From c653de4916e66cfd22f5f52cbcc7cac85a081d14 Mon Sep 17 00:00:00 2001 From: danielbusnz-lgtm Date: Fri, 29 May 2026 12:25:27 -0400 Subject: [PATCH 1/3] Fix stale comments in training and export calibrate_temperature said the search range was [0.05, 20]; it is [0.5, 20.0]. threshold_analysis hard-coded "124-row holdout"; use the actual count. Drop a few export_onnx labels that restated the next call. --- src/routelet/export_onnx.py | 10 ++-------- src/routelet/train_setfit.py | 6 +++--- 2 files changed, 5 insertions(+), 11 deletions(-) diff --git a/src/routelet/export_onnx.py b/src/routelet/export_onnx.py index dc01719..d3afc0a 100644 --- a/src/routelet/export_onnx.py +++ b/src/routelet/export_onnx.py @@ -156,18 +156,14 @@ def main() -> None: print(f"ST pooling mode: {pooling_mode}") print(f"ST modules: {[type(m).__name__ for m in body]}") - # Build the exportable wrapper. wrapper = EncoderWithPooling(body) wrapper.eval() - - # Export fp32 ONNX. _export_embedder(wrapper, EMBEDDER_OUT) - # Quantize to int8. quantize_dynamic(EMBEDDER_OUT, EMBEDDER_INT8_OUT, weight_type=QuantType.QInt8) print(f"[quantize] saved {EMBEDDER_INT8_OUT}") - # Load fitted temperature T from the file written by train_setfit.py. + # Temperature is fitted and written by train_setfit.py; absent means no scaling. temp_path = Path(TEMPERATURE_FILE) if temp_path.exists(): temperature = json.loads(temp_path.read_text())["temperature"] @@ -176,7 +172,7 @@ def main() -> None: temperature = 1.0 print(f"[temperature] {TEMPERATURE_FILE} not found, using T=1.0 (no scaling)") - # Dump LR head to JSON. classes_ order is what argmax maps to. + # classes_ order is the column order the Rust consumer's argmax maps back to labels. labels = head.classes_.tolist() head_data = { "coef": head.coef_.tolist(), @@ -194,11 +190,9 @@ def main() -> None: shutil.copy(f"{SETFIT_DIR}/tokenizer.json", TOKENIZER_OUT) print(f"[tokenizer] copied -> {TOKENIZER_OUT}") - # Print I/O signature. fp32_sess = ort.InferenceSession(EMBEDDER_OUT, providers=["CPUExecutionProvider"]) _print_session_info(fp32_sess) - # File sizes. fp32_bytes = Path(EMBEDDER_OUT).stat().st_size int8_bytes = Path(EMBEDDER_INT8_OUT).stat().st_size print("\nfile sizes:") diff --git a/src/routelet/train_setfit.py b/src/routelet/train_setfit.py index 43bc7e2..7bdab76 100644 --- a/src/routelet/train_setfit.py +++ b/src/routelet/train_setfit.py @@ -70,8 +70,8 @@ def calibrate_temperature( ) -> float: """Fit a scalar temperature T on calib_examples. - Minimizes NLL of softmax(logits / T) against true labels using - scipy.optimize.minimize_scalar with Brent's method (bounded to [0.05, 20]). + Minimizes NLL of softmax(logits / T) against true labels with + scipy.optimize.minimize_scalar (bounded method) over T in [0.5, 20.0]. Returns T > 0. @@ -176,7 +176,7 @@ def threshold_analysis( n = len(test_examples) def _print_table(conf: np.ndarray, label: str) -> None: - print(f"\n--- confidence threshold analysis (124-row holdout, {label}) ---") + print(f"\n--- confidence threshold analysis ({n}-row holdout, {label}) ---") print( f"{'threshold':>10} {'deferred':>10} {'defer%':>8} " f"{'kept_acc':>10} {'defer_acc':>10}" From 975efd88d2efcdf9fa80e4393374aa82a227f70f Mon Sep 17 00:00:00 2001 From: danielbusnz-lgtm Date: Fri, 29 May 2026 12:25:32 -0400 Subject: [PATCH 2/3] Remove the unbuilt serve.py stub It was a docstring and a TODO, nothing imported it, and Aegis runs the model in-process via ONNX. 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Kept stable so it caches across the # per-command calls. -SYSTEM = """You are an intent router. Classify each user command into exactly one of five intents: +SYSTEM = """You are an intent classifier for short voice commands. Classify each into one of five +intents. First strip filler words (um, uh, like) and self-corrections, then classify. -- find_action: locate or operate a UI element on the current screen. +- find_action: locate or operate a named UI element on the current screen. - integration: one discrete action against an app or service. -- chat: answer from general knowledge or conversation. No app action, no personal data. -- memory: store or recall a personal fact (storing needs an explicit remember/note/save). -- agent: a task needing two or more chained steps or a plan. +- chat: general knowledge or conversation. No app action, no personal data. The default. +- memory: store or recall a personal fact. Storing needs an explicit remember/note/save. +- agent: a task needing two or more steps or a plan. -Tie-breakers for the tricky cases: -- Two or more chained actions ("X and then Y") is agent, not integration. -- A question answered from a stored personal fact is memory; from world knowledge it is chat. -- A UI verb (click/tap/scroll) on a named element is find_action, even if an app is named. +Apply these boundary rules first for the tricky cases: +- Steps: two or more chained actions ("X and then Y"), or an implied multi-step task + needing a plan ("book me a restaurant"), is agent, not integration. +- Source: answered from a stored personal fact is memory; from world knowledge it is chat. +- Storing: "remember/note/save X" is memory even when it looks like another intent. +- A UI verb (click/tap/scroll/select) on a named element is find_action, even if an app is named. - Playback (skip, pause, next, volume) is integration, not find_action, unless a button is named. -- "explain how to..." or "talk me through..." is chat, even when it names an app action.""" +- "Explain how to..." or "talk me through..." is chat, even when it names an app action. + +If a command still fits more than one after these rules, pick the first match in this order: +agent, memory, integration, find_action, chat.""" INTENT_SCHEMA = { "type": "object",