misc: update python requirements

Dockerfile

@@ -1,7 +1,7 @@
-FROM nvidia/cuda:11.8.0-runtime-ubuntu20.04 as base
-ARG PYTORCH_VERSION=2.4.0
+FROM nvidia/cuda:12.4.0-runtime-ubuntu20.04 as base
+ARG PYTORCH_VERSION=2.5.1
 ARG PYTHON_VERSION=3.9
-ARG CUDA_VERSION=11.8
+ARG CUDA_VERSION=12.4
 ARG MAMBA_VERSION=23.1.0-1
 ARG TARGETPLATFORM
 
@@ -36,8 +36,7 @@ RUN case ${TARGETPLATFORM} in \
 WORKDIR /root
 
 COPY ./requirements.txt /lightllm/requirements.txt
-RUN pip install -r /lightllm/requirements.txt --no-cache-dir --ignore-installed --extra-index-url https://download.pytorch.org/whl/cu118
-RUN pip install nvidia-nccl-cu12==2.20.5
+RUN pip install -r /lightllm/requirements.txt --no-cache-dir --ignore-installed --extra-index-url https://download.pytorch.org/whl/cu124
 
 COPY . /lightllm
 RUN pip install -e /lightllm --no-cache-dir

README.md

@@ -76,15 +76,15 @@ LightLLM is a Python-based LLM (Large Language Model) inference and serving fram
 
 ### Requirements
 
-The code has been tested with Pytorch>=1.3, CUDA 11.8, and Python 3.9. To install the necessary dependencies, please refer to the provided **requirements.txt** and follow the instructions as
+The code has been tested with Pytorch>=1.3, CUDA 12.4, and Python 3.9. To install the necessary dependencies, please refer to the provided **requirements.txt** and follow the instructions as
 
 ~~~shell
-# for cuda 11.8
-pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118
-# this version nccl can support torch cuda graph 
-pip install nvidia-nccl-cu12==2.20.5
+# for cuda 12.4
+pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu124
 ~~~
 
+NOTE: If you are using torch with cuda 11.x instead, run `pip install nvidia-nccl-cu12==2.20.5` to support torch cuda graph.
+
 ### Container
 
 You can use the official Docker container to run the model more easily. To do this, follow these steps:

docs/CN/source/getting_started/installation.rst

@@ -67,15 +67,14 @@ Lightllm 是一个纯python开发的推理框架，其中的算子使用triton
     $ git clone https://github.com/ModelTC/lightllm.git
     $ cd lightllm
     $
-    $ # 安装lightllm的依赖 (cuda 11.8)
-    $ pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118
-    $
-    $ # 这个版本的 nccl 可以支持 torch cuda graph
-    $ pip install nvidia-nccl-cu12==2.20.5
+    $ # 安装lightllm的依赖 (cuda 12.4)
+    $ pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu124
     $
     $ # 安装lightllm
     $ python setup.py install
 
+NOTE: 如果您出于一些原因使用了cuda 11.x的torch, 请运行 `pip install nvidia-nccl-cu12==2.20.5` 以支持 torch cuda graph.
+
 .. note::
 
     Lightllm 的代码在多种GPU上都进行了测试，包括 V100, A100, A800, 4090, 和 H800。

docs/EN/source/getting_started/installation.rst

@@ -71,13 +71,13 @@ You can also install Lightllm from source:
     $ cd lightllm
     $
     $ # Install Lightllm's dependencies
-    $ pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118
-    $
-    $ pip install nvidia-nccl-cu12==2.20.5
+    $ pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu124
     $
     $ # Install Lightllm
     $ python setup.py install
 
+NOTE: If you are using torch with cuda 11.x instead, run `pip install nvidia-nccl-cu12==2.20.5` to support torch cuda graph.
+
 .. note::
 
     The Lightllm code has been tested on various GPUs, including V100, A100, A800, 4090, and H800.

requirements.txt

@@ -57,16 +57,16 @@ sentencepiece==0.1.99
 setuptools==65.6.3
 six==1.16.0
 sniffio==1.3.0
-sympy==1.12
+sympy==1.13.1
 sortedcontainers==2.4.0
 toolz==0.12.0
-torch==2.4.0
-torchvision==0.19.0
+torch==2.5.1
+torchvision==0.20.1
 tqdm==4.65.0
 transformers==4.45.2
 tokenizers==0.20.3
 huggingface-hub==0.24.6
-triton==3.0.0
+triton==3.1.0
 urllib3==1.26.16
 uvicorn==0.19.0
 uvloop==0.17.0