From 2ce4a20764a61482fe3825984e64541cf1af2de5 Mon Sep 17 00:00:00 2001 From: Mr-Neutr0n <64578610+Mr-Neutr0n@users.noreply.github.com> Date: Mon, 5 Oct 2026 11:51:47 +0000 Subject: [PATCH] Fix #3690: benchmarks: code-intelligence result inaccessible; BENCHMARK Signed-off-by: Mr-Neutr0n <64578610+Mr-Neutr0n@users.noreply.github.com> (cherry picked from commit c7bbf6c834cef8875126c5d6e763a70035ede488) --- BENCHMARKS.md | 16 ++++++++++++++++ README.md | 1 + 2 files changed, 17 insertions(+) diff --git a/BENCHMARKS.md b/BENCHMARKS.md index 6c1a6d331..cdab7867a 100644 --- a/BENCHMARKS.md +++ b/BENCHMARKS.md @@ -30,6 +30,7 @@ Highlights: | Memory | LOCOMO (300) | QA accuracy | 45.3% | supermemory 49.7% (11x ingest cost), bm25 31.3%, mem0 27.3% | | Memory | LOCOMO (300) | recall@10 | 0.497 | bm25 0.362, mem0 0.048 | | Memory | LongMemEval-S (50) | QA accuracy | 76% | dense RAG 76%, hybrid 74%, mem0 70% | +| Code | ERPNext cross-tool (6) | key-fact coverage | 82.0% | grep/read baseline 70.8% | | Cost | LOCOMO ingest | USD | ~$1.40 | supermemory $15.67, mem0 $3.48 | | Cost | graph build | LLM credits | $0 | n/a | @@ -148,6 +149,21 @@ graphify pays for itself in accuracy against searching raw files, and avoids the context-stuffing anti-pattern of packing the whole repo into every turn (which costs roughly 20x the tokens for lower coverage). +### INFERRED cross-file edge precision (FastAPI demo corpus) + +The README hero graph is the upstream [FastAPI](https://github.com/fastapi/fastapi) +library extracted AST-only (no semantic pass). To check the `INFERRED` confidence +tag on cross-file resolver edges, we manually audited every such edge +(`calls`, `indirect_call`, `imports`, `imports_from`, `inherits`) whose source and +target both live under `fastapi/` (production package sources, excluding the test +tree). This is a dated manual spot-check, not a continuously-measured metric: on a +fresh AST-only extract (2026-10-05) all 12 such edges were correct. Reproduce by +running `graphify .` against a FastAPI checkout and inspecting the INFERRED +cross-file edges whose endpoints both sit under `fastapi/`. Homonymous helpers in +`tests/` produce noisier INFERRED `calls` edges; the tag is most meaningful on +production cross-file resolution, where the resolver prefers no edge over a wrong +one. + ## Results: temporal (15 years of ERPNext) 689 weekly AST checkpoints, 2011 to 2026, built deterministically with no LLM. diff --git a/README.md b/README.md index fd72e793a..fb8eaf372 100644 --- a/README.md +++ b/README.md @@ -126,6 +126,7 @@ What you get out of the box: | LOCOMO (n=300) | recall@10 | **0.497** | mem0 0.048, supermemory 0.149 | | LOCOMO (n=300) | QA accuracy | 45.3% | supermemory 49.7%, mem0 27.3% | | LongMemEval-S (n=50) | QA accuracy | **76%** | tied with dense RAG | +| ERPNext cross-tool (n=6) | key-fact coverage | **82.0%** | grep/read baseline 70.8% | | Graph build | LLM credits | **0** | per-token for most systems | Every system ran on the same harness with the same model and budgets, scored by a judge blind-validated against a second judge (90.6% agreement, Cohen's kappa 0.81). Full per-system tables, the code-intelligence result, and reproduction commands: **[BENCHMARKS.md](./BENCHMARKS.md)**.