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fix(complexity_router): Address Greptile review round 2
1. **Empty user message handling** - Changed from falsy check to None check
to properly distinguish 'no user message' from 'empty string message'
2. **ReDoS prevention** - Changed 'first.*then' to 'first.*?then' (non-greedy)
to prevent regex backtracking on pathological inputs
3. **Documentation sync** - Updated README.md to match actual config values:
- Tier boundaries: 0.15/0.35/0.60 (not 0.25/0.50/0.75)
- Dimension weights: tokenCount=0.10, codePresence=0.30, technicalTerms=0.25,
simpleIndicators=0.05, multiStepPatterns=0.03, questionComplexity=0.02
4. **Missing UI component** - Added ComplexityRouterConfig.tsx with:
- Tier-to-model dropdown selectors
- Descriptions and examples for each tier
- How classification works explanation
5. **Inline import comment** - Added explanation for why ComplexityRouter
import is inline (matches AutoRouter pattern, avoids circular imports)
This commit is contained in:
OpenClaw Assistant
parent
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commit
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4 changed files with 163 additions and 24 deletions
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@ -6301,6 +6301,8 @@ class Router:
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This will initialize the complexity-router and add it to the complexity-routers dictionary.
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"""
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# Import here to match AutoRouter pattern and avoid circular imports
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# (ComplexityRouter is a CustomLogger subclass that imports litellm internals)
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from litellm.router_strategy.complexity_router.complexity_router import ComplexityRouter
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complexity_router_config: Optional[
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@ -17,22 +17,22 @@ The router scores each request across 7 dimensions:
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| Dimension | Description | Weight |
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|-----------|-------------|--------|
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| `tokenCount` | Short prompts = simple, long = complex | 0.15 |
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| `codePresence` | Code keywords (function, class, etc.) | 0.20 |
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| `tokenCount` | Short prompts = simple, long = complex | 0.10 |
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| `codePresence` | Code keywords (function, class, etc.) | 0.30 |
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| `reasoningMarkers` | "step by step", "think through", etc. | 0.25 |
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| `technicalTerms` | Domain complexity indicators | 0.15 |
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| `simpleIndicators` | "what is", "define" (negative weight) | 0.15 |
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| `multiStepPatterns` | "first...then", numbered steps | 0.05 |
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| `questionComplexity` | Multiple question marks | 0.05 |
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| `technicalTerms` | Domain complexity indicators | 0.25 |
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| `simpleIndicators` | "what is", "define" (negative weight) | 0.05 |
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| `multiStepPatterns` | "first...then", numbered steps | 0.03 |
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| `questionComplexity` | Multiple question marks | 0.02 |
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The weighted sum is mapped to tiers using configurable boundaries:
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| Tier | Score Range | Typical Use |
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|------|-------------|-------------|
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| SIMPLE | < 0.25 | Basic questions, greetings |
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| MEDIUM | 0.25 - 0.50 | Standard queries |
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| COMPLEX | 0.50 - 0.75 | Technical, multi-part requests |
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| REASONING | > 0.75 | Chain-of-thought, analysis |
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| SIMPLE | < 0.15 | Basic questions, greetings |
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| MEDIUM | 0.15 - 0.35 | Standard queries |
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| COMPLEX | 0.35 - 0.60 | Technical, multi-part requests |
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| REASONING | > 0.60 | Chain-of-thought, analysis |
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## Configuration
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@ -68,9 +68,9 @@ model_list:
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# Tier boundaries (normalized scores)
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tier_boundaries:
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simple_medium: 0.25
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medium_complex: 0.50
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complex_reasoning: 0.75
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simple_medium: 0.15
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medium_complex: 0.35
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complex_reasoning: 0.60
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# Token count thresholds
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token_thresholds:
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@ -79,13 +79,13 @@ model_list:
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# Dimension weights (must sum to ~1.0)
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dimension_weights:
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tokenCount: 0.15
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codePresence: 0.20
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tokenCount: 0.10
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codePresence: 0.30
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reasoningMarkers: 0.25
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technicalTerms: 0.15
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simpleIndicators: 0.15
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multiStepPatterns: 0.05
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questionComplexity: 0.05
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technicalTerms: 0.25
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simpleIndicators: 0.05
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multiStepPatterns: 0.03
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questionComplexity: 0.02
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# Override default keyword lists
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code_keywords:
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@ -93,8 +93,9 @@ class ComplexityRouter(CustomLogger):
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self.simple_keywords = self.config.simple_keywords or DEFAULT_SIMPLE_KEYWORDS
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# Pre-compile regex patterns for efficiency
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# Use non-greedy .*? to prevent ReDoS on pathological inputs
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self._multi_step_patterns = [
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re.compile(r"first.*then", re.IGNORECASE),
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re.compile(r"first.*?then", re.IGNORECASE),
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re.compile(r"step\s*\d", re.IGNORECASE),
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re.compile(r"\d+\.\s"),
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re.compile(r"[a-z]\)\s", re.IGNORECASE),
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@ -359,19 +360,19 @@ class ComplexityRouter(CustomLogger):
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return None
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# Extract the last user message and the last system prompt
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user_message = ""
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system_prompt = None
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user_message: Optional[str] = None
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system_prompt: Optional[str] = None
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for msg in reversed(messages):
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role = msg.get("role", "")
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content = msg.get("content", "")
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if isinstance(content, str):
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if role == "user" and not user_message:
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if role == "user" and user_message is None:
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user_message = content
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elif role == "system" and system_prompt is None:
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system_prompt = content
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if not user_message:
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if user_message is None:
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verbose_router_logger.debug(
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"ComplexityRouter: No user message found, skipping routing"
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)
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@ -0,0 +1,136 @@
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import { InfoCircleOutlined } from "@ant-design/icons";
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import { Select as AntdSelect, Card, Divider, Space, Tooltip, Typography } from "antd";
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import React from "react";
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import { ModelGroup } from "../playground/llm_calls/fetch_models";
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const { Text } = Typography;
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interface ComplexityTiers {
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SIMPLE: string;
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MEDIUM: string;
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COMPLEX: string;
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REASONING: string;
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}
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interface ComplexityRouterConfigProps {
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modelInfo: ModelGroup[];
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value: ComplexityTiers;
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onChange: (tiers: ComplexityTiers) => void;
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}
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const TIER_DESCRIPTIONS: Record<keyof ComplexityTiers, { label: string; description: string; examples: string }> = {
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SIMPLE: {
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label: "Simple",
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description: "Basic questions, greetings, simple factual queries",
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examples: '"Hello!", "What is Python?", "Thanks!"',
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},
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MEDIUM: {
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label: "Medium",
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description: "Standard queries requiring some reasoning or explanation",
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examples: '"Explain how REST APIs work", "Debug this error"',
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},
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COMPLEX: {
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label: "Complex",
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description: "Technical, multi-part requests requiring deep knowledge",
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examples: '"Design a microservices architecture", "Implement a rate limiter"',
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},
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REASONING: {
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label: "Reasoning",
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description: "Chain-of-thought, analysis, explicit reasoning requests",
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examples: '"Think step by step...", "Analyze the pros and cons..."',
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},
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};
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const ComplexityRouterConfig: React.FC<ComplexityRouterConfigProps> = ({ modelInfo, value, onChange }) => {
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// Prepare model options for dropdowns
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const modelOptions = modelInfo.map((model) => ({
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value: model.model_group,
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label: model.model_group,
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}));
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const handleTierChange = (tier: keyof ComplexityTiers, model: string) => {
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onChange({
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...value,
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[tier]: model,
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});
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};
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return (
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<div className="w-full max-w-none">
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<Space align="center" style={{ marginBottom: 16 }}>
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<Typography.Title level={4} style={{ margin: 0 }}>
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Complexity Tier Configuration
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</Typography.Title>
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<Tooltip title="Map each complexity tier to a model. Simple queries use cheaper/faster models, complex queries use more capable models.">
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<InfoCircleOutlined className="text-gray-400" />
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</Tooltip>
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</Space>
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<Text type="secondary" style={{ display: "block", marginBottom: 24 }}>
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The complexity router automatically classifies requests by complexity using rule-based scoring (no API calls,
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<1ms latency). Configure which model handles each tier.
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</Text>
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<Card>
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{(Object.keys(TIER_DESCRIPTIONS) as Array<keyof ComplexityTiers>).map((tier, index) => {
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const tierInfo = TIER_DESCRIPTIONS[tier];
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return (
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<div key={tier}>
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{index > 0 && <Divider style={{ margin: "16px 0" }} />}
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<div className="mb-4">
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<div className="flex items-center gap-2 mb-2">
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<Text strong style={{ fontSize: 16 }}>
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{tierInfo.label} Tier
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</Text>
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<Tooltip title={tierInfo.description}>
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<InfoCircleOutlined className="text-gray-400" />
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</Tooltip>
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</div>
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<Text type="secondary" style={{ display: "block", marginBottom: 8, fontSize: 12 }}>
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Examples: {tierInfo.examples}
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</Text>
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<AntdSelect
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value={value[tier]}
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onChange={(model) => handleTierChange(tier, model)}
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placeholder={`Select model for ${tierInfo.label.toLowerCase()} queries`}
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showSearch
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style={{ width: "100%" }}
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options={modelOptions}
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/>
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</div>
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</div>
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);
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})}
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</Card>
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<Divider />
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<Card className="bg-gray-50">
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<Text strong style={{ display: "block", marginBottom: 8 }}>
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How Classification Works
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</Text>
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<Text type="secondary" style={{ fontSize: 13 }}>
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The router scores each request across 7 dimensions: token count, code presence, reasoning markers, technical
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terms, simple indicators, multi-step patterns, and question complexity. The weighted score determines the
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tier:
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</Text>
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<ul style={{ marginTop: 8, marginBottom: 0, paddingLeft: 20, fontSize: 13, color: "rgba(0, 0, 0, 0.45)" }}>
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<li>
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<strong>SIMPLE</strong>: Score < 0.15
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</li>
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<li>
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<strong>MEDIUM</strong>: Score 0.15 - 0.35
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</li>
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<li>
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<strong>COMPLEX</strong>: Score 0.35 - 0.60
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</li>
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<li>
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<strong>REASONING</strong>: Score > 0.60 (or 2+ reasoning markers)
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</li>
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</ul>
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</Card>
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</div>
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);
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};
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export default ComplexityRouterConfig;
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