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Running on Zero
Running on Zero
File size: 7,147 Bytes
37dfff7 08b2383 37dfff7 08b2383 37dfff7 08b2383 37dfff7 08b2383 37dfff7 a48f23b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 | import os
import sys
from pathlib import Path
import io
import json
import asyncio
import traceback
import pandas as pd
import uvicorn
from fastapi import FastAPI, WebSocket, WebSocketDisconnect, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
from fastapi.responses import StreamingResponse
# Add project root and backend directory to sys.path
CURRENT_DIR = Path(__file__).resolve().parent
ROOT_DIR = CURRENT_DIR if (CURRENT_DIR / "index.html").exists() else CURRENT_DIR.parent
BACKEND_DIR = ROOT_DIR / "backend"
for d in [str(ROOT_DIR), str(BACKEND_DIR), str(CURRENT_DIR)]:
if d not in sys.path:
sys.path.insert(0, d)
try:
from backend.cv_solver import solve_cv
except ImportError:
try:
from cv_solver import solve_cv
except ImportError:
from FD_solver import solve_cv
# ZeroGPU Support: Use Hugging Face ZeroGPU @spaces.GPU decorator if running on ZeroGPU
try:
import spaces
has_spaces = True
except Exception:
has_spaces = False
if has_spaces:
@spaces.GPU(duration=120)
def compute_solve_cv(df, config, pot_col, cur_col, queue, loop):
solve_cv(df, config, pot_col, cur_col, queue, loop)
else:
def compute_solve_cv(df, config, pot_col, cur_col, queue, loop):
solve_cv(df, config, pot_col, cur_col, queue, loop)
app = FastAPI(title="CV Curve Fitting Pro - JAX Engine")
# Enable Cross-Origin Resource Sharing (CORS) for all origins
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/health")
@app.get("/api/health")
def health_check():
import jax
devices = [str(d) for d in jax.devices()]
is_gpu = any("gpu" in d.lower() or "cuda" in d.lower() for d in devices)
return {
"status": "ok",
"engine": "JAX Hardware Accelerated (ZeroGPU / A100)" if (has_spaces or is_gpu) else "JAX Hardware Accelerated (CPU/XLA)",
"hardware": "Hugging Face ZeroGPU (NVIDIA A100/H100)" if has_spaces else ("GPU" if is_gpu else "CPU / Local"),
"cost": "100% Free",
"devices": devices,
"features": ["ZeroGPU Dynamic Allocation", "Automatic Differentiation", "JIT Parallelized Scan", "L-BFGS-B Multi-stage"]
}
@app.post("/api/solve")
@app.post("/solve")
async def api_solve_stream(request: Request):
data = await request.json()
raw_config = data.get("config", {})
file_content = data.get("file_content", "")
if not file_content:
return {"type": "error", "message": "No CSV file content received. Please select and upload a CV file."}
config = {
"scan_rate_v_s": float(raw_config.get("scan_rate", 0.010)),
"film_thickness": float(raw_config.get("film_thickness", 1e-4)),
"v_min": float(raw_config.get("v_min", -1.0)),
"v_max": float(raw_config.get("v_max", 1.0)),
"skip_factor": int(raw_config.get("skip_factor", 5)),
"num_peaks": int(raw_config.get("num_peaks", 50)),
"max_iter": int(raw_config.get("max_iter", 100)),
"tol_ftol": float(raw_config.get("tol_ftol", 1e-8)),
"tol_gtol": float(raw_config.get("tol_gtol", 1e-7)),
"num_terms": int(raw_config.get("num_terms", 50)),
"loss_weight_const": float(raw_config.get("loss_weight_const", 1.0))
}
pot_col = int(raw_config.get("pot_col", 8))
cur_col = int(raw_config.get("cur_col", 9))
df = pd.read_csv(io.StringIO(file_content), sep=None, engine='python')
queue = asyncio.Queue()
loop = asyncio.get_running_loop()
def run_solver():
try:
compute_solve_cv(df, config, pot_col, cur_col, queue, loop)
except Exception as e:
loop.call_soon_threadsafe(
queue.put_nowait, {
"type": "error",
"message": str(e),
"trace": traceback.format_exc()
}
)
asyncio.create_task(asyncio.to_thread(run_solver))
async def event_generator():
while True:
msg = await queue.get()
yield json.dumps(msg) + "\n"
if msg.get("type") in ("done", "error"):
break
return StreamingResponse(event_generator(), media_type="application/x-ndjson")
async def handle_solver_websocket(websocket: WebSocket):
await websocket.accept()
try:
data = await websocket.receive_json()
raw_config = data.get("config", {})
file_content = data.get("file_content", "")
if not file_content:
await websocket.send_json({"type": "error", "message": "No CSV file content received. Please select and upload a CV file."})
return
config = {
"scan_rate_v_s": float(raw_config.get("scan_rate", 0.010)),
"film_thickness": float(raw_config.get("film_thickness", 1e-4)),
"v_min": float(raw_config.get("v_min", -1.0)),
"v_max": float(raw_config.get("v_max", 1.0)),
"skip_factor": int(raw_config.get("skip_factor", 5)),
"num_peaks": int(raw_config.get("num_peaks", 50)),
"max_iter": int(raw_config.get("max_iter", 100)),
"tol_ftol": float(raw_config.get("tol_ftol", 1e-8)),
"tol_gtol": float(raw_config.get("tol_gtol", 1e-7)),
"num_terms": int(raw_config.get("num_terms", 50)),
"loss_weight_const": float(raw_config.get("loss_weight_const", 1.0))
}
pot_col = int(raw_config.get("pot_col", 8))
cur_col = int(raw_config.get("cur_col", 9))
df = pd.read_csv(io.StringIO(file_content), sep=None, engine='python')
queue = asyncio.Queue()
loop = asyncio.get_running_loop()
def run_solver():
try:
compute_solve_cv(df, config, pot_col, cur_col, queue, loop)
except Exception as e:
loop.call_soon_threadsafe(
queue.put_nowait, {
"type": "error",
"message": str(e),
"trace": traceback.format_exc()
}
)
asyncio.create_task(asyncio.to_thread(run_solver))
while True:
msg = await queue.get()
await websocket.send_json(msg)
if msg.get("type") in ("done", "error"):
break
except WebSocketDisconnect:
pass
except Exception as e:
try:
await websocket.send_json({"type": "error", "message": str(e)})
except Exception:
pass
@app.websocket("/ws/solve")
async def websocket_solve(websocket: WebSocket):
await handle_solver_websocket(websocket)
@app.websocket("/ws")
async def websocket_root(websocket: WebSocket):
await handle_solver_websocket(websocket)
if __name__ == "__main__":
port = int(os.environ.get("PORT", 8000))
uvicorn.run("main:app", host="0.0.0.0", port=port, reload=False) |