destengssv006_home/bin/create_pod_pytorch.sh

#!/bin/bash

# To be run by user llm to create the pod and container with
# PyTorch + HTTP API, to pull ColNomic embedding model if missing and
# to create the systemd service

set -e

# Environment variables
POD_NAME='pytorch_pod'
CTR_NAME='pytorch_ctr'
# NVIDIA NGC PyTorch container with CUDA 13.0 (25.08 release)
BASE_IMAGE='nvcr.io/nvidia/pytorch:25.08-py3'
CUSTOM_IMAGE='localhost/pytorch-api:25.08-cuda13.0'
HF_MODEL_ID='nomic-ai/colnomic-embed-multimodal-7b'
HF_MODEL_URL='https://huggingface.co/nomic-ai/colnomic-embed-multimodal-7b'
HOST_LOCAL_IP='127.0.0.1'
PYTORCH_HOST_PORT='8086'
PYTORCH_CONTAINER_PORT='8000'
BIND_DIR="$HOME/.local/share/$POD_NAME"
AI_MODELS_DIR="$BIND_DIR/ai-models"
PYTHON_APPS_DIR="$BIND_DIR/python-apps"
USER_SYSTEMD_DIR="$HOME/.config/systemd/user"
CONTAINERFILE="$BIND_DIR/containerfile"
PY_APP="$PYTHON_APPS_DIR/embed-multimodal-7b.py"

echo "$PY_APP"

# Prepare directories
mkdir -p "$AI_MODELS_DIR" "$PYTHON_APPS_DIR" "$USER_SYSTEMD_DIR"

# Generate containerfile
cat >"$CONTAINERFILE" <<'EOF'
# Containerfile for PyTorch + FastAPI + ColPali (ColNomic embed model support)

ARG BASE_IMAGE
FROM ${BASE_IMAGE}

# Hugging Face caches and Python apps directory (bind-mounted at runtime)
ENV HF_HOME=/models/hf \
    TRANSFORMERS_CACHE=/models/hf/transformers \
    PYTHON_APPS_DIR=/python-apps

# Ensure directories exist
RUN mkdir -p /models/hf/transformers /python-apps

# Install git (for colpali) and clean apt lists
RUN apt-get update && \
    apt-get install -y --no-install-recommends git && \
    rm -rf /var/lib/apt/lists/*

# Upgrade pip and install runtime dependencies:
# - fastapi, uvicorn for the HTTP API
# - transformers, accelerate, peft for HF + ColPali ecosystem
# - flash-attn to provide FlashAttention-2 kernels
# - colpali pinned to specific commit, installed WITHOUT deps to avoid
#   overriding the PyTorch provided by the base image.
RUN python -m pip install --upgrade pip && \
    python -m pip install --no-cache-dir \
        fastapi \
        "uvicorn[standard]" \
        transformers \
        accelerate \
        peft && \
    python -m pip install --no-cache-dir flash-attn --no-build-isolation && \
    python -m pip install --no-cache-dir --no-deps \
        "git+https://github.com/illuin-tech/colpali.git@97e389a" && \
    python -m pip cache purge

# Make /python-apps importable by default
ENV PYTHONPATH=/python-apps:${PYTHONPATH}

WORKDIR /workspace

# Default command can be overridden by podman run.
CMD ["bash"]
EOF

# Build custom container image
podman build \
  --build-arg BASE_IMAGE="$BASE_IMAGE" \
  -t "$CUSTOM_IMAGE" \
  -f "$CONTAINERFILE" \
  "$(dirname "$CONTAINERFILE")"

# Create pod if not yet existing
if ! podman pod exists "$POD_NAME"; then
  podman pod create -n "$POD_NAME" \
    -p "$HOST_LOCAL_IP:$PYTORCH_HOST_PORT:$PYTORCH_CONTAINER_PORT"
  echo "Pod '$POD_NAME' created (rc=$?)"
else
  echo "Pod '$POD_NAME' already exists."
fi

# PyTorch + HTTP API container
# Remove old container
podman rm -f "$CTR_NAME"
# New container
podman run -d --name "$CTR_NAME" --pod "$POD_NAME" \
  --device nvidia.com/gpu=all \
  -e HF_MODEL_ID="$HF_MODEL_ID" \
  -e HF_MODEL_URL="$HF_MODEL_URL" \
  -e PYTORCH_CONTAINER_PORT="$PYTORCH_CONTAINER_PORT" \
  -v "$AI_MODELS_DIR":/models \
  -v "$PYTHON_APPS_DIR":/python-apps \
  "$CUSTOM_IMAGE" \
  python /python-apps/embed-multimodal-7b.py

# Wait for API readiness (/health)
HEALTH_URL="http://$HOST_LOCAL_IP:$PYTORCH_HOST_PORT/health"
echo -n "Waiting for PyTorch API at $HEALTH_URL ..."
for attempt in $(seq 1 30); do
  if curl -fsS "$HEALTH_URL" >/dev/null 2>&1; then
    echo "ready."
    break
  fi
  sleep 2
  if [ "$attempt" -eq 30 ]; then
    echo "timeout error." >&2
    echo "Container logs:" >&2
    podman logs "$CTR_NAME"
    exit 1
  fi
done

# Smoke tests

# GPU availability
GPU_JSON="$(
  podman exec "$CTR_NAME" python -c '
import json, sys
try:
    import torch
except Exception as e:
    # Exit code 1 -> internal error (import torch failed, etc.)
    print(json.dumps({"error": f"import torch failed: {e}"}))
    sys.exit(1)

data = {
    "cuda_available": bool(torch.cuda.is_available()),
    "device_count": int(torch.cuda.device_count()),
}
print(json.dumps(data))
# Exit code 0 -> cuda_available is True
# Exit code 2 -> cuda_available is False
sys.exit(0 if data["cuda_available"] else 2)
'
)"
GPU_RC=$?
# echo "podman exec exit code: $GPU_RC"
# echo "GPU_JSON: $GPU_JSON"
if [ "$GPU_RC" -eq 0 ]; then
  echo "GPU is available in container $CTR_NAME (cuda_available == true)."
elif [ "$GPU_RC" -eq 2 ]; then
  echo "ERROR: CUDA GPU is NOT available inside the container." >&2
  echo "Details: $GPU_JSON" >&2
  echo "This may be due to missing NVIDIA CDI configuration or SELinux labeling." >&2
  exit 1
else
  echo "ERROR: podman exec GPU test failed (exit code $GPU_RC)." >&2
  echo "Details: $GPU_JSON" >&2
  echo "Container logs for debugging:" >&2
  podman logs "$CTR_NAME" || true
  exit 1
fi

# Python API /health
HEALTH_JSON="$(curl -fsS "$HEALTH_URL")"
echo "$HEALTH_JSON"
if ! printf '%s' "$HEALTH_JSON" | grep -q '"status":"ok"'; then
  echo "ERROR: /health endpoint did not report status \"ok\"." >&2
  exit 1
fi

# Python API /embed
EMBED_URL="http://$HOST_LOCAL_IP:$PYTORCH_HOST_PORT/embed-texts"
EMBED_JSON="$(curl -fsS -X POST "$EMBED_URL" \
  -H "Content-Type: application/json" \
  -d '{"texts":["hello world from colnomic"]}')"
echo "$EMBED_JSON"
if ! printf '%s' "$EMBED_JSON" | grep -q '"results"'; then
  echo "ERROR: /embed endpoint did not return embeddings as expected." >&2
  exit 1
fi

# Generate systemd service files
cd "$USER_SYSTEMD_DIR"
podman generate systemd --name --new --files "$POD_NAME"
echo "Generated systemd service files (rc=$?)"

# Stop & remove live pod and containers
podman pod stop --ignore --time 15 "$POD_NAME"
podman pod rm -f --ignore "$POD_NAME"
if podman pod exists "$POD_NAME"; then
  echo "ERROR: Pod $POD_NAME still exists." >&2
  exit 1
else
  echo "Stopped & removed live pod $POD_NAME and containers"
fi

# Enable systemd service
systemctl --user daemon-reload
systemctl --user enable --now "pod-${POD_NAME}.service"
systemctl --user is-enabled "pod-$POD_NAME.service"
systemctl --user is-active "pod-$POD_NAME.service"
echo "Enabled systemd service pod-${POD_NAME}.service (rc=$?)"
echo "To view status: systemctl --user status pod-${POD_NAME}.service"
echo "To view logs: journalctl --user -u pod-${POD_NAME}.service -f"
systemctl --user enable --now "container-${CTR_NAME}.service"
systemctl --user is-enabled "container-${CTR_NAME}.service"
systemctl --user is-active "container-${CTR_NAME}.service"
echo "Enabled systemd service container-${CTR_NAME}.service (rc=$?)"
echo "To view status: systemctl --user status container-${CTR_NAME}.service"
echo "To view logs: journalctl --user -u container-${CTR_NAME}.service -f"

echo "PyTorch API is reachable at http://$HOST_LOCAL_IP:$PYTORCH_HOST_PORT"