Implement configurable and interpretable semantic routing rules system #195

Copilot · 2025-09-22T22:14:58Z

This PR implements a comprehensive hybrid routing system that transforms the semantic router from a black-box ML classifier into an interpretable, configurable platform that supports both model-based and rule-based routing approaches.

Problem Addressed

The existing semantic router suffered from several critical limitations:

Opaque decisions: No visibility into why requests were routed to specific models
No threshold control: Unable to adjust classification confidence or routing sensitivity
Limited customizability: Constrained to predefined categories without business logic integration
No debugging capabilities: When routing failed, no way to understand or fix decision logic
Scalability concerns: Static model approach couldn't handle growing routing requirements

Solution Overview

The implementation extends the existing system with a hybrid architecture that preserves all current functionality while adding powerful rule-based capabilities:

Core Components

RuleEngine (pkg/rules/engine.go): Evaluates routing rules with multiple condition types
HybridRouter (pkg/rules/hybrid_router.go): Orchestrates rule-based and model-based routing
RuleManagementAPI (pkg/rules/api.go): HTTP endpoints for dynamic rule management

Configuration Extensions

Extended RouterConfig to support:

routing_strategy:
  type: "hybrid"  # "model", "rules", or "hybrid"
  model_routing:
    enabled: true
    confidence_threshold: 0.7
  rule_routing:
    enabled: true
    fallback_to_model: true

routing_rules:
  - name: "enterprise-math-routing"
    priority: 100
    conditions:
      - type: "category_classification"
        category: "math"
        threshold: 0.8
      - type: "content_complexity"  
        metric: "token_count"
        threshold: 50
    actions:
      - type: "route_to_model"
        model: "math-specialized-model"
      - type: "enable_reasoning"
        reasoning_effort: "high"

Rule Types Implemented

Condition Types:

Category classification: ML-based classification with configurable thresholds
Content complexity: Token/character/line count analysis
Request headers: Metadata-based routing (user tiers, API keys)
Pattern matching: Content filtering and keyword detection
Time-based: Temporal routing logic

Action Types:

Route to model: Direct model selection
Enable reasoning: Configure reasoning mode and effort
Set headers: Request modification
Block requests: Security and policy enforcement

Decision Transparency

Every routing decision now includes detailed explanations:

{
  "rule_matched": true,
  "selected_model": "math-specialized-model", 
  "explanation": {
    "decision_type": "rule_based",
    "rule_name": "enterprise-math-routing",
    "matched_conditions": [...],
    "executed_actions": [...],
    "reasoning": "Rule matched based on math content and complexity",
    "confidence": 0.95
  },
  "evaluation_time_ms": 2
}

API Endpoints

New rule management endpoints:

GET/POST /api/v1/rules - List/create rules
GET/PUT/DELETE /api/v1/rules/{name} - Manage specific rules
POST /api/v1/rules/evaluate - Test rule evaluation
POST /api/v1/rules/test - Test rules with sample data

Integration & Compatibility

Seamless integration: Modified OpenAIRouter to use HybridRouter while maintaining existing interfaces
Backward compatibility: All existing model-based routing continues to work unchanged
Performance optimized: Sub-millisecond rule evaluation with priority-based processing
Fallback mechanisms: Rules can fallback to model routing and vice versa

Testing & Demonstration

Comprehensive test suite: 6 test scenarios covering all major functionality
Interactive demonstration: examples/hybrid-routing-demo.go shows real routing decisions
Build verification: Successfully compiles and integrates with existing codebase

The demonstration shows the system successfully:

Routing math problems to specialized models with high reasoning
Routing premium users to premium models based on headers
Blocking inappropriate content with custom messages
Falling back to model-based routing when no rules match
Respecting rule precedence for complex scenarios

This implementation addresses all requirements from the original issue, providing the interpretability, configurability, and scalability needed for production environments while maintaining the proven ML capabilities of the existing system.

Fixes #194.

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Copilot · 2025-09-22T22:15:00Z

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netlify · 2025-09-22T22:15:32Z

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Co-authored-by: wangchen615 <[email protected]>

github-actions · 2025-09-23T16:29:19Z

👥 vLLM Semantic Team Notification

The following members have been identified for the changed files in this PR and have been automatically assigned:

📁 `config`

Owners: @rootfs
Files changed:

config/config-hybrid-example.yaml

📁 `Root Directory`

Owners: @rootfs, @Xunzhuo
Files changed:

examples/CONFIGURATION_COMPARISON.md
examples/hybrid-routing-demo.go

📁 `src`

Owners: @rootfs, @Xunzhuo, @wangchen615
Files changed:

src/semantic-router/pkg/rules/README.md
src/semantic-router/pkg/rules/api.go
src/semantic-router/pkg/rules/engine.go
src/semantic-router/pkg/rules/engine_test.go
src/semantic-router/pkg/rules/hybrid_router.go
src/semantic-router/pkg/api/server.go
src/semantic-router/pkg/config/config.go
src/semantic-router/pkg/extproc/model_selector.go
src/semantic-router/pkg/extproc/request_handler.go
src/semantic-router/pkg/extproc/router.go

🎉 Thanks for your contributions!

This comment was automatically generated based on the OWNER files in the repository.

rootfs · 2025-09-23T16:32:11Z

This PR looks to me an extension of #147, i.e. using a rule based routing, in parallel (and potentially addition) to the semantic based route, to instruct the inference request. @copilot does this eval make sense?

@Xunzhuo WDYT?

Copilot · 2025-09-23T16:35:01Z

This PR looks to me an extension of #147, i.e. using a rule based routing, in parallel (and potentially addition) to the semantic based route, to instruct the inference request. @copilot does this eva...

You're right that this PR implements rule-based routing as an extension to the semantic routing system. However, I don't have visibility into the specific implementation details of #147 to determine if this is a direct extension of that work.

My implementation (commit 28d0f13) provides:

Hybrid approach: Combines existing semantic classification with configurable rules
Rule engine: Evaluates conditions (category classification, content complexity, headers, patterns)
Decision transparency: Explains why each routing decision was made
API management: CRUD operations for rules via HTTP endpoints

The key difference is this maintains the existing semantic classification as the foundation while adding a rule layer on top, rather than replacing it entirely. Rules can either:

Override semantic routing when they match
Fallback to semantic routing when no rules apply
Work alongside semantic classification with configurable thresholds

Could you clarify how this relates to the approach taken in #147? I'd be happy to adjust the implementation if there are specific aspects that should align with or build upon that previous work.

Initial plan

7ec9d3a

Copilot AI assigned Copilot and wangchen615 Sep 22, 2025

Copilot started work on behalf of wangchen615 September 22, 2025 22:15 View session

Copilot AI and others added 3 commits September 22, 2025 22:33

Implement rule engine infrastructure for hybrid routing

f967f08

Co-authored-by: wangchen615 <[email protected]>

Complete hybrid routing implementation with working tests and demo

28d0f13

Co-authored-by: wangchen615 <[email protected]>

Implement configurable and interpretable semantic routing rules system

5d05547

Co-authored-by: wangchen615 <[email protected]>

Copilot AI changed the title ~~[WIP] Configurable and Interpretable Semantic Routing Rules Support~~ Implement configurable and interpretable semantic routing rules system Sep 22, 2025

Copilot AI requested a review from wangchen615 September 22, 2025 22:41

Copilot finished work on behalf of wangchen615 September 22, 2025 22:41

Merge branch 'main' into copilot/fix-194

45aa374

github-actions bot assigned rootfs and Xunzhuo Sep 23, 2025

Copilot started work on behalf of rootfs September 23, 2025 16:32 View session

Copilot finished work on behalf of rootfs September 23, 2025 16:35

Copilot AI requested a review from rootfs September 23, 2025 16:35

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Implement configurable and interpretable semantic routing rules system #195

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Problem Addressed

Solution Overview

Core Components

Configuration Extensions

Rule Types Implemented

Decision Transparency

API Endpoints

Integration & Compatibility

Testing & Demonstration

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📁 config

📁 Root Directory

📁 src

🎉 Thanks for your contributions!

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📁 `config`

📁 `Root Directory`

📁 `src`