Updated Dockerfile for CUDA backend

Enabled NVIDIA CUDA backend build stage in the Dockerfile for enhanced performance with GPU support. Moved the environment variable defining the device type for the embedding and TTS models to be shared between CPU and GPU configurations. The default device type for CPU build is now explicitly set to "cpu", while the CUDA build retains "cuda", ensuring clarity and performance optimization across different hardware setups.

Dockerfile-cuda

@@ -14,9 +14,11 @@ RUN npm run build
 
 ######## CPU-only WebUI backend ########
 # To support both CPU and GPU backend, we need to keep the ability to build the CPU-only image.
-#FROM python:3.11-slim-bookworm as base
-FROM --platform=linux/amd64 cgr.dev/chainguard/python:latest-dev AS cpu-build-amd64
+#FROM --platform=linux/amd64 python:3.11-slim-bookworm as base
 #FROM --platform=linux/amd64 ubuntu:22.04 AS cpu-builder-amd64
+#FROM --platform=linux/amd64 cgr.dev/chainguard/python:latest-dev AS cpu-build-amd64
+# device type for whisper tts and embedding models - "cpu" (default), "cuda" (NVIDIA GPU and CUDA required), or "mps" (apple silicon) - choosing this right can lead to better performance
+#ENV RAG_EMBEDDING_MODEL_DEVICE_TYPE="cpu"
 
 #FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
 #RUN OPENWEBUI_CPU_TARGET="cpu" sh gen_linux.sh
@@ -28,7 +30,7 @@ FROM --platform=linux/amd64 cgr.dev/chainguard/python:latest-dev AS cpu-build-am
 #RUN OPENWEBUI_CPU_TARGET="cpu_avx2" sh gen_linux.sh
 
 ######## CUDA WebUI backend ########
-#FROM --platform=linux/amd64 nvidia/cuda:"$CUDA_VERSION"-devel-ubuntu22.04 AS cuda-build-amd64
+FROM --platform=linux/amd64 nvidia/cuda:"$CUDA_VERSION"-devel-ubuntu22.04 AS cuda-build-amd64
 #FROM --platform=linux/amd64 cgr.dev/chainguard/pytorch-cuda12:latest AS cuda-build-amd64 # fails with python requirements conflicts
 
 # Set environment variables for NVIDIA Container Toolkit
@@ -60,8 +62,6 @@ ENV WHISPER_MODEL="base" \
 # for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB)
 # IMPORTANT: If you change the default model (all-MiniLM-L6-v2) and vice versa, you aren't able to use RAG Chat with your previous documents loaded in the WebUI! You need to re-embed them.
 ENV RAG_EMBEDDING_MODEL="all-MiniLM-L6-v2" \
-    # device type for whisper tts and embedding models - "cpu" (default), "cuda" (NVIDIA GPU and CUDA required), or "mps" (apple silicon) - choosing this right can lead to better performance
-    RAG_EMBEDDING_MODEL_DEVICE_TYPE="cuda" \
     RAG_EMBEDDING_MODEL_DIR="/app/backend/data/cache/embedding/models" \
     SENTENCE_TRANSFORMERS_HOME=$RAG_EMBEDDING_MODEL_DIR