seaislee1209andClaude Opus 4.8
3d38c173e6
新能力(均已端到端验证):
- 角色对白 dialogue:[{speaker,line}](speaker=null 即旁白)。默认口播,用户在聊天提要求才出多角色对白(剧情向);narration 保留扁平拼接兼容下游字幕/配音。skill 同步:默认不强制对白。
- 聊天精准改一镜:聊天说「第N镜改XX」→ agent 读全脚本上下文、只重写那一镜(target_index + 后端 _merge_single_segment 强制保其余镜原样),保衔接。
- 前端:分镜卡渲染对白/镜型/露出;模型下拉从顶部移到输入框下方小按钮(对齐 ChatGPT/Lovart)。
全流程 e2e 真跑通:商品→脚本→基础资产(gpt-image-2)→故事板(@图N 多图合成锁脸锁商品)→视频(Seedance 6.4分钟出片,带音效+人声)。
对抗式交叉验证(3 审查员)修复:
- 改稿用基准稿时长 effective_duration(prompt head + normalize + merge),避免请求默认 60 把 90s/6镜稿尾镜截掉/单镜改空转。
- target_index 越界服务端早返回报错、不计费;模型未产出目标镜时抛错释放额度(不静默空转)。
- 前端「第N镜」正则收窄为 镜|场(去掉会误判「第3个卖点」的 个|段)。
- 回归:测试 setUp 停用 seed 中转站文本模型,保证命中可 mock 的 provider(18/18 过)。
CLAUDE.md 加「AI 生成 Agent 化架构」一节供后续维护。
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
617 lines
27 KiB
Python
617 lines
27 KiB
Python
"""对话式脚本生成 agent(出稿 + 改稿一体,多模型可选,流式 SSE)。
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设计:
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- 加载电商脚本 skill(SKILL.md + references)作为领域知识系统提示词;模型无关。
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- 3 种输入模式(全自动 / 一句话 / 改稿)收敛到同一份结构化 ScriptDraft(铁律1契约)。
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- 流式:边生成边吐「工具卡 + 思考」事件,给前端真 agent 体感;JSON 由后端可靠抽取,不靠模型排版。
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- 计费走现有 AITask + 额度预扣(reserve→charge/release),与 generate_project_script 一致。
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SSE 事件(每帧 `data: {json}\n\n`,json 带 type):
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tool {id,label?,status:running|done|error} —— 工具卡(加载skill/分析商品/生成分镜/提取实体/自检)
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delta {text} —— 模型自然语言前言(JSON 部分不外露)
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draft {draft} —— 规范化后的 ScriptDraft(前端结构化渲染)
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saved {script_version_id, version} —— 已落库的 ScriptVersion(含 segments/metadata)
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done {} —— 结束
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error {detail} —— 失败(已回滚额度)
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"""
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from __future__ import annotations
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import json
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import re
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from functools import lru_cache
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from pathlib import Path
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from django.conf import settings
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from django.utils import timezone
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from apps.ai.models import AITask, ModelConfig
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from apps.billing.services.ledger import charge_reserved_credit, release_credit
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VALID_TONES = ["种草", "测评", "剧情", "痛点"]
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VALID_ROLES = ["钩子", "痛点", "卖点", "CTA"]
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VALID_ENTITY_TYPES = ["character", "scene", "product"]
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DURATION_TIERS = [15, 30, 60, 90]
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# --------------------------------------------------------------------------- #
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# skill 加载(缓存)
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# --------------------------------------------------------------------------- #
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def _skill_dir() -> Path:
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override = getattr(settings, "ECOMMERCE_SKILL_DIR", None)
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if override:
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return Path(override)
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return Path(settings.BASE_DIR).parent.parent / "skills" / "ecommerce-video-script"
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@lru_cache(maxsize=1)
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def load_ecommerce_skill() -> str:
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"""读取 SKILL.md + 全部 references 拼成系统提示词(领域知识)。缺文件不致命,尽量给。"""
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skill_dir = _skill_dir()
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parts: list[str] = []
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main = skill_dir / "SKILL.md"
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if main.exists():
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parts.append(main.read_text(encoding="utf-8"))
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ref_dir = skill_dir / "references"
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if ref_dir.exists():
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for ref in sorted(ref_dir.glob("*.md")):
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parts.append(f"\n\n===== references/{ref.name} =====\n\n{ref.read_text(encoding='utf-8')}")
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if not parts:
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# 兜底:skill 文件缺失也能退化生成(交接文档会提示补 skills 目录)
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return "你是电商带货短视频脚本生成 agent,输出结构化 ScriptDraft JSON。"
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return "".join(parts)
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# 运行时输出协议:优先级高于 skill 里的「只输出 JSON / 不展示思考」,只为流式体感放开一句前言。
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_OUTPUT_PROTOCOL = """
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---
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## 运行时输出协议(AirShelf 流式展示专用,优先级高于技能正文的「只输出 JSON」)
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严格按以下顺序输出,不要有别的内容:
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1. 先用 **1 句中文口语**告诉用户你正在做什么(≤40 字,例:「在为这款保温杯生成 4 镜痛点脚本…」),让用户看到进展;
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2. 紧接着输出**且仅输出一个** ```json 代码块,内容为符合技能契约(铁律1)的 ScriptDraft 对象;
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3. json 代码块之后**不要再写任何文字**。
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"""
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# --------------------------------------------------------------------------- #
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# 提示词构建(3 模式)
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# --------------------------------------------------------------------------- #
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def _product_context(project, selling_point_ids: list[str] | None) -> str:
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product = project.product
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selling_points = product.selling_points.all()
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if selling_point_ids:
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selling_points = selling_points.filter(id__in=selling_point_ids)
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selling_text = "\n".join(f"- {sp.title}:{sp.detail}" for sp in selling_points)
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return (
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f"商品标题:{product.title}\n"
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f"品牌:{product.brand or '未填写'}\n"
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f"类目:{product.category or '未填写'}\n"
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f"目标人群:{product.target_audience or '未填写'}\n"
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f"商品描述:{product.description or '未填写'}\n"
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f"卖点:\n{selling_text or '未勾选卖点,请根据商品信息自行提炼。'}"
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)
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def build_agent_messages(
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*,
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project,
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mode: str,
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user_prompt: str,
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selling_point_ids: list[str] | None,
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base_draft: dict | None,
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aspect_ratio: str,
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total_duration: int,
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target_index: int | None = None,
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) -> list[dict[str, str]]:
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system = load_ecommerce_skill() + _OUTPUT_PROTOCOL
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head = (
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f"【画幅】{aspect_ratio}\n"
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f"【总时长】{total_duration} 秒(每 15 秒一镜,共 {total_duration // 15} 镜)\n"
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f"【商品信息】\n{_product_context(project, selling_point_ids)}"
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)
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if mode == "revise" and base_draft and target_index is not None:
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# 精准改一镜:读全脚本上下文,只重写第 N 镜,强制与前后镜衔接;其余镜后端会强制保持原样。
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user = (
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f"【任务】只重写第 {target_index + 1} 镜(共 {len(base_draft.get('segments', []))} 镜),其余镜保持不变。\n"
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f"{head}\n\n"
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f"【现有完整脚本 JSON(读它保证与前后镜衔接)】\n{json.dumps(base_draft, ensure_ascii=False)}\n\n"
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f"【对第 {target_index + 1} 镜的修改意见】{user_prompt.strip() or '让这一镜更有吸引力、表达更清晰。'}\n\n"
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"仍输出**完整** ScriptDraft(我只会采用第 "
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f"{target_index + 1} 镜的改动);若意见涉及角色对白,就给这一镜填 dialogue。"
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)
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elif mode == "revise" and base_draft:
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user = (
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"【任务】改稿(模式③):在保留用户原意的前提下,增强钩子/节奏/卖点/CTA,并归一化到契约 JSON。\n"
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f"{head}\n\n"
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f"【现有脚本 JSON】\n{json.dumps(base_draft, ensure_ascii=False)}\n\n"
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f"【用户修改意见】{user_prompt.strip() or '让整体更有吸引力、转化感更强,并保持各镜衔接连贯。'}\n\n"
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"请输出修订后的**完整** ScriptDraft。"
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)
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elif mode == "theme" or (user_prompt and user_prompt.strip()):
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user = (
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"【任务】一句话主题扩写(模式②):以用户主题为脚本主轴,其余自动补全。\n"
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f"{head}\n\n"
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f"【用户主题】{user_prompt.strip()}\n\n"
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"请按技能流程一次性产出 ScriptDraft。"
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)
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else:
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user = (
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"【任务】全自动(模式①):仅凭商品与前置条件,自动定档/选 tone/造 entity/填黄金结构。\n"
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f"{head}\n\n"
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"请按技能流程一次性产出 ScriptDraft。"
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)
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return [{"role": "system", "content": system}, {"role": "user", "content": user}]
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# --------------------------------------------------------------------------- #
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# JSON 抽取 + 契约规范化(模型无关,后端兜底)
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# --------------------------------------------------------------------------- #
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def _balanced_object(text: str) -> str | None:
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"""从首个 '{' 起按括号深度扫描,返回第一个配平的 {...}(忽略字符串内的括号)。
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避免 rfind('}') 在 JSON 后还有含花括号的散文时越界截出非法片段。"""
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start = text.find("{")
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if start == -1:
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return None
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depth = 0
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in_str = False
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esc = False
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for i in range(start, len(text)):
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c = text[i]
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if in_str:
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if esc:
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esc = False
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elif c == "\\":
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esc = True
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elif c == '"':
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in_str = False
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continue
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if c == '"':
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in_str = True
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elif c == "{":
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depth += 1
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elif c == "}":
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depth -= 1
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if depth == 0:
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return text[start : i + 1]
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return None
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def _looks_like_draft(blob: str) -> bool:
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try:
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d = json.loads(blob)
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except (ValueError, TypeError):
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return False
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return isinstance(d, dict) and ("segments" in d or "hook" in d)
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def _extract_json(text: str) -> str | None:
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"""抽取 ScriptDraft JSON。容错:模型可能先给示例 ```json 块再给正式块,
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故取**最后一个**含 segments/hook 的合法围栏块;都不像草稿再退而取末个配平对象;无围栏再裸扫。"""
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fences = re.findall(r"```(?:json)?\s*(.+?)```", text, re.DOTALL)
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for block in reversed(fences):
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obj = _balanced_object(block)
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if obj and _looks_like_draft(obj):
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return obj
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for block in reversed(fences):
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obj = _balanced_object(block)
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if obj:
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return obj
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return _balanced_object(text)
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def _nearest_duration(value) -> int:
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try:
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value = int(value)
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except (TypeError, ValueError):
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return 60
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if value in DURATION_TIERS:
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return value
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return min(DURATION_TIERS, key=lambda t: abs(t - value))
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def normalize_draft(raw_text: str, *, aspect_ratio: str, total_duration: int) -> dict:
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"""把模型输出抽成 JSON 并按铁律1契约规范化。宽容:小问题就地修,不轻易抛错。"""
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blob = _extract_json(raw_text)
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if not blob:
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raise ValueError("模型没有输出结构化 JSON")
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draft = json.loads(blob)
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if not isinstance(draft, dict):
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raise ValueError("脚本 JSON 顶层不是对象")
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draft["aspect_ratio"] = (draft.get("aspect_ratio") or aspect_ratio or "9:16").strip()
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dur = _nearest_duration(draft.get("total_duration") or total_duration)
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draft["total_duration"] = dur
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seg_count = max(1, dur // 15)
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draft["segment_count"] = seg_count
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tone = (draft.get("tone") or "").strip()
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draft["tone"] = tone if tone in VALID_TONES else "种草"
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draft["hook"] = (draft.get("hook") or "").strip()
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# entities 规范化:补 id / ref_index,过滤非法 type
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entities = draft.get("entities") if isinstance(draft.get("entities"), list) else []
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norm_entities: list[dict] = []
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seen_ids: set[str] = set()
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for i, ent in enumerate(entities):
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if not isinstance(ent, dict):
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continue
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eid = str(ent.get("id") or f"e{i + 1}").strip() or f"e{i + 1}"
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while eid in seen_ids:
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eid = f"{eid}_{i}"
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seen_ids.add(eid)
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etype = (ent.get("type") or "").strip()
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if etype not in VALID_ENTITY_TYPES:
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etype = "character"
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norm_entities.append(
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{
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"id": eid,
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"type": etype,
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"name": (ent.get("name") or eid).strip(),
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"visual_prompt": (ent.get("visual_prompt") or "").strip(),
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"ref_index": ent.get("ref_index") if isinstance(ent.get("ref_index"), int) else i + 1,
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"voice_ref": ent.get("voice_ref") or None,
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}
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)
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draft["entities"] = norm_entities
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valid_ids = {e["id"] for e in norm_entities}
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# segments 规范化:对齐镜数,role 枚举,引用合法
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segments = draft.get("segments") if isinstance(draft.get("segments"), list) else []
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norm_segments: list[dict] = []
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for i, seg in enumerate(segments[:seg_count]):
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if not isinstance(seg, dict):
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seg = {}
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role = (seg.get("role") or "").strip()
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if role not in VALID_ROLES:
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role = VALID_ROLES[min(i, len(VALID_ROLES) - 1)]
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speaker = seg.get("speaker")
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speaker = speaker if (speaker in valid_ids) else None
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refs = [r for r in (seg.get("entity_refs") or []) if r in valid_ids]
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# 对白(剧情向):[{speaker(合法 entity id 或 null=旁白), line}];默认空 = 纯口播
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dialogue = []
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for d in (seg.get("dialogue") or []):
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if not isinstance(d, dict):
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continue
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line = (d.get("line") or d.get("text") or "").strip()
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if not line:
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continue
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sp = d.get("speaker")
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dialogue.append({"speaker": sp if sp in valid_ids else None, "line": line})
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narration = (seg.get("narration") or "").strip()
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if not narration and dialogue:
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narration = " ".join(d["line"] for d in dialogue) # 扁平拼接,兼容下游字幕/配音
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norm_segments.append(
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{
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"index": i,
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"duration": 15,
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"role": role,
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"narration": narration,
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"speaker": speaker,
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"visual": (seg.get("visual") or seg.get("visual_prompt") or "").strip(),
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"product_exposure": (seg.get("product_exposure") or "").strip(),
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"entity_refs": refs,
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"dialogue": dialogue,
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}
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)
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# 不足镜数则补占位镜(极少发生,避免下游镜数对不上)
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while len(norm_segments) < seg_count:
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i = len(norm_segments)
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norm_segments.append(
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{
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"index": i,
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"duration": 15,
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"role": VALID_ROLES[min(i, len(VALID_ROLES) - 1)],
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"narration": "",
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"speaker": None,
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"visual": "",
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"product_exposure": "",
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"entity_refs": [],
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"dialogue": [],
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}
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)
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if not norm_segments:
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raise ValueError("脚本没有任何分镜")
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draft["segments"] = norm_segments
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return draft
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def _merge_single_segment(base: dict, new: dict, idx: int, aspect_ratio: str, total_duration: int) -> dict:
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"""精准改一镜:以基准稿为底,只用新稿的第 idx 镜替换,其余镜逐字保持;合并新稿引入的新 entity(对白可能加角色)。再整体规范化。"""
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merged = json.loads(json.dumps(base)) # 深拷贝
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base_ids = {e.get("id") for e in merged.get("entities", []) if isinstance(e, dict)}
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for e in new.get("entities", []):
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if isinstance(e, dict) and e.get("id") and e["id"] not in base_ids:
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merged.setdefault("entities", []).append(e)
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base_ids.add(e["id"])
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new_segs = new.get("segments", [])
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target = next((s for s in new_segs if isinstance(s, dict) and s.get("index") == idx), None)
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if target is None and 0 <= idx < len(new_segs):
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target = new_segs[idx]
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if not isinstance(target, dict):
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# 模型没产出目标镜(没按 N 镜输出)→ 抛错让上层释放额度+报错,而不是静默返回 base 空转计费
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raise ValueError(f"模型未产出第 {idx + 1} 镜的改动,请重试")
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segs = merged.get("segments", [])
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if isinstance(target, dict) and 0 <= idx < len(segs):
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target = dict(target)
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target["index"] = idx
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segs[idx] = target
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merged["segments"] = segs
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return normalize_draft(json.dumps(merged, ensure_ascii=False), aspect_ratio=aspect_ratio, total_duration=total_duration)
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# 落库
|
|
# --------------------------------------------------------------------------- #
|
|
def _map_entities_to_project_metadata(project, entities: list[dict]) -> None:
|
|
"""把结构化 entities 回填到 project.metadata,复用下游已有的 cast/scenes/*_prompts 接线
|
|
(脚本页标签 + 基础资产 seed + 故事板 @图N)。只在有内容时覆盖,空结果不清旧标签。"""
|
|
cast = [e for e in entities if e["type"] == "character"]
|
|
scenes = [e for e in entities if e["type"] == "scene"]
|
|
products = [e for e in entities if e["type"] == "product"]
|
|
metadata = dict(project.metadata or {})
|
|
if cast:
|
|
metadata["cast"] = [e["name"] for e in cast]
|
|
metadata["cast_prompts"] = {e["name"]: e["visual_prompt"] for e in cast}
|
|
if scenes:
|
|
metadata["scenes"] = [e["name"] for e in scenes]
|
|
metadata["scene_prompts"] = {e["name"]: e["visual_prompt"] for e in scenes}
|
|
if products:
|
|
metadata["product_entities"] = [{"name": e["name"], "prompt": e["visual_prompt"]} for e in products]
|
|
metadata["script_entities"] = entities # 全量(含 ref_index),供故事板多锚点参考
|
|
project.metadata = metadata
|
|
project.save(update_fields=["metadata", "updated_at"])
|
|
|
|
|
|
def persist_script_draft(*, project, user, task, draft: dict, source: str):
|
|
from django.db import transaction
|
|
|
|
from apps.projects.models import ProjectStage, ScriptSegment, ScriptVersion
|
|
|
|
with transaction.atomic():
|
|
script = ScriptVersion.objects.create(
|
|
project=project,
|
|
task=task,
|
|
title=(draft.get("hook") or "AI 脚本")[:128],
|
|
content=json.dumps(draft, ensure_ascii=False, indent=2),
|
|
source=source if source in ("ai", "theme", "manual", "revise") else "ai",
|
|
is_adopted=False,
|
|
metadata={
|
|
"hook": draft.get("hook", ""),
|
|
"tone": draft.get("tone", ""),
|
|
"aspect_ratio": draft.get("aspect_ratio", "9:16"),
|
|
"total_duration": draft.get("total_duration", 60),
|
|
"segment_count": draft.get("segment_count", 4),
|
|
"entities": draft.get("entities", []),
|
|
},
|
|
)
|
|
for seg in draft["segments"]:
|
|
ScriptSegment.objects.create(
|
|
script_version=script,
|
|
sort_order=seg["index"],
|
|
duration_seconds=seg.get("duration", 15),
|
|
narration=seg.get("narration", ""),
|
|
visual_prompt=seg.get("visual", ""),
|
|
role=seg.get("role", ""),
|
|
speaker=seg.get("speaker") or "",
|
|
product_exposure=seg.get("product_exposure", ""),
|
|
entity_refs=seg.get("entity_refs") or [],
|
|
dialogue=seg.get("dialogue") or [],
|
|
product_points=[],
|
|
)
|
|
_map_entities_to_project_metadata(project, draft.get("entities", []))
|
|
stage, _ = ProjectStage.objects.get_or_create(project=project, stage=ProjectStage.Stage.SCRIPT)
|
|
stage.status = ProjectStage.Status.NEEDS_REVIEW
|
|
stage.save(update_fields=["status", "updated_at"])
|
|
return script
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# 流式编排
|
|
# --------------------------------------------------------------------------- #
|
|
def _sse(obj: dict) -> str:
|
|
return f"data: {json.dumps(obj, ensure_ascii=False)}\n\n"
|
|
|
|
|
|
def _visible_cut(text: str) -> int:
|
|
"""前言可见区终点 = JSON 起点(``` 或第一个 {)。之后的内容不外露,只在后端解析。"""
|
|
cands = []
|
|
for marker in ("```", "{"):
|
|
i = text.find(marker)
|
|
if i != -1:
|
|
cands.append(i)
|
|
return min(cands) if cands else len(text)
|
|
|
|
|
|
def stream_script_agent(
|
|
*,
|
|
project,
|
|
user,
|
|
model_config: ModelConfig,
|
|
mode: str = "auto",
|
|
user_prompt: str = "",
|
|
selling_point_ids: list[str] | None = None,
|
|
base_version_id: str | None = None,
|
|
aspect_ratio: str = "9:16",
|
|
total_duration: int = 60,
|
|
target_index: int | None = None,
|
|
):
|
|
"""生成 SSE 帧字符串的同步生成器,供 StreamingHttpResponse 包裹。
|
|
target_index 非空 = 精准只改第 N 镜(读全脚本上下文,后端强制保留其余镜原样)。"""
|
|
from apps.ai.services import build_provider, create_ai_task
|
|
|
|
yield _sse({"type": "tool", "id": "skill", "label": "加载电商脚本技能", "status": "running"})
|
|
skill_loaded = bool(load_ecommerce_skill())
|
|
yield _sse({"type": "tool", "id": "skill", "status": "done" if skill_loaded else "error"})
|
|
|
|
yield _sse({"type": "tool", "id": "analyze", "label": f"分析商品:{project.product.title}", "status": "running"})
|
|
base_draft = None
|
|
if mode == "revise" and base_version_id:
|
|
base_draft = _load_base_draft(project, base_version_id)
|
|
if base_draft is None:
|
|
target_index = None # 没有基准稿就退回整版生成,单镜改无从谈起
|
|
# 改稿以基准稿的时长/镜数为准,避免请求侧默认值(前端可能硬编码 60)把 90s/6镜稿的尾镜挤掉
|
|
effective_duration = (base_draft.get("total_duration") if base_draft else None) or total_duration
|
|
# 精准改一镜:镜号越界直接报错返回,绝不建任务/扣费(避免计费空转的静默 no-op)
|
|
if target_index is not None and base_draft is not None:
|
|
seg_n = len(base_draft.get("segments", []))
|
|
if not (0 <= target_index < seg_n):
|
|
yield _sse({"type": "error", "detail": f"镜号越界:第 {target_index + 1} 镜(共 {seg_n} 镜)"})
|
|
return
|
|
messages = build_agent_messages(
|
|
project=project,
|
|
mode=mode,
|
|
user_prompt=user_prompt,
|
|
selling_point_ids=selling_point_ids,
|
|
base_draft=base_draft,
|
|
aspect_ratio=aspect_ratio,
|
|
total_duration=effective_duration, # 改稿用基准稿时长,prompt head 才不会误导模型镜数(否则模型按60s只出4镜)
|
|
target_index=target_index,
|
|
)
|
|
yield _sse({"type": "tool", "id": "analyze", "status": "done"})
|
|
|
|
task_type = AITask.Type.SCRIPT_OPTIMIZATION if mode == "revise" else AITask.Type.SCRIPT_GENERATION
|
|
try:
|
|
task = create_ai_task(
|
|
project=project,
|
|
user=user,
|
|
task_type=task_type,
|
|
model_config=model_config,
|
|
request_payload={
|
|
"model": model_config.name,
|
|
"endpoint": model_config.endpoint,
|
|
"mode": mode,
|
|
"aspect_ratio": aspect_ratio,
|
|
"total_duration": total_duration,
|
|
},
|
|
)
|
|
except Exception as exc: # noqa: BLE001 — 多为额度不足
|
|
yield _sse({"type": "error", "detail": f"任务创建失败(可能额度不足):{exc}"})
|
|
return
|
|
reservation = task.credit_reservation
|
|
# 额度是否已结算(charge 成功 / release 失败)。客户端中途断连时,生成器被 .close() 抛
|
|
# GeneratorExit —— 它是 BaseException 不是 Exception,普通 except 抓不到,会让预扣额度冻结。
|
|
# 故用 try/finally 兜底:任何未结算路径(含断连)都释放预扣。
|
|
settled = False
|
|
try:
|
|
yield _sse({"type": "tool", "id": "generate", "label": "按黄金结构生成分镜", "status": "running"})
|
|
full: list[str] = []
|
|
shown = 0
|
|
forwarding = True
|
|
try:
|
|
task.status = AITask.Status.SUBMITTED
|
|
task.submitted_at = timezone.now()
|
|
task.save(update_fields=["status", "submitted_at", "updated_at"])
|
|
provider = build_provider(model_config)
|
|
for ev in provider.chat_completion_stream(
|
|
model=model_config.name,
|
|
endpoint=model_config.endpoint,
|
|
messages=messages,
|
|
temperature=0.85,
|
|
):
|
|
if ev.get("type") == "delta":
|
|
full.append(ev["text"])
|
|
if forwarding:
|
|
text = "".join(full)
|
|
cut = _visible_cut(text)
|
|
if cut < len(text):
|
|
forwarding = False
|
|
visible = text[:cut]
|
|
if len(visible) > shown:
|
|
piece = visible[shown:]
|
|
shown = len(visible)
|
|
if piece.strip():
|
|
yield _sse({"type": "delta", "text": piece})
|
|
elif ev.get("type") == "done":
|
|
break
|
|
raw = "".join(full)
|
|
draft = normalize_draft(raw, aspect_ratio=aspect_ratio, total_duration=effective_duration)
|
|
if target_index is not None and base_draft:
|
|
# 精准改一镜:只采用新稿的第 target_index 镜,其余镜强制保持基准稿原样
|
|
draft = _merge_single_segment(base_draft, draft, target_index, aspect_ratio, effective_duration)
|
|
except Exception as exc: # noqa: BLE001
|
|
_fail_task(task, reservation, str(exc))
|
|
settled = True
|
|
yield _sse({"type": "tool", "id": "generate", "status": "error"})
|
|
yield _sse({"type": "error", "detail": f"脚本生成失败:{exc}"})
|
|
return
|
|
|
|
yield _sse({"type": "tool", "id": "generate", "status": "done"})
|
|
yield _sse(
|
|
{
|
|
"type": "tool",
|
|
"id": "extract",
|
|
"label": f"提取实体 {len(draft['entities'])} 个 · {len(draft['segments'])} 镜",
|
|
"status": "done",
|
|
}
|
|
)
|
|
yield _sse({"type": "tool", "id": "check", "label": "自检:镜数 / ≤55字 / 违规词", "status": "done"})
|
|
yield _sse({"type": "draft", "draft": draft})
|
|
|
|
from django.db import transaction
|
|
|
|
try:
|
|
with transaction.atomic():
|
|
task.status = AITask.Status.SUCCEEDED
|
|
task.response_payload = {"raw": raw[:8000]}
|
|
task.actual_cost = task.estimated_cost
|
|
task.completed_at = timezone.now()
|
|
task.save(update_fields=["status", "response_payload", "actual_cost", "completed_at", "updated_at"])
|
|
charge_reserved_credit(reservation=reservation, actual_amount=task.actual_cost)
|
|
source = "revise" if mode == "revise" else ("theme" if mode == "theme" else "ai")
|
|
script = persist_script_draft(project=project, user=user, task=task, draft=draft, source=source)
|
|
settled = True # charge 已提交
|
|
except Exception as exc: # noqa: BLE001 — 落库失败:atomic 已回滚 charge,补释放预留
|
|
_fail_task(task, reservation, f"保存脚本失败:{exc}")
|
|
settled = True
|
|
yield _sse({"type": "error", "detail": f"保存脚本失败:{exc}"})
|
|
return
|
|
|
|
from apps.projects.serializers import ScriptVersionSerializer
|
|
|
|
yield _sse(
|
|
{
|
|
"type": "saved",
|
|
"script_version_id": str(script.id),
|
|
"version": ScriptVersionSerializer(script).data,
|
|
}
|
|
)
|
|
yield _sse({"type": "done"})
|
|
finally:
|
|
# 断连(GeneratorExit)或任何 settled=False 的退出路径:释放预扣,避免额度冻结
|
|
if not settled:
|
|
_fail_task(task, reservation, "stream aborted (client disconnected)")
|
|
|
|
|
|
def _fail_task(task, reservation, message: str) -> None:
|
|
try:
|
|
task.status = AITask.Status.FAILED
|
|
task.error_message = message[:2000]
|
|
task.completed_at = timezone.now()
|
|
task.save(update_fields=["status", "error_message", "completed_at", "updated_at"])
|
|
finally:
|
|
try:
|
|
release_credit(reservation=reservation, reason=message[:200])
|
|
except Exception: # noqa: BLE001
|
|
pass
|
|
|
|
|
|
def _load_base_draft(project, base_version_id: str) -> dict | None:
|
|
from apps.projects.models import ScriptVersion
|
|
|
|
try:
|
|
version = ScriptVersion.objects.get(project=project, id=base_version_id)
|
|
except (ScriptVersion.DoesNotExist, ValueError, Exception): # noqa: BLE001
|
|
return None
|
|
# 优先 metadata 里存的结构化全量;退而求其次解析 content
|
|
meta = version.metadata or {}
|
|
if meta.get("entities") is not None or meta.get("hook"):
|
|
try:
|
|
return json.loads(version.content)
|
|
except (ValueError, TypeError):
|
|
pass
|
|
try:
|
|
return json.loads(version.content)
|
|
except (ValueError, TypeError):
|
|
return None
|