Update app.py

app.py

@@ -1,6 +1,25 @@
 import os
 os.environ["RWKV_JIT_ON"] = '1'
 os.environ["RWKV_CUDA_ON"] = '1' # if '1' then use CUDA kernel for seq mode (much faster)
+
+def install_cuda_toolkit():
+    CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run"
+    # CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run"
+    CUDA_TOOLKIT_FILE = "/tmp/%s" % os.path.basename(CUDA_TOOLKIT_URL)
+    subprocess.call(["wget", "-q", CUDA_TOOLKIT_URL, "-O", CUDA_TOOLKIT_FILE])
+    subprocess.call(["chmod", "+x", CUDA_TOOLKIT_FILE])
+    subprocess.call([CUDA_TOOLKIT_FILE, "--silent", "--toolkit"])
+    
+    os.environ["CUDA_HOME"] = "/usr/local/cuda"
+    os.environ["PATH"] = "%s/bin:%s" % (os.environ["CUDA_HOME"], os.environ["PATH"])
+    os.environ["LD_LIBRARY_PATH"] = "%s/lib:%s" % (
+        os.environ["CUDA_HOME"],
+        "" if "LD_LIBRARY_PATH" not in os.environ else os.environ["LD_LIBRARY_PATH"],
+    )
+    # Fix: arch_list[-1] += '+PTX'; IndexError: list index out of range
+    os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6"
+    
+install_cuda_toolkit()
 # make sure cuda dir is in the same level as modeling_rwkv.py
 from modeling_rwkv import RWKV