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Add Dockerfile and HF Spaces deployment config
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import io
import json
import os
import pathlib
import time
from typing import Optional
import httpx
import pdfplumber
from docx import Document as DocxDocument
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Field
load_dotenv()
CONCENTRATE_API_KEY = os.getenv("CONCENTRATE_API_KEY", "")
CONCENTRATE_BASE_URL = "https://api.concentrate.ai/v1"
app = FastAPI(title="LLM Arena Backend")
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# ── Model list cache ──────────────────────────────────────────────────────────
_models_cache: dict = {"data": None, "fetched_at": 0.0}
CACHE_TTL_SECONDS = 300
def _headers() -> dict[str, str]:
return {
"Authorization": f"Bearer {CONCENTRATE_API_KEY}",
"Content-Type": "application/json",
}
@app.get("/api/models")
async def list_models():
"""Return available models, cached for 5 minutes."""
now = time.time()
if _models_cache["data"] and now - _models_cache["fetched_at"] < CACHE_TTL_SECONDS:
return _models_cache["data"]
if not CONCENTRATE_API_KEY:
raise HTTPException(status_code=500, detail="CONCENTRATE_API_KEY not set")
async with httpx.AsyncClient(timeout=15) as client:
resp = await client.get(f"{CONCENTRATE_BASE_URL}/models", headers=_headers())
if resp.status_code != 200:
raise HTTPException(status_code=resp.status_code, detail=resp.text)
raw = resp.json()
models_list = raw.get("data", raw) if isinstance(raw, dict) else raw
simplified = []
for m in models_list:
slug = m.get("slug", "")
display_name = m.get("name", slug)
author = m.get("author", {}).get("slug", "unknown")
providers = m.get("providers", {})
if providers:
for provider_slug in providers:
model_id = f"{provider_slug}/{slug}"
simplified.append({"id": model_id, "name": display_name, "provider": provider_slug})
else:
simplified.append({"id": slug, "name": display_name, "provider": author})
simplified.sort(key=lambda x: (x["provider"], x["name"]))
_models_cache["data"] = simplified
_models_cache["fetched_at"] = now
return simplified
# ── File upload ───────────────────────────────────────────────────────────────
MAX_FILE_SIZE = 10 * 1024 * 1024 # 10 MB
ALLOWED_EXTENSIONS = {".pdf", ".docx", ".doc", ".txt", ".md"}
def _extract_text_pdf(data: bytes) -> str:
with pdfplumber.open(io.BytesIO(data)) as pdf:
pages = []
for page in pdf.pages:
text = page.extract_text()
if text:
pages.append(text)
return "\n\n".join(pages)
def _extract_text_docx(data: bytes) -> str:
doc = DocxDocument(io.BytesIO(data))
return "\n\n".join(p.text for p in doc.paragraphs if p.text.strip())
def _extract_text_plain(data: bytes) -> str:
return data.decode("utf-8", errors="replace")
@app.post("/api/upload")
async def upload_file(file: UploadFile):
"""Extract text from an uploaded PDF, DOCX, or TXT file."""
if not file.filename:
raise HTTPException(status_code=400, detail="No filename provided")
ext = os.path.splitext(file.filename)[1].lower()
if ext not in ALLOWED_EXTENSIONS:
raise HTTPException(
status_code=400,
detail=f"Unsupported file type '{ext}'. Allowed: {', '.join(sorted(ALLOWED_EXTENSIONS))}",
)
data = await file.read()
if len(data) > MAX_FILE_SIZE:
raise HTTPException(status_code=400, detail="File exceeds 10 MB limit")
try:
if ext == ".pdf":
text = _extract_text_pdf(data)
elif ext in (".docx", ".doc"):
text = _extract_text_docx(data)
else:
text = _extract_text_plain(data)
except Exception as e:
raise HTTPException(status_code=422, detail=f"Failed to extract text: {e}")
if not text.strip():
raise HTTPException(status_code=422, detail="No readable text found in file")
char_count = len(text)
word_count = len(text.split())
return {
"filename": file.filename,
"text": text,
"char_count": char_count,
"word_count": word_count,
}
# ── Streaming proxy ───────────────────────────────────────────────────────────
class StreamRequest(BaseModel):
model: str
prompt: str
document_text: Optional[str] = None
temperature: Optional[float] = Field(None, ge=0, le=2)
max_output_tokens: Optional[int] = Field(None, ge=1, le=16384)
top_p: Optional[float] = Field(None, ge=0, le=1)
@app.post("/api/stream")
async def stream_response(req: StreamRequest):
"""SSE proxy: streams a Concentrate AI response back to the browser."""
if not CONCENTRATE_API_KEY:
raise HTTPException(status_code=500, detail="CONCENTRATE_API_KEY not set")
if req.document_text:
full_input = (
f"The user has provided the following document for context:\n\n"
f"---\n{req.document_text}\n---\n\n"
f"User's question/instruction: {req.prompt}"
)
else:
full_input = req.prompt
body: dict = {
"model": req.model,
"input": full_input,
"stream": True,
}
if req.temperature is not None:
body["temperature"] = req.temperature
if req.max_output_tokens is not None:
body["max_output_tokens"] = req.max_output_tokens
if req.top_p is not None:
body["top_p"] = req.top_p
async def event_generator():
start_time = time.time()
first_token_time: float | None = None
async with httpx.AsyncClient(timeout=httpx.Timeout(connect=10, read=120, write=10, pool=10)) as client:
async with client.stream(
"POST",
f"{CONCENTRATE_BASE_URL}/responses",
headers=_headers(),
json=body,
) as resp:
if resp.status_code != 200:
error_body = await resp.aread()
yield f"event: error\ndata: {json.dumps({'error': error_body.decode()})}\n\n"
return
async for raw_line in resp.aiter_lines():
if not raw_line.strip():
continue
if raw_line.startswith("event: "):
yield raw_line + "\n"
continue
if raw_line.startswith("data: "):
data_str = raw_line[6:]
try:
event = json.loads(data_str)
except json.JSONDecodeError:
yield raw_line + "\n\n"
continue
event_type = event.get("type", "")
if event_type == "response.output_text.delta" and first_token_time is None:
first_token_time = time.time()
yield raw_line + "\n\n"
if event_type in ("response.completed", "response.failed", "response.incomplete"):
end_time = time.time()
stats = {
"type": "arena.stats",
"total_time_ms": round((end_time - start_time) * 1000),
"time_to_first_token_ms": (
round((first_token_time - start_time) * 1000)
if first_token_time
else None
),
}
if event_type == "response.completed":
usage = event.get("response", {}).get("usage", {})
stats["usage"] = usage
yield f"event: arena.stats\ndata: {json.dumps(stats)}\n\n"
else:
yield raw_line + "\n\n"
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@app.get("/api/health")
async def health():
return {"status": "ok"}
# ── Static file serving (production / HF Spaces) ─────────────────────────────
STATIC_DIR = pathlib.Path(__file__).resolve().parent / "static"
if STATIC_DIR.is_dir():
app.mount("/assets", StaticFiles(directory=STATIC_DIR / "assets"), name="assets")
@app.get("/{full_path:path}")
async def serve_spa(full_path: str):
"""Serve the React SPA for any non-API route."""
file_path = STATIC_DIR / full_path
if file_path.is_file():
return FileResponse(file_path)
return FileResponse(STATIC_DIR / "index.html")