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1be30f5129
* feat(router): Add complexity-based auto routing strategy
Adds a rule-based routing strategy that classifies requests by complexity
and routes them to appropriate models - with zero API calls and sub-millisecond
latency.
## Features
- **Zero external API calls** - all scoring is local
- **Sub-millisecond latency** - typically <1ms per classification
- **Weighted multi-dimensional scoring** across 7 dimensions:
- Token count (short=simple, long=complex)
- Code presence (code keywords → complex)
- Reasoning markers ("step by step" → reasoning tier)
- Technical terms (domain complexity)
- Simple indicators ("what is" → simple, negative weight)
- Multi-step patterns (numbered steps)
- Question complexity (multiple questions)
- **Configurable tier boundaries** and model mappings
- **Reasoning override** - 2+ reasoning markers force REASONING tier
## Usage
```yaml
model_list:
- model_name: smart-router
litellm_params:
model: auto_router/complexity_router
complexity_router_config:
tiers:
SIMPLE: gpt-4o-mini
MEDIUM: gpt-4o
COMPLEX: claude-sonnet-4
REASONING: o1-preview
```
Inspired by ClawRouter: https://github.com/BlockRunAI/ClawRouter
## Files Added
- litellm/router_strategy/complexity_router/complexity_router.py - Main router class
- litellm/router_strategy/complexity_router/config.py - Configuration and defaults
- litellm/router_strategy/complexity_router/__init__.py - Package exports
- litellm/router_strategy/complexity_router/README.md - Documentation
- tests/test_litellm/router_strategy/test_complexity_router.py - Test suite (37 tests)
## Files Modified
- litellm/router.py - Integration with pre_routing_hook
- litellm/types/router.py - New config params
* feat(router): Add complexity-based auto routing strategy
Adds a new rule-based routing strategy that classifies requests by complexity
and routes them to appropriate models - without any external API calls.
## Features
- Weighted scoring across 7 dimensions: token count, code presence, reasoning
markers, technical terms, simple indicators, multi-step patterns, questions
- Maps to 4 tiers: SIMPLE, MEDIUM, COMPLEX, REASONING
- Each tier configurable to a different model
- Zero API calls, <1ms latency
- Inspired by ClawRouter
## Configuration
```yaml
model_list:
- model_name: smart_router
litellm_params:
model: auto_router/complexity_router
complexity_router_config:
tiers:
SIMPLE: gemini-2.0-flash
MEDIUM: gpt-4o-mini
COMPLEX: claude-sonnet-4
REASONING: claude-opus-4
```
## Use Cases
- Cost optimization: route simple queries to cheaper models
- Quality optimization: route complex queries to capable models
- Zero configuration: works out of the box with sensible defaults
* feat(router): Add complexity-based auto routing strategy
Adds a new rule-based routing strategy that classifies requests by complexity
and routes them to appropriate models - without any external API calls.
- Weighted scoring across 7 dimensions: token count, code presence, reasoning
markers, technical terms, simple indicators, multi-step patterns, questions
- Maps to 4 tiers: SIMPLE, MEDIUM, COMPLEX, REASONING
- Each tier configurable to a different model
- Zero API calls, <1ms latency
- Inspired by ClawRouter
```yaml
model_list:
- model_name: smart_router
litellm_params:
model: auto_router/complexity_router
complexity_router_config:
tiers:
SIMPLE: gemini-2.0-flash
MEDIUM: gpt-4o-mini
COMPLEX: claude-sonnet-4
REASONING: claude-opus-4
```
- Cost optimization: route simple queries to cheaper models
- Quality optimization: route complex queries to capable models
- Zero configuration: works out of the box with sensible defaults
* feat: add enterprise presets for complexity router
Adds preset configurations for different cloud providers:
- bedrock: AWS Bedrock (Claude models)
- vertex: Google Vertex AI (Gemini models)
- azure: Azure OpenAI (GPT + o1)
- standard: Direct API (OpenAI + Anthropic)
- cost_optimized: Maximum savings (Gemini Flash + cheaper models)
Usage:
```yaml
complexity_router_config:
preset: bedrock # or vertex, azure, standard, cost_optimized
```
* feat(ui): update auto router submit handler for complexity router
- Handle complexity_router model type in submit handler
- Generate correct litellm_params for complexity router:
- model: auto_router/complexity_router
- complexity_router_config: { tiers: { SIMPLE, MEDIUM, COMPLEX, REASONING } }
- Keep existing semantic router handling intact
- Add success notification with router type name
* docs: update PR description with UI changes
* chore: remove preset feature, keep simple tier config
* fix: exclude complexity_router from auto_router check
The _is_auto_router_deployment() was matching all auto_router/* models,
causing complexity_router to fail initialization. Now it explicitly
excludes auto_router/complexity_router which has its own handler.
* fix(complexity_router): Address Greptile review feedback
Fixes 5 issues flagged in code review:
1. **Mutable singleton mutation bug** - Now always creates a new
ComplexityRouterConfig instance instead of reusing DEFAULT_COMPLEXITY_CONFIG
singleton, preventing cross-instance config pollution.
2. **Substring matching false positives** - Added word boundaries (spaces)
to short keywords like 'ok', 'try', 'api', 'git', 'node', 'java', 'vue'
to prevent matching within longer words (e.g., 'capital' matching 'api').
3. **Redundant message extraction** - Simplified to single reverse loop that
extracts both last user message and last system prompt efficiently.
4. **Unused imports** - Removed unused DEFAULT_CREATIVE_KEYWORDS and
DEFAULT_MULTI_STEP_PATTERNS imports.
5. **Missing async_pre_routing_hook tests** - Added comprehensive tests for:
- Multi-turn conversations
- List-type content handling
- No user message case
- Empty string content
- Message preservation
- Singleton mutation prevention
* fix(complexity_router): Address Greptile review feedback
- Use word boundary matching for short keywords (<5 chars) to avoid
false positives (e.g., 'api' matching 'capital', 'git' matching 'digital')
- Remove 'ok' from simple keywords (too many false positives)
- Add tests for keyword false positive prevention
- Fix test expectations for edge cases (empty string content, list content)
Addresses: 2/5 Greptile score feedback on PR #21789
* docs(auto_routing): Add complexity router documentation
- Add Complexity Router section to auto_routing.md
- Include comparison table with semantic auto router
- Add Python SDK and Proxy Server configuration examples
- Document all configuration options (tier boundaries, token thresholds, dimension weights)
- Explain how complexity scoring works
* feat(complexity_router): Add eval suite + tune scoring parameters
Added comprehensive evaluation suite with 29 test cases covering:
- SIMPLE tier: greetings, definitions, factual questions
- MEDIUM tier: technical explanations, comparisons, debugging
- COMPLEX tier: architecture design, complex coding
- REASONING tier: explicit reasoning requests
- Regression tests: substring false positive prevention
Tuned scoring parameters based on eval results:
- Lowered tier boundaries (0.15/0.35/0.60) for better tier distribution
- Increased code/technical weights (0.30/0.25) for complex prompts
- Reduced simple indicator weight (0.05) to avoid over-penalizing
- Fixed 'hey'/'hi' keywords to require leading space
Eval results: 29/29 passed (100%)
* 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)
* docs(auto_routing): fix dimension weights and tier boundaries to match config.py defaults
* fix(complexity_router): skip empty string content in async_pre_routing_hook
* fix(router): remove or {} masking None complexity_router_config
* fix(config): remove unused DEFAULT_MULTI_STEP_PATTERNS and DEFAULT_CREATIVE_KEYWORDS exports
* fix(complexity_router): use word boundary matching for all single-word keywords, avoid double-scanning reasoning keywords
* fix(router): clarify circular import comment for ComplexityRouter
* docs(README): fix token thresholds to match config.py defaults
* test(complexity_router): add false positive tests for error/class/merge keyword matching
* fix(complexity_router): align .get() fallbacks with config.py defaults, document system prompt scoring
* fix(config): deduplicate keywords across code and technical lists
---------
Co-authored-by: OpenClaw Assistant <assistant@openclaw.ai>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
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|---|---|---|
| .. | ||
| test_auto_router.py | ||
| test_base_routing_strategy.py | ||
| test_budget_limiter_hotpath.py | ||
| test_complexity_router.py | ||
| test_router_tag_routing.py | ||