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Native Code Submission Portal β Language, Decoded / Expedition Tiny Aya
=======================================================================
A Gradio app for collecting natively-written Legesher code from
native speakers of Chinese, Spanish, and Urdu.
Contributors write Python in their native language using Legesher,
run it to verify it works, then submit it for research use.
HF Space secrets required:
HF_TOKEN β write token for pushing submissions to the dataset repo
HF_DATASET_ID β target dataset repo (e.g. "legesher-research/native-code-submissions")
"""
import json
import logging
import os
import subprocess
import sys
import tempfile
from pathlib import Path
# ---------------------------------------------------------------------------
# Install bundled Legesher wheels (not on PyPI) β runs on HF Spaces startup
# ---------------------------------------------------------------------------
def _install_legesher_wheels():
wheels_dir = Path(__file__).parent / "wheels"
if not wheels_dir.exists():
return
wheels = sorted(wheels_dir.glob("*.whl"))
if not wheels:
return
print(f"Installing {len(wheels)} Legesher wheel(s)...")
result = subprocess.run(
[sys.executable, "-m", "pip", "install", "--quiet"] + [str(w) for w in wheels],
capture_output=True, text=True
)
if result.returncode == 0:
print("Legesher wheels installed.")
else:
print("Wheel install warning:", result.stderr[-300:])
_install_legesher_wheels()
import uuid
from datetime import datetime, timezone
import gradio as gr
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Legesher setup
# ---------------------------------------------------------------------------
try:
from legesher_core import TokenTranslator
LEGESHER_OK = True
logger.info("Legesher loaded successfully.")
except ImportError as e:
LEGESHER_OK = False
logger.warning(f"Legesher not available: {e}. Run/translate disabled.")
# Cache translators so we don't reload on every button click
_translators: dict[str, TokenTranslator] = {}
def _get_native_to_en(lang: str) -> TokenTranslator:
if lang not in _translators:
en_to_native = TokenTranslator.from_language_pack(lang)
_translators[lang] = en_to_native.reverse()
return _translators[lang]
# ---------------------------------------------------------------------------
# Exercises
# ---------------------------------------------------------------------------
EXERCISES_PATH = Path(__file__).parent / "exercises.json"
with open(EXERCISES_PATH, encoding="utf-8") as _f:
_ALL_EXERCISES: dict = json.load(_f)
TIER_KEYS = ["tier1", "tier2", "tier3"]
TIER_LABELS = ["Tier 1 β Basic (10β20 lines)", "Tier 2 β Applied (20β50 lines)", "Tier 3 β Domain (50β100 lines)"]
LANGUAGES = {
"zh": "δΈζ (Chinese)",
"es": "EspaΓ±ol (Spanish)",
"ur": "Ψ§Ψ±Ψ―Ω (Urdu)",
}
# Reverse map: display label -> code (handles Gradio 6 returning label instead of value)
_LABEL_TO_CODE = {v: k for k, v in LANGUAGES.items()}
# ---------------------------------------------------------------------------
# Keyword reference β loaded from REFERENCE.md files per language
# ---------------------------------------------------------------------------
_REFERENCES_DIR = Path(__file__).parent / "references"
def load_reference(lang: str) -> str:
"""Load the Legesher REFERENCE.md for the given language."""
path = _REFERENCES_DIR / f"{lang}.md"
if path.exists():
return path.read_text(encoding="utf-8")
return f"_Reference file not found for `{lang}`._"
def normalize_lang(lang_input: str) -> str:
"""Accept either a language code ('ur') or display label ('Ψ§Ψ±Ψ―Ω (Urdu)') and return the code."""
if lang_input in LANGUAGES:
return lang_input
if lang_input in _LABEL_TO_CODE:
return _LABEL_TO_CODE[lang_input]
logger.warning(f"Unknown lang input: {lang_input!r}, falling back to zh")
return "zh"
def get_exercise_choices(lang: str, tier_idx: int) -> list[str]:
tier_key = TIER_KEYS[tier_idx]
exercises = _ALL_EXERCISES.get(lang, {}).get(tier_key, [])
return [ex["title"] for ex in exercises]
def get_exercise(lang: str, tier_idx: int, title: str) -> dict | None:
tier_key = TIER_KEYS[tier_idx]
for ex in _ALL_EXERCISES.get(lang, {}).get(tier_key, []):
if ex["title"] == title:
return ex
return None
# ---------------------------------------------------------------------------
# HuggingFace dataset submission
# ---------------------------------------------------------------------------
HF_TOKEN = os.environ.get("HF_TOKEN", "")
HF_DATASET_ID = os.environ.get("HF_DATASET_ID", "legesher-research/native-code-submissions")
def push_submission(row: dict) -> bool:
"""Push a single submission row to the HF dataset as a JSONL entry."""
if not HF_TOKEN:
logger.warning("HF_TOKEN not set β submission not saved to HF.")
return False
try:
from huggingface_hub import HfApi
api = HfApi(token=HF_TOKEN)
filename = f"submissions/{row['language']}/{row['id']}.json"
content = json.dumps(row, ensure_ascii=False, indent=2).encode("utf-8")
api.upload_file(
path_or_fileobj=content,
path_in_repo=filename,
repo_id=HF_DATASET_ID,
repo_type="dataset",
commit_message=f"[submission] {row['language']} {row['exercise_id']} {row['id'][:8]}",
)
return True
except Exception as e:
logger.error(f"HF upload failed: {e}")
return False
# ---------------------------------------------------------------------------
# Core actions
# ---------------------------------------------------------------------------
def run_code(code: str, lang: str, stdin: str = "") -> str:
"""Translate native code to English Python and execute it safely."""
lang = normalize_lang(lang)
if not code.strip():
return "Write some code first."
if not LEGESHER_OK:
return "Legesher is not available in this environment. Code execution disabled."
try:
translator = _get_native_to_en(lang)
english_code = translator.translate_code(code)
except Exception as e:
return f"Translation error: {e}"
try:
with tempfile.NamedTemporaryFile(
mode="w", suffix=".py", delete=False, encoding="utf-8"
) as tmp:
tmp.write(english_code)
tmp_path = tmp.name
result = subprocess.run(
[sys.executable, "-X", "utf8", tmp_path],
input=stdin if stdin.strip() else None,
capture_output=True,
text=True,
timeout=10,
encoding="utf-8",
env={**os.environ, "PYTHONIOENCODING": "utf-8", "PYTHONUTF8": "1"},
)
os.unlink(tmp_path)
out = result.stdout.strip()
err = result.stderr.strip()
if err:
out = (out + "\n\nβ οΈ Errors:\n" + err).strip()
return out or "(no output β did you call your function at the bottom?)"
except subprocess.TimeoutExpired:
return "Timed out after 10 seconds. Check for infinite loops or missing input."
except Exception as e:
return f"Execution error: {e}"
def submit_code(
code: str,
lang: str, # normalized below
tier_idx: int,
exercise_title: str,
time_spent: int,
consent: bool,
profile: gr.OAuthProfile | None,
) -> str:
if profile is None:
return "Please sign in with your HuggingFace account (button above) before submitting."
lang = normalize_lang(lang)
if not consent:
return "Please tick the consent checkbox before submitting."
if not code.strip():
return "Code is empty β nothing to submit."
if not exercise_title:
return "Select an exercise before submitting."
ex = get_exercise(lang, tier_idx, exercise_title)
exercise_id = ex["id"] if ex else f"{lang}-unknown"
row = {
"id": str(uuid.uuid4()),
"code": code,
"language": lang,
"exercise_id": exercise_id,
"exercise_title": exercise_title,
"tier": tier_idx + 1,
"time_spent_minutes": time_spent,
"submitted_at": datetime.now(timezone.utc).isoformat(),
"consent_given": True,
"legesher_version": "0.7.3",
"hf_username": profile.username,
}
saved = push_submission(row)
if saved:
return f"Submitted! Your contribution ID: `{row['id'][:8]}`. Thank you for contributing to Language, Decoded."
else:
# Fallback: save locally so nothing is lost
fallback_dir = Path(__file__).parent / "local_submissions"
fallback_dir.mkdir(exist_ok=True)
(fallback_dir / f"{row['id']}.json").write_text(
json.dumps(row, ensure_ascii=False, indent=2), encoding="utf-8"
)
return f"Saved locally (HF upload unavailable). ID: `{row['id'][:8]}`."
# ---------------------------------------------------------------------------
# UI helpers
# ---------------------------------------------------------------------------
def update_exercise_dropdown(lang: str, tier_idx: int):
choices = get_exercise_choices(lang, tier_idx)
value = choices[0] if choices else None
return gr.update(choices=choices, value=value)
def update_prompt(lang: str, tier_idx: int, exercise_title: str) -> str:
if not exercise_title:
return ""
ex = get_exercise(lang, tier_idx, exercise_title)
if not ex:
return ""
time_note = f"*Estimated time: ~{ex['time_estimate_min']} minutes*\n\n"
return time_note + ex["prompt"]
def update_on_lang_change(lang: str, tier_idx: int):
choices = get_exercise_choices(lang, tier_idx)
value = choices[0] if choices else None
prompt = update_prompt(lang, tier_idx, value) if value else ""
return gr.Dropdown(choices=choices, value=value), prompt
# ---------------------------------------------------------------------------
# Gradio UI
# ---------------------------------------------------------------------------
HEADER_MD = """
# Native Code Contribution Portal
### Language, Decoded β Expedition Tiny Aya
Write Python code in your native language using [Legesher](https://legesher.io) and contribute to our research on native-language programming.
**How it works:**
1. Select your language and an exercise
2. Write your solution using Legesher (native keywords + native variable names)
3. Click **Run** to verify your code works
4. Fill in the metadata and click **Submit**
---
"""
CONSENT_TEXT = (
"I confirm I am a native or fluent speaker of the selected language and wrote this code myself. "
"I grant permission for this code to be used in the Language, Decoded research project and "
"released as part of an open dataset under Apache 2.0 / CC-BY-4.0. "
"I retain copyright over my submission. My HuggingFace username will be stored alongside my "
"contribution for attribution and credit β no other personal information is collected."
)
SIDEBAR_MD = """
### What counts as native code?
- Variables, functions, and classes named in your language
- Written from scratch β not translated from an English solution
- Reflects how *you* would naturally think about the problem
- Uses Legesher keywords throughout
### What doesn't qualify?
- Word-for-word translations of English code
- AI-generated code
- English variable names with only keywords swapped
Need help? Read the full [criteria document](https://linear.app/legesher-research/document/native-code-criteria-qualification-disqualification-and-quality-rubric-5705fc83d6e8).
"""
def build_app() -> gr.Blocks:
with gr.Blocks(title="Native Code Submission β Language, Decoded") as app:
gr.Markdown(HEADER_MD)
# HF OAuth login β must be at top level of Blocks for the redirect to work
with gr.Row():
with gr.Column(scale=0, min_width=200):
gr.LoginButton()
with gr.Column(scale=1):
gr.Markdown("_Sign in with your HuggingFace account so we can credit your contribution._")
with gr.Row():
# ---- Left column: config + exercise ----
with gr.Column(scale=1):
lang_dropdown = gr.Dropdown(
label="Your language",
choices=[(v, k) for k, v in LANGUAGES.items()],
value="zh",
)
tier_radio = gr.Radio(
label="Exercise tier",
choices=TIER_LABELS,
value=TIER_LABELS[0],
)
exercise_dropdown = gr.Dropdown(
label="Exercise",
choices=get_exercise_choices("zh", 0),
value=get_exercise_choices("zh", 0)[0],
)
exercise_prompt = gr.Markdown(
value=update_prompt("zh", 0, get_exercise_choices("zh", 0)[0]),
label="Exercise prompt",
)
gr.Markdown(SIDEBAR_MD)
with gr.Accordion("Legesher keyword reference", open=False):
cheatsheet = gr.Markdown(
value=load_reference("zh"),
)
# ---- Right column: editor + run + submit ----
with gr.Column(scale=2):
gr.Markdown(
"_Write your solution using Legesher β use native-language variable and function names_",
)
code_editor = gr.Code(
label="Your Legesher code",
language="python",
lines=20,
value="",
)
with gr.Row():
run_btn = gr.Button("Run code", variant="secondary")
clear_btn = gr.Button("Clear", variant="stop")
stdin_input = gr.Textbox(
label="Program input (stdin) β one value per line",
placeholder="e.g. 15\n(leave blank if your code needs no input)",
lines=2,
)
run_output = gr.Textbox(
label="Output",
lines=6,
placeholder="Run your code to see output here...",
interactive=False,
)
gr.Markdown("---")
gr.Markdown("### Submit your solution")
time_slider = gr.Slider(
label="Time spent (minutes)",
minimum=1,
maximum=120,
step=1,
value=15,
)
consent_checkbox = gr.Checkbox(
label=CONSENT_TEXT,
value=False,
)
submit_btn = gr.Button("Submit contribution", variant="primary")
submit_status = gr.Textbox(
label="Submission status",
interactive=False,
)
# ---- State ----
tier_idx_state = gr.State(value=0)
lang_state = gr.State(value="zh")
# ---- Event wiring ----
def tier_to_idx(tier_label: str) -> int:
return TIER_LABELS.index(tier_label)
def on_tier_change(tier_label: str, lang: str):
try:
idx = TIER_LABELS.index(tier_label) if tier_label in TIER_LABELS else 0
choices = get_exercise_choices(lang, idx)
value = choices[0] if choices else None
prompt = update_prompt(lang, idx, value) if value else ""
return idx, gr.update(choices=choices, value=value), prompt
except Exception as e:
logger.error(f"on_tier_change error: {e!r} | tier_label={tier_label!r} lang={lang!r}")
return 0, gr.update(), ""
def on_lang_change(lang_raw: str, tier_label: str):
try:
lang_code = normalize_lang(lang_raw)
logger.info(f"on_lang_change: raw={lang_raw!r} -> code={lang_code!r} tier={tier_label!r}")
idx = TIER_LABELS.index(tier_label) if tier_label in TIER_LABELS else 0
choices = get_exercise_choices(lang_code, idx)
value = choices[0] if choices else None
prompt = update_prompt(lang_code, idx, value) if value else ""
sheet = load_reference(lang_code)
logger.info(f"on_lang_change OK: choices={choices}")
return lang_code, gr.update(choices=choices, value=value), prompt, sheet
except Exception as e:
logger.error(f"on_lang_change error: {e!r} | lang_raw={lang_raw!r}")
return "zh", gr.update(), "", load_reference("zh")
def on_exercise_change(exercise_title: str, lang_raw: str, tier_idx: int):
# Use lang_dropdown value directly (always current), not lang_state (can be stale)
try:
lang_code = normalize_lang(lang_raw)
return update_prompt(lang_code, tier_idx, exercise_title)
except Exception as e:
logger.error(f"on_exercise_change error: {e!r}")
return ""
lang_dropdown.change(
on_lang_change,
inputs=[lang_dropdown, tier_radio],
outputs=[lang_state, exercise_dropdown, exercise_prompt, cheatsheet],
)
tier_radio.change(
on_tier_change,
inputs=[tier_radio, lang_state],
outputs=[tier_idx_state, exercise_dropdown, exercise_prompt],
)
exercise_dropdown.change(
on_exercise_change,
inputs=[exercise_dropdown, lang_dropdown, tier_idx_state],
outputs=[exercise_prompt],
)
run_btn.click(
fn=run_code,
inputs=[code_editor, lang_state, stdin_input],
outputs=[run_output],
)
clear_btn.click(
fn=lambda: ("", "", ""),
outputs=[code_editor, stdin_input, run_output],
)
submit_btn.click(
fn=submit_code,
inputs=[
code_editor,
lang_state,
tier_idx_state,
exercise_dropdown,
time_slider,
consent_checkbox,
],
outputs=[submit_status],
)
return app
if __name__ == "__main__":
app = build_app()
app.launch(theme=gr.themes.Soft(primary_hue="blue"))
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