Files
projectAIpopular/router_system/inference.py
T
tzt ce0f6170d3 chore: T-P-1 工作区收敛——并行会话成果与历史未入库文件整理入库
- 入库历史遗漏源码/测试:router_system 9 模块(agent/executors/inference/knowledge/
  memory/planner/skills/trace)、tests 11 个测试文件、config/knowledge 领域知识
- 入库根目录方案文档(v2/v3/可行性×2)、references 文献(arxiv 14-18/cnki_open/
  参考文献清单)、research 论文素材(routerarena/paper/中文文献 PDF)
- 前端构建产物刷新(新 hash);webapp 误写文档删除
- gitignore 增补:deepseek-harness、research/_refs、.mimosa/.zcode、网关日志/pid、
  临时调试脚本、tests/e2e/node_modules、AI代理功能开发/prefix
- 基线确认:318 passed
2026-09-05 08:28:25 +08:00

94 lines
4.0 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
"""前向链推理机:知识库规则驱动的工作记忆演化(专家系统推理核心,零依赖)。
流程(经典前向链 forward chaining):
1. 初始化黑板:写入领域/难度/置信度等事实
2. 循环:在领域内匹配规则(未触发过的)→ 按优先级执行
- 命中即记录轨迹 rule:<id>@<priority>
- 规则带 output 模板 → 渲染后写入黑板章节(部分解)
- 规则带 actions → 执行动作(写事实/写章节)
3. 终止:无新规则可触发 / 达到步数上限(防死循环)
确定性保证:规则匹配基于子串包含,无随机性;同输入 → 同轨迹。
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional
from .knowledge import KnowledgeBase, Rule
from .memory import WorkingMemory
def render_template(template: str, query: str, facts: Dict[str, Any]) -> str:
"""渲染输出模板:替换 {query} 与 {facts.<key>} 占位符;缺失以 [未提供] 占位,不抛异常。"""
out = template.replace("{query}", query)
for key, value in facts.items():
out = out.replace(f"{{facts.{key}}}", str(value))
# 剩余占位符兜底
while "{" in out and "}" in out:
start = out.find("{")
end = out.find("}", start)
if end == -1:
break
out = out[:start] + "[未提供]" + out[end + 1:]
return out
class InferenceEngine:
"""前向链推理机。"""
def __init__(self, kb: KnowledgeBase, max_steps: int = 20):
self.kb = kb
self.max_steps = max_steps
# ---------------------------------------------------------------
def initialize(self, query: str, domain: str, difficulty: str,
confidence: float, memory: WorkingMemory) -> None:
"""把分类结果写入黑板(事实初始化)。"""
memory.write_fact("query", query)
memory.write_fact("domain", domain)
memory.write_fact("difficulty", difficulty)
memory.write_fact("confidence", round(confidence, 4))
memory.add_trace(f"init:domain={domain},difficulty={difficulty},conf={confidence:.2f}")
# ---------------------------------------------------------------
def run(self, query: str, domain: str, memory: WorkingMemory,
max_steps: Optional[int] = None) -> List[str]:
"""前向链主循环。返回触发规则 id 列表(按触发顺序)。"""
steps = max_steps or self.max_steps
fired: List[str] = []
for _ in range(steps):
rules = self.kb.match(query, domain=domain)
# 选第一个"未触发过"的规则
target: Optional[Rule] = None
for r in rules:
if r.id not in fired:
target = r
break
if target is None:
break # 无新规则可触发 → 终止
fired.append(target.id)
self._fire(target, query, memory)
return fired
# ---------------------------------------------------------------
def _fire(self, rule: Rule, query: str, memory: WorkingMemory) -> None:
"""执行一条规则:记录轨迹 + 写事实 + 产出章节。"""
memory.add_trace(f"rule:{rule.id}@{rule.priority}")
# 规则动作
for action in rule.actions:
self._apply_action(action, rule, query, memory)
# 规则输出模板 → 章节
if rule.output:
text = render_template(rule.output, query, memory.facts)
memory.write_section(rule.id, text)
def _apply_action(self, action: str, rule: Rule, query: str,
memory: WorkingMemory) -> None:
"""动作格式:write_fact:key=valuevalue 支持 {query} 占位)。"""
if action.startswith("write_fact:"):
kv = action[len("write_fact:"):]
key, _, value = kv.partition("=")
value = value.replace("{query}", query)
memory.write_fact(key.strip(), value.strip(), rule_id=rule.id)
# 其他动作类型暂不实现(保留扩展位)