diff --git a/Dockerfile b/Dockerfile
index f7270a8..3c8b2f9 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,27 +1,20 @@
 # syntax=docker/dockerfile:1
-# Initialize device type args
-# use build args in the docker build command with --build-arg="BUILDARG=true"
+
+# Argumenty budowania
 ARG USE_CUDA=false
 ARG USE_OLLAMA=false
-# Tested with cu117 for CUDA 11 and cu121 for CUDA 12 (default)
 ARG USE_CUDA_VER=cu121
-# any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers
-# Leaderboard: https://huggingface.co/spaces/mteb/leaderboard 
-# 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 embedding model (sentence-transformers/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.
 ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
 ARG USE_RERANKING_MODEL=""
-
-# Tiktoken encoding name; models to use can be found at https://huggingface.co/models?library=tiktoken
 ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base"
-
 ARG BUILD_HASH=dev-build
-# Override at your own risk - non-root configurations are untested
 ARG UID=0
 ARG GID=0
 
-######## WebUI frontend ########
+# Etap budowania frontendu
 FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build
+ARG TARGETPLATFORM
+ARG BUILDPLATFORM
 ARG BUILD_HASH
 
 WORKDIR /app
@@ -33,10 +26,11 @@ COPY . .
 ENV APP_BUILD_HASH=${BUILD_HASH}
 RUN npm run build
 
-######## WebUI backend ########
-FROM --platform=$BUILDPLATFORM python:3.11-slim-bookworm AS base
+# Etap budowania backendu
+FROM --platform=$TARGETPLATFORM python:3.11-slim-bookworm AS base
 
-# Use args
+# Użyj argumentów
+ARG TARGETPLATFORM
 ARG USE_CUDA
 ARG USE_OLLAMA
 ARG USE_CUDA_VER
@@ -45,53 +39,35 @@ ARG USE_RERANKING_MODEL
 ARG UID
 ARG GID
 
-## Basis ##
+# Ustawienia środowiskowe
 ENV ENV=prod \
     PORT=8080 \
-    # pass build args to the build
     USE_OLLAMA_DOCKER=${USE_OLLAMA} \
     USE_CUDA_DOCKER=${USE_CUDA} \
     USE_CUDA_DOCKER_VER=${USE_CUDA_VER} \
     USE_EMBEDDING_MODEL_DOCKER=${USE_EMBEDDING_MODEL} \
-    USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL}
-
-## Basis URL Config ##
-ENV OLLAMA_BASE_URL="/ollama" \
-    OPENAI_API_BASE_URL=""
-
-## API Key and Security Config ##
-ENV OPENAI_API_KEY="" \
+    USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL} \
+    OLLAMA_BASE_URL="/ollama" \
+    OPENAI_API_BASE_URL="" \
+    OPENAI_API_KEY="" \
     WEBUI_SECRET_KEY="" \
     SCARF_NO_ANALYTICS=true \
     DO_NOT_TRACK=true \
-    ANONYMIZED_TELEMETRY=false
-
-#### Other models #########################################################
-## whisper TTS model settings ##
-ENV WHISPER_MODEL="base" \
-    WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"
-
-## RAG Embedding model settings ##
-ENV RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL_DOCKER" \
-    RAG_RERANKING_MODEL="$USE_RERANKING_MODEL_DOCKER" \
-    SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"
-
-## Tiktoken model settings ##
-ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \
-    TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken"
-
-## Hugging Face download cache ##
-ENV HF_HOME="/app/backend/data/cache/embedding/models"
-
-## Torch Extensions ##
-# ENV TORCH_EXTENSIONS_DIR="/.cache/torch_extensions"
-
-#### Other models ##########################################################
+    ANONYMIZED_TELEMETRY=false \
+    WHISPER_MODEL="base" \
+    WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models" \
+    RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL" \
+    RAG_RERANKING_MODEL="$USE_RERANKING_MODEL" \
+    SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models" \
+    TIKTOKEN_ENCODING_NAME="cl100k_base" \
+    TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken" \
+    HF_HOME="/app/backend/data/cache/embedding/models"
 
 WORKDIR /app/backend
 
 ENV HOME=/root
-# Create user and group if not root
+
+# Tworzenie użytkownika i grupy, jeśli nie root
 RUN if [ $UID -ne 0 ]; then \
     if [ $GID -ne 0 ]; then \
     addgroup --gid $GID app; \
@@ -102,65 +78,40 @@ RUN if [ $UID -ne 0 ]; then \
 RUN mkdir -p $HOME/.cache/chroma
 RUN echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id
 
-# Make sure the user has access to the app and root directory
+# Upewnij się, że użytkownik ma dostęp do katalogów
 RUN chown -R $UID:$GID /app $HOME
 
-RUN if [ "$USE_OLLAMA" = "true" ]; then \
-    apt-get update && \
-    # Install pandoc and netcat
-    apt-get install -y --no-install-recommends git build-essential pandoc netcat-openbsd curl && \
-    apt-get install -y --no-install-recommends gcc python3-dev && \
-    # for RAG OCR
-    apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \
-    # install helper tools
-    apt-get install -y --no-install-recommends curl jq && \
-    # install ollama
-    curl -fsSL https://ollama.com/install.sh | sh && \
-    # cleanup
-    rm -rf /var/lib/apt/lists/*; \
-    else \
-    apt-get update && \
-    # Install pandoc, netcat and gcc
-    apt-get install -y --no-install-recommends git build-essential pandoc gcc netcat-openbsd curl jq && \
-    apt-get install -y --no-install-recommends gcc python3-dev && \
-    # for RAG OCR
-    apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && \
-    # cleanup
-    rm -rf /var/lib/apt/lists/*; \
-    fi
+# Instalacja zależności systemowych
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    git build-essential pandoc gcc netcat-openbsd curl jq \
+    python3-dev ffmpeg libsm6 libxext6 && \
+    if [ "$USE_OLLAMA" = "true" ]; then \
+    curl -fsSL https://ollama.com/install.sh | sh; \
+    fi && \
+    rm -rf /var/lib/apt/lists/*
 
-# install python dependencies
+# Instalacja zależności Pythona
 COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt
 
 RUN pip3 install uv && \
     if [ "$USE_CUDA" = "true" ]; then \
-    # If you use CUDA the whisper and embedding model will be downloaded on first use
-    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \
-    uv pip install --system -r requirements.txt --no-cache-dir && \
-    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
-    python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
-    python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
+    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir; \
     else \
-    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
+    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir; \
+    fi && \
     uv pip install --system -r requirements.txt --no-cache-dir && \
     python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
-    python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
-    python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
-    fi; \
+    python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])" && \
+    python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])" && \
     chown -R $UID:$GID /app/backend/data/
 
-
-
-# copy embedding weight from build
-# RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2
-# COPY --from=build /app/onnx /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx
-
-# copy built frontend files
+# Kopiowanie plików frontendowych
 COPY --chown=$UID:$GID --from=build /app/build /app/build
 COPY --chown=$UID:$GID --from=build /app/CHANGELOG.md /app/CHANGELOG.md
 COPY --chown=$UID:$GID --from=build /app/package.json /app/package.json
 
-# copy backend files
+# Kopiowanie plików backendowych
 COPY --chown=$UID:$GID ./backend .
 
 EXPOSE 8080