Upload folder using huggingface_hub

Dockerfile

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+FROM python:3.10-slim
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+COPY app.py .
+EXPOSE 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+import io, json, logging, os, time, uuid, asyncio
+from collections import defaultdict, deque
+
+import torch
+from fastapi import FastAPI, HTTPException, Depends, Request
+from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
+from fastapi.responses import JSONResponse
+from huggingface_hub import HfApi
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from pydantic import BaseModel
+
+# ---------- Config ----------
+MODEL_ID = "wolethereader/STORM-OS-MT-3B"
+ORG_NAME = "wolethereader"
+TGT_LANG = "eng_Latn"
+LANG_CODES = {"yo": "yor_Latn", "ha": "hau_Latn", "ig": "ibo_Latn", "pcm": "pcm_Latn"}
+VALID_LANGS = set(LANG_CODES.keys())
+MAX_TEXT_CHARS = 2000
+
+app = FastAPI(title="STORM-OS MT API")
+
+def log_event(event, **fields):
+    print(json.dumps({"event": event, "ts": time.time(), **fields}))
+
+# ---------- Auth: HF token AND must belong to the org ----------
+security = HTTPBearer()
+hf_api = HfApi()
+_token_cache = {}
+TOKEN_CACHE_TTL = 300
+
+EXTERNAL_ACCESS_TOKEN = os.environ.get("EXTERNAL_ACCESS_TOKEN")
+
+async def verify_org_token(creds: HTTPAuthorizationCredentials = Depends(security)):
+    token = creds.credentials
+
+    if EXTERNAL_ACCESS_TOKEN and token == EXTERNAL_ACCESS_TOKEN:
+        log_event("auth_external_token_used")
+        return "external-collaborator"
+
+    now = time.time()
+    cached = _token_cache.get(token)
+    if cached and cached[1] > now:
+        return cached[0]
+    try:
+        info = hf_api.whoami(token=token)
+    except Exception:
+        log_event("auth_failed_invalid_token")
+        raise HTTPException(status_code=401, detail="Invalid or expired Hugging Face token")
+    username = info.get("name", "unknown")
+    user_orgs = [o.get("name") for o in info.get("orgs", [])]
+    if ORG_NAME not in user_orgs:
+        log_event("auth_failed_not_org_member", user=username, orgs=user_orgs)
+        raise HTTPException(status_code=403, detail=f"Token does not belong to a member of '{ORG_NAME}'")
+    _token_cache[token] = (username, now + TOKEN_CACHE_TTL)
+    return username
+
+# ---------- Rate limiting ----------
+_rate_state = defaultdict(deque)
+RATE_LIMIT_PER_MIN = 30
+
+def check_rate_limit(username: str):
+    now = time.time()
+    q = _rate_state[username]
+    while q and q[0] < now - 60:
+        q.popleft()
+    if len(q) >= RATE_LIMIT_PER_MIN:
+        raise HTTPException(status_code=429, detail="Rate limit exceeded, try again shortly")
+    q.append(now)
+
+# ---------- Model ----------
+tokenizer = None
+model = None
+
+@app.on_event("startup")
+async def startup():
+    global tokenizer, model
+    log_event("loading_model", model=MODEL_ID)
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+    model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID, torch_dtype=torch.bfloat16)
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+    model.eval()
+    log_event("model_loaded_ok", device=device)
+
+class TranslateRequest(BaseModel):
+    text: str
+    source_lang: str
+    max_new_tokens: int = 128
+
+@app.get("/")
+def root():
+    return {"status": "ok", "languages": sorted(VALID_LANGS), "engine": MODEL_ID}
+
+@app.get("/health")
+def health():
+    return {"status": "ok" if model is not None else "loading"}
+
+@app.post("/translate")
+async def translate(req: TranslateRequest, username: str = Depends(verify_org_token)):
+    check_rate_limit(username)
+
+    if req.source_lang not in VALID_LANGS:
+        raise HTTPException(status_code=400, detail=f"source_lang must be one of {sorted(VALID_LANGS)}")
+    if not req.text or not req.text.strip():
+        raise HTTPException(status_code=400, detail="text must not be empty")
+    if len(req.text) > MAX_TEXT_CHARS:
+        raise HTTPException(status_code=400, detail=f"text exceeds {MAX_TEXT_CHARS} character limit")
+
+    request_id = str(uuid.uuid4())
+    start = time.time()
+
+    tokenizer.src_lang = LANG_CODES[req.source_lang]
+    inputs = tokenizer(req.text, return_tensors="pt", truncation=True, max_length=128).to(model.device)
+    tgt_id = tokenizer.convert_tokens_to_ids(TGT_LANG)
+    with torch.no_grad():
+        out = model.generate(
+            **inputs,
+            forced_bos_token_id=tgt_id,
+            max_new_tokens=req.max_new_tokens,
+            max_length=None,
+        )
+    translated = tokenizer.decode(out[0], skip_special_tokens=True)
+    elapsed_s = round(time.time() - start, 2)
+
+    log_event("translate_ok", request_id=request_id, user=username,
+              source_lang=req.source_lang, elapsed_s=elapsed_s)
+
+    return {
+        "request_id": request_id,
+        "source_lang": req.source_lang,
+        "target_lang": "en",
+        "translated_text": translated,
+        "elapsed_s": elapsed_s,
+    }
+
+@app.exception_handler(HTTPException)
+async def http_exception_handler(request: Request, exc: HTTPException):
+    log_event("request_error", path=str(request.url.path), status_code=exc.status_code, detail=exc.detail)
+    return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})

requirements.txt

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+fastapi
+uvicorn
+transformers==5.15.0
+torch
+sentencepiece
+accelerate
+python-multipart