#!/bin/bash
# Which machine am I on, and what can I do here?
#
#   bash scripts/whichserver.sh          # verdict + capability summary
#   bash scripts/whichserver.sh --id     # just the name: aws | babel | unknown
#
# This repo runs on two machines that share one git remote and have very
# different capabilities. Getting them confused wastes hours: planning a
# Claude Code sweep on babel (no SDK, no gateway) or a quick debug loop on
# aws (every GPU request queues behind a full cluster) both fail late rather
# than immediately.
#
# Hostname is NOT a usable signal. A Claude Code session runs inside a
# sandbox pod whose hostname is `claude-sandbox-pod` on aws regardless of the
# host underneath it. The checks below use things the sandbox inherits:
# the Slurm cluster name, the storage layout, and which binaries exist.
set -uo pipefail

score_aws=0
score_babel=0
ev_aws=()
ev_babel=()

note() { if [[ $1 == aws ]]; then score_aws=$((score_aws+$2)); ev_aws+=("$3"); else score_babel=$((score_babel+$2)); ev_babel+=("$3"); fi; }

# --- Slurm identity: the single most reliable signal on either machine ----
cluster="$(sacctmgr -n -P show cluster format=Cluster 2>/dev/null | head -1)"
parts="$(sinfo -h -o '%P' 2>/dev/null | tr -d '*' | sort -u | tr '\n' ' ')"
[[ $cluster == *wearables-aws* ]] && note aws   3 "slurm cluster = $cluster"
[[ $cluster == *babel*        ]] && note babel 3 "slurm cluster = $cluster"
[[ $parts == *h100* && $parts != *preempt* ]] && note aws   2 "partitions: $parts"
[[ $parts == *preempt* || $parts == *general* ]] && note babel 2 "partitions: $parts"

# --- storage layout -------------------------------------------------------
[[ -d /lustre-storage/fsx_2/user/jiaruiliu ]] && note aws   2 "/lustre-storage/fsx_2/user/jiaruiliu exists"
[[ -d /data/group_data ]]                     && note babel 2 "/data/group_data exists (CMU group storage)"
[[ $HOME == /home/jiaruiliu ]]                && note aws   1 "HOME=$HOME"
[[ $HOME == /home/jiaruil5 ]]                 && note babel 1 "HOME=$HOME"

# --- tooling that only one side has --------------------------------------
command -v x2pagentd >/dev/null 2>&1 && note aws 2 "x2pagentd present (Meta model gateway)"

verdict=unknown
(( score_aws > score_babel && score_aws >= 3 )) && verdict=aws
(( score_babel > score_aws && score_babel >= 3 )) && verdict=babel

if [[ ${1:-} == --id ]]; then echo "$verdict"; exit 0; fi

echo "=============================================================="
echo " server: ${verdict^^}    (aws score $score_aws / babel score $score_babel)"
echo "=============================================================="
for e in "${ev_aws[@]}";   do echo "  [aws]   $e"; done
for e in "${ev_babel[@]}"; do echo "  [babel] $e"; done
echo

case $verdict in
aws)
  cat <<'TXT'
CAN DO here (aws)
  - Abundant H100s via Slurm. QOS `ar-ai-research-interns` is NOT preemptible
    (128-GPU group cap); `midpri` IS preemptible and will restart 10h jobs
    from zero. Use the former for anything long.
  - Claude Code SDK and Codex SDK, both installed, reaching the model
    providers through the x2pagentd gateway. This is what the agent sweeps run on.
  - Meta model gateway (x2pagentd). No direct OpenAI/Anthropic billing is used.
  - Apptainer containers -- on COMPUTE NODES only, not here in the sandbox pod.
  - Compute nodes reach the public internet directly (verified 2026-10-22 by
    fetching cl100k_base from Azure blob storage in a batch job).

CANNOT DO here (aws)
  - No internet from this sandbox pod or the login node. `curl` returns 000.
    Anything that needs to download: submit a tiny batch job instead.
  - The PostTrainBench agent sandbox is deliberately `--network=none`. That is
    the experimental design, not a defect -- do not "fix" it.
  - No GPU on the login/sandbox pod itself; `nvidia-smi` is absent. All GPU
    work goes through sbatch.
  - No OpenAI API: `.env` OPENAI_API_KEY is empty and api.openai.com is
    unreachable. The two LLM-graded benchmarks use a local vLLM judge instead.
TXT
  ;;
babel)
  cat <<'TXT'
CAN DO here (babel)
  - Internet access directly from the shell -- downloads, pip, HF pulls.
  - Small GPUs, good for debugging a script before it goes to aws.
  - Read and edit the repo; everything that is CPU-only or small-scale.

CANNOT DO here (babel)
  - No Meta model gateway / MetaGen keys.
  - No Claude Code SDK and no Codex SDK, so NO agent sweeps can run here.
  - No PostTrainBench data, HF cache, or results tree -- those live on aws
    under /lustre-storage/fsx_2/user/jiaruiliu/ptb-data.
  Plan any agent run, any 10-hour cell, and any full sweep for aws.
TXT
  ;;
*)
  cat <<'TXT'
Could not identify this machine from the usual signals.

Do not guess. Check by hand and then update this script:
  sacctmgr -n -P show cluster format=Cluster
  sinfo -h -o '%P' | sort -u
  ls -d /lustre-storage/fsx_2/user/jiaruiliu /data/group_data
  echo "$HOME"; command -v x2pagentd
Capability matrix: docs/setup/servers_aws_vs_babel.md
TXT
  exit 2
  ;;
esac

echo
echo "Full matrix and the rules for cross-server docs:"
echo "  docs/setup/servers_aws_vs_babel.md"