from __future__ import annotations from typing import Dict, TYPE_CHECKING from pathlib import Path import random if TYPE_CHECKING: from src.classes.avatar import Avatar from src.utils.config import CONFIG from src.utils.llm import call_llm_with_task_name from src.classes.relation.relations import ( process_relation_changes, get_relation_change_context ) from src.i18n import t story_styles = [ "Plain narration: Restrained language, minimal embellishment, recording like a bystander.", "Emotion in scenery: Expressing emotion through scenery, blending feelings with the setting.", "Freehand ancient style: Focus on imagery and metaphor, concise, avoiding obscure archaic language.", "Marketplace life: Grounded writing, using colloquialisms, simple and natural, without pretension.", "Poetic lyricism: Short sentences and parallelism, sparse use of allusions, avoiding flowery language.", "Philosophical fable: Asking questions through events, containing one or two punchlines, without preaching.", "Chronicle style: Like a historian's record, orderly events, few adjectives.", "Personification of scenery: Slight personification of scenery, embedding aspirations in the view, not overused.", "Taoist nature: Tinted with Taoist vocabulary, not obscure, focusing on a single thought.", "Buddhist emptiness: Insights of impermanence and emptiness interwoven, light and not mysterious.", "Folk storytelling: Like a storyteller's tone but in written language, fast-paced, vivid and interesting.", "Elegant scholarly: Scholarly atmosphere, slight touch of citations, without showing off.", "Bold and open: Grand words, majestic momentum, informal, expressing feelings directly.", "Gorgeous and bizarre: Heavy sensory description, ornate and seductive language, emphasizing the strangeness of light and color.", "Cold and concise: Mainly short sentences, every word counts, like metal striking stone, no extra emotional rendering.", "Fine line drawing: No decoration, capturing subtle movements and expressions to convey spirit, real and delicate.", ] class StoryTeller: """ 故事生成器：基于模板与 LLM，将给定事件扩展为简短的小故事。 同时负责处理可能的后天关系变化。 """ TEMPLATE_SINGLE_FILE = "story_single.txt" TEMPLATE_DUAL_FILE = "story_dual.txt" TEMPLATE_GATHERING_FILE = "story_gathering.txt" @staticmethod def _get_template_path(filename: str) -> Path: """获取当前语言环境下的模板路径""" return CONFIG.paths.templates / filename @staticmethod def _build_avatar_infos(*actors: "Avatar") -> Dict[str, dict]: """ 构建角色信息字典。 - 双人故事：第一个角色使用 expanded_info（包含共同事件），第二个使用普通 info - 单人故事：使用 expanded_info """ non_null = [a for a in actors if a is not None] avatar_infos: Dict[str, dict] = {} if len(non_null) >= 2: avatar_infos[non_null[0].name] = non_null[0].get_expanded_info(other_avatar=non_null[1], detailed=True) avatar_infos[non_null[1].name] = non_null[1].get_info(detailed=True) elif non_null: avatar_infos[non_null[0].name] = non_null[0].get_expanded_info(detailed=True) return avatar_infos @staticmethod def _build_template_data(event: str, res: str, avatar_infos: Dict[str, dict], prompt: str, *actors: "Avatar") -> dict: """构建模板渲染所需的数据字典""" # 默认空关系列表 avatar_name_1 = "" avatar_name_2 = "" world_info = actors[0].world.static_info # 如果有两个有效角色，计算可能的关系 non_null = [a for a in actors if a is not None] if len(non_null) >= 2: avatar_name_1 = non_null[0].name avatar_name_2 = non_null[1].name return { "world_info": world_info, "avatar_infos": avatar_infos, "avatar_name_1": avatar_name_1, "avatar_name_2": avatar_name_2, "event": event, "res": res, "style": t(random.choice(story_styles)), "story_prompt": prompt, } @staticmethod def _make_fallback_story(event: str, res: str, style: str) -> str: """生成降级文案""" # 不再显示 style，避免出戏 return f"{event}。{res}。" @staticmethod async def tell_story(event: str, res: str, *actors: "Avatar", prompt: str = "", allow_relation_changes: bool = False) -> str: """ 生成小故事（异步版本）。 根据 allow_relation_changes 参数选择模板： - True: 使用 story_dual.txt，支持关系变化（需要至少2个角色） - False: 使用 story_single.txt，仅生成故事（无论角色数量） Args: event: 事件描述 res: 结果描述 *actors: 参与的角色（1-2个） prompt: 可选的故事提示词 allow_relation_changes: 是否允许故事导致关系变化，默认为False（单人模式） """ non_null = [a for a in actors if a is not None] # 只有当允许关系变化且有至少2个角色时，才使用双人模板 is_dual = allow_relation_changes and len(non_null) >= 2 template_file = StoryTeller.TEMPLATE_DUAL_FILE if is_dual else StoryTeller.TEMPLATE_SINGLE_FILE template_path = StoryTeller._get_template_path(template_file) avatar_infos = StoryTeller._build_avatar_infos(*actors) infos = StoryTeller._build_template_data(event, res, avatar_infos, prompt, *actors) # 移除了 try-except 块，允许异常向上冒泡，以便 Fail Fast data = await call_llm_with_task_name("story_teller", template_path, infos) story = data.get("story", "").strip() if story: return story return StoryTeller._make_fallback_story(event, res, infos["style"]) @staticmethod async def tell_gathering_story( gathering_info: str, events_text: str, details_text: str, related_avatars: list["Avatar"], prompt: str = "" ) -> str: """ 生成聚会/拍卖会等多人事件的故事。 通用接口，适配 story_gathering.txt 模板。 Args: gathering_info: 事件本身的设定信息（如地点、背景、规则等） events_text: 发生的具体事件/交互记录 details_text: 详细信息（包括角色信息、物品信息等） related_avatars: 参与的角色列表（主要用于获取世界背景信息） prompt: 额外提示词 """ if not related_avatars: return events_text # 使用第一个角色的世界信息 world_info = related_avatars[0].world.static_info infos = { "world_info": world_info, "gathering_info": gathering_info, "events": events_text, "details": details_text, "style": t(random.choice(story_styles)), "story_prompt": prompt } # 增加 token 上限以支持长故事 template_path = StoryTeller._get_template_path(StoryTeller.TEMPLATE_GATHERING_FILE) data = await call_llm_with_task_name("story_teller", template_path, infos) story = data.get("story", "").strip() if story: return story return events_text __all__ = ["StoryTeller"]