mirror of
https://github.com/onestardao/WFGY.git
synced 2026-04-28 19:50:17 +00:00
162 lines
8.5 KiB
Markdown
162 lines
8.5 KiB
Markdown
# Eval: Latency vs Accuracy Trade-off
|
||
|
||
This page defines how to measure, report, and optimize the trade-off between model latency and retrieval/answer accuracy. It is not enough to chase precision; stable systems must also meet latency SLOs while holding ΔS and λ within guardrails.
|
||
|
||
## Open these first
|
||
|
||
* Core eval protocols: [Eval Benchmarking](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval/eval_benchmarking.md)
|
||
* Precision/recall metrics: [Eval RAG Precision/Recall](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval/eval_rag_precision_recall.md)
|
||
* Observability instruments: [deltaS\_thresholds.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval_Observability/deltaS_thresholds.md), [lambda\_observe.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval_Observability/lambda_observe.md)
|
||
* Drift and variance: [variance\_and\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval_Observability/variance_and_drift.md)
|
||
|
||
---
|
||
|
||
## Acceptance targets
|
||
|
||
* **Latency**:
|
||
|
||
* Median ≤ 1.2× baseline
|
||
* P90 ≤ 1.5× baseline
|
||
|
||
* **Accuracy**:
|
||
|
||
* Precision ≥ 0.80
|
||
* Recall ≥ 0.70
|
||
* ΔS(question, cited) ≤ 0.45 for ≥ 80 percent of runs
|
||
* λ convergent across paraphrases
|
||
|
||
* **Cost stability**:
|
||
|
||
* Tokens or API cost per correct answer ≤ 1.3× baseline
|
||
|
||
If accuracy improves but latency inflates beyond thresholds, classify as *not production-ready*. Only ship when both dimensions pass.
|
||
|
||
---
|
||
|
||
## Measurement protocol
|
||
|
||
1. **Dual track runs**
|
||
|
||
* Run with and without extra retrieval steps (rerank, multi-hop, HyDE, etc).
|
||
* Record latency per stage (retrieve, rerank, reason).
|
||
|
||
2. **Buckets**
|
||
|
||
* Short queries: <50 tokens
|
||
* Medium queries: 50–200 tokens
|
||
* Long queries: >200 tokens
|
||
Latency vs accuracy must be reported per bucket.
|
||
|
||
3. **Seeds and paraphrases**
|
||
|
||
* Use 2 random seeds, 3 paraphrases each.
|
||
* Average and variance required for both latency and accuracy metrics.
|
||
|
||
4. **Normalization**
|
||
|
||
* Report cost per correct answer, not raw tokens.
|
||
* Normalize across providers for fair comparison.
|
||
|
||
---
|
||
|
||
## Reporting schema
|
||
|
||
Append to the JSONL logs from [Eval Benchmarking](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval/eval_benchmarking.md):
|
||
|
||
```json
|
||
{
|
||
"suite": "v1_latency",
|
||
"arm": "with_rerank",
|
||
"provider": "openai",
|
||
"model": "gpt-4o-mini-2025-07",
|
||
"bucket": "medium",
|
||
"precision": 0.82,
|
||
"recall": 0.71,
|
||
"ΔS_avg": 0.39,
|
||
"λ_flip_rate": 0.02,
|
||
"latency_ms": { "retrieve": 120, "rerank": 85, "reason": 910 },
|
||
"latency_total_ms": 1115,
|
||
"latency_vs_baseline": 1.35,
|
||
"tokens": { "in": 1980, "out": 510 },
|
||
"cost_per_correct": 1.25,
|
||
"notes": "acceptable trade-off"
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## Diagnostic questions
|
||
|
||
When latency grows faster than accuracy:
|
||
|
||
* Is reranking adding value or just delay? → check ΔS histograms pre/post rerank.
|
||
* Are paraphrases redundant? → drop to 2 if λ stability holds.
|
||
* Is retrieval k too large? → compare 5, 10, 20.
|
||
* Are you re-embedding too often? → reuse cached vectors.
|
||
* Is model size the bottleneck? → test smaller model + WFGY vs large model baseline.
|
||
|
||
---
|
||
|
||
## Escalation and fixes
|
||
|
||
* **Latency regressions without accuracy gain** → cut rerank or hybrid steps. See [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md).
|
||
* **High ΔS despite more steps** → rebuild index and re-chunk. See [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md).
|
||
* **Unstable λ across seeds** → clamp variance with BBAM, see [variance\_and\_drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Eval_Observability/variance_and_drift.md).
|
||
|
||
---
|
||
|
||
## Minimal 60-second run
|
||
|
||
1. Pick 5 medium-length questions.
|
||
2. Run baseline and WFGY rerank arm.
|
||
3. Record latency\_total\_ms and accuracy metrics.
|
||
4. Accept only if ΔS ≤ 0.45 and latency inflation ≤ 1.5× baseline.
|
||
|
||
---
|
||
|
||
### 🔗 Quick-Start Downloads (60 sec)
|
||
|
||
| Tool | Link | 3-Step Setup |
|
||
| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
|
||
| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
|
||
| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
|
||
|
||
---
|
||
|
||
### 🧭 Explore More
|
||
|
||
| Module | Description | Link |
|
||
| ------------------------ | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
|
||
| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
|
||
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
|
||
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
|
||
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
|
||
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
|
||
| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
|
||
| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
|
||
|
||
---
|
||
|
||
> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
|
||
> Engineers, hackers, and open source builders who supported WFGY from day one.
|
||
|
||
> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
|
||
|
||
<div align="center">
|
||
|
||
[](https://github.com/onestardao/WFGY)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
|
||
|
||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
|
||
|
||
|
||
</div>
|