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| import json | |
| import time | |
| from functools import partial | |
| from pathlib import Path | |
| import gradio as gr | |
| from . import evaluation | |
| from .config import display | |
| from .hub import model_repos, newest, revisions | |
| from .predictors import load | |
| from .text import ( | |
| CLASSIFY, | |
| EVALUATE, | |
| LOADING, | |
| NO_MODEL, | |
| SCORING, | |
| STATUS_FAILED, | |
| STATUS_LOADING, | |
| WARM_FAILED, | |
| WARMING, | |
| pushed_at, | |
| status_line, | |
| status_ready, | |
| ) | |
| from .turns import window | |
| EXAMPLES = json.loads((Path(__file__).parent / "examples.json").read_text(encoding="utf-8")) | |
| def classify(repo: str, revision: str, transcript: str) -> tuple[dict[str, float], str, str]: | |
| """Score a caller's turns for breakdown risk.""" | |
| text = window(transcript) | |
| if not repo or not text: | |
| return {}, "", "" | |
| predictor, sha = load(repo, revision) | |
| started = time.perf_counter() # after load, so the reading is inference alone | |
| labels, probabilities = predictor([text]) | |
| elapsed = (time.perf_counter() - started) * 1000 | |
| scores = {display(name): float(p) for name, p in zip(labels, probabilities[0])} | |
| return scores, text, f"`{sha[:7]}` · `{elapsed:.0f} ms`" | |
| def _actions(ready: bool, busy: str = "") -> tuple[gr.Button, gr.Button]: | |
| """Both actions at once: they wait on the same model, so they move together.""" | |
| return ( | |
| gr.Button(busy or CLASSIFY, interactive=ready), | |
| gr.Button(busy or EVALUATE, interactive=ready), | |
| ) | |
| # What each session is waiting on, so a pick that got superseded lets go quietly. | |
| _awaited: dict[str, tuple[str, str]] = {} | |
| def warm(repo: str, revision: str, request: gr.Request): | |
| """Fetch the picked revision up front, so an action only ever runs inference.""" | |
| if not repo: | |
| yield (*_actions(ready=False), status_line(NO_MODEL)) | |
| return | |
| pick = (repo, revision) | |
| _awaited[request.session_hash] = pick | |
| yield (*_actions(ready=False, busy=WARMING), status_line(STATUS_LOADING)) | |
| try: | |
| predictor, _ = load(repo, revision) | |
| sample = [EXAMPLES[0]["text"]] | |
| predictor(sample) # the first call pays torch's lazy init; pay it here | |
| started = time.perf_counter() | |
| predictor(sample) # so the reading matches what a click will cost | |
| ms = (time.perf_counter() - started) * 1000 | |
| except Exception as failure: | |
| if _awaited.get(request.session_hash) != pick: | |
| return | |
| # a bad revision must hand the buttons back, not dead-end the interface | |
| yield (*_actions(ready=True), status_line(STATUS_FAILED)) | |
| raise gr.Error(f"{WARM_FAILED}: {failure}") from failure | |
| if _awaited.get(request.session_hash) == pick: # else a newer pick owns the buttons | |
| yield (*_actions(ready=True), status_line(status_ready(ms))) | |
| def summary(report: evaluation.Report) -> str: | |
| return ( | |
| f"### {report.hits}/{report.total} — accuracy {report.hits / report.total:.1%}\n" | |
| f"`{report.repo}` @ `{report.model_sha[:7]}` · data `{report.dataset_sha[:7]}`" | |
| f" · {report.ms_per_case:.0f} ms per case" | |
| ) | |
| def evaluate(repo: str, revision: str, progress=gr.Progress()): | |
| if not repo: | |
| return NO_MODEL, [], [] | |
| progress(0, desc=LOADING) | |
| predictor, sha = load(repo, revision) | |
| track = partial(progress.tqdm, desc=SCORING) | |
| report = evaluation.run(repo, sha, predict=predictor, track=track) | |
| return summary(report), report.confusion, report.cases | |
| def pick_revision(repo: str) -> tuple[gr.Dropdown, str]: | |
| choices = revisions(repo) | |
| return ( | |
| gr.Dropdown(choices=choices, value=choices[0][1] if choices else None), | |
| pushed_at(model_repos().get(repo)), | |
| ) | |
| def refresh(repo: str, revision: str) -> tuple[gr.Dropdown, gr.Dropdown, str]: | |
| pushes = model_repos() | |
| chosen = repo if repo in pushes else newest(pushes) | |
| choices = revisions(chosen) if chosen else [] | |
| shas = [sha for _, sha in choices] | |
| keep = revision if revision in shas else (shas[0] if shas else None) | |
| return ( | |
| gr.Dropdown(choices=list(pushes), value=chosen), | |
| gr.Dropdown(choices=choices, value=keep), | |
| pushed_at(pushes[chosen] if chosen else None), | |
| ) | |