206 lines
7.2 KiB
Python
206 lines
7.2 KiB
Python
"""Build bounded, traceable seat input from MAF roundtable context.
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Converts the shared roundtable state (task, previous turns, fact ledger,
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stage instructions) into a single human message for a seat's DeerFlow thread.
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Design constraints (MAF-02-06):
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- Bounded: total output STRICTLY never exceeds ``max_context_chars``.
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- Trimmable: each section is independently truncatable.
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- Traceable: includes turn references so the seat can cite prior work.
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- Never injects credentials, tokens, or raw binary content.
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- All content is sanitized before inclusion.
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"""
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from __future__ import annotations
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from typing import Any
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from app.maf_roundtable.sanitize import sanitize
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_DEFAULT_MAX_CONTEXT_CHARS = 12000
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_DEFAULT_MAX_TURN_CHARS = 2000
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_DEFAULT_MAX_FACT_CHARS = 3000
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def build_seat_input(
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*,
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task_text: str,
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stage_instruction: str,
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role_description: str,
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prior_turns: list[dict[str, Any]],
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fact_ledger: dict[str, Any] | None = None,
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max_context_chars: int = _DEFAULT_MAX_CONTEXT_CHARS,
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max_turn_chars: int = _DEFAULT_MAX_TURN_CHARS,
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max_fact_chars: int = _DEFAULT_MAX_FACT_CHARS,
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) -> str:
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"""Assemble the human message for a seat's DeerFlow run.
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The total output length is STRICTLY <= max_context_chars. Truncation
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happens per-section first, then a final hard cap ensures no overflow.
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"""
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sections: list[str] = []
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sections.append(f"【任务】\n{task_text}")
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if role_description:
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sections.append(f"【你的角色】\n{role_description}")
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if stage_instruction:
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sections.append(f"【本阶段要求】\n{stage_instruction}")
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if prior_turns:
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turns_text = _format_prior_turns(prior_turns, max_turn_chars)
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if turns_text:
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sections.append(f"【已有讨论】\n{turns_text}")
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if fact_ledger:
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sanitized_ledger = sanitize(fact_ledger)
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if isinstance(sanitized_ledger, dict):
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facts_text = _format_fact_ledger(sanitized_ledger, max_fact_chars)
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if facts_text:
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sections.append(f"【共享事实账本】\n{facts_text}")
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result = "\n\n".join(sections)
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if len(result) > max_context_chars:
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result = result[:max_context_chars]
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return result
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def build_manager_synthesis_input(
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*,
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task_text: str,
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seat_results: list[dict[str, Any]],
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fact_ledger: dict[str, Any] | None = None,
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max_context_chars: int = _DEFAULT_MAX_CONTEXT_CHARS,
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) -> str:
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"""Build the manager's final synthesis prompt."""
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sections: list[str] = []
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sections.append(f"【原始任务】\n{task_text}")
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sections.append("【各席位分析结果】")
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for r in seat_results:
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agent_id = r.get("agent_id", "unknown")
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content = str(r.get("content", ""))
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if len(content) > 3000:
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content = content[:3000] + "..."
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sections.append(f"--- {agent_id} ---\n{content}")
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if fact_ledger:
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sanitized_ledger = sanitize(fact_ledger)
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if isinstance(sanitized_ledger, dict):
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facts_text = _format_fact_ledger(sanitized_ledger, _DEFAULT_MAX_FACT_CHARS)
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if facts_text:
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sections.append(f"【共享事实账本】\n{facts_text}")
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sections.append(
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"【综合要求】\n"
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"请基于以上各席位分析和事实账本，生成最终结论。要求：\n"
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"1. 明确标注共识点和分歧点\n"
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"2. 区分「建议动作」和「已实际执行的动作」\n"
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"3. 引用具体证据来源\n"
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"4. 列出失败或状态不确定的动作"
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)
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result = "\n\n".join(sections)
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if len(result) > max_context_chars:
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result = result[:max_context_chars]
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return result
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# ── internal helpers ──────────────────────────────────────────────────────────
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def _format_prior_turns(turns: list[dict[str, Any]], max_per_turn: int) -> str:
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lines: list[str] = []
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for t in turns:
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agent_id = t.get("agent_id", "unknown")
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turn_idx = t.get("turn_index", "?")
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summary = str(t.get("summary", ""))
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if len(summary) > max_per_turn:
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summary = summary[:max_per_turn] + "..."
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lines.append(f"[轮次{turn_idx}] {agent_id}: {summary}")
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return "\n".join(lines)
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def _format_fact_ledger(ledger: dict[str, Any], max_chars: int) -> str:
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parts: list[str] = []
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candidates = ledger.get("candidate_facts")
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if candidates and isinstance(candidates, list):
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# Phase-3: candidate facts are UNVERIFIED seat claims — label them
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# explicitly so downstream seats / the finalizer never treat them as
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# established conclusions.
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parts.append("未经核验的席位主张（不能作为结论）:")
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for c in candidates[:20]:
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if isinstance(c, dict):
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parts.append(f" - {c.get('text', c)}")
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else:
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parts.append(f" - {c}")
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facts = ledger.get("confirmed_facts")
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if facts and isinstance(facts, list):
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parts.append("已确认事实（经交叉审查核验）:")
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for f in facts[:20]:
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if isinstance(f, dict):
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parts.append(f" - {f.get('text', f)}")
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else:
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parts.append(f" - {f}")
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evidence = ledger.get("evidence")
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if evidence and isinstance(evidence, list):
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parts.append("证据引用:")
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for e in evidence[:10]:
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if isinstance(e, dict):
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parts.append(f" - {e.get('ref') or e.get('text') or e}")
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else:
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parts.append(f" - {e}")
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tool_results = ledger.get("tool_results")
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if tool_results and isinstance(tool_results, list):
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parts.append("工具执行结果:")
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for tr in tool_results[:10]:
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if isinstance(tr, dict):
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parts.append(f" - {tr.get('tool_name', '?')}: {tr.get('status', '?')}")
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else:
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parts.append(f" - {tr}")
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proposed = ledger.get("proposed_actions")
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if proposed and isinstance(proposed, list):
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parts.append("建议动作(未执行):")
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for p in proposed[:8]:
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parts.append(f" - {p}")
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executed = ledger.get("executed_actions")
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if executed and isinstance(executed, list):
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parts.append("已执行外部写入:")
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for e in executed[:8]:
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if isinstance(e, dict):
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parts.append(f" - {e.get('tool_name', '?')} ({e.get('action_id', '')})")
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else:
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parts.append(f" - {e}")
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conflicts = ledger.get("conflicts")
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if conflicts and isinstance(conflicts, list):
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parts.append("未解决冲突:")
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for c in conflicts[:5]:
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parts.append(f" - {c}")
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pending = ledger.get("pending_actions")
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if pending and isinstance(pending, list):
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parts.append("等待确认动作:")
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for p in pending[:5]:
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parts.append(f" - {p}")
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failed = ledger.get("failed_or_unknown_actions")
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if failed and isinstance(failed, list):
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parts.append("失败或状态不确定的动作:")
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for f in failed[:5]:
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parts.append(f" - {f}")
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result = "\n".join(parts)
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if len(result) > max_chars:
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result = result[:max_chars]
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return result
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