feat: 新增文件

engine/script_gen.py

@@ -0,0 +1,80 @@
+from __future__ import annotations
+
+import json
+import os
+from typing import Any
+
+from openai import OpenAI
+
+from .config import AppConfig
+from .types import Scene
+
+
+def _system_prompt(scene_count: int, min_chars: int, max_chars: int) -> str:
+    return f"""你是一个专业短视频编剧与分镜师。
+请把用户的创意扩展为 {scene_count} 个分镜(Scene) 的 JSON。
+
+硬性约束：
+1) 三个分镜的主角描述（Character Description）必须保持一致：姓名/外观/服饰/风格不可前后矛盾。
+2) 每个分镜必须包含字段：image_prompt, video_motion, narration。
+3) narration 为中文旁白，每段严格控制在约 {min_chars}-{max_chars} 字左右（宁可略短，不要超过太多）。
+4) 画面描述要具体可视化，video_motion 描述镜头运动/人物动作。
+5) 只输出 JSON，不要输出任何解释、markdown、代码块。
+
+输出 JSON Schema（示例结构）：
+{{
+  "character_description": "...一致的主角设定...",
+  "scenes": [
+    {{"image_prompt":"...","video_motion":"...","narration":"..."}},
+    {{"image_prompt":"...","video_motion":"...","narration":"..."}},
+    {{"image_prompt":"...","video_motion":"...","narration":"..."}}
+  ]
+}}
+"""
+
+
+def generate_scenes(user_prompt: str, cfg: AppConfig) -> list[Scene]:
+    scene_count = int(cfg.get("script_gen.scene_count", 3))
+    min_chars = int(cfg.get("script_gen.narration_min_chars", 15))
+    max_chars = int(cfg.get("script_gen.narration_max_chars", 20))
+
+    api_key_env = str(cfg.get("openai.api_key_env", "OPENAI_API_KEY"))
+    base_url_env = str(cfg.get("openai.base_url_env", "OPENAI_BASE_URL"))
+    model = str(cfg.get("openai.model", "gpt-4o-mini"))
+
+    api_key = os.environ.get(api_key_env)
+    if not api_key:
+        raise RuntimeError(f"Missing env var {api_key_env} for OpenAI API key")
+
+    client = OpenAI(
+        api_key=api_key,
+        base_url=os.environ.get(base_url_env) or None,
+    )
+
+    resp = client.chat.completions.create(
+        model=model,
+        messages=[
+            {"role": "system", "content": _system_prompt(scene_count, min_chars, max_chars)},
+            {"role": "user", "content": user_prompt},
+        ],
+        response_format={"type": "json_object"},
+        temperature=0.6,
+    )
+
+    content = resp.choices[0].message.content or "{}"
+    data: Any = json.loads(content)
+    scenes_raw = data.get("scenes")
+    if not isinstance(scenes_raw, list) or len(scenes_raw) != scene_count:
+        raise ValueError(f"Model returned invalid scenes length: {type(scenes_raw)}")
+
+    scenes: list[Scene] = []
+    for i, s in enumerate(scenes_raw):
+        if not isinstance(s, dict):
+            raise ValueError(f"Scene[{i}] must be object, got {type(s)}")
+        image_prompt = str(s.get("image_prompt", "")).strip()
+        video_motion = str(s.get("video_motion", "")).strip()
+        narration = str(s.get("narration", "")).strip()
+        if not image_prompt or not narration:
+            raise ValueError(f"Scene[{i}] missing required fields")
+        scenes.append(Scene(image_prompt=image_prompt, video_motion=video_motion, narration=narration))
+    return scenes