'commit'

dsLightRag/Doc/2、Conda维护.txt

@@ -15,7 +15,7 @@ conda info -e
 conda list
 
 # 激活虚拟环境
-conda activate rag
+conda activate py310
 
 # 对虚拟环境中安装额外的包
 conda install -n rag $package_name 

dsLightRag/Doc/8、安装VideoRAG.md

@@ -0,0 +1,44 @@
+conda activate py310
+
+# Core numerical and deep learning libraries
+pip install numpy==1.26.4
+pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2
+pip install accelerate==0.30.1
+pip install bitsandbytes==0.43.1
+
+# Video processing utilities
+pip install moviepy==1.0.3
+pip install git+https://github.com/facebookresearch/pytorchvideo.git@28fe037d212663c6a24f373b94cc5d478c8c1a1d
+
+# Multi-modal and vision libraries
+pip install timm ftfy regex einops fvcore eva-decord==0.6.1 iopath matplotlib types-regex cartopy
+
+# Audio processing and vector databases
+pip install ctranslate2==4.4.0 faster_whisper==1.0.3 neo4j hnswlib xxhash nano-vectordb
+
+# Language models and utilities
+pip install transformers==4.37.1
+pip install tiktoken openai tenacity
+
+# Ensure git-lfs is installed
+git lfs install
+
+# Set up git proxy
+git config -l
+git config  --global --unset http.proxy
+git config  --global --unset https.proxy
+# git config --global https.proxy https://127.0.0.1:1080
+
+# Download MiniCPM-V model
+git lfs clone https://huggingface.co/openbmb/MiniCPM-V-2_6-int4
+
+
+# Download Whisper model
+git lfs clone https://huggingface.co/Systran/faster-distil-whisper-large-v3
+
+# Download ImageBind checkpoint
+mkdir .checkpoints
+cd .checkpoints
+wget https://dl.fbaipublicfiles.com/imagebind/imagebind_huge.pth
+cd ../
+

dsLightRag/DownloadModel.py

@@ -0,0 +1,10 @@
+# 在这里进行搜索 https://modelscope.cn/models
+
+# 1、用命令行下载模型
+# modelscope download --model=OpenBMB/MiniCPM-V-2_6-int4 --local_dir d:/model
+# modelscope download --model=Systran/faster-distil-whisper-large-v3 --local_dir d:/model
+
+# 2、用代码下载模型
+from modelscope import snapshot_download
+#snapshot_download('OpenBMB/MiniCPM-V-2_6-int4', cache_dir='d:/model')
+snapshot_download('Systran/faster-distil-whisper-large-v3', cache_dir='d:/model')