872ed24f0c
Inspired by zeroclaw's lightweight patterns for slow hardware: - Response cache (SQLite + SHA-256 keyed) to skip redundant LLM calls - History compaction — LLM-summarize old messages when history exceeds 50 - Query classifier routes simple/research queries to cheaper models - Credential scrubbing removes secrets from tool output before sending to LLM - Cost tracker with daily/monthly budget enforcement (SQLite) - Resilient provider with retry + exponential backoff + fallback provider - Approval engine gains session "always allow" and audit log Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
"""Query classifier — route queries to appropriate models."""
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from __future__ import annotations
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import re
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from dataclasses import dataclass
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from typing import Any
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@dataclass
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class ClassificationResult:
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"""Result of classifying a query."""
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category: str # "simple", "code", "research", "complex"
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model_hint: str # suggested model override, or "" to use default
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# Short, trivial queries — greetings, thanks, yes/no, etc.
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_SIMPLE_PATTERNS = [
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re.compile(r"^(hi|hello|hey|thanks|thank you|ok|yes|no|sure|bye|good\s*(morning|evening|night))[\s!.?]*$", re.IGNORECASE),
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re.compile(r"^(what time|what date|what day)[\s\S]{0,20}\??\s*$", re.IGNORECASE),
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]
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# Code-related queries
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_CODE_PATTERNS = [
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re.compile(r"\b(function|class|def|import|const|let|var|return|async|await)\b"),
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re.compile(r"\b(refactor|debug|fix|implement|code|compile|build|test|lint|deploy)\b", re.IGNORECASE),
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re.compile(r"```"),
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re.compile(r"\.(py|js|ts|rs|go|java|cpp|c|rb|php|swift|kt)\b"),
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]
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# Research / information queries
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_RESEARCH_PATTERNS = [
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re.compile(r"\b(search|find|look\s*up|research|summarize|explain|compare|analyze)\b", re.IGNORECASE),
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re.compile(r"\b(what is|how does|why does|can you explain)\b", re.IGNORECASE),
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]
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class QueryClassifier:
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"""Classify queries for model routing.
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Configure with a mapping of category → model override.
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Categories: "simple", "code", "research", "complex".
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"""
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def __init__(self, model_map: dict[str, str] | None = None) -> None:
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self._model_map = model_map or {}
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def classify(self, query: str) -> ClassificationResult:
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"""Classify a query and suggest a model."""
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query_stripped = query.strip()
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# Very short queries are likely simple
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if len(query_stripped) < 20:
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for pattern in _SIMPLE_PATTERNS:
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if pattern.match(query_stripped):
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return ClassificationResult(
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category="simple",
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model_hint=self._model_map.get("simple", ""),
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)
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# Code patterns
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code_score = sum(1 for p in _CODE_PATTERNS if p.search(query_stripped))
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if code_score >= 2:
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return ClassificationResult(
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category="code",
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model_hint=self._model_map.get("code", ""),
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)
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# Research patterns
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research_score = sum(1 for p in _RESEARCH_PATTERNS if p.search(query_stripped))
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if research_score >= 1:
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return ClassificationResult(
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category="research",
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model_hint=self._model_map.get("research", ""),
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)
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# Long or complex queries
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if len(query_stripped) > 500 or query_stripped.count("\n") > 5:
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return ClassificationResult(
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category="complex",
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model_hint=self._model_map.get("complex", ""),
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)
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# Default — no override
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return ClassificationResult(category="complex", model_hint="")
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