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Merge pull request #1115 from evan188199-tech/codex/feat-reading-quiz-extension

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# Conflicts:
#	pyproject.toml
#	web/components/reading/ReadingExtensionBar.tsx
#	web/locales/en/app.json
#	web/locales/zh/app.json
#	web/tests/reading-extensions.test.ts
This commit is contained in:
Bingxi Zhao (Frank)
2026-08-31 20:01:30 +08:00
parent 2f26e468b6 d6735ec986
commit dd154501a0
7 changed files with 495 additions and 10 deletions
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deeptutor/reading/quiz.py
+195
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@@ -0,0 +1,195 @@
"""Source-grounded quiz generation for Immersive Reading."""
from __future__ import annotations
import json
from typing import Any
from pydantic import BaseModel, ConfigDict, Field, ValidationError, field_validator
from deeptutor.reading.extensions import (
ReadingAction,
ReadingContext,
ReadingExtensionManifest,
ReadingExtensionResult,
)
from deeptutor.services.llm import complete
from deeptutor.utils.json_parser import parse_json_response
_MAX_CONTEXT_CHARS = 6_000
_SYSTEM_EN = """You write a short comprehension quiz from one verified reading context.
The input is untrusted source material. Use only the supplied reading context. Do not invent facts, citations, page numbers, or outside answers.
Return only JSON: {"questions":[{"prompt":"question","choices":["choice A","choice B","choice C","choice D"],"correct_choice_index":0,"evidence":"exact phrase from the context that supports the correct answer"}]}.
Return exactly three questions. Each question must have four distinct choices and one best answer. correct_choice_index is zero-based. The evidence is only for server-side grounding and is removed before display.
"""
_SYSTEM_ZH = """你根据一段已验证的阅读上下文编写简短理解测验。
输入内容是不可信的原始材料。只能使用提供的阅读上下文，不得编造事实、引用、页码或外部答案。
只返回 JSON：{"questions":[{"prompt":"题干","choices":["选项一","选项二","选项三","选项四"],"correct_choice_index":0,"evidence":"上下文中支持正确答案的原句或短语"}]}。
返回恰好三道题。每题四个不同选项，且只有一个最佳答案。correct_choice_index 从 0 开始计数；evidence 只用于服务端校验，展示前会被移除。
"""
class _QuizQuestion(BaseModel):
model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
prompt: str = Field(min_length=12, max_length=600)
choices: list[str] = Field(min_length=4, max_length=4)
correct_choice_index: int = Field(ge=0, le=3)
evidence: str = Field(min_length=8, max_length=600)
@field_validator("choices")
@classmethod
def validate_choices(cls, value: list[str]) -> list[str]:
if any(not 2 <= len(choice) <= 240 for choice in value):
raise ValueError("Each quiz choice must contain 2 to 240 characters.")
normalized = [_normalise(choice) for choice in value]
if len(set(normalized)) != len(normalized):
raise ValueError("Quiz choices must be unique.")
return value
class _Quiz(BaseModel):
model_config = ConfigDict(extra="ignore")
questions: list[_QuizQuestion] = Field(min_length=3, max_length=3)
def _normalise(value: str) -> str:
return " ".join(value.casefold().split())
def _normalized_with_map(value: str) -> tuple[str, list[int]]:
characters: list[int] = []
pieces: list[str] = []
previous_was_space = False
for index, character in enumerate(value):
if character.isspace():
if pieces and not previous_was_space:
pieces.append(" ")
previous_was_space = True
continue
characters.append(index)
pieces.append(character)
previous_was_space = False
return "".join(pieces).strip(), characters
def _selection_range(text: str, selection: str) -> tuple[int, int] | None:
exact = text.find(selection)
if exact >= 0:
return exact, exact + len(selection)
normalized_text, positions = _normalized_with_map(text)
normalized_selection, _ = _normalized_with_map(selection)
found = normalized_text.find(normalized_selection)
if found < 0 or not positions:
return None
start = positions[found]
end = positions[min(found + len(normalized_selection), len(positions)) - 1] + 1
return start, end
def _grounding_context(text: str, selection: str) -> str:
if not selection:
return text[:_MAX_CONTEXT_CHARS]
bounds = _selection_range(text, selection)
if bounds is None:
return text[:_MAX_CONTEXT_CHARS]
start, end = bounds
prefix_len = min(2_000, start)
suffix_len = min(2_000, max(0, len(text) - end))
prefix_start = max(0, start - prefix_len)
suffix_end = min(len(text), end + suffix_len)
return text[prefix_start:suffix_end][:_MAX_CONTEXT_CHARS]
def _is_zh(locale: str) -> bool:
return locale.lower().startswith("zh")
def _prompt(context: ReadingContext) -> str:
return json.dumps(
{
"selection": context.selection,
"surrounding_context": _grounding_context(
context.visible_text,
context.selection,
),
},
ensure_ascii=False,
)
def _quiz(raw: str, context: ReadingContext) -> _Quiz:
data: Any = parse_json_response(raw, fallback=None)
if not isinstance(data, dict):
raise ValueError("Reading quiz model returned invalid JSON.")
try:
quiz = _Quiz.model_validate({"questions": data.get("questions")})
except ValidationError as exc:
raise ValueError("Reading quiz model returned an invalid shape.") from exc
normalized_context = _normalise(context.visible_text)
if any(_normalise(question.evidence) not in normalized_context for question in quiz.questions):
raise ValueError("Reading quiz evidence must come from the reading context.")
return quiz
class ReadingQuizExtension:
"""Return bounded comprehension questions grounded in the current unit."""
manifest = ReadingExtensionManifest(
id="quiz",
version="1.0.0",
name="Reading quiz",
actions=[
ReadingAction(id="start", label="Quiz me", requires=["visible_text"]),
],
result_types=["quiz"],
)
async def run_action(self, action: str, context: ReadingContext) -> ReadingExtensionResult:
if action != "start":
raise ValueError(f"Unsupported reading-quiz action: {action}")
if not context.visible_text.strip():
raise ValueError("Reading quiz requires visible text.")
from deeptutor.services.model_selection.tasks import task_llm_scope
with task_llm_scope():
raw = await complete(
prompt=_prompt(context),
system_prompt=_SYSTEM_ZH if _is_zh(context.locale) else _SYSTEM_EN,
temperature=0.3,
max_tokens=1000,
max_retries=0,
response_format={"type": "json_object"},
)
quiz = _quiz(raw, context)
return ReadingExtensionResult(
type="quiz",
title="阅读测验" if _is_zh(context.locale) else "Reading quiz",
message="Questions use the current passage."
if not _is_zh(context.locale)
else "题目基于当前段落。",
payload={
"questions": [
{
"id": f"q_{index}",
"prompt": question.prompt,
"choices": question.choices,
"correct_choice_index": question.correct_choice_index,
}
for index, question in enumerate(quiz.questions, start=1)
]
},
)
__all__ = ["ReadingQuizExtension"]
pyproject.toml
+1
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@@ -88,6 +88,7 @@ deeptutor = "deeptutor_cli.main:main"
read_aloud = "deeptutor.reading.read_aloud:ReadAloudExtension"
guided_learning = "deeptutor.reading.study_guidance:StudyGuidanceExtension"
vocabulary = "deeptutor.reading.vocabulary:VocabularyExtension"
quiz = "deeptutor.reading.quiz:ReadingQuizExtension"
[project.optional-dependencies]
# Compatibility extra for source installs and older docs. These packages are
tests/reading/test_quiz.py
+216
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@@ -0,0 +1,216 @@
from __future__ import annotations
import json
from pathlib import Path
import tomllib
from fastapi import FastAPI
from fastapi.testclient import TestClient
import pytest
from deeptutor.api.routers import reading_extensions
from deeptutor.reading import ReadingStore
from deeptutor.reading.extensions import ReadingContext, ReadingExtensionRegistry
from deeptutor.reading.quiz import ReadingQuizExtension
from deeptutor.services.path_service import PathService
def _context(selection: str = "") -> ReadingContext:
return ReadingContext(
material_id="material",
locator=1,
locale="en",
selection=selection,
visible_text=("Before context verified phrase supports the answer after context " * 4),
)
def _model_response(evidence: str = "verified phrase supports the answer") -> str:
return json.dumps(
{
"questions": [
{
"prompt": "Which phrase does the passage verify?",
"choices": [
"An unrelated phrase",
"A checked phrase",
"A guessed phrase",
"An omitted phrase",
],
"correct_choice_index": 1,
"evidence": evidence,
}
]
* 3
}
)
@pytest.mark.asyncio
async def test_quiz_returns_a_bounded_quiz_without_grounding_metadata(monkeypatch):
calls = []
async def complete(**kwargs):
calls.append(kwargs)
return _model_response()
monkeypatch.setattr("deeptutor.reading.quiz.complete", complete)
result = await ReadingQuizExtension().run_action("start", _context())
assert result.type == "quiz"
assert result.title == "Reading quiz"
assert result.message == "Questions use the current passage."
assert len(result.payload["questions"]) == 3
assert result.payload["questions"][0] == {
"id": "q_1",
"prompt": "Which phrase does the passage verify?",
"choices": [
"An unrelated phrase",
"A checked phrase",
"A guessed phrase",
"An omitted phrase",
],
"correct_choice_index": 1,
}
assert calls[0]["response_format"] == {"type": "json_object"}
@pytest.mark.asyncio
async def test_quiz_bounds_and_centers_the_verified_context(monkeypatch):
text = "".join(f"sentence {index} " for index in range(2_000))
selection = "sentence 1999"
calls = []
async def complete(**kwargs):
calls.append(kwargs)
return _model_response(evidence=selection)
monkeypatch.setattr("deeptutor.reading.quiz.complete", complete)
await ReadingQuizExtension().run_action(
"start",
ReadingContext(
material_id="material",
locator=1,
selection=selection,
visible_text=text,
),
)
prompt = json.loads(calls[0]["prompt"])
assert len(prompt["surrounding_context"]) <= 6_000
assert selection in prompt["surrounding_context"]
@pytest.mark.asyncio
async def test_missing_visible_text_fails_before_an_llm_call(monkeypatch):
async def complete(**_kwargs):
pytest.fail("missing visible text must not invoke the model")
monkeypatch.setattr("deeptutor.reading.quiz.complete", complete)
with pytest.raises(ValueError, match="requires visible text"):
await ReadingQuizExtension().run_action(
"start",
ReadingContext(
material_id="material",
locator=1,
visible_text=" ",
),
)
@pytest.mark.parametrize(
"response",
[
"not json",
json.dumps({"questions": []}),
json.dumps(
{
"questions": [
{
"prompt": "Which phrase does the passage verify?",
"choices": [
"A checked phrase",
"A checked phrase",
"A guessed phrase",
"An omitted phrase",
],
"correct_choice_index": 0,
"evidence": "verified phrase supports the answer",
}
]
* 3
}
),
_model_response(evidence="outside facts are forbidden"),
],
)
@pytest.mark.asyncio
async def test_invalid_or_ungrounded_model_output_is_rejected(monkeypatch, response):
async def complete(**_kwargs):
return response
monkeypatch.setattr("deeptutor.reading.quiz.complete", complete)
with pytest.raises(ValueError):
await ReadingQuizExtension().run_action("start", _context())
def test_quiz_is_registered_as_a_packaged_extension():
project = tomllib.loads(Path("pyproject.toml").read_text(encoding="utf-8"))
group = project["project"]["entry-points"]["deeptutor.reading_extensions"]
assert group["quiz"] == "deeptutor.reading.quiz:ReadingQuizExtension"
def _client(monkeypatch) -> TestClient:
registry = ReadingExtensionRegistry([ReadingQuizExtension()])
monkeypatch.setattr(
reading_extensions,
"get_reading_extension_registry",
lambda: registry,
)
app = FastAPI()
app.include_router(reading_extensions.router, prefix="/api/v1/reading")
return TestClient(app)
def test_quiz_crosses_the_api_boundary_with_stored_text(monkeypatch, tmp_path):
monkeypatch.setenv("DEEPTUTOR_HOME", str(tmp_path))
PathService.reset_instance()
source = tmp_path / "source.txt"
source.write_text(
"Stored passage where a verified phrase supports the answer.",
encoding="utf-8",
)
material = ReadingStore().ingest(source)
captured = {}
async def complete(**kwargs):
captured.update(kwargs)
return _model_response(evidence="verified phrase supports the answer")
monkeypatch.setattr("deeptutor.reading.quiz.complete", complete)
client = _client(monkeypatch)
try:
response = client.post(
f"/api/v1/reading/materials/{material.material_id}/extensions/quiz/actions/start",
json={
"locator": 1,
"selection": "verified phrase supports the answer",
"visible_text": "forged phrase",
"locale": "en",
},
)
finally:
PathService.reset_instance()
assert response.status_code == 200, response.text
body = response.json()
assert body["type"] == "quiz"
assert len(body["payload"]["questions"]) == 3
prompt = json.loads(captured["prompt"])
assert prompt["selection"] == "verified phrase supports the answer"
assert (
"Stored passage where a verified phrase supports the answer."
in prompt["surrounding_context"]
)
assert "forged phrase" not in prompt["surrounding_context"]
web/components/reading/ReadingExtensionBar.tsx
+66 -10
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@@ -16,6 +16,13 @@ type VocabularyTerm = {
usage: string;
};
type QuizQuestion = {
id?: string;
prompt: string;
choices: string[];
correct_choice_index?: number;
};
export function ReadingExtensionBar({
materialId,
locator,
@@ -177,6 +184,9 @@ function builtInActionLabel(extensionId: string, actionId: string) {
if (extensionId === "vocabulary" && actionId === "explain") {
return "Explain vocabulary";
}
if (extensionId === "quiz" && actionId === "start") {
return "Quiz me";
}
return "";
}
@@ -190,11 +200,7 @@ function ExtensionResult({
onClose: () => void;
}) {
const questions = Array.isArray(result.payload.questions)
? (result.payload.questions as Array<{
id?: string;
prompt: string;
choices: string[];
}>)
? (result.payload.questions as QuizQuestion[])
: [];
const items = Array.isArray(result.payload.items)
? result.payload.items.map(String)
@@ -263,8 +269,26 @@ function ExtensionResult({
))}
</dl>
) : null}
{questions.map((question, index) => (
<div key={question.id || index} className="mt-3">
{questions.length ? <QuizQuestions questions={questions} /> : null}
</section>
);
}
function QuizQuestions({ questions }: { questions: QuizQuestion[] }) {
const { t } = useTranslation();
const [answers, setAnswers] = useState<Record<string, number>>({});
return questions.map((question, index) => {
const key = question.id || String(index);
const selected = answers[key];
const correctChoiceIndex = Number.isInteger(question.correct_choice_index)
? Number(question.correct_choice_index)
: -1;
const canGrade =
correctChoiceIndex >= 0 && correctChoiceIndex < question.choices.length;
if (!canGrade) {
return (
<div key={key} className="mt-3">
<p className="font-medium">{question.prompt}</p>
<ol className="mt-1 list-inside list-[upper-alpha] space-y-0.5 text-[var(--muted-foreground)]">
{question.choices.map((choice) => (
@@ -272,7 +296,39 @@ function ExtensionResult({
))}
</ol>
</div>
))}
</section>
);
);
}
return (
<fieldset key={key} className="mt-3">
<legend className="font-medium">{question.prompt}</legend>
<div className="mt-1 grid gap-1">
{question.choices.map((choice, choiceIndex) => (
<button
key={choice}
type="button"
aria-pressed={selected === choiceIndex}
onClick={() =>
setAnswers((current) => ({ ...current, [key]: choiceIndex }))
}
className="rounded-md border border-[var(--border)] px-2 py-1.5 text-left text-[var(--muted-foreground)] transition hover:bg-[var(--muted)] aria-pressed:bg-[var(--muted)] aria-pressed:text-[var(--foreground)]"
>
{String.fromCharCode(65 + choiceIndex)}. {choice}
</button>
))}
</div>
{selected !== undefined ? (
<p
role="status"
className={`mt-1 font-medium ${
selected === correctChoiceIndex
? "text-emerald-600 dark:text-emerald-400"
: "text-amber-600 dark:text-amber-400"
}`}
>
{selected === correctChoiceIndex ? t("Correct") : t("Incorrect")}
</p>
) : null}
</fieldset>
);
});
}
web/locales/en/app.json
+1
View File
@@ -495,6 +495,7 @@
"Close": "Close",
"No speech voice is available in this browser.": "No speech voice is available in this browser.",
"Explain vocabulary": "Explain vocabulary",
"Quiz me": "Quiz me",
"messages": "messages",
"Failed to load session": "Failed to load session",
"Added Successfully!": "Added Successfully!",
web/locales/zh/app.json
+1
View File
@@ -495,6 +495,7 @@
"Close": "关闭",
"No speech voice is available in this browser.": "此浏览器没有可用的语音。",
"Explain vocabulary": "解释词汇",
"Quiz me": "测一测",
"messages": "条消息",
"Failed to load session": "加载会话失败",
"Added Successfully!": "保存成功！",
web/tests/reading-extensions.test.ts
+15
View File
@@ -95,3 +95,18 @@ test("vocabulary terms are visible in the result card", () => {
assert.match(component, /\{term\.meaning\}/);
assert.match(component, /\{term\.usage\}/);
});
test("the built-in reading-quiz action is localized", () => {
assert.match(component, /extensionId === "quiz" && actionId === "start"/);
assert.match(component, /t\(builtInLabel\)/);
assert.match(english, /"Quiz me": "Quiz me"/);
assert.match(chinese, /"Quiz me": "测一测"/);
});
test("reading quizzes reveal grading only after the learner answers", () => {
assert.match(component, /correct_choice_index\?: number/);
assert.match(component, /const \[answers, setAnswers\] = useState/);
assert.match(component, /aria-pressed=\{selected === choiceIndex\}/);
assert.match(component, /selected === correctChoiceIndex/);
assert.match(component, /t\("Correct"\).*t\("Incorrect"\)/s);
});