Cursor Agentandhaijd
9c6afcb61a
需求未定稿时可先跑通追问/判定/出方案；槽位与判定树外置 YAML，后续可接 Ragflow。 Co-authored-by: haijd <haijd@163.com>
114 lines
4.0 KiB
Python
114 lines
4.0 KiB
Python
from __future__ import annotations
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from typing import Any
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from .config_loader import business_config
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from .decision import evaluate_tree
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from .retrieval import retrieve_for_scheme
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from .session_store import (
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Session,
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looks_like_handoff,
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naive_fill_slots,
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next_slot_prompt,
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store,
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)
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def create_session() -> Session:
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return store.create()
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def handle_message(session_id: str, message: str) -> dict[str, Any]:
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session = store.get(session_id)
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if not session:
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raise KeyError("session_not_found")
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text = (message or "").strip()
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session.messages.append({"role": "user", "content": text})
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if looks_like_handoff(text, business_config.handoff_phrases):
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session.phase = "handoff"
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reply = "已为您标记转人工。请留下称呼与联系方式，销售同事会跟进。（原型：仅记录意图，未接 Chatwoot）"
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return _finish(session, reply, need_handoff=True)
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# fill slots while collecting
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if session.phase in ("collecting", "scheme_ready"):
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session.slots = naive_fill_slots(text, business_config.slots, session.slots)
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nxt = next_slot_prompt(business_config.slots, session.slots)
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if nxt and session.phase == "collecting":
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# first turn with empty slots: greet + first question
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if len(session.messages) == 1 and not any(session.slots.values()):
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# put first user utterance into first slot if they already answered something
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session.slots = naive_fill_slots(text, business_config.slots, session.slots)
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nxt = next_slot_prompt(business_config.slots, session.slots)
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if nxt:
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reply = nxt["prompt"]
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return _finish(session, reply, asking_slot=nxt["id"])
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# all required (+ optional asked or filled) → scheme
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decision = evaluate_tree(business_config.rules, session.slots)
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confidence = float(decision.get("confidence") or 0)
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need_handoff = bool(decision.get("handoff")) or confidence < business_config.handoff_confidence_below
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bundle = list(decision.get("product_bundle") or [])
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retrieval = retrieve_for_scheme(session.slots, bundle)
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scheme = {
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"tech_line": decision.get("tech_line"),
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"product_bundle": bundle,
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"summary": decision.get("summary"),
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"confidence": confidence,
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"rule_id": decision.get("rule_id"),
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"citations": [
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{"id": c.get("id"), "title": c.get("title"), "content": c.get("content")}
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for c in retrieval.chunks
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],
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"slots": dict(session.slots),
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}
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session.last_scheme = scheme
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session.phase = "handoff" if need_handoff else "scheme_ready"
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lines = [
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business_config.closing_prompt,
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"",
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f"技术路线：{scheme['tech_line']}",
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f"推荐组合：{', '.join(bundle)}",
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f"说明：{scheme['summary']}",
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f"置信度：{confidence:.0%}",
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]
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if scheme["citations"]:
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lines.append("")
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lines.append("知识依据（原型检索）：")
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for c in scheme["citations"][:3]:
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lines.append(f"- {c['title']}：{c['content']}")
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if need_handoff:
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lines.append("")
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lines.append("系统建议转人工确认后再对外发送方案。回复「转人工」可进入人工流程。")
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else:
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lines.append("")
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lines.append("可继续补充约束，或回复「转人工」交给销售。")
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reply = "\n".join(lines)
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return _finish(session, reply, scheme=scheme, need_handoff=need_handoff)
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def _finish(
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session: Session,
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reply: str,
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*,
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asking_slot: str | None = None,
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scheme: dict[str, Any] | None = None,
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need_handoff: bool = False,
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) -> dict[str, Any]:
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session.messages.append({"role": "assistant", "content": reply})
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store.touch(session)
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return {
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"session_id": session.id,
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"reply": reply,
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"phase": session.phase,
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"slots": session.slots,
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"asking_slot": asking_slot,
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"scheme": scheme or session.last_scheme,
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"need_handoff": need_handoff,
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}
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