FastEmbed v2 Audit Report (Plan vs Current Codebase)
This audit compares fastembed-improvement-plan.md against the current implementation in:
cascadeflow/routing/domain.pycascadeflow/quality/complexity.pytests/test_domain_detection.py
Scope exclusions (per request):
- OpenClaw integrations
- Skills integration
Executive Summary
- P0 items: ✅ Implemented.
- P1 items: ✅ Implemented.
- P2 item (SemanticAlignmentChecker): ⏭️ Not implemented in the audited files and not required for this session.
- No missing P0/P1 gaps found in the audited scope.
Plan Item Status Matrix
| Priority |
Plan item |
Status |
Evidence |
Action needed |
| P0 |
Add domain exemplars (finance, conversation, factual) |
✅ Implemented |
DOMAIN_EXEMPLARS includes expanded exemplar sets for FINANCIAL, CONVERSATION, and FACTUAL. |
None |
| P0 |
Enable hybrid mode by default |
✅ Implemented |
SemanticDomainDetector.__init__(..., use_hybrid: bool = True) defaults hybrid on. |
None |
| P1 |
Domain-specific confidence thresholds |
✅ Implemented |
DOMAIN_THRESHOLDS exists with lowered thresholds for conversation/financial/factual and stricter ones for medical/legal. |
None |
| P1 |
Add FastEmbed semantic layer to complexity detection |
✅ Implemented |
COMPLEXITY_EXEMPLARS and SemanticComplexityDetector are present in complexity.py. |
None |
| P2 |
SemanticAlignmentChecker for query-response alignment |
⏭️ Not in audited files |
No alignment checker implementation in reviewed files; likely handled elsewhere (alignment_scorer.py area mentioned in AGENTS context). |
Not required for this task |
Detailed Findings
1) Enhanced Domain Exemplars (P0)
Implemented.
The plan called for richer exemplar coverage in weak domains. Current DOMAIN_EXEMPLARS contains expanded and targeted examples for:
Domain.FINANCIAL (e.g., compound interest, ROI, tax implications, diversification, P/E ratio)Domain.CONVERSATION (greetings, chat prompts, social dialogue markers)Domain.FACTUAL (capital/country questions, historical fact checks, verification-style prompts)
Test coverage present:
TestFastEmbedPlanEnhancements checks exemplar counts and representative prompts for these domains.
2) Smart Hybrid Mode Default (P0)
Implemented.
SemanticDomainDetector has use_hybrid=True by default and blends semantic + rule-based scoring in detect_with_scores.
Notes:
- Hybrid weighting is dynamic (
70/30 when semantic confidence is high, else 50/50).
- This differs from the exact pseudo-logic in the plan but achieves the same goal (hybrid-first behavior with confidence-aware blending).
3) Domain-Specific Thresholds (P1)
Implemented.
DOMAIN_THRESHOLDS includes domain-specific cutoffs:
- Lower:
CONVERSATION=0.50, FINANCIAL=0.55, FACTUAL=0.50
- Higher safety bars:
MEDICAL=0.70, LEGAL=0.70
- Fallback:
GENERAL=0.40
SemanticDomainDetector.detect_with_scores applies per-domain thresholding before fallback.
Test coverage present:
- Threshold-focused assertions exist and verify lower/higher threshold expectations.
4) Semantic Complexity Detection (P1)
Implemented.
complexity.py contains:
COMPLEXITY_EXEMPLARS for each complexity levelSemanticComplexityDetector using embeddings + cosine similarity- Optional hybrid blending with rule-based detector
Notes:
- The plan named this concept
SemanticComplexityBooster; the implementation name is SemanticComplexityDetector.
- Functional intent is satisfied.
5) Semantic Alignment Checker (P2)
Not in this audited scope.
No code changes required here for requested deliverables.
What’s Not Needed (for this session)
- No additional P0/P1 implementation work is required in the audited files because those items are already present.
- No OpenClaw or Skills integration work performed (explicitly skipped).
- No UI/frontend screenshot required (backend/test/docs-only changes).
Recommended Follow-ups (Optional)
- Add dedicated tests for
SemanticDomainDetector runtime behavior (with mocked embedder) to validate:
- hybrid default behavior,
- per-domain threshold fallback logic,
- disagreement resolution between rule vs semantic scores.
- Add/verify complexity semantic tests if not present in
tests/ for SemanticComplexityDetector.
- If alignment enhancement is still desired, audit
cascadeflow/quality/alignment_scorer.py separately for FastEmbed parity.
1---2name: 2405-fastembed-audit-report-dc0348b93description: FastEmbed v2 Audit Report (Plan vs Current Codebase)4---5# FastEmbed v2 Audit Report (Plan vs Current Codebase)67This audit compares `fastembed-improvement-plan.md` against the current implementation in:8- `cascadeflow/routing/domain.py`9- `cascadeflow/quality/complexity.py`10- `tests/test_domain_detection.py`1112Scope exclusions (per request):13- OpenClaw integrations14- Skills integration1516## Executive Summary1718- **P0 items:** ✅ Implemented.19- **P1 items:** ✅ Implemented.20- **P2 item (SemanticAlignmentChecker):** ⏭️ Not implemented in the audited files and not required for this session.21- **No missing P0/P1 gaps found** in the audited scope.2223---2425## Plan Item Status Matrix2627| Priority | Plan item | Status | Evidence | Action needed |28|---|---|---|---|---|29| P0 | Add domain exemplars (finance, conversation, factual) | ✅ Implemented | `DOMAIN_EXEMPLARS` includes expanded exemplar sets for `FINANCIAL`, `CONVERSATION`, and `FACTUAL`. | None |30| P0 | Enable hybrid mode by default | ✅ Implemented | `SemanticDomainDetector.__init__(..., use_hybrid: bool = True)` defaults hybrid on. | None |31| P1 | Domain-specific confidence thresholds | ✅ Implemented | `DOMAIN_THRESHOLDS` exists with lowered thresholds for conversation/financial/factual and stricter ones for medical/legal. | None |32| P1 | Add FastEmbed semantic layer to complexity detection | ✅ Implemented | `COMPLEXITY_EXEMPLARS` and `SemanticComplexityDetector` are present in `complexity.py`. | None |33| P2 | SemanticAlignmentChecker for query-response alignment | ⏭️ Not in audited files | No alignment checker implementation in reviewed files; likely handled elsewhere (`alignment_scorer.py` area mentioned in AGENTS context). | Not required for this task |3435---3637## Detailed Findings3839### 1) Enhanced Domain Exemplars (P0)4041**Implemented.**4243The plan called for richer exemplar coverage in weak domains. Current `DOMAIN_EXEMPLARS` contains expanded and targeted examples for:44- `Domain.FINANCIAL` (e.g., compound interest, ROI, tax implications, diversification, P/E ratio)45- `Domain.CONVERSATION` (greetings, chat prompts, social dialogue markers)46- `Domain.FACTUAL` (capital/country questions, historical fact checks, verification-style prompts)4748**Test coverage present:**49- `TestFastEmbedPlanEnhancements` checks exemplar counts and representative prompts for these domains.5051### 2) Smart Hybrid Mode Default (P0)5253**Implemented.**5455`SemanticDomainDetector` has `use_hybrid=True` by default and blends semantic + rule-based scoring in `detect_with_scores`.5657**Notes:**58- Hybrid weighting is dynamic (`70/30` when semantic confidence is high, else `50/50`).59- This differs from the exact pseudo-logic in the plan but achieves the same goal (hybrid-first behavior with confidence-aware blending).6061### 3) Domain-Specific Thresholds (P1)6263**Implemented.**6465`DOMAIN_THRESHOLDS` includes domain-specific cutoffs:66- Lower: `CONVERSATION=0.50`, `FINANCIAL=0.55`, `FACTUAL=0.50`67- Higher safety bars: `MEDICAL=0.70`, `LEGAL=0.70`68- Fallback: `GENERAL=0.40`6970`SemanticDomainDetector.detect_with_scores` applies per-domain thresholding before fallback.7172**Test coverage present:**73- Threshold-focused assertions exist and verify lower/higher threshold expectations.7475### 4) Semantic Complexity Detection (P1)7677**Implemented.**7879`complexity.py` contains:80- `COMPLEXITY_EXEMPLARS` for each complexity level81- `SemanticComplexityDetector` using embeddings + cosine similarity82- Optional hybrid blending with rule-based detector8384**Notes:**85- The plan named this concept `SemanticComplexityBooster`; the implementation name is `SemanticComplexityDetector`.86- Functional intent is satisfied.8788### 5) Semantic Alignment Checker (P2)8990**Not in this audited scope.**9192No code changes required here for requested deliverables.9394---9596## What’s Not Needed (for this session)9798- No additional P0/P1 implementation work is required in the audited files because those items are already present.99- No OpenClaw or Skills integration work performed (explicitly skipped).100- No UI/frontend screenshot required (backend/test/docs-only changes).101102---103104## Recommended Follow-ups (Optional)1051061. Add dedicated tests for `SemanticDomainDetector` runtime behavior (with mocked embedder) to validate:107 - hybrid default behavior,108 - per-domain threshold fallback logic,109 - disagreement resolution between rule vs semantic scores.1102. Add/verify complexity semantic tests if not present in `tests/` for `SemanticComplexityDetector`.1113. If alignment enhancement is still desired, audit `cascadeflow/quality/alignment_scorer.py` separately for FastEmbed parity.
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