Update via HuggingBot

entrypoint.sh

@@ -0,0 +1,108 @@
+#!/usr/bin/env bash
+# ─────────────────────────────────────────────────────────────────────────────
+# OpenJev zero-GPU entrypoint (Docker Space).
+#   1. Download the chosen GGUF once into /data (HF persistent storage) — the
+#      16.2 GB load survives restarts/sleeps, so wake-ups are fast.
+#   2. Fetch the OpenJev tokenizer (needs tokenizer.json + chat template).
+#   3. Start llama.cpp `llama-server` on CPU with logprobs enabled.
+#   4. Start the OFFICIAL openjev-server, its `vllm` backend pointed at the
+#      llama.cpp OpenAI endpoint (top-logprobs fallback path, no code changes).
+#      openjev-server binds $OPENJEV_PORT (7860) - the HF Spaces ingress.
+# ─────────────────────────────────────────────────────────────────────────────
+set -euo pipefail
+
+log() { printf '\n\033[1;34m[entrypoint]\033[0m %s\n' "$*"; }
+
+# config
+MODEL_REPO="${MODEL_REPO:-openjev/openjev-GGUF}"
+MODEL_FILE="${MODEL_FILE:-OpenJev-Q4_K_M.gguf}"
+TOKENIZER_REPO="${TOKENIZER_REPO:-openjev/openjev}"
+LLAMA_PORT="${LLAMA_PORT:-8080}"
+OPENJEV_PORT="${OPENJEV_PORT:-7860}"
+LLAMA_CTX="${LLAMA_CTX:-8192}"
+LLAMA_MAX_LOGPROBS="${LLAMA_MAX_LOGPROBS:-64}"
+LLAMA_PARALLEL="${LLAMA_PARALLEL:-1}"
+LLAMA_THREADS="${LLAMA_THREADS:-}"
+LLAMA_THREADS_BATCH="${LLAMA_THREADS_BATCH:-}"
+MODEL_DIR="${MODEL_DIR:-/data/models}"
+MODEL_PATH="${MODEL_DIR}/${MODEL_FILE}"
+TOKENIZER_DIR="${TOKENIZER_DIR:-/data/tokenizer}"
+
+mkdir -p "$MODEL_DIR" "$TOKENIZER_DIR"
+
+# ── 1. model (one-time download; persists in /data across restarts) ─────────
+if [ ! -s "$MODEL_PATH" ]; then
+  log "downloading $MODEL_REPO/$MODEL_FILE -> $MODEL_DIR  (one-time, ~16 GB, persistent)"
+  HF_HUB_ENABLE_HF_TRANSFER="${HF_HUB_ENABLE_HF_TRANSFER:-1}" python - <<'PY'
+import os
+from huggingface_hub import hf_hub_download
+repo, fname, d = os.environ["MODEL_REPO"], os.environ["MODEL_FILE"], os.environ["MODEL_DIR"]
+print("hf_hub_download:", repo, fname)
+p = hf_hub_download(repo_id=repo, filename=fname, local_dir=d, resume_download=True)
+print("downloaded to", p)
+PY
+else
+  log "model already on disk: $MODEL_PATH ($(du -h "$MODEL_PATH" | cut -f1))"
+fi
+
+# ── 2. tokenizer snapshot (openjev-server needs tokenizer.json + chat template)
+if [ ! -e "$TOKENIZER_DIR/tokenizer.json" ]; then
+  log "fetching tokenizer from $TOKENIZER_REPO"
+  python - <<'PY'
+import os
+from huggingface_hub import snapshot_download
+print(snapshot_download(repo_id=os.environ["TOKENIZER_REPO"], local_dir=os.environ["TOKENIZER_DIR"],
+                        allow_patterns=["tokenizer*", "vocab*", "merges*", "*.json", "config*", "special_tokens_map*", "*.jinja"]))
+PY
+else
+  log "tokenizer already present in $TOKENIZER_DIR"
+fi
+
+# ── 3. llama.cpp server (CPU) ───────────────────────────────────────────────
+LLAMA_ARGS=(
+  --host 127.0.0.1 --port "$LLAMA_PORT"
+  --model "$MODEL_PATH"
+  --ctx-size "$LLAMA_CTX"
+  --n-predict 1
+  --parallel "$LLAMA_PARALLEL"
+  --logprobs "$LLAMA_MAX_LOGPROBS"
+  --alias openjev
+  --log-file /tmp/llama-server.log
+  --no-warmup
+)
+[ -n "$LLAMA_THREADS" ]       && LLAMA_ARGS+=(--threads "$LLAMA_THREADS")
+[ -n "$LLAMA_THREADS_BATCH" ] && LLAMA_ARGS+=(--threads-batch "$LLAMA_THREADS_BATCH")
+
+log "starting llama-server (CPU) on 127.0.0.1:$LLAMA_PORT"
+llama-server "${LLAMA_ARGS[@]}" &
+LLAMA_PID=$!
+
+# wait until llama.cpp accepts requests (up to 15 min on a cold boot)
+python - <<'PY'
+import os, sys, time, urllib.request
+url = f"http://127.0.0.1:{os.environ['LLAMA_PORT']}/v1/models"
+for _ in range(450):
+    try:
+        with urllib.request.urlopen(url, timeout=10) as r:
+            if r.status == 200:
+                print("llama-server is ready"); sys.exit(0)
+    except Exception:
+        pass
+    time.sleep(2)
+print("llama-server did not become ready in time"); sys.exit(1)
+PY
+
+# ── 4. official openjev-server (vllm backend -> llama.cpp fallback path) ────
+export OPENJEV_BACKEND=vllm \
+       OPENJEV_VLLM_URL="http://127.0.0.1:${LLAMA_PORT}/v1" \
+       OPENJEV_MODEL="$TOKENIZER_DIR" \
+       OPENJEV_SERVED_MODEL_NAME="${OPENJEV_SERVED_MODEL_NAME:-openjev}" \
+       OPENJEV_HOST=0.0.0.0 \
+       OPENJEV_PORT="$OPENJEV_PORT" \
+       OPENJEV_PROFILE="${OPENJEV_PROFILE:-openjev}"
+
+cleanup() { kill "$LLAMA_PID" 2>/dev/null || true; }
+trap cleanup EXIT INT TERM
+
+log "openjev-server listening on 0.0.0.0:$OPENJEV_PORT  (UI + /v1/systemone + /docs + /healthz)"
+exec openjev serve --force