@ -838,7 +851,11 @@ async def generate_character_preview(project_id: int, char_id: int, user: User,
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backend_type = user.user_preferences.get("default_backend", "aliyun") if user.user_preferences else "aliyun"
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user_api_key = None
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if backend_type == "aliyun" and user.aliyun_api_key:
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if backend_type == "aliyun":
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encrypted = crud.get_system_setting(db, "aliyun_api_key")
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if encrypted:
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user_api_key = decrypt_api_key(encrypted)
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elif user.aliyun_api_key:
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user_api_key = decrypt_api_key(user.aliyun_api_key)
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backend = await TTSServiceFactory.get_backend(backend_type, user_api_key)
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@@ -218,15 +218,14 @@ class LLMService:
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"你是一个专业的有声书制作助手。请将给定的章节文本解析为对话片段列表。"
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f"已知角色列表(必须从中选择):{names_str}。"
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"所有非对话的叙述文字归属于narrator角色。\n"
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"同时根据语境为每个片段判断情绪类型和强度(emo_alpha)。\n"
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"可选情绪:开心、愤怒、悲伤、恐惧、厌恶、低沉、惊讶、中性。\n"
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"强度参考值(仅供参考,请根据实际语境自行判断):开心≈0.4、愤怒≈0.08、悲伤≈0.1、恐惧≈0.1、厌恶≈0.4、低沉≈0.4、惊讶≈0.3、中性≈0.3。\n"
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"强度建议控制在0.5以下,情绪越激烈越应克制,强烈情绪不超过0.45。\n"
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"同一角色的连续台词,情绪应尽量保持一致或仅有微弱变化,避免情绪在相邻片段间跳跃。\n"
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"narrator旁白及情绪不明显的片段,emo_text设为\"\",emo_alpha设为0.3。\n"
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"同时根据语境为每个片段判断是否有明显情绪,有则设置情绪类型(emo_text)和强度(emo_alpha),无则留空。\n"
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"可选情绪:开心、愤怒、悲伤、恐惧、厌恶、低沉、惊讶。\n"
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"情绪不明显或narrator旁白时,emo_text设为\"\",emo_alpha设为0。\n"
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"各情绪强度上限(严格不超过):开心=0.35、愤怒=0.15、悲伤=0.1、恐惧=0.1、厌恶=0.35、低沉=0.35、惊讶=0.1。\n"
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"同一角色的连续台词,情绪应尽量保持一致或仅有微弱变化,避免相邻片段间情绪跳跃。\n"
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"只输出JSON数组,不要有其他文字,格式如下:\n"
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'[{"character": "narrator", "text": "叙述文字", "emo_text": "", "emo_alpha": 0.3}, '
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'{"character": "角色名", "text": "对话内容", "emo_text": "开心", "emo_alpha": 0.4}, ...]'
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'[{"character": "narrator", "text": "叙述文字", "emo_text": "", "emo_alpha": 0}, '
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'{"character": "角色名", "text": "对话内容", "emo_text": "开心", "emo_alpha": 0.3}, ...]'
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)
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user_message = f"请解析以下章节文本:\n\n{chapter_text}"
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result = await self.stream_chat_json(system_prompt, user_message, on_token, max_tokens=16384, usage_callback=usage_callback)
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