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Hugging Science Feedback API
A minimal FastAPI app that accepts feedback submissions and appends them
to the hugging-science/feedback HF dataset.
Deploy as a HF Space (Docker SDK):
hugging-science/feedback-api
Required Space secret:
HF_TOKEN — a write-scoped token for the hugging-science org
"""
import os
import json
import uuid
from datetime import datetime, timezone
from typing import Optional
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, field_validator
from huggingface_hub import HfApi, hf_hub_download
import tempfile
# ── Config ────────────────────────────────────────────────────────────────────
DATASET_REPO = "hugging-science/feedback"
FEEDBACK_FILE = "feedback.jsonl"
HF_TOKEN = os.environ.get("HF_TOKEN")
if not HF_TOKEN:
raise RuntimeError("HF_TOKEN secret is not set")
api = HfApi(token=HF_TOKEN)
# ── App ───────────────────────────────────────────────────────────────────────
app = FastAPI(title="Hugging Science Feedback API", version="1.0.0")
app.add_middleware(
CORSMiddleware,
allow_origins=["https://huggingscience.co", "http://localhost:5173"],
allow_methods=["POST", "GET"],
allow_headers=["Content-Type"],
)
# ── Schema ────────────────────────────────────────────────────────────────────
VALID_TYPES = {"dataset", "model", "challenge", "feedback"}
class FeedbackItem(BaseModel):
type: str
title: Optional[str] = None
description: str
submitted_at: Optional[str] = None
source: Optional[str] = "huggingscience.co"
@field_validator("type")
@classmethod
def validate_type(cls, v):
if v not in VALID_TYPES:
raise ValueError(f"type must be one of {VALID_TYPES}")
return v
@field_validator("description")
@classmethod
def validate_description(cls, v):
v = v.strip()
if len(v) < 5:
raise ValueError("description must be at least 5 characters")
if len(v) > 2000:
raise ValueError("description must be under 2000 characters")
return v
# ── Helpers ───────────────────────────────────────────────────────────────────
def load_existing() -> list[dict]:
"""Download the current feedback.jsonl from the dataset, return as list."""
try:
path = hf_hub_download(
repo_id=DATASET_REPO,
filename=FEEDBACK_FILE,
repo_type="dataset",
token=HF_TOKEN,
)
with open(path) as f:
return [json.loads(line) for line in f if line.strip()]
except Exception:
# File doesn't exist yet — start fresh
return []
def save_feedback(rows: list[dict]) -> None:
"""Upload the full feedback.jsonl back to the dataset."""
content = "\n".join(json.dumps(r, ensure_ascii=False) for r in rows) + "\n"
with tempfile.NamedTemporaryFile(mode="w", suffix=".jsonl", delete=False) as f:
f.write(content)
tmp_path = f.name
api.upload_file(
path_or_fileobj=tmp_path,
path_in_repo=FEEDBACK_FILE,
repo_id=DATASET_REPO,
repo_type="dataset",
commit_message=f"Add feedback entry ({rows[-1]['id'][:8]})",
)
# ── Routes ────────────────────────────────────────────────────────────────────
@app.get("/")
def root():
return {"status": "ok", "service": "Hugging Science Feedback API"}
@app.post("/submit", status_code=201)
def submit_feedback(item: FeedbackItem):
entry = {
"id": str(uuid.uuid4()),
"type": item.type,
"title": item.title or "",
"description": item.description,
"submitted_at": item.submitted_at or datetime.now(timezone.utc).isoformat(),
"source": item.source or "huggingscience.co",
"status": "pending",
}
try:
rows = load_existing()
rows.append(entry)
save_feedback(rows)
except Exception as e:
raise HTTPException(status_code=500, detail=f"Failed to save feedback: {e}")
return {"ok": True, "id": entry["id"]}
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