This commit is contained in:
Javier Martinez
2024-11-26 15:53:18 +05:30
committed by GitHub
3 changed files with 119 additions and 0 deletions

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Dockerfile.local-cuda Normal file
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FROM nvidia/cuda:12.5.1-cudnn-devel-ubuntu22.04 as base
# For tzdata
ENV DEBIAN_FRONTEND="noninteractive" TZ="Etc/UTC"
RUN apt-get update && apt-get upgrade -y \
&& apt-get install -y git build-essential \
python3 python3-pip python3.11-venv gcc wget \
ocl-icd-opencl-dev opencl-headers clinfo \
libclblast-dev libopenblas-dev \
&& mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd \
&& ln -sf /usr/bin/python3.11 /usr/bin/python3 \
&& python3 --version
# Install poetry
RUN pip install pipx
RUN python3 -m pipx ensurepath
RUN pipx install poetry==1.8.3
ENV PATH="/root/.local/bin:$PATH"
ENV PATH=".venv/bin/:$PATH"
# Dependencies to build llama-cpp
RUN apt update && apt install -y \
libopenblas-dev\
ninja-build\
build-essential\
pkg-config\
wget
# https://python-poetry.org/docs/configuration/#virtualenvsin-project
ENV POETRY_VIRTUALENVS_IN_PROJECT=true
FROM base as dependencies
WORKDIR /home/worker/app
COPY pyproject.toml poetry.lock ./
ARG POETRY_EXTRAS="ui embeddings-huggingface llms-llama-cpp vector-stores-qdrant"
RUN poetry install --no-root --extras "${POETRY_EXTRAS}"
# Enable GPU support
ENV CUDA_DOCKER_ARCH=all
ENV GGML_CUDA=1
ENV TOKENIZERS_PARALLELISM=true
RUN CMAKE_ARGS="-DGGML_CUDA=on" \
poetry run pip install \
--force-reinstall \
--no-cache-dir \
--verbose \
llama-cpp-python==0.2.84 \
numpy==1.26.0
FROM base as app
ENV PYTHONUNBUFFERED=1
ENV PORT=8080
ENV APP_ENV=prod
ENV PYTHONPATH="$PYTHONPATH:/home/worker/app/private_gpt/"
EXPOSE 8080
# Prepare a non-root user
# More info about how to configure UIDs and GIDs in Docker:
# https://github.com/systemd/systemd/blob/main/docs/UIDS-GIDS.md
# Define the User ID (UID) for the non-root user
# UID 100 is chosen to avoid conflicts with existing system users
ARG UID=1000
# Define the Group ID (GID) for the non-root user
# GID 65534 is often used for the 'nogroup' or 'nobody' group
ARG GID=65534
RUN adduser --system --gid ${GID} --uid ${UID} --home /home/worker worker
WORKDIR /home/worker/app
RUN chown worker /home/worker/app
RUN mkdir local_data && chown worker local_data
RUN mkdir models && chown worker models
COPY --chown=worker --from=dependencies /home/worker/app/.venv/ .venv
COPY --chown=worker private_gpt/ private_gpt
COPY --chown=worker *.yaml ./
COPY --chown=worker scripts/ scripts
USER worker
ENTRYPOINT python -m private_gpt

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@@ -53,6 +53,26 @@ services:
profiles:
- llamacpp-cpu
# Private-GPT service for the local mode (with CUDA support)
# This service builds from a local Dockerfile and runs the application in local mode.
private-gpt-llamacpp-cuda:
image: ${PGPT_IMAGE:-zylonai/private-gpt}${PGPT_TAG:-0.6.1}-llamacpp-cuda
build:
context: .
dockerfile: Dockerfile.llamacpp-cuda
volumes:
- ./local_data/:/home/worker/app/local_data
- ./models/:/home/worker/app/models
entrypoint: sh -c ".venv/bin/python scripts/setup && .venv/bin/python -m private_gpt"
ports:
- "8001:8001"
environment:
PORT: 8001
PGPT_PROFILES: local
HF_TOKEN: ${HF_TOKEN}
profiles:
- llamacpp-cuda
#-----------------------------------
#---- Ollama services --------------
#-----------------------------------

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@@ -82,6 +82,21 @@ HF_TOKEN=<your_hf_token> docker-compose --profile llamacpp-cpu up
```
Replace `<your_hf_token>` with your actual Hugging Face token.
#### 2. LlamaCPP CUDA
**Description:**
This profile runs the Private-GPT services locally using `llama-cpp` and Hugging Face models.
**Requirements:**
A **Hugging Face Token (HF_TOKEN)** is required for accessing Hugging Face models. Obtain your token following [this guide](/installation/getting-started/troubleshooting#downloading-gated-and-private-models).
**Run:**
Start the services with your Hugging Face token using pre-built images:
```sh
HF_TOKEN=<your_hf_token> docker-compose --profile llamacpp-cuda up
```
Replace `<your_hf_token>` with your actual Hugging Face token.
## Building Locally
If you prefer to build Docker images locally, which is useful when making changes to the codebase or the Dockerfiles, follow these steps: