#!/usr/bin/env bash
set -euo pipefail

# ---------------------------------------------------------------------------
# train.sh - Training orchestrator: submits K8s Jobs to the GPU pool
# ---------------------------------------------------------------------------
# Usage:
#   ./infra/scripts/train.sh <preset> [--model MODEL] [--symbol SYMBOL]
#                                      [--trials N] [--max-steps N] [--timeout N]
#
# Presets:
#   quick-test    - fast sanity check (max-steps=500, requires --model)
#   single-model  - full training run for one model (requires --model)
#   full-ensemble - trains all 10 models sequentially (dqn ppo tft mamba2 tggn tlob liquid kan xlstm diffusion)
#   hyperopt      - hyperparameter optimisation (requires --model, uses --trials)
# ---------------------------------------------------------------------------

# --- Defaults -------------------------------------------------------------
SYMBOL="ES.FUT"
TRIALS=20
MAX_STEPS=2000
TIMEOUT=3600  # default; hyperopt preset overrides to 6h below
DATA_DIR="/data/futures-baseline"
NAMESPACE="foxhunt"
IMAGE="gitlab-registry.foxhunt.svc.cluster.local:5000/root/foxhunt/foxhunt-training-runtime:latest"
MODEL=""
PRESET=""
TIMESTAMP="$(date +%s)"
S3_BUCKET="foxhunt-models"
MINIO_ENDPOINT="http://minio.foxhunt.svc.cluster.local:9000"
RUN_ID="$(date +%Y%m%d-%H%M%S)"

ALL_MODELS=(dqn ppo tft mamba2 tggn tlob liquid kan xlstm diffusion)

# --- Model-to-binary mapping ----------------------------------------------
declare -A MODEL_BINARY=(
  [dqn]=train_baseline_rl
  [ppo]=train_baseline_rl
  [tft]=train_baseline_supervised
  [mamba2]=train_baseline_supervised
  [tggn]=train_baseline_supervised
  [tlob]=train_baseline_supervised
  [liquid]=train_baseline_supervised
  [kan]=train_baseline_supervised
  [xlstm]=train_baseline_supervised
  [diffusion]=train_baseline_supervised
)

# Hyperopt uses separate binaries
declare -A HYPEROPT_BINARY=(
  [dqn]=hyperopt_baseline_rl
  [ppo]=hyperopt_baseline_rl
  [tft]=hyperopt_baseline_supervised
  [mamba2]=hyperopt_baseline_supervised
  [tggn]=hyperopt_baseline_supervised
  [tlob]=hyperopt_baseline_supervised
  [liquid]=hyperopt_baseline_supervised
  [kan]=hyperopt_baseline_supervised
  [xlstm]=hyperopt_baseline_supervised
  [diffusion]=hyperopt_baseline_supervised
)

EVAL_BINARY="evaluate_baseline"

# --- Helpers --------------------------------------------------------------
usage() {
  cat <<'USAGE'
Usage: ./infra/scripts/train.sh <preset> [OPTIONS]

Presets:
  quick-test      Fast sanity check (requires --model, max-steps=500)
  single-model    Full training run (requires --model)
  full-ensemble   Trains all 10 models sequentially (dqn ppo tft mamba2 tggn tlob liquid kan xlstm diffusion)
  hyperopt        Hyperparameter search (requires --model, uses --trials)
  evaluate        Evaluate trained models (requires --run-id from prior training run)

Options:
  --model MODEL     Model name: dqn | ppo | tft | mamba2 | tggn | tlob | liquid | kan | xlstm | diffusion
  --symbol SYMBOL   Trading symbol          (default: ES.FUT)
  --trials N        Hyperopt trial count    (default: 20)
  --max-steps N     Max steps per epoch     (default: 2000)
  --timeout N       Job timeout in seconds  (default: 3600)
  -h, --help        Show this help message
USAGE
  exit 0
}

die() { echo "ERROR: $*" >&2; exit 1; }

validate_model() {
  local m="$1"
  [[ -n "${MODEL_BINARY[$m]+x}" ]] || die "Unknown model '${m}'. Valid: ${!MODEL_BINARY[*]}"
}

# --- Parse arguments -------------------------------------------------------
[[ $# -eq 0 ]] && usage

PRESET="$1"; shift

while [[ $# -gt 0 ]]; do
  case "$1" in
    --model)    MODEL="$2";     shift 2 ;;
    --symbol)   SYMBOL="$2";    shift 2 ;;
    --trials)   TRIALS="$2";    shift 2 ;;
    --max-steps) MAX_STEPS="$2"; shift 2 ;;
    --timeout)  TIMEOUT="$2";   shift 2 ;;
    --run-id)   RUN_ID="$2";    shift 2 ;;
    -h|--help)  usage ;;
    *) die "Unknown option: $1" ;;
  esac
done

# --- Preset validation -----------------------------------------------------
case "$PRESET" in
  quick-test)
    [[ -z "$MODEL" ]] && die "quick-test preset requires --model"
    validate_model "$MODEL"
    MAX_STEPS=500
    ;;
  single-model)
    [[ -z "$MODEL" ]] && die "single-model preset requires --model"
    validate_model "$MODEL"
    ;;
  full-ensemble)
    # Trains all models; --model is ignored if provided
    MODEL=""
    ;;
  hyperopt)
    [[ -z "$MODEL" ]] && die "hyperopt preset requires --model"
    validate_model "$MODEL"
    # Hyperopt runs 20 trials × 8 epochs — needs 6h unless user specified --timeout
    if [[ "$TIMEOUT" -eq 3600 ]]; then
      TIMEOUT=21600
    fi
    ;;
  evaluate)
    [[ -z "$RUN_ID" ]] && die "evaluate preset requires --run-id (from a previous training run)"
    ;;
  *)
    die "Unknown preset '${PRESET}'. Valid: quick-test, single-model, full-ensemble, hyperopt, evaluate"
    ;;
esac


# --- Generate K8s Job manifest --------------------------------------------
generate_job_manifest() {
  local model="$1"
  local job_name="train-${model}-${TIMESTAMP}"
  local binary
  if [[ "$PRESET" == "hyperopt" ]]; then
    binary="${HYPEROPT_BINARY[$model]}"
  else
    binary="${MODEL_BINARY[$model]}"
  fi

  # Build CLI args (excluding binary name)
  local cli_args=("--model" "$model" "--symbol" "$SYMBOL" "--data-dir" "/data/futures-baseline")
  cli_args+=("--mbp10-data-dir" "/data/futures-baseline-mbp10")
  cli_args+=("--trades-data-dir" "/data/futures-baseline-trades")
  cli_args+=("--output-dir" "/output")
  if [[ "$PRESET" == "hyperopt" ]]; then
    cli_args+=("--trials" "$TRIALS")
  fi

  # Convert args array to YAML list items
  local args_yaml=""
  for arg in "${cli_args[@]}"; do
    args_yaml="${args_yaml}
            - \"${arg}\""
  done

  cat <<EOF
apiVersion: batch/v1
kind: Job
metadata:
  name: ${job_name}
  namespace: ${NAMESPACE}
  labels:
    foxhunt/job-type: training
    foxhunt/model: ${model}
    foxhunt/preset: ${PRESET}
    foxhunt/run-id: "${RUN_ID}"
spec:
  activeDeadlineSeconds: ${TIMEOUT}
  backoffLimit: 1
  ttlSecondsAfterFinished: 600
  template:
    metadata:
      annotations:
        prometheus.io/scrape: "true"
        prometheus.io/port: "9094"
        prometheus.io/path: "/metrics"
      labels:
        app.kubernetes.io/part-of: foxhunt
        app.kubernetes.io/component: training-workflow
        foxhunt/job-type: training
        foxhunt/model: ${model}
        foxhunt/preset: ${PRESET}
    spec:
      restartPolicy: Never
      nodeSelector:
        k8s.scaleway.com/pool-name: ci-training-h100
      tolerations:
        - key: nvidia.com/gpu
          operator: Exists
          effect: NoSchedule
        - key: node.cilium.io/agent-not-ready
          operator: Exists
          effect: NoSchedule
      imagePullSecrets:
        - name: gitlab-registry
      initContainers:
        - name: fetch-binary
          image: ${IMAGE}
          command: ["/bin/sh", "-c"]
          args:
            - |
              set -e
              BINARY="${binary}"
              curl -fSL -o "/binaries/\${BINARY}" \\
                --header "DEPLOY-TOKEN: \${GITLAB_DEPLOY_TOKEN}" \\
                "\${GITLAB_API}/projects/1/packages/generic/foxhunt-training/\${FOXHUNT_RELEASE}/\${BINARY}"
              chmod +x "/binaries/\${BINARY}"
              echo "Fetched \${BINARY} \${FOXHUNT_RELEASE} (\$(stat -c%s /binaries/\${BINARY}) bytes)"
          env:
            - name: GITLAB_DEPLOY_TOKEN
              valueFrom:
                secretKeyRef:
                  name: gitlab-deploy-token
                  key: token
            - name: GITLAB_API
              value: "http://gitlab-webservice-default.foxhunt.svc.cluster.local:8181/api/v4"
            - name: FOXHUNT_RELEASE
              value: "latest"
          volumeMounts:
            - name: binaries
              mountPath: /binaries
          resources:
            requests:
              cpu: 100m
              memory: 64Mi
            limits:
              cpu: 500m
              memory: 128Mi
        - name: sync-training-data
          image: ${IMAGE}
          command: ["/bin/sh", "-c"]
          args:
            - |
              set -e
              RCLONE_FLAGS="--s3-provider=Minio --s3-endpoint=http://minio.foxhunt.svc.cluster.local:9000 --s3-access-key-id=\${MINIO_ACCESS_KEY} --s3-secret-access-key=\${MINIO_SECRET_KEY} --s3-no-check-bucket"
              echo "Syncing OHLCV data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline" /data/futures-baseline \$RCLONE_FLAGS --stats-one-line -v
              echo "Syncing MBP-10 data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline-mbp10" /data/futures-baseline-mbp10 \$RCLONE_FLAGS --stats-one-line -v
              echo "Syncing trades data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline-trades" /data/futures-baseline-trades \$RCLONE_FLAGS --stats-one-line -v
              echo "Data sync complete:"
              du -sh /data/futures-baseline/ /data/futures-baseline-mbp10/ /data/futures-baseline-trades/ 2>/dev/null || true
          env:
            - name: MINIO_ACCESS_KEY
              valueFrom:
                secretKeyRef:
                  name: minio-credentials
                  key: access-key
            - name: MINIO_SECRET_KEY
              valueFrom:
                secretKeyRef:
                  name: minio-credentials
                  key: secret-key
          volumeMounts:
            - name: training-data
              mountPath: /data
          resources:
            requests:
              cpu: "1"
              memory: 512Mi
            limits:
              cpu: "2"
              memory: 1Gi
      containers:
        - name: training
          image: ${IMAGE}
          command: ["/binaries/${binary}"]
          args:${args_yaml}
          env:
            - name: RUST_LOG
              value: info
            - name: SQLX_OFFLINE
              value: "true"
            - name: OTEL_EXPORTER_OTLP_ENDPOINT
              value: "http://tempo.foxhunt.svc.cluster.local:4317"
          resources:
            requests:
              nvidia.com/gpu: "1"
              cpu: "4"
              memory: "16Gi"
            limits:
              nvidia.com/gpu: "1"
              cpu: "8"
              memory: "32Gi"
          volumeMounts:
            - name: training-data
              mountPath: /data
              readOnly: true
            - name: output
              mountPath: /output
            - name: binaries
              mountPath: /binaries
              readOnly: true
      volumes:
        - name: training-data
          persistentVolumeClaim:
            claimName: training-data-pvc
        - name: output
          emptyDir:
            sizeLimit: 2Gi
        - name: binaries
          emptyDir:
            sizeLimit: 500Mi
EOF
}

generate_eval_manifest() {
  local job_name="eval-${RUN_ID}-${TIMESTAMP}"

  cat <<EOF
apiVersion: batch/v1
kind: Job
metadata:
  name: ${job_name}
  namespace: ${NAMESPACE}
  labels:
    foxhunt/job-type: evaluate
    foxhunt/run-id: "${RUN_ID}"
spec:
  activeDeadlineSeconds: ${TIMEOUT}
  backoffLimit: 1
  ttlSecondsAfterFinished: 600
  template:
    metadata:
      labels:
        app.kubernetes.io/part-of: foxhunt
        app.kubernetes.io/component: training-workflow
        foxhunt/job-type: evaluate
      annotations:
        prometheus.io/scrape: "true"
        prometheus.io/port: "9094"
        prometheus.io/path: "/metrics"
    spec:
      restartPolicy: Never
      nodeSelector:
        k8s.scaleway.com/pool-name: ci-training-h100
      tolerations:
        - key: nvidia.com/gpu
          operator: Exists
          effect: NoSchedule
        - key: node.cilium.io/agent-not-ready
          operator: Exists
          effect: NoSchedule
      imagePullSecrets:
        - name: gitlab-registry
      initContainers:
        - name: fetch-binary
          image: ${IMAGE}
          command: ["/bin/sh", "-c"]
          args:
            - |
              set -e
              BINARY="${EVAL_BINARY}"
              curl -fSL -o "/binaries/\${BINARY}" \\
                --header "DEPLOY-TOKEN: \${GITLAB_DEPLOY_TOKEN}" \\
                "\${GITLAB_API}/projects/1/packages/generic/foxhunt-training/\${FOXHUNT_RELEASE}/\${BINARY}"
              chmod +x "/binaries/\${BINARY}"
              echo "Fetched \${BINARY} \${FOXHUNT_RELEASE} (\$(stat -c%s /binaries/\${BINARY}) bytes)"
          env:
            - name: GITLAB_DEPLOY_TOKEN
              valueFrom:
                secretKeyRef:
                  name: gitlab-deploy-token
                  key: token
            - name: GITLAB_API
              value: "http://gitlab-webservice-default.foxhunt.svc.cluster.local:8181/api/v4"
            - name: FOXHUNT_RELEASE
              value: "latest"
          volumeMounts:
            - name: binaries
              mountPath: /binaries
          resources:
            requests:
              cpu: 100m
              memory: 64Mi
            limits:
              cpu: 500m
              memory: 128Mi
        - name: sync-training-data
          image: ${IMAGE}
          command: ["/bin/sh", "-c"]
          args:
            - |
              set -e
              RCLONE_FLAGS="--s3-provider=Minio --s3-endpoint=http://minio.foxhunt.svc.cluster.local:9000 --s3-access-key-id=\${MINIO_ACCESS_KEY} --s3-secret-access-key=\${MINIO_SECRET_KEY} --s3-no-check-bucket"
              echo "Syncing OHLCV data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline" /data/futures-baseline \$RCLONE_FLAGS --stats-one-line -v
              echo "Syncing MBP-10 data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline-mbp10" /data/futures-baseline-mbp10 \$RCLONE_FLAGS --stats-one-line -v
              echo "Syncing trades data..."
              rclone sync ":s3:foxhunt-training-data/futures-baseline-trades" /data/futures-baseline-trades \$RCLONE_FLAGS --stats-one-line -v
              echo "Data sync complete:"
              du -sh /data/futures-baseline/ /data/futures-baseline-mbp10/ /data/futures-baseline-trades/ 2>/dev/null || true
          env:
            - name: MINIO_ACCESS_KEY
              valueFrom:
                secretKeyRef:
                  name: minio-credentials
                  key: access-key
            - name: MINIO_SECRET_KEY
              valueFrom:
                secretKeyRef:
                  name: minio-credentials
                  key: secret-key
          volumeMounts:
            - name: training-data
              mountPath: /data
          resources:
            requests:
              cpu: "1"
              memory: 512Mi
            limits:
              cpu: "2"
              memory: 1Gi
      containers:
        - name: evaluate
          image: ${IMAGE}
          command: ["/binaries/${EVAL_BINARY}"]
          args:
            - "--model=both"
            - "--data-dir=/data/futures-baseline"
            - "--models-dir=/output/models"
          env:
            - name: RUST_LOG
              value: info
            - name: SQLX_OFFLINE
              value: "true"
          resources:
            requests:
              nvidia.com/gpu: "1"
              cpu: "4"
              memory: "16Gi"
            limits:
              nvidia.com/gpu: "1"
              cpu: "8"
              memory: "32Gi"
          volumeMounts:
            - name: training-data
              mountPath: /data
              readOnly: true
            - name: output
              mountPath: /output
            - name: binaries
              mountPath: /binaries
              readOnly: true
      volumes:
        - name: training-data
          persistentVolumeClaim:
            claimName: training-data-pvc
        - name: output
          emptyDir:
            sizeLimit: 2Gi
        - name: binaries
          emptyDir:
            sizeLimit: 500Mi
EOF
}

# --- Submit a single job and collect its name ------------------------------
submitted_jobs=()

submit_job() {
  local model="$1"
  local job_name="train-${model}-${TIMESTAMP}"

  echo "--- Submitting job: ${job_name} (model=${model}, preset=${PRESET})"
  generate_job_manifest "$model" | kubectl apply -f -
  submitted_jobs+=("$job_name")
}

# --- Main dispatch ---------------------------------------------------------
echo "======================================================================"
echo "  Foxhunt Training Orchestrator"
echo "  Preset : ${PRESET}"
echo "  Symbol : ${SYMBOL}"
echo "  Image  : ${IMAGE}"
echo "  NS     : ${NAMESPACE}"
echo "  Run ID : ${RUN_ID}"
echo "  MinIO  : minio://${S3_BUCKET}/runs/${RUN_ID}/"
echo "======================================================================"
echo ""

case "$PRESET" in
  quick-test|single-model|hyperopt)
    submit_job "$MODEL"
    ;;
  full-ensemble)
    for m in "${ALL_MODELS[@]}"; do
      submit_job "$m"
      echo "  Waiting for ${m} to complete before next model..."
      kubectl -n "${NAMESPACE}" wait --for=condition=complete "job/train-${m}-${TIMESTAMP}" --timeout="${TIMEOUT}s" 2>/dev/null || true
    done
    ;;
  evaluate)
    echo "--- Submitting evaluation job for run ${RUN_ID}"
    generate_eval_manifest | kubectl apply -f -
    submitted_jobs+=("eval-${RUN_ID}-${TIMESTAMP}")
    ;;
esac

echo ""
echo "======================================================================"
echo "  All jobs submitted."
echo "======================================================================"
echo ""
echo "Monitor with:"
echo ""
for jn in "${submitted_jobs[@]}"; do
  echo "  kubectl -n ${NAMESPACE} get job ${jn}"
  echo "  kubectl -n ${NAMESPACE} logs job/${jn} -f"
  echo ""
done
echo "  kubectl -n ${NAMESPACE} get jobs -l foxhunt/preset=${PRESET}"
echo "  kubectl -n ${NAMESPACE} get pods -l foxhunt/job-type=training --watch"