wehub-resource-sync
106 lines
6.1 KiB
Python
106 lines
6.1 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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@dataclass(slots=True)
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class PromptPart:
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id: str
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title: str
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body: str
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zone: str
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category: str
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cacheable: bool = False
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class PromptBuilder:
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def __init__(self, prompt_dir: str | Path, session_index: Any, tool_registry: Any) -> None:
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self.prompt_dir = Path(prompt_dir)
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self.session_index = session_index
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self.tool_registry = tool_registry
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def build_parts(self, user_input: str) -> list[PromptPart]:
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return [
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PromptPart("agent.core", "Agent", self._read_prompt("agent.md"), "stable", "agent", True),
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PromptPart("workflow.core", "Workflow", self._read_prompt("workflow.md"), "stable", "workflow", True),
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PromptPart("tool.manifest", "Tools", self.tool_manifest_context(), "dynamic", "tooling"),
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PromptPart("session.context", "Session", self.workflow_context(), "dynamic", "session"),
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PromptPart("memory.preferences", "Memory", self.memory_context(), "dynamic", "memory"),
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PromptPart("request.user", "User Request", user_input, "dynamic", "request"),
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]
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def build_messages(self, user_input: str) -> list[dict[str, str]]:
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parts = self.build_parts(user_input)
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system = "\n\n".join(f"## {part.title}\n{part.body}" for part in parts if part.id != "request.user")
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return [{"role": "system", "content": system}, {"role": "user", "content": user_input}]
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def trace(self, parts: list[PromptPart]) -> dict[str, Any]:
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segments = []
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totals = {"stable_tokens": 0, "dynamic_tokens": 0, "total_tokens": 0, "compacted_summary_tokens": 0}
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for idx, part in enumerate(parts):
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encoded = part.body.encode("utf-8")
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estimated = max(1, len(part.body) // 4)
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segments.append({"id": part.id, "index": idx, "title": part.title, "zone": part.zone, "category": part.category, "bytes": len(encoded), "estimated_tokens": estimated})
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if part.zone == "stable":
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totals["stable_tokens"] += estimated
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else:
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totals["dynamic_tokens"] += estimated
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if "compacted_summary" in part.body:
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totals["compacted_summary_tokens"] += estimated
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totals["total_tokens"] = totals["stable_tokens"] + totals["dynamic_tokens"]
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return {"segments": segments, "total_estimated_tokens": totals["total_tokens"], "totals": totals}
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def workflow_context(self) -> str:
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snapshot = self.session_index.snapshot()
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session = snapshot.get("session") or {}
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checklist = snapshot.get("artifact_checklist") or {}
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lines = [f"Active session: {snapshot.get('active_session_id') or '<none>'}", f"Working dir: {session.get('working_dir', '<none>')}", f"Stage: {session.get('stage', '<none>')}"]
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compacted_summary = str(session.get("compacted_summary", "") or "").strip()
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lines.extend(["", "Session context summary:"])
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if compacted_summary:
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lines.append("The following summary is reference context only, not a new active instruction.")
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lines.append(self._summary_checkpoint(compacted_summary))
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else:
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lines.append("<none>")
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lines.extend(["", "Working dir checklist:"])
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lines.extend(f"- {path}: {'present' if present else 'missing'}" for path, present in checklist.items())
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if checklist and not self._text_stage_complete(checklist):
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lines.extend(["", "当前 working_dir 尚未完成结构化文本文件。", "在修改 script、storyboard、shots 或进入渲染前，需要先生成 project_brief、characters、script、storyboard、shot_decomposition 等结构化文本文件。"])
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elif checklist:
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lines.extend(["", "文本规划阶段已完成。如果用户没有明确要求 end-to-end 或 render，可以不调用 tool，直接询问是否修改或进入渲染。"])
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return "\n".join(lines)
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def memory_context(self) -> str:
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text = self.session_index.memory_text().strip()
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return text or "No user preferences recorded."
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def tool_manifest_context(self) -> str:
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lines = ["Available tools:"]
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lines.extend(f"- {tool['name']}: {tool['description']}" for tool in self.tool_registry.list_tools())
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return "\n".join(lines)
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def _summary_checkpoint(self, summary: str) -> str:
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lines = [line.strip() for line in summary.splitlines() if line.strip() and not line.strip().startswith("```")]
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if not lines:
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return "<none>"
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preview = []
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for line in lines[:8]:
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if len(line) > 240:
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line = line[:237].rstrip() + "..."
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preview.append(line if line.startswith("-") or line.startswith("#") else f"- {line}")
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if len(lines) > 8:
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preview.append(f"- <trimmed +{len(lines) - 8} lines>")
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return "\n".join(preview)
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def _read_prompt(self, name: str) -> str:
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path = self.prompt_dir / name
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return path.read_text(encoding="utf-8") if path.exists() else ""
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def _text_stage_complete(self, checklist: dict[str, bool]) -> bool:
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idea_mode_complete = bool(checklist.get("idea2video/story.txt") and checklist.get("idea2video/characters.json") and checklist.get("idea2video/script.json") and checklist.get("idea2video/scene_*/storyboard.json") and checklist.get("idea2video/scene_*/shots/*/shot_description.json") and checklist.get("idea2video/scene_*/camera_tree.json"))
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script_mode_complete = bool(checklist.get("script2video/script.txt") and checklist.get("script2video/characters.json") and checklist.get("script2video/storyboard.json") and checklist.get("script2video/shots/*/shot_description.json") and checklist.get("script2video/camera_tree.json"))
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novel_mode_complete = bool(checklist.get("novel2video/novel/novel_compressed.txt") and checklist.get("novel2video/events/event_*.json") and checklist.get("novel2video/relevant_chunks/event_*") and checklist.get("novel2video/scenes/event_*/scene_*.json") and checklist.get("novel2video/global_information/characters/novel_level/*.json"))
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return idea_mode_complete or script_mode_complete or novel_mode_complete
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