diff --git a/.dockerignore b/.dockerignore index 6818aa5..74ca175 100644 --- a/.dockerignore +++ b/.dockerignore @@ -4,8 +4,10 @@ __pycache__/ *.pyc *.egg-info/ -# Data — mounted at runtime, not baked in -data/ +# Data — mounted at runtime, not baked in. Anchored to the top-level data/ only +# (leading slash) so small in-repo data dirs like environment/bpo/data/ — which the +# BPO server needs baked in — are NOT excluded. +/data/ apis/m3/rest/db/ apis/retrievers/chroma_data/ apis/retrievers/queries/ diff --git a/.gitignore b/.gitignore index deaf128..c09c7c5 100644 --- a/.gitignore +++ b/.gitignore @@ -43,4 +43,6 @@ parlant-data/ # But still ignore any __pycache__ inside helpers/data helpers/data/**/__pycache__/ -gpt-oss-120b* \ No newline at end of file +gpt-oss-120b* +# Code Engine deploy: generated URLs (deployment-specific, not for commit) +deploy/ce/.ce_urls.env diff --git a/agents/llm.py b/agents/llm.py index 7ed056f..de2c7d3 100644 --- a/agents/llm.py +++ b/agents/llm.py @@ -37,7 +37,7 @@ class RITSChatModel(BaseChatModel): "mistral-large-3-675b-2512-fp4": "mistralai/Mistral-Large-3-675B-Instruct-2512-NVFP4", "glm-5-1": "", "moonshotai-kimi-k2-5":"moonshotai/Kimi-K2.5", - "gpt-oss-120b": "openai/gpt-oss-120b", + "gpt-oss-120b": "openai/gpt-oss-120b-a100", # smaller models "llama-3-3-70b-instruct": "meta-llama/llama-3-3-70b-instruct", "qwen2-5-72b-instruct": "Qwen/Qwen2.5-72B-Instruct", diff --git a/benchmark/mcp_client.py b/benchmark/mcp_client.py index cd8ca19..64cd1f8 100644 --- a/benchmark/mcp_client.py +++ b/benchmark/mcp_client.py @@ -57,7 +57,9 @@ def load_mcp_config(config_path: str) -> Dict[int, MCPConnectionConfig]: container_env=v.get("container_env", None), command=cmd, args=v.get("args", None), - server_url=v.get("server_url", None), + # Expand ${ENV} in server_url so a committed CE config can reference the + # per-app URLs written by deploy/ce/3_deploy_apps.sh (see .ce_urls.env). + server_url=(os.path.expandvars(v["server_url"]) if v.get("server_url") else None), secondary_container_command=v.get("secondary_container_command", None), ) return result @@ -135,6 +137,37 @@ async def create_client_and_connect( f"Failed to connect to MCP server via stdio: {e}" ) from e + elif cfg.mode in ("http", "streamable-http"): + # Remote MCP over streamable HTTP (e.g. Code Engine). Per-domain scoping is + # preserved by the server side: the domain is carried in the URL path + # (/mcp/) and an X-MCP-Domain header, and the bridge spawns a + # subprocess pinned to that MCP_DOMAIN — so list_tools() returns only that + # domain's tools, exactly as in stdio/docker-exec mode. + if not cfg.server_url: + raise ValueError("http mode requires server_url") + if "${" in cfg.server_url: + raise RuntimeError( + f"server_url still contains an unexpanded variable: {cfg.server_url!r}. " + "Run the CE deploy (deploy/ce/3_deploy_apps.sh) and " + "`source deploy/ce/.ce_urls.env` before benchmarking against Code Engine." + ) + if "{domain}" in cfg.server_url: + url = cfg.server_url.format(domain=domain) + else: + url = f"{cfg.server_url.rstrip('/')}/{domain}" if domain else cfg.server_url + headers = {"X-MCP-Domain": domain} if domain else {} + logger.info("Connecting to MCP server via streamable HTTP: %s", url) + from mcp.client.streamable_http import streamablehttp_client + try: + async with streamablehttp_client(url, headers=headers) as (read, write, _get_session_id): + async with ClientSession(read, write) as session: + await session.initialize() + yield session + except Exception as e: + raise RuntimeError( + f"Failed to connect to MCP server at {url!r}: {e}" + ) from e + elif cfg.mode == "websocket": if not cfg.server_url: raise ValueError("websocket mode requires server_url") @@ -152,7 +185,7 @@ async def create_client_and_connect( else: raise ValueError( - f"Unknown mode: {cfg.mode!r}. Must be 'stdio' or 'websocket'" + f"Unknown mode: {cfg.mode!r}. Must be 'stdio', 'http', or 'websocket'" ) def stop_mcp_server(cfg: MCPConnectionConfig): @@ -162,8 +195,9 @@ def stop_mcp_server(cfg: MCPConnectionConfig): container. For subprocess stdio and websocket modes the transport's own context manager handles teardown, so this is a no-op. """ - if cfg.mode == "websocket": - # WebSocket connection is closed by the context manager; nothing to do. + if cfg.mode in ("websocket", "http", "streamable-http"): + # Network transports are closed by the client context manager; the CE + # bridge tears down its per-domain subprocess on session end. Nothing to do. return if cfg.mode == "stdio" and not cfg.command and cfg.container_name: diff --git a/benchmark/mcp_connection_config.ce.yaml b/benchmark/mcp_connection_config.ce.yaml new file mode 100644 index 0000000..3a89616 --- /dev/null +++ b/benchmark/mcp_connection_config.ce.yaml @@ -0,0 +1,34 @@ +# ============================================================================= +# MCP connection config — CODE ENGINE (HTTP) variant. +# +# Use this to benchmark against the deployed VAKRA apps instead of local +# containers, WITHOUT changing benchmark_runner.py: +# +# 1. Deploy: cd deploy/ce && ./3_deploy_apps.sh (writes .ce_urls.env) +# 2. Point at CE: source deploy/ce/.ce_urls.env +# 3. Run: python benchmark_runner.py --capability_id 2 --domain address \ +# --mcp-config benchmark/mcp_connection_config.ce.yaml +# +# The ${VAKRA_CAPn_URL} vars are filled in by deploy/ce/3_deploy_apps.sh and +# expanded when this file is loaded (see load_mcp_config). The literal {domain} +# is filled per-run by the client, so each connection is scoped to ONE domain — +# the CE bridge spawns a subprocess pinned to MCP_DOMAIN=, so list_tools() +# returns only that domain's tools (identical to the local docker-exec behaviour). +# ============================================================================= + +tasks: + 1: + mode: http + server_url: "${VAKRA_CAP1_URL}/mcp/{domain}" + + 2: + mode: http + server_url: "${VAKRA_CAP2_URL}/mcp/{domain}" + + 3: + mode: http + server_url: "${VAKRA_CAP3_URL}/mcp/{domain}" + + 4: + mode: http + server_url: "${VAKRA_CAP4_URL}/mcp/{domain}" diff --git a/benchmark_runner.py b/benchmark_runner.py index 2cedf11..dbc8bd7 100644 --- a/benchmark_runner.py +++ b/benchmark_runner.py @@ -379,6 +379,8 @@ async def run_capability( tlog(f"Mode: {cfg.mode}") if not cfg.command and cfg.mode == "stdio": tlog(f"Container name: {cfg.container_name}") + elif cfg.mode in ("http", "streamable-http"): + tlog(f"Server URL: {cfg.server_url}") tlog(f"Processing {len(domain_list)} domain(s): {domain_list}") # Skip domains that already have output files (resume support) diff --git a/deploy/ce/0_push_data_to_cos.py b/deploy/ce/0_push_data_to_cos.py new file mode 100755 index 0000000..ebfba56 --- /dev/null +++ b/deploy/ce/0_push_data_to_cos.py @@ -0,0 +1,244 @@ +#!/usr/bin/env python3 +""" +Step 0 — Push VAKRA benchmark data to the new COS bucket. + +Reuses the EXISTING download (`make download` -> benchmark_setup.py) to pull the +HuggingFace dataset to local `data/`, then mirrors it (plus environment/configs) +to the COS bucket with the SAME layout the containers expect: + + data/databases -> /databases/... + data/indexed_documents -> /indexed_documents/... + data/queries -> /queries/... (if present) + data/test -> /test/... (for the CE explorer) + environment/configs -> /configs/... + +Idempotent: objects whose size already matches are skipped. + +Prereqs: pip install boto3 (only needed on the machine that pushes) + COS service-credential JSON at $COS_CREDS_JSON (default ~/.cos_creds.json) + +Usage: + # from repo root + python deploy/ce/0_push_data_to_cos.py # download (if needed) + upload + python deploy/ce/0_push_data_to_cos.py --skip-download # upload only + python deploy/ce/0_push_data_to_cos.py --only databases,configs + python deploy/ce/0_push_data_to_cos.py --dry-run +""" +import argparse +import json +import os +import shutil +import subprocess +import sys +from pathlib import Path + +REPO_ROOT = Path(__file__).resolve().parents[2] +HF_REPO = "ibm-research/VAKRA" + +# Top-level dataset subtrees to stream (download -> upload -> delete), largest first. +# 'configs' comes from the repo (tiny) and is handled separately. +HF_PREFIXES = ["databases", "indexed_documents", "queries", "test"] + +# local dir -> bucket prefix +UPLOAD_MAP = { + REPO_ROOT / "data" / "databases": "databases", + REPO_ROOT / "data" / "indexed_documents": "indexed_documents", + REPO_ROOT / "data" / "queries": "queries", + REPO_ROOT / "data" / "test": "test", + REPO_ROOT / "environment" / "configs": "configs", +} + + +def _cos_creds(): + creds_path = Path(os.environ.get("COS_CREDS_JSON", str(Path.home() / ".cos_creds.json"))) + # Prefer env (exported by config.sh); fall back to the creds JSON directly. + endpoint = os.environ.get("COS_ENDPOINT") + bucket = os.environ.get("COS_BUCKET") + key = os.environ.get("COS_HMAC_ACCESS_KEY_ID") + secret = os.environ.get("COS_HMAC_SECRET_ACCESS_KEY") + region = os.environ.get("REGION", "us-east") + if not (key and secret) and creds_path.exists(): + c = json.load(open(creds_path))["credentials"] + key = key or c["cos_hmac_keys"]["access_key_id"] + secret = secret or c["cos_hmac_keys"]["secret_access_key"] + endpoint = endpoint or f"https://s3.{region}.cloud-object-storage.appdomain.cloud" + bucket = bucket or f"vakra-benchmark-data-{region}" + if not (key and secret): + sys.exit("Could not resolve COS HMAC keys. Source deploy/ce/config.sh or set " + "COS_HMAC_ACCESS_KEY_ID / COS_HMAC_SECRET_ACCESS_KEY.") + return endpoint, bucket, key, secret + + +def _client(endpoint, key, secret): + try: + import boto3 + from botocore.client import Config + except ImportError: + sys.exit("boto3 is required for the upload. Run: pip install boto3") + return boto3.client( + "s3", endpoint_url=endpoint, + aws_access_key_id=key, aws_secret_access_key=secret, + config=Config(signature_version="s3v4"), + ) + + +def _ensure_bucket(client, bucket: str, region: str) -> None: + """Create the bucket if it doesn't exist (idempotent). Safe if step 1 also creates it.""" + from botocore.exceptions import ClientError + try: + client.head_bucket(Bucket=bucket) + print(f" bucket '{bucket}' exists — reusing.") + return + except ClientError: + pass + try: + client.create_bucket( + Bucket=bucket, + CreateBucketConfiguration={"LocationConstraint": f"{region}-standard"}, + ) + print(f" created bucket '{bucket}' in {region}.") + except ClientError as e: + code = e.response.get("Error", {}).get("Code", "") + if code in ("BucketAlreadyOwnedByYou", "BucketAlreadyExists"): + print(f" bucket '{bucket}' already owned — reusing.") + else: + raise + + +def _existing_sizes(client, bucket, prefix): + sizes = {} + paginator = client.get_paginator("list_objects_v2") + for page in paginator.paginate(Bucket=bucket, Prefix=prefix + "/"): + for obj in page.get("Contents", []): + sizes[obj["Key"]] = obj["Size"] + return sizes + + +def upload_dir(client, bucket, local_dir: Path, prefix: str, dry_run: bool): + if not local_dir.exists(): + print(f" [skip] {local_dir} (not present locally)") + return 0, 0 + from boto3.s3.transfer import TransferConfig + cfg = TransferConfig(multipart_threshold=64 * 1024 * 1024, + multipart_chunksize=64 * 1024 * 1024, + max_concurrency=8, use_threads=True) + remote_sizes = {} if dry_run else _existing_sizes(client, bucket, prefix) + n_up = n_skip = 0 + total_bytes = 0 + for path in sorted(local_dir.rglob("*")): + if not path.is_file(): + continue + rel = path.relative_to(local_dir).as_posix() + key = f"{prefix}/{rel}" + size = path.stat().st_size + if remote_sizes.get(key) == size: + n_skip += 1 + continue + total_bytes += size + if dry_run: + print(f" [would upload] {key} ({size/1e6:.1f} MB)") + else: + client.upload_file(str(path), bucket, key, Config=cfg) + n_up += 1 + if n_up % 25 == 0: + print(f" [{prefix}] uploaded {n_up} files, {total_bytes/1e9:.2f} GB ...", flush=True) + print(f" [{prefix}] {'would upload' if dry_run else 'uploaded'} {n_up if not dry_run else '?'} " + f"file(s), skipped {n_skip} unchanged ({total_bytes/1e9:.2f} GB)") + return n_up, n_skip + + +def _download_prefix(prefix: str) -> None: + """Download just one dataset subtree into data/ (skips train/).""" + from huggingface_hub import snapshot_download + snapshot_download( + repo_id=HF_REPO, + repo_type="dataset", + allow_patterns=[f"{prefix}/**"], + local_dir=str(REPO_ROOT / "data"), + ) + + +def _free_gb(path: Path) -> float: + total, used, free = shutil.disk_usage(str(path)) + return free / 1e9 + + +def stream_push(client, bucket, only, dry_run): + """Low-disk path: for each subtree, download -> upload -> delete, so peak local + usage is one subtree (~25 GB for databases) instead of the full ~32 GB.""" + for prefix in HF_PREFIXES: + if only and prefix not in only: + continue + local_dir = REPO_ROOT / "data" / prefix + print(f"\n--- stream '{prefix}': download -> upload -> delete " + f"(free: {_free_gb(REPO_ROOT):.1f} GB) ---") + if not dry_run: + try: + _download_prefix(prefix) + except Exception as e: # noqa: BLE001 + print(f" [skip] {prefix}: download failed/empty: {e}") + if not local_dir.exists(): + print(f" [skip] {prefix}: not present in dataset") + continue + upload_dir(client, bucket, local_dir, prefix, dry_run) + if not dry_run: + shutil.rmtree(local_dir, ignore_errors=True) + print(f" [freed] {local_dir} (free now: {_free_gb(REPO_ROOT):.1f} GB)") + + # configs live in the repo (tiny) — upload directly, no download/delete. + if not only or "configs" in only: + cfg = REPO_ROOT / "environment" / "configs" + print(f"\n--- environment/configs -> {bucket}/configs/ ---") + upload_dir(client, bucket, cfg, "configs", dry_run) + + +def main(): + ap = argparse.ArgumentParser(description="Push VAKRA data to COS") + ap.add_argument("--stream", action="store_true", + help="Low-disk: download+upload+delete one subtree at a time " + "(peak ~25 GB). Recommended if free disk < ~40 GB.") + ap.add_argument("--skip-download", action="store_true", help="Don't download; upload existing data/ only") + ap.add_argument("--only", default="", help="Comma list of prefixes (databases,indexed_documents,queries,test,configs)") + ap.add_argument("--dry-run", action="store_true", help="List what would upload, don't upload") + args = ap.parse_args() + + only = {p.strip() for p in args.only.split(",") if p.strip()} + endpoint, bucket, key, secret = _cos_creds() + region = os.environ.get("REGION", "us-east") + client = None if args.dry_run else _client(endpoint, key, secret) + if client is not None: + _ensure_bucket(client, bucket, region) + + if args.stream: + print(f"=== STREAM push to COS bucket '{bucket}' ({endpoint}) ===") + print(f" free disk: {_free_gb(REPO_ROOT):.1f} GB (peak use ~25 GB during 'databases')") + stream_push(client, bucket, only, args.dry_run) + else: + if not args.skip_download: + free = _free_gb(REPO_ROOT) + if free < 35: + sys.exit( + f"Only {free:.1f} GB free; a full download needs ~35 GB.\n" + "Use the low-disk path instead: python deploy/ce/0_push_data_to_cos.py --stream\n" + "(or free up disk, or --skip-download if data/ is already present)." + ) + print("=== Downloading data (reuses `make download`) ===") + rc = subprocess.run([sys.executable, str(REPO_ROOT / "benchmark_setup.py"), "--download-data"], + cwd=str(REPO_ROOT)).returncode + if rc != 0: + sys.exit(f"data download failed (rc={rc})") + + print(f"\n=== Uploading to COS bucket '{bucket}' ({endpoint}) ===") + for local_dir, prefix in UPLOAD_MAP.items(): + if only and prefix not in only: + continue + print(f"\n--- {local_dir.relative_to(REPO_ROOT)} -> {bucket}/{prefix}/ ---") + upload_dir(client, bucket, local_dir, prefix, args.dry_run) + + print("\nDone." + (" (dry run — nothing uploaded)" if args.dry_run else "")) + if not args.dry_run: + print("Next: cd deploy/ce && VAKRA_CE_ADMIN=1 ./1_create_bucket_and_pds.sh") + + +if __name__ == "__main__": + main() diff --git a/deploy/ce/1_create_bucket_and_pds.sh b/deploy/ce/1_create_bucket_and_pds.sh new file mode 100755 index 0000000..e82e830 --- /dev/null +++ b/deploy/ce/1_create_bucket_and_pds.sh @@ -0,0 +1,62 @@ +#!/bin/bash +# ============================================================ +# Step 1 — Create the NEW COS bucket, an HMAC access secret, and a Code Engine +# persistent data store (pds) that mounts that bucket into the apps. +# +# Reuses your EXISTING COS instance (never creates a new instance, never +# touches other buckets). Safe to re-run: skips/refreshes what already exists. +# ============================================================ +set -euo pipefail +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +source "${SCRIPT_DIR}/config.sh" +admin_guard "${1:-}" +require_login +ce_target + +if [[ -z "${COS_INSTANCE_CRN:-}" || -z "${COS_HMAC_ACCESS_KEY_ID:-}" ]]; then + echo "Could not read COS creds (apikey/CRN/HMAC) from $COS_CREDS_JSON"; exit 1 +fi + +# --- 1a. Create the bucket (regional, in $REGION). Reuse if already owned. --- +echo "Configuring COS CLI for instance ${COS_INSTANCE_CRN} ..." +ibmcloud cos config crn --crn "$COS_INSTANCE_CRN" >/dev/null 2>&1 || true + +echo "Creating bucket '$COS_BUCKET' in region '$REGION' ..." +if ibmcloud cos bucket-create --bucket "$COS_BUCKET" --region "$REGION" \ + --ibm-service-instance-id "$COS_INSTANCE_CRN" 2>/tmp/vakra_cos_err; then + echo " bucket created." +elif ibmcloud cos bucket-head --bucket "$COS_BUCKET" --region "$REGION" >/dev/null 2>&1; then + # Create can fail with "already exists" / "name is not available" (the COS + # namespace is global). If we can head the bucket, it's ours — reuse it. + echo " bucket already exists and is accessible — reusing." +else + echo " bucket-create failed and the bucket is not accessible with these creds:" + cat /tmp/vakra_cos_err + exit 1 +fi + +# --- 1b. HMAC access secret that the pds uses to read the bucket ------------ +echo "Creating CE HMAC secret '$COS_ACCESS_SECRET_NAME' ..." +ibmcloud ce secret delete --name "$COS_ACCESS_SECRET_NAME" -f >/dev/null 2>&1 || true +ibmcloud ce secret create --name "$COS_ACCESS_SECRET_NAME" \ + --format hmac \ + --access-key-id "$COS_HMAC_ACCESS_KEY_ID" \ + --secret-access-key "$COS_HMAC_SECRET_ACCESS_KEY" + +# --- 1c. Persistent data store bound to the bucket ------------------------- +echo "Creating persistent data store '$PDS_NAME' -> bucket '$COS_BUCKET' ..." +if ibmcloud ce pds get --name "$PDS_NAME" >/dev/null 2>&1; then + echo " pds '$PDS_NAME' already exists — deleting and recreating to ensure fresh binding." + ibmcloud ce pds delete --name "$PDS_NAME" -f >/dev/null 2>&1 || true +fi +ibmcloud ce pds create --name "$PDS_NAME" \ + --cos-access-secret "$COS_ACCESS_SECRET_NAME" \ + --cos-bucket-name "$COS_BUCKET" \ + --cos-bucket-location "$REGION" + +echo "" +echo "Done." +echo " bucket : $COS_BUCKET" +echo " secret : $COS_ACCESS_SECRET_NAME (hmac)" +echo " pds : $PDS_NAME" +echo "Next: VAKRA_CE_ADMIN=1 ./2_build_push_image.sh" diff --git a/deploy/ce/2_build_push_image.sh b/deploy/ce/2_build_push_image.sh new file mode 100755 index 0000000..9187f45 --- /dev/null +++ b/deploy/ce/2_build_push_image.sh @@ -0,0 +1,65 @@ +#!/bin/bash +# ============================================================ +# Step 2 — Build the SAME image docker-compose builds (docker/Dockerfile.unified) +# with a Code Engine buildrun (cloud-side; no local docker needed) and push it to +# icr.io/routing_namespace/vakra-benchmark:latest. +# +# The 32 GB dataset is NOT part of the image — it's excluded from the build +# context (staged copy below), so the image stays lean and data lives in COS. +# ============================================================ +set -euo pipefail +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +source "${SCRIPT_DIR}/config.sh" +admin_guard "${1:-}" +require_login +ce_target + +if ! ibmcloud ce secret get -n "$REGISTRY_SECRET_NAME" >/dev/null 2>&1; then + echo "Registry secret '$REGISTRY_SECRET_NAME' not found in '$CE_PROJECT_NAME'."; exit 1 +fi + +# Stage a clean build context that EXCLUDES the giant data/ dir, .git, venvs, etc. +# This captures the current working tree (including uncommitted bridge changes) +# and guarantees we never upload 32 GB to the buildrun. +STAGE="$(mktemp -d -t vakra-build-XXXXXX)" +trap 'rm -rf "$STAGE"' EXIT +echo "Staging build context (excluding data/, .git, venvs) -> $STAGE ..." +rsync -a \ + --exclude '/data/' \ + --exclude '.git/' \ + --exclude '.venv/' --exclude '*.venv/' --exclude 'venv/' \ + --exclude '__pycache__/' \ + --exclude '*.sqlite*' \ + --exclude '/output/' \ + --exclude 'parlant-data/' \ + "$APP_ROOT/" "$STAGE/" +# NOTE: '/data/' is anchored (leading slash) so ONLY the top-level 34 GB data/ is +# skipped — small in-repo data dirs like environment/bpo/data/ (needed by the BPO +# server) are kept. A bare 'data/' would recursively drop those too. + +CTX_SIZE=$(du -sh "$STAGE" 2>/dev/null | cut -f1) +echo "Build context size: ${CTX_SIZE:-?}" + +uuid=$(uuidgen | tr '[:upper:]' '[:lower:]' | awk -F- '{print $1}') +BUILD_NAME="vakra-build-${uuid}" + +echo "Submitting buildrun '$BUILD_NAME' -> $IMAGE_REF (image is large; ~10-20 min) ..." +ibmcloud ce buildrun submit \ + --name "$BUILD_NAME" \ + --source "$STAGE" \ + --strategy dockerfile \ + --dockerfile docker/Dockerfile.unified \ + --image "$IMAGE_REF" \ + --registry-secret "$REGISTRY_SECRET_NAME" \ + --size xlarge \ + --timeout 2400 + +ibmcloud ce buildrun logs -f -n "$BUILD_NAME" + +# Surface the final status so a failed build doesn't look like success. +STATUS=$(ibmcloud ce buildrun get -n "$BUILD_NAME" -o json 2>/dev/null \ + | python3 -c "import sys,json;print(json.load(sys.stdin).get('status',{}).get('reason','') or json.load(sys.stdin).get('status',''))" 2>/dev/null || echo "") +echo "" +echo "Buildrun status: ${STATUS:-see logs above}" +echo "Image: $IMAGE_REF" +echo "Next: VAKRA_CE_ADMIN=1 ./3_deploy_apps.sh" diff --git a/deploy/ce/3_deploy_apps.sh b/deploy/ce/3_deploy_apps.sh new file mode 100755 index 0000000..6a5cd0b --- /dev/null +++ b/deploy/ce/3_deploy_apps.sh @@ -0,0 +1,99 @@ +#!/bin/bash +# ============================================================ +# Step 3 — Deploy the 4 capability apps to Code Engine (one per capability, all +# from the same image). Serves MCP over HTTP at /mcp/. +# +# DATA_SOURCE=mount (default): mounts the COS pds at the paths the servers expect. +# DATA_SOURCE=sync : app downloads data from COS to ephemeral disk on start. +# +# Writes deploy/ce/.ce_urls.env — `source` it before benchmarking against CE. +# Idempotent: re-running updates the apps in place. +# ============================================================ +set -euo pipefail +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +source "${SCRIPT_DIR}/config.sh" +admin_guard "${1:-}" +require_login +ce_target + +# A per-deploy revision stamp. The image tag is ':latest', and CE only re-pulls a +# tag when it creates a NEW revision — so we change this env every deploy to force +# a fresh revision (and thus pick up a rebuilt image). +DEPLOY_REV="$(date +%s)" + +# Build the common flags for one app. $1=app name $2=capability id +deploy_app() { + local name="$1" cap="$2" + local cpu="$CPU" mem="$MEMORY" eph="$EPHEMERAL" + if [[ "$cap" == "4" ]]; then cpu="$CAP4_CPU"; mem="$CAP4_MEMORY"; eph="$CAP4_EPHEMERAL"; fi + + local args=( + --image "$IMAGE_REF" + --registry-secret "$REGISTRY_SECRET_NAME" + --port "$BRIDGE_PORT" + --min-scale "$MIN_SCALE" --max-scale "$MAX_SCALE" + --cpu "$cpu" --memory "$mem" --ephemeral-storage "$eph" + --env "SERVE_MODE=http" + --env "CAPABILITY_ID=$cap" + --env "BRIDGE_PORT=$BRIDGE_PORT" + --env "DATA_SOURCE=$DATA_SOURCE" + --env "DEPLOY_REV=$DEPLOY_REV" + --request-timeout 600 + ) + + if [[ "$DATA_SOURCE" == "mount" ]]; then + # Mount the COS bucket subpaths at the exact paths the servers already use. + args+=( --mount-data-store "/app/db=${PDS_NAME}:databases" ) + args+=( --mount-data-store "/app/environment/configs=${PDS_NAME}:configs" ) + if [[ "$cap" == "4" ]]; then + args+=( --mount-data-store "/app/retrievers/chroma_data=${PDS_NAME}:indexed_documents" ) + args+=( --mount-data-store "/app/retrievers/queries=${PDS_NAME}:queries" ) + fi + else + # sync mode: give the container the creds + coordinates to pull from COS. + args+=( --env "COS_ENDPOINT=$COS_ENDPOINT" ) + args+=( --env "COS_BUCKET=$COS_BUCKET" ) + args+=( --env "COS_ACCESS_KEY_ID=$COS_HMAC_ACCESS_KEY_ID" ) + args+=( --env "COS_SECRET_ACCESS_KEY=$COS_HMAC_SECRET_ACCESS_KEY" ) + fi + + # Delete + recreate for a clean redeploy. `ce app update` can't re-apply an + # existing --mount-data-store ("duplicate") and has no --unmount, so recreating + # is the reliable way to refresh mounts/env and re-pull :latest. The app name + # (hence the URL) is stable across delete/recreate. + if ibmcloud ce app get -n "$name" >/dev/null 2>&1; then + echo "Deleting existing app '$name' for a clean redeploy ..." + ibmcloud ce app delete --name "$name" --force --wait --ignore-not-found + fi + echo "Creating app '$name' (capability $cap, data=$DATA_SOURCE) ..." + ibmcloud ce app create --name "$name" "${args[@]}" +} + +deploy_app "$APP_CAP1" 1 +deploy_app "$APP_CAP2" 2 +deploy_app "$APP_CAP3" 3 +deploy_app "$APP_CAP4" 4 + +# Capture the public URLs into .ce_urls.env for the benchmark client + explorer. +echo "# Generated by deploy/ce/3_deploy_apps.sh — source before benchmarking CE." > "$URLS_ENV_FILE" +i=1 +for name in "$APP_CAP1" "$APP_CAP2" "$APP_CAP3" "$APP_CAP4"; do + url=$(ibmcloud ce app get --name "$name" --output url) + echo "export VAKRA_CAP${i}_URL=\"$url\"" >> "$URLS_ENV_FILE" + i=$((i+1)) +done + +echo "" +echo "===================================================" +echo " VAKRA capability apps are live. URLs written to:" +echo " $URLS_ENV_FILE" +cat "$URLS_ENV_FILE" +echo "===================================================" +echo "" +echo "Test it:" +echo " source $URLS_ENV_FILE" +echo " python deploy/ce/5_test_ce.py" +echo " python benchmark_runner.py --capability_id 2 --domain address \\" +echo " --mcp-config benchmark/mcp_connection_config.ce.yaml" +echo "" +echo "Optional hosted explorer: VAKRA_CE_ADMIN=1 ./4_deploy_explorer.sh" diff --git a/deploy/ce/4_deploy_explorer.sh b/deploy/ce/4_deploy_explorer.sh new file mode 100755 index 0000000..9b76000 --- /dev/null +++ b/deploy/ce/4_deploy_explorer.sh @@ -0,0 +1,74 @@ +#!/bin/bash +# ============================================================ +# Step 4 (OPTIONAL) — Build + deploy the MCP Tools Explorer as a 5th Code Engine +# app, pointed at the 4 deployed capability apps. Gives you a shareable hosted +# explorer. (You can also just run it locally — see the README.) +# +# Requires step 3 to have run (reads deploy/ce/.ce_urls.env). +# ============================================================ +set -euo pipefail +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +source "${SCRIPT_DIR}/config.sh" +admin_guard "${1:-}" +require_login +ce_target + +if [[ ! -f "$URLS_ENV_FILE" ]]; then + echo "Missing $URLS_ENV_FILE — run ./3_deploy_apps.sh first."; exit 1 +fi +source "$URLS_ENV_FILE" + +# --- Build the explorer image (cloud-side buildrun from a clean staged context) --- +STAGE="$(mktemp -d -t vakra-explorer-XXXXXX)" +trap 'rm -rf "$STAGE"' EXIT +rsync -a --exclude '/data/' --exclude '.git/' --exclude '.venv/' --exclude '__pycache__/' \ + --exclude '*.sqlite*' "$APP_ROOT/" "$STAGE/" +# The repo's root .dockerignore is tuned for the MAIN image (it excludes benchmark/, +# *.json, etc.). The explorer image needs benchmark/ + tools_explorer/, so drop that +# ignore file from the (already data-free) staged context. +rm -f "$STAGE/.dockerignore" + +uuid=$(uuidgen | tr '[:upper:]' '[:lower:]' | awk -F- '{print $1}') +BUILD_NAME="vakra-explorer-build-${uuid}" +echo "Building explorer image -> $EXPLORER_IMAGE_REF ..." +ibmcloud ce buildrun submit \ + --name "$BUILD_NAME" \ + --source "$STAGE" \ + --strategy dockerfile \ + --dockerfile deploy/ce/Dockerfile.explorer \ + --image "$EXPLORER_IMAGE_REF" \ + --registry-secret "$REGISTRY_SECRET_NAME" \ + --size medium \ + --timeout 900 +ibmcloud ce buildrun logs -f -n "$BUILD_NAME" + +# --- Deploy the explorer app --- +args=( + --image "$EXPLORER_IMAGE_REF" + --registry-secret "$REGISTRY_SECRET_NAME" + --port 8080 + --min-scale "${MIN_SCALE}" --max-scale 1 + --cpu 0.5 --memory 1G + --env "MCP_CONFIG=benchmark/mcp_connection_config.ce.yaml" + --env "VAKRA_CAP1_URL=$VAKRA_CAP1_URL" + --env "VAKRA_CAP2_URL=$VAKRA_CAP2_URL" + --env "VAKRA_CAP3_URL=$VAKRA_CAP3_URL" + --env "VAKRA_CAP4_URL=$VAKRA_CAP4_URL" + # Mount the small test/ tree so the domain dropdown is populated from real data. + --mount-data-store "/app/data/test=${PDS_NAME}:test" +) + +# Delete + recreate (ce app update can't re-apply an existing --mount-data-store). +if ibmcloud ce app get -n "$APP_EXPLORER" >/dev/null 2>&1; then + echo "Deleting existing explorer app '$APP_EXPLORER' for a clean redeploy ..." + ibmcloud ce app delete --name "$APP_EXPLORER" --force --wait --ignore-not-found +fi +echo "Creating explorer app '$APP_EXPLORER' ..." +ibmcloud ce app create --name "$APP_EXPLORER" "${args[@]}" + +URL=$(ibmcloud ce app get --name "$APP_EXPLORER" --output url) +echo "" +echo "===================================================" +echo " MCP Tools Explorer (hosted) is live:" +echo " $URL" +echo "===================================================" diff --git a/deploy/ce/5_test_ce.py b/deploy/ce/5_test_ce.py new file mode 100755 index 0000000..5b2933e --- /dev/null +++ b/deploy/ce/5_test_ce.py @@ -0,0 +1,105 @@ +#!/usr/bin/env python3 +""" +Step 5 — Smoke-test the deployed VAKRA Code Engine apps. + +For each capability it: + 1. GETs /healthz on the app (reports capability_id the bridge sees). + 2. Opens an MCP session for a sample domain over HTTP (same client path the + benchmark runner uses) and calls list_tools() — proving per-domain scoping + works end-to-end from your machine against Code Engine. + +Run AFTER deploying: + source deploy/ce/.ce_urls.env + python deploy/ce/5_test_ce.py # all capabilities, default domains + python deploy/ce/5_test_ce.py --capability 2 --domain address + python deploy/ce/5_test_ce.py --verify-checksums +""" +import argparse +import asyncio +import os +import sys +from pathlib import Path + +REPO_ROOT = Path(__file__).resolve().parents[2] +sys.path.insert(0, str(REPO_ROOT)) + +from benchmark.mcp_client import load_mcp_config, create_client_and_connect # noqa: E402 + +# Representative domain(s) to probe per capability. Override with --domain. +DEFAULT_DOMAINS = {1: "address", 2: "address", 3: "bpo", 4: "address"} + +GREEN, RED, CYAN, RESET = "\033[0;32m", "\033[0;31m", "\033[0;36m", "\033[0m" +if not sys.stdout.isatty(): + GREEN = RED = CYAN = RESET = "" + + +def _health(base_url: str) -> str: + import httpx + url = base_url.rstrip("/") + "/healthz" + try: + r = httpx.get(url, timeout=30) + return f"{r.status_code} {r.text[:200]}" + except Exception as e: # noqa: BLE001 + return f"ERROR {type(e).__name__}: {e}" + + +async def _list_tools(cfg, domain: str): + async with create_client_and_connect(cfg, domain=domain) as session: + return (await session.list_tools()).tools + + +def main() -> int: + ap = argparse.ArgumentParser(description="Smoke-test VAKRA on Code Engine") + ap.add_argument("--capability", type=int, default=0, help="Only test this capability (1-4)") + ap.add_argument("--domain", default="", help="Override the probe domain") + ap.add_argument("--config", default=str(REPO_ROOT / "benchmark" / "mcp_connection_config.ce.yaml")) + ap.add_argument("--verify-checksums", action="store_true", + help="Also run verify_checksum(cap, domain, tools)") + args = ap.parse_args() + + configs = load_mcp_config(args.config) + caps = [args.capability] if args.capability else [1, 2, 3, 4] + + verify = None + if args.verify_checksums: + from environment.tool_checksums import verify_checksum as verify + + n_pass = n_fail = 0 + for cap in caps: + cfg = configs.get(cap) + print(f"\n{CYAN}=== Capability {cap} ==={RESET}") + if not cfg: + print(f"{RED} [FAIL] capability {cap} not in {args.config}{RESET}"); n_fail += 1; continue + + base = os.environ.get(f"VAKRA_CAP{cap}_URL", "") + if not base: + print(f"{RED} [FAIL] VAKRA_CAP{cap}_URL not set — did you 'source deploy/ce/.ce_urls.env'?{RESET}") + n_fail += 1 + continue + + print(f" url: {base}") + print(f" health: {_health(base)}") + + domain = args.domain or DEFAULT_DOMAINS.get(cap, "address") + try: + tools = asyncio.run(_list_tools(cfg, domain)) + names = [t.name for t in tools] + print(f"{GREEN} [PASS] list_tools(domain={domain!r}) -> {len(tools)} tools{RESET}") + print(f" e.g. {names[:6]}{' ...' if len(names) > 6 else ''}") + if verify: + try: + verify(cap, domain, tools) + print(f"{GREEN} [PASS] checksum matches for (cap {cap}, {domain}){RESET}") + except Exception as e: # noqa: BLE001 + print(f"{RED} [FAIL] checksum: {e}{RESET}"); n_fail += 1; continue + n_pass += 1 + except Exception as e: # noqa: BLE001 + print(f"{RED} [FAIL] list_tools(domain={domain!r}): {type(e).__name__}: {e}{RESET}") + n_fail += 1 + + print(f"\n{'='*40}\n {GREEN}{n_pass} passed{RESET}, {RED if n_fail else ''}{n_fail} failed{RESET}\n{'='*40}") + return 1 if n_fail else 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/deploy/ce/CHEATSHEET.md b/deploy/ce/CHEATSHEET.md new file mode 100644 index 0000000..dc18de6 --- /dev/null +++ b/deploy/ce/CHEATSHEET.md @@ -0,0 +1,101 @@ +# VAKRA on Code Engine — Cheatsheet + +One-page command reference. Full detail + gotchas: [RUNBOOK.md](RUNBOOK.md) · +consumer guide: [USING.md](USING.md). All admin scripts need `VAKRA_CE_ADMIN=1` +(add `YES=1` to skip the prompt). Run from the repo root unless noted. + +## 0. One-time setup +```bash +ibmcloud login --sso +ibmcloud plugin install code-engine -f && ibmcloud plugin install cloud-object-storage -f +ibmcloud target -r us-east -g routing && ibmcloud ce project select --name ce-project-routing + +# ONE project venv (framework python; don't mix Python tools) +python3.12 -m venv .venv && source .venv/bin/activate +pip install -e ".[agents,mcp,init]" boto3 openai # + langchain-ibm for watsonx +``` + +## Deploy from scratch +```bash +# 1. data -> COS (~35 GB; --stream = low disk, peak ~25 GB; resumable) +python deploy/ce/0_push_data_to_cos.py --stream + +cd deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./1_create_bucket_and_pds.sh # HMAC secret + data store +VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh # cloud build -> ICR (~15 min) +VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh # 4 apps; writes .ce_urls.env +VAKRA_CE_ADMIN=1 YES=1 ./4_deploy_explorer.sh # optional hosted explorer +cd .. +``` + +## Verify +```bash +source deploy/ce/.ce_urls.env +python deploy/ce/5_test_ce.py # health + list_tools per cap (expect 4/4) +python deploy/ce/5_test_ce.py --verify-checksums # also assert exact tool sets +``` + +## Benchmark against CE (same runner, `--mcp-config` differs) +```bash +source .venv/bin/activate && source deploy/ce/.ce_urls.env +CFG=benchmark/mcp_connection_config.ce.yaml +# need data/test locally? python -c "from huggingface_hub import snapshot_download; snapshot_download('ibm-research/VAKRA',repo_type='dataset',allow_patterns=['test/**'],local_dir='data')" + +# no-LLM sanity (best first check): +python benchmark_runner.py --capability_id 2 --domain california_schools --list-tools --mcp-config $CFG + +# real run — OpenAI: +export OPENAI_API_KEY=sk-... +python benchmark_runner.py --capability_id 2 --domain california_schools \ + --max-samples-per-domain 2 --provider openai --model gpt-4o --mcp-config $CFG + +# real run — gpt-oss-120b on watsonx (needs: pip install langchain-ibm): +export WATSONX_APIKEY=... WATSONX_PROJECT_ID=... # optional WATSONX_URL (default us-south) +python benchmark_runner.py --capability_id 2 --domain california_schools \ + --max-samples-per-domain 2 --provider watsonx --model openai/gpt-oss-120b --mcp-config $CFG +``` +Results → `output/capability__/.json`. Drop `--mcp-config $CFG` to run local. + +## Use the endpoints directly (any MCP client) +``` +GET /healthz +MCP /mcp/ # streamable HTTP +base = https://vakra-cap{1..4}..us-east.codeengine.appdomain.cloud (see .ce_urls.env) +``` + +## Operate +```bash +# health / logs / events +source deploy/ce/.ce_urls.env; curl -s "$VAKRA_CAP2_URL/healthz" +ibmcloud ce app logs -n vakra-cap3 +ibmcloud ce app events -n vakra-cap3 + +# ship a new version (rebuild + redeploy; redeploy delete+recreates, re-pulls :latest) +cd deploy/ce && VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh && VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh + +# data changed? re-run step 0 (only changed objects upload) +# cap4 ChromaDB write issues on the mount? redeploy with sync: +VAKRA_CE_ADMIN=1 YES=1 DATA_SOURCE=sync ./3_deploy_apps.sh + +# teardown (only vakra-*) +VAKRA_CE_ADMIN=1 YES=1 ./teardown.sh # --delete-bucket to also drop data +``` + +## Facts +- Names: apps `vakra-cap1..4` + `vakra-explorer` · bucket `vakra-benchmark-data-us-east` · + data store `vakra-store` · image `icr.io/routing_namespace/vakra-benchmark:latest`. +- Region `us-east`, RG `routing`, project `ce-project-routing`, push secret `icr-secret-1`. +- MCP pinned `mcp==1.27.0`. Data default `DATA_SOURCE=mount` (COS pds), fallback `sync`. +- Valid `--domain` = task-file names under `data/test/capability__*/input/` (server also + serves extra domains like `address` that have no benchmark tasks). + +## First-aid (full table in RUNBOOK.md) +| Symptom | Fix | +|---|---| +| disk-full during push | free ~10 GB, use `--stream` | +| HF download hangs | Ctrl-C + re-run (resumable); `HF_HUB_DOWNLOAD_TIMEOUT=30` | +| `bucket name not available` | it's yours — re-run step 1 (reuses via bucket-head) | +| `Mount … is a duplicate` | scripts delete+recreate — re-run | +| runner `No module named 'encodings'` | corrupt `.venv` — `rm -rf .venv`, recreate with ONE tool | +| RITS 120b 404 | endpoint drift — use watsonx for 120b, or fix `MODEL_NAME_MAPPING` | +| cap3 `bpo` missing parquet | rebuild image (bakes `environment/bpo/data/`) | diff --git a/deploy/ce/Dockerfile.explorer b/deploy/ce/Dockerfile.explorer new file mode 100644 index 0000000..e395b81 --- /dev/null +++ b/deploy/ce/Dockerfile.explorer @@ -0,0 +1,21 @@ +# MCP Tools Explorer — Code Engine image. +# Serves tools_explorer/app.py, pointed at the deployed VAKRA capability apps +# (via MCP_CONFIG=benchmark/mcp_connection_config.ce.yaml + VAKRA_CAPn_URL env). +FROM python:3.11-slim + +WORKDIR /app + +RUN pip install --no-cache-dir \ + fastapi "uvicorn[standard]" pydantic pyyaml "mcp==1.27.0" httpx + +# App code only (data is git-ignored / excluded by the staged build context). +COPY tools_explorer/ tools_explorer/ +COPY benchmark/ benchmark/ +COPY environment/__init__.py environment/__init__.py +COPY environment/tool_checksums.py environment/tool_checksums.py + +ENV PYTHONPATH=/app \ + MCP_CONFIG=benchmark/mcp_connection_config.ce.yaml + +EXPOSE 8080 +CMD ["uvicorn", "tools_explorer.app:app", "--host", "0.0.0.0", "--port", "8080"] diff --git a/deploy/ce/README.md b/deploy/ce/README.md new file mode 100644 index 0000000..3f12e4f --- /dev/null +++ b/deploy/ce/README.md @@ -0,0 +1,75 @@ +# VAKRA on IBM Code Engine + COS + +An **optional, admin-only** path to run the VAKRA benchmark environment on **IBM Code +Engine**, with the ~35 GB dataset living in **IBM COS**. It is **purely additive** — the +local `make` / docker-compose flow, the MCP servers, and existing CE/COS deployments are +untouched. All resources are named `vakra-*`. + +- **4 capability apps** (`vakra-cap1..4`), one image, serving **MCP over HTTP** at `/mcp/`. +- **Data in COS** (bucket `vakra-benchmark-data-us-east`), mounted into the apps. +- **Benchmark from your laptop** with the same runner — only `--mcp-config` changes. +- Optional **hosted MCP Tools Explorer** (`vakra-explorer`). + +## Which doc do I want? + +| I want to… | Read | +|---|---| +| A **visual landing page** — what this is + links to try/deploy/benchmark | **[index.html](index.html)** (open in a browser) | +| **Reproduce the whole setup from scratch** (deploy data + apps), with every gotcha + fix | **[RUNBOOK.md](RUNBOOK.md)** ← authoritative | +| **Use the already-deployed apps** — call the MCP endpoints, run the benchmark, browse tools | **[USING.md](USING.md)** | +| A **one-page command cheatsheet** (deploy · use · operate) | **[CHEATSHEET.md](CHEATSHEET.md)** | + +> RUNBOOK.md is the single source of truth for step detail. This README and the cheatsheet +> intentionally don't duplicate step specifics (so they can't drift) — they point to it. + +--- + +## How it works (the two seams) + +**Transport.** Locally, clients reach the MCP servers via `docker exec` (stdio). Code Engine +has no `docker exec`, so `docker/mcp_http_bridge.py` serves MCP over HTTP at `/mcp/`, +running only when the container starts with `SERVE_MODE=http`. For each request it spawns a +fresh, domain-pinned `mcp_dispatch.py` subprocess (same `MCP_DOMAIN` mechanism as +`docker exec -e`), so `list_tools()` is scoped to exactly one domain — a client on +`/mcp/california_schools` can't see another domain's tools, and `verify_checksum` still passes. + +**Data.** Default `DATA_SOURCE=mount` mounts the COS bucket into each app at the paths the +servers already expect (`/app/db`, `/app/environment/configs`, and for cap 4 +`/app/retrievers/chroma_data` + `/app/retrievers/queries`). Fallback `DATA_SOURCE=sync` +downloads the data to the container's ephemeral disk at startup (bigger instances; use if +the s3fs mount is too slow or cap 4's ChromaDB needs writes). + +``` +your laptop: benchmark_runner.py --mcp-config …ce.yaml (reads data/test/ locally for inputs) + │ MCP over HTTPS (/mcp/) + ▼ + 4 Code Engine apps: vakra-cap1..4 (same image, SERVE_MODE=http, CAPABILITY_ID=1..4) + mcp_http_bridge ──spawn(MCP_DOMAIN)──► mcp_dispatch.py ──► FastAPI backends :8000/:8001 + data mounted from COS pds ◄── vakra-store ◄── bucket vakra-benchmark-data-us-east +``` + +Account conventions (reused, overridable in `config.sh`): region `us-east`, resource group +`routing`, CE project `ce-project-routing`, registry `icr.io/routing_namespace` (push secret +`icr-secret-1`), and a COS service-credential JSON via `COS_CREDS_JSON` (default `~/.cos_creds.json`; see RUNBOOK.md → Prerequisites for the required fields). + +--- + +## Files + +| File | What it does | +|---|---| +| `config.sh` | shared config + `admin_guard` (sourced by the scripts; never run directly) | +| `0_push_data_to_cos.py` | reuses the HF download → mirrors `data/` + configs to COS (`--stream` for low disk) | +| `1_create_bucket_and_pds.sh` | bucket (reuse if owned) + HMAC secret + CE persistent data store | +| `2_build_push_image.sh` | cloud buildrun of `docker/Dockerfile.unified` → ICR | +| `3_deploy_apps.sh` | deploy `vakra-cap1..4` (delete+recreate); writes `.ce_urls.env` | +| `4_deploy_explorer.sh` | optional hosted explorer (`vakra-explorer`) | +| `5_test_ce.py` | health + MCP `list_tools` per capability (`--verify-checksums` optional) | +| `teardown.sh` | delete only `vakra-*` resources (`--delete-bucket` to also drop the bucket) | +| `Dockerfile.explorer` | image for the hosted explorer | +| `.ce_urls.env` | generated by step 3 — `source` it before using the runner/explorer | +| `../../docker/mcp_http_bridge.py` | stdio→HTTP MCP bridge (only when `SERVE_MODE=http`) | +| `../../docker/cos_sync.py` | COS→local sync (only when `DATA_SOURCE=sync`) | +| `../../benchmark/mcp_connection_config.ce.yaml` | HTTP config for the runner/explorer | + +Everything is gated behind `VAKRA_CE_ADMIN=1` and prompts once (add `YES=1` or `-y` to skip). diff --git a/deploy/ce/RUNBOOK.md b/deploy/ce/RUNBOOK.md new file mode 100644 index 0000000..75e79e7 --- /dev/null +++ b/deploy/ce/RUNBOOK.md @@ -0,0 +1,423 @@ +# VAKRA on Code Engine + COS — Reproduce-From-Scratch Runbook + +This is the **complete, ordered, battle-tested** procedure to put VAKRA's benchmark +environment on IBM Code Engine with its ~35 GB of data in IBM COS, and to benchmark +against it. Every step lists the command, what it does, the expected output, and the +**gotchas we actually hit** (all already fixed in the scripts — the notes explain why). + +It is an **additive, admin-only** path: it never changes the local docker-compose flow, +existing Code Engine apps, or other COS buckets. All resources are named `vakra-*`. + +> TL;DR happy path (details below): +> ``` +> ibmcloud login --sso +> python deploy/ce/0_push_data_to_cos.py --stream # data -> COS (~35 GB, hours) +> cd deploy/ce +> VAKRA_CE_ADMIN=1 YES=1 ./1_create_bucket_and_pds.sh # secret + data store +> VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh # build image (~15 min) +> VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh # 4 CE apps +> cd .. && source deploy/ce/.ce_urls.env +> python deploy/ce/5_test_ce.py # expect 4/4 pass +> python benchmark_runner.py --capability_id 2 --domain california_schools --max-samples-per-domain 2 \ +> --provider openai --model gpt-4o --mcp-config benchmark/mcp_connection_config.ce.yaml +> ``` +> All `python …` commands run in the project venv created in Prerequisites (activate it first). + +--- + +## Architecture (what gets deployed and why) + +Locally, benchmark clients reach the MCP servers via `docker exec` (stdio), with the +domain injected as `MCP_DOMAIN` into a freshly-spawned server process. **Code Engine has +no `docker exec` and no local bind mounts**, so two seams are bridged — *for CE only*: + +1. **Transport** — `docker/mcp_http_bridge.py` serves MCP over HTTP at `/mcp/`. + It runs only when the container starts with `SERVE_MODE=http`. For each request it + spawns a fresh, domain-pinned `mcp_dispatch.py` subprocess (same `MCP_DOMAIN` + mechanism as `docker exec -e`), so `list_tools()` is scoped to exactly one domain. +2. **Data** — the ~35 GB dataset lives in a COS bucket, mounted into each app at the + paths the servers already expect (`/app/db`, `/app/environment/configs`, and for + cap 4 `/app/retrievers/chroma_data` + `/app/retrievers/queries`). + +``` +your laptop: benchmark_runner.py --mcp-config …ce.yaml (reads data/test/ locally for inputs) + │ MCP over HTTPS (/mcp/) + ▼ + 4 Code Engine apps: vakra-cap1..4 (same image, SERVE_MODE=http, CAPABILITY_ID=1..4) + mcp_http_bridge ──spawn(MCP_DOMAIN)──► mcp_dispatch.py ──► FastAPI backends :8000/:8001 + data mounted read-only from COS pds ◄── vakra-store ◄── bucket vakra-benchmark-data-us-east +``` + +The 4 capabilities all run one image (`icr.io/routing_namespace/vakra-benchmark:latest`), +differentiated only by `CAPABILITY_ID` and which pds subpaths they mount. + +--- + +## Account conventions (reused from the `routing` account — nothing to fill in) + +| Setting | Value | +|---|---| +| Region / resource group / CE project | `us-east` / `routing` / `ce-project-routing` | +| Registry / push secret | `icr.io/routing_namespace` / `icr-secret-1` | +| Capability image | `icr.io/routing_namespace/vakra-benchmark:latest` | +| Explorer image | `icr.io/routing_namespace/vakra-explorer:latest` | +| COS instance | your existing instance, via a service-credential JSON (`COS_CREDS_JSON`) | +| COS bucket (NEW) | `vakra-benchmark-data-us-east` | +| CE HMAC secret / data store | `vakra-cos-access` / `vakra-store` | +| Apps | `vakra-cap1..4`, `vakra-explorer` | + +All overridable via env — see `config.sh`. + +--- + +## Prerequisites + +- `ibmcloud` CLI with the `code-engine` and `cloud-object-storage` plugins. +- `rsync`, `uuidgen`, and `python3` (3.11/3.12). +- A **COS service-credential JSON** — create it in IBM Cloud on your COS instance with + **Include HMAC Credential** enabled. Point `COS_CREDS_JSON` at the file (default + `~/.cos_creds.json`). It must contain `apikey`, the instance CRN, and HMAC keys: + ```json + { + "credentials": { + "apikey": "", + "resource_instance_id": "crn:v1:bluemix:public:cloud-object-storage:global:...::", + "cos_hmac_keys": { + "access_key_id": "", + "secret_access_key": "" + } + } + } + ``` + +```bash +ibmcloud login --sso +ibmcloud plugin install code-engine -f +ibmcloud plugin install cloud-object-storage -f +ibmcloud target -r us-east -g routing +ibmcloud ce project select --name ce-project-routing +``` + +### Create ONE project venv (used for the push, the smoke test, and the runner) + +Use a real CPython **3.11/3.12 framework build** (e.g. Homebrew `python3.12`). Don't mix +Python tools — a venv created by one Python but relinked to another corrupts it (the +`No module named 'encodings'` / `base_prefix='/install'` failure we hit; uv's +build-standalone Pythons can trigger it, so a framework `python3.12` is the safe choice). + +```bash +cd +python3.12 -m venv .venv && source .venv/bin/activate +pip install -e ".[agents,mcp,init]" boto3 openai +``` + +This installs the package's **core** deps (pandas, numpy, dotenv, pyyaml, sentence-transformers) +plus the `agents` (langchain/langgraph), `mcp`, and `init` (huggingface_hub) extras — the +complete set the push, smoke test, and runner all need. **`requirements_benchmark.txt` alone +is NOT enough** (it omits core deps like `pandas`/`dotenv`). Every `python …` command below +assumes this venv is **activated**. Add a provider client only if you use it: +`langchain-ibm` for `--provider watsonx`, `anthropic` for `--provider anthropic`. + +Sanity-check it boots (a healthy base, not `/install`): +`python -c "import sys; print(sys.base_prefix)"`. + +> **Admin gate:** every resource-creating script requires `VAKRA_CE_ADMIN=1` and prompts +> once. Add `YES=1` (or pass `-y`) to skip the prompt. + +--- + +## Step 1 — Push the data to COS + +Reuses the existing HuggingFace download (`benchmark_setup.py --download-data`) and mirrors +`data/{databases,indexed_documents,queries,test}` + `environment/configs` to the bucket +with the same layout the containers expect. The bucket is **auto-created** here (idempotent). + +```bash +cd +python3 deploy/ce/0_push_data_to_cos.py --stream +``` + +- **Use `--stream`** unless you have ≥ ~40 GB free disk. It downloads one subtree → + uploads it → deletes it → next, so peak local use is ~25 GB (the `databases` subtree) + instead of the full ~35 GB. The full path (`0_push_data_to_cos.py` with no flag) needs + ~35 GB free and refuses to run under 35 GB. +- Other flags: `--skip-download` (upload an existing `data/`), `--only databases,configs`, + `--dry-run`. +- **Resumable:** HF download resumes via `.incomplete` files; the upload skips objects whose + size already matches. Safe to re-run after any interruption. + +**Verify what landed** (any Python with boto3): +```bash +python3 - <<'PY' +import json, os, boto3 +from botocore.client import Config +c=json.load(open(os.path.expanduser(os.environ.get("COS_CREDS_JSON","~/.cos_creds.json"))))['credentials'] +r="us-east"; b=f"vakra-benchmark-data-{r}" +cli=boto3.client("s3",endpoint_url=f"https://s3.{r}.cloud-object-storage.appdomain.cloud", + aws_access_key_id=c['cos_hmac_keys']['access_key_id'], + aws_secret_access_key=c['cos_hmac_keys']['secret_access_key'],config=Config(signature_version="s3v4")) +n=tot=0; per={} +for pg in cli.get_paginator("list_objects_v2").paginate(Bucket=b): + for o in pg.get("Contents",[]): + n+=1; tot+=o["Size"]; t=o["Key"].split("/")[0]; per[t]=per.get(t,0)+o["Size"] +print(f"{b}: {n} objects, {tot/1e9:.1f} GB"); [print(f" {k:20s}{v/1e9:6.2f} GB") for k,v in sorted(per.items())] +PY +``` +Expected ≈ `databases 26.9 GB · indexed_documents 7.8 GB · test 0.05 GB · configs`. + +> **Gotchas we hit here** +> - *Only 31 GB free / disk 97 % full* → the full download won't fit. Free ~10 GB and use +> `--stream` (peak ~25 GB). The script guards this and points you to `--stream`. +> - *HF download hung for hours on one file* (dead connection, no read timeout). Fix: the +> script is resumable — Ctrl-C and re-run; set `HF_HUB_DOWNLOAD_TIMEOUT=30` so a stall +> errors-and-retries instead of hanging. `HF_HUB_ENABLE_HF_TRANSFER=1` (with +> `pip install hf_transfer`) is faster/more resilient. +> - *A 5 GB `.sqlite` seemed "stuck"* — it was mid-multipart; a multipart object only appears +> in the bucket once all parts finish. Not stuck. +> - *`boto3` not found* even after `pip install` → it went to a different interpreter. Install +> into the same Python you run the script with (`python3 -m pip install boto3`). + +--- + +## Step 2 — HMAC secret + persistent data store + +The bucket already exists (Step 1). This adds a Code Engine HMAC access secret and registers +the bucket as a **persistent data store** (`vakra-store`) that the apps mount. + +```bash +cd /deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./1_create_bucket_and_pds.sh +``` + +Expected tail: +``` + bucket already exists and is accessible — reusing. + Creating CE HMAC secret 'vakra-cos-access' ... + Creating persistent data store 'vakra-store' -> bucket 'vakra-benchmark-data-us-east' ... +Done. +``` + +> **Gotcha:** `bucket-create` returned *"The requested bucket name is not available"* (COS +> names are globally unique — it's yours from Step 1). The script now falls back to +> `ibmcloud cos bucket-head`; if the bucket is accessible, it reuses it instead of failing. + +--- + +## Step 3 — Build + push the image (cloud buildrun) + +Builds the *same* image docker-compose uses (`docker/Dockerfile.unified`) in the cloud and +pushes to ICR. The 35 GB dataset is **excluded** from the build context (staged copy). + +```bash +cd /deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh # ~10–20 min (large ML image) +``` + +Watch the streamed log for the `pip install`, the granite embedding-model pre-download, and +the final push. Ends with `Buildrun status: succeeded`. + +> **Gotchas we hit here** +> - *cap3 `bpo` failed at runtime with `candidate_data.parquet not found`.* The rsync that +> stages the build context used `--exclude 'data/'` — unanchored, so rsync dropped **every** +> `data/` dir, including the small in-repo `environment/bpo/data/` the BPO server needs. +> Fixed: the exclude is now `--exclude '/data/'` (anchored to the top-level 35 GB only), and +> the root `.dockerignore` uses `/data/` too. In-repo data dirs are now baked in. +> - *`mcp` behaved inconsistently across rebuilds.* Both images now pin `mcp==1.27.0` (the +> version proven locally), which also busts stale BuildKit pip-layer caches. + +--- + +## Step 4 — Deploy the 4 capability apps + +Creates `vakra-cap1..4` (same image, `SERVE_MODE=http`), mounts the COS data store, and writes +the public URLs to `deploy/ce/.ce_urls.env`. + +```bash +cd /deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh +``` + +- **Default `DATA_SOURCE=mount`** (COS pds mount). Fallback: `DATA_SOURCE=sync` downloads the + data to the container's ephemeral disk at startup (bigger instances; use if the s3fs mount + is too slow, or if cap 4's ChromaDB needs writes): + `VAKRA_CE_ADMIN=1 YES=1 DATA_SOURCE=sync ./3_deploy_apps.sh` +- Re-running **deletes + recreates** each app. The app name/URL is stable across recreate. + +Confirm health (Ready + `/healthz` on all 4): +```bash +cd && source deploy/ce/.ce_urls.env +ibmcloud ce project select --name ce-project-routing >/dev/null +for i in 1 2 3 4; do n="vakra-cap$i"; u=$(eval echo \$VAKRA_CAP${i}_URL) + printf "%-11s " "$n"; ibmcloud ce app get -n "$n" -o json | python3 -c "import sys,json;print('Ready='+ {c['type']:c['status'] for c in json.load(sys.stdin)['status']['conditions']}.get('Ready','?'))" + curl -s -m 15 "$u/healthz"; echo; done +``` + +> **Gotchas we hit here** +> - *`ce app update` → "Mount directory … is a duplicate".* `app update` can't re-apply an +> existing `--mount-data-store` and has no `--unmount`. Fixed: the script now **delete + +> recreate**s each app (with `app delete --wait`). +> - *CE doesn't re-pull an unchanged `:latest`.* The script stamps a per-deploy `DEPLOY_REV` +> env so every deploy is a new revision and pulls the freshly-built image. +> - *The bridge crashed with "attempted to exit a cancel scope…".* The first bridge version +> cached one backend subprocess and reused it across HTTP request tasks — an anyio +> scope violation. Fixed: spawn a fresh, scope-local subprocess per request (validated with +> a local dummy-server harness before rebuilding). + +--- + +## Step 5 — Smoke test (functional health) + +Proves each app lists tools for a sample domain over MCP (exercises the data mount + per-domain +scoping) — the real "is it working" check. + +```bash +cd && source deploy/ce/.ce_urls.env +python deploy/ce/5_test_ce.py +# add --verify-checksums to assert the exact tool set per (capability, domain) +``` +Expected: `4 passed, 0 failed` — e.g. cap1 → 9 tools, cap2 → 139 (`address`), cap4 → 144, +cap3 (`bpo`) → BPO tools. + +--- + +## Step 6 — Benchmark against Code Engine (the runner) + +The runner is **unchanged** vs. a local run — only `--mcp-config` differs. Per-domain +scoping is automatic: `create_client_and_connect(cfg, domain)` connects to +`…/mcp/`, so `list_tools()` returns just that domain's tools and +`verify_checksum` still passes. + +**Three prerequisites** (beyond a deployed, green Step 5): + +1. **The project venv from Prerequisites, activated** (`source .venv/bin/activate`). It + already has the agent stack + `openai`. Add `anthropic` if you use `--provider anthropic`. +2. **Local benchmark inputs.** The runner reads task inputs from **local** + `data/test/capability__*/input/*.json` (only *tools* come from CE). If `data/test/` + isn't present, fetch just it (~45 MB): + ```bash + cd + python - <<'PY' + from huggingface_hub import snapshot_download + snapshot_download("ibm-research/VAKRA", repo_type="dataset", + allow_patterns=["test/**"], local_dir="data") + PY + ``` + **Valid `--domain` values are the task-file names there** — e.g. cap 2 has + `california_schools, card_games, chicago_crime, financial, formula_1, movie, movielens, …`. + (Note: the server also serves domains that have no benchmark tasks — e.g. `address` works + in `5_test_ce.py`'s `list_tools` but isn't a cap 2 *benchmark* domain. Pick a wrong domain + and the runner prints the available list.) +3. **An LLM provider + key** (see the provider table below). `--provider` is one of + `openai|watsonx|rits|anthropic|litellm|ollama` (default `ollama`). + +**Run it (point the same runner at CE via the CE config):** +```bash +cd +source .venv/bin/activate # the project venv from Prerequisites +source deploy/ce/.ce_urls.env +CFG=benchmark/mcp_connection_config.ce.yaml + +# (a) zero-LLM sanity — just list a domain's tools via CE (no key needed): +python benchmark_runner.py --capability_id 2 --domain california_schools --list-tools --mcp-config $CFG + +# (b) tiny real benchmark — 2 samples, cap2/california_schools, OpenAI: +export OPENAI_API_KEY=sk-... +python benchmark_runner.py --capability_id 2 --domain california_schools \ + --max-samples-per-domain 2 --provider openai --model gpt-4o --mcp-config $CFG + +# (c) all of cap 2's domains, in parallel: +python benchmark_runner.py --capability_id 2 --parallel \ + --provider openai --model gpt-4o --mcp-config $CFG +``` + +Results are written to `output/capability__/.json`. To run locally +instead of CE, drop `--mcp-config $CFG` (defaults to the docker-exec config). + +### LLM providers (env to export before running) + +| `--provider` | `--model` | Required env | Notes | +|---|---|---|---| +| `openai` | `gpt-4o` (any) | `OPENAI_API_KEY` | client already installed | +| `watsonx` | `openai/gpt-oss-120b` (default) | `WATSONX_APIKEY`, `WATSONX_PROJECT_ID` (or `WATSONX_SPACE_ID`); optional `WATSONX_URL` (default `https://us-south.ml.cloud.ibm.com`) | **the reliable gpt-oss-120b path**; needs `pip install langchain-ibm`; model must exist in your region | +| `anthropic` | `claude-sonnet-4-5-…` | `ANTHROPIC_API_KEY` | needs `pip install anthropic` | +| `rits` | `gpt-oss-120b` (short key) | `RITS_API_KEY` | URL = `{base}/{short-key}/v1/chat/completions`; `MODEL_NAME_MAPPING` in `agents/llm.py` maps short→payload. If it 404s, the endpoint name drifted — fix the mapping (prefer watsonx for 120b). | +| `litellm` | provider-specific | `LITELLM_API_KEY`, `LITELLM_BASE_URL` | | +| `ollama` | e.g. `llama3.1:8b` | — (local) | default provider | + +**gpt-oss-120b via watsonx** (recommended): +```bash +export WATSONX_APIKEY= +export WATSONX_PROJECT_ID= # or WATSONX_SPACE_ID +# export WATSONX_URL=https://us-south.ml.cloud.ibm.com # set if your region differs +python benchmark_runner.py --capability_id 2 --domain california_schools \ + --max-samples-per-domain 2 --provider watsonx --model openai/gpt-oss-120b --mcp-config $CFG +``` + +> Notes: `--list-tools` is the best first check (no LLM, no cost — just proves CE +> connectivity + scoping). `--max-samples-per-domain N` keeps a first run cheap. If a local +> step ever needs the BPO parquet, `pip install pyarrow`. + +## Using the deployed endpoints (for consumers, not deployers) + +If you just want to *use* the already-deployed apps (call the MCP endpoints, run the +benchmark, browse tools) — not deploy them — see **[USING.md](USING.md)**. For a condensed +command reference, see **[CHEATSHEET.md](CHEATSHEET.md)**. + +--- + +## Step 7 — (optional) Hosted MCP Tools Explorer + +```bash +cd /deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./4_deploy_explorer.sh +``` +Prints the explorer URL. Or run it locally against CE: +```bash +source deploy/ce/.ce_urls.env +MCP_CONFIG=benchmark/mcp_connection_config.ce.yaml \ + python -m uvicorn tools_explorer.app:app --port 7860 +``` + +> **Gotchas we hit here** +> - *Build: `"/benchmark": not found`.* The root `.dockerignore` (tuned for the main image) +> excludes `benchmark/`, which the explorer needs. Fixed: the explorer build drops that +> `.dockerignore` from its (already data-free) staged context. +> - *Runtime: `cannot import name 'streamablehttp_client'`.* Stale cached pip layer with an old +> `mcp`. Fixed by pinning `mcp==1.27.0` (busts the cache). +> - *Deploy: duplicate mount* — same delete+recreate fix as Step 4. +> - cap3 `bpo` only works in the explorer **after** Step 3/4 include the BPO parquet. + +--- + +## Ship a new version later +```bash +cd deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh && VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh +``` +Data changed? Re-run Step 1 (only changed objects upload). + +## Teardown (only `vakra-*`; never touches other resources) +```bash +cd deploy/ce +VAKRA_CE_ADMIN=1 YES=1 ./teardown.sh # keeps the bucket + data +VAKRA_CE_ADMIN=1 YES=1 ./teardown.sh --delete-bucket # also empties + deletes the bucket +``` + +--- + +## Troubleshooting quick reference + +| Symptom | Cause / fix | +|---|---| +| `only N GB free` refusal in Step 1 | Free ~10 GB and use `--stream` (peak ~25 GB). | +| HF download stalls for a long time | Ctrl-C + re-run (resumable); set `HF_HUB_DOWNLOAD_TIMEOUT=30`. | +| `boto3` not found | `python3 -m pip install boto3` into the *same* interpreter you run scripts with. | +| `bucket name is not available` (Step 2) | It's yours; script now reuses via `bucket-head`. Re-run. | +| `candidate_data.parquet not found` (cap3) | The in-repo `environment/bpo/data/` must be baked in — rebuild with the anchored `/data/` excludes (Step 3). | +| `Mount directory … is a duplicate` | `app update` can't re-mount; scripts now delete+recreate. Re-run. | +| App serves old code after rebuild | `DEPLOY_REV` forces a new revision; or delete+recreate. | +| Bridge `cancel scope` crash | Fresh-subprocess-per-request bridge (current code). Rebuild. | +| Explorer `streamablehttp_client` ImportError | Pin `mcp==1.27.0` (busts stale pip cache). Rebuild explorer. | +| cap4 ChromaDB write errors on the mount | Redeploy with `DATA_SOURCE=sync`. | +| Runner: `ModuleNotFoundError: No module named 'encodings'` / `base_prefix='/install'` | A **corrupt `.venv`** (mixed Pythons, or a build-standalone base). `deactivate; rm -rf .venv`, then recreate with a framework Python per Prerequisites: `python3.12 -m venv .venv`. | +| Diagnosing any app | `ibmcloud ce app logs -n vakra-capN` and `ibmcloud ce app events -n vakra-capN`. | diff --git a/deploy/ce/USING.md b/deploy/ce/USING.md new file mode 100644 index 0000000..ed88f6b --- /dev/null +++ b/deploy/ce/USING.md @@ -0,0 +1,118 @@ +# Using the deployed VAKRA endpoints + +For people who want to **use** the already-running Code Engine apps — call the MCP tools, +run the benchmark, or browse tools — **without deploying anything**. (Deployers: see +[RUNBOOK.md](RUNBOOK.md).) + +## What's deployed — the contract + +Four public HTTPS apps, each an MCP server for one capability, reachable over +**streamable HTTP** at `/mcp/`: + +| Capability | App URL (base) | What it serves | +|---|---|---| +| 1 — bi_apis (slot-fill/selection) | `https://vakra-cap1..us-east.codeengine.appdomain.cloud` | RouterMCP tools | +| 2 — dashboard_apis (SQL/REST) | `https://vakra-cap2.…` | M3 REST tools | +| 3 — multihop_reasoning | `https://vakra-cap3.…` | BPO **or** M3 REST (by domain) | +| 4 — multiturn (REST + retriever) | `https://vakra-cap4.…` | M3 REST + semantic retriever | + +- **MCP endpoint:** `/mcp/` (streamable HTTP). The domain is scoped per + connection — you only see that domain's tools. +- **Health:** `GET /healthz` → `{"status":"ok","capability_id":"N"}`. +- **Auth:** none — the endpoints are **public**. Treat the URLs as semi-secret. + +### Get the URLs +Ask the deployer for `deploy/ce/.ce_urls.env` (it lists all four), or if you have Code +Engine access: +```bash +ibmcloud ce project select --name ce-project-routing +for i in 1 2 3 4; do ibmcloud ce app get -n vakra-cap$i --output url; done +``` + +### Valid domains +`` must be one this capability serves. The definitive list per capability is the +task-file names under `data/test/capability__*/input/` in the repo, or just browse them +in the hosted explorer (below). Examples for cap 2: `california_schools, card_games, +chicago_crime, financial, formula_1, movie, movielens`. + +--- + +## Option A — call the MCP tools directly (any MCP client) + +Minimal Python client (needs `pip install "mcp>=1.9"`): +```python +import asyncio +from mcp import ClientSession +from mcp.client.streamable_http import streamablehttp_client + +BASE = "https://vakra-cap2..us-east.codeengine.appdomain.cloud" +DOMAIN = "california_schools" + +async def main(): + url = f"{BASE}/mcp/{DOMAIN}" + async with streamablehttp_client(url, headers={"X-MCP-Domain": DOMAIN}) as (r, w, _): + async with ClientSession(r, w) as s: + await s.initialize() + tools = (await s.list_tools()).tools + print(f"{len(tools)} tools:", [t.name for t in tools][:5], "...") + # result = await s.call_tool(tools[0].name, { ... }) + +asyncio.run(main()) +``` +Any streamable-HTTP MCP client works the same way — point it at `/mcp/`. The +`X-MCP-Domain` header is optional (the path already carries the domain). + +Quick curl health check (no MCP client needed): +```bash +curl -s https://vakra-cap2..us-east.codeengine.appdomain.cloud/healthz +``` + +--- + +## Option B — run the VAKRA benchmark against these endpoints + +Same runner as local; only `--mcp-config` differs. + +```bash +git clone && cd vakra-july25 +python3.12 -m venv .venv && source .venv/bin/activate +pip install -e ".[agents,mcp,init]" openai # + langchain-ibm for --provider watsonx + +# point the client at the deployed apps +source deploy/ce/.ce_urls.env # from the deployer; sets VAKRA_CAP1..4_URL +# benchmark inputs are read locally — fetch just data/test if you don't have it (~45 MB): +python -c "from huggingface_hub import snapshot_download; snapshot_download('ibm-research/VAKRA', repo_type='dataset', allow_patterns=['test/**'], local_dir='data')" + +CFG=benchmark/mcp_connection_config.ce.yaml +# no-LLM sanity: +python benchmark_runner.py --capability_id 2 --domain california_schools --list-tools --mcp-config $CFG +# a real run (pick a provider — see RUNBOOK.md "LLM providers"): +export WATSONX_APIKEY=... WATSONX_PROJECT_ID=... +python benchmark_runner.py --capability_id 2 --domain california_schools \ + --max-samples-per-domain 2 --provider watsonx --model openai/gpt-oss-120b --mcp-config $CFG +``` +`.ce_urls.env` fills the `${VAKRA_CAPn_URL}` placeholders in +`benchmark/mcp_connection_config.ce.yaml`; the runner appends `/mcp/` per run, so +domain scoping is automatic. Full provider/env details: [RUNBOOK.md](RUNBOOK.md) → *LLM providers*. + +--- + +## Option C — browse tools in the hosted explorer + +If the deployer ran step 4, there's a hosted explorer: +``` +https://vakra-explorer..us-east.codeengine.appdomain.cloud +``` +Pick a capability + domain to list tools and invoke them from the browser — no setup. + +--- + +## Notes & limits + +- **Public, unauthenticated** — anyone with a URL can call the tools. Don't post the URLs + publicly; ask the deployer to add a bearer-token gate in `mcp_http_bridge.py` if needed. +- **Per-call latency:** the bridge spawns a fresh subprocess per MCP call, so heavy + `--parallel` runs carry some overhead. Fine for interactive/small runs. +- **cap 3 `bpo` domain** needs the BPO data baked into the image (deployer's build step) — + other cap 3 domains use the M3 REST path. +- If a call fails, the deployer can check `ibmcloud ce app logs -n vakra-cap`. diff --git a/deploy/ce/config.sh b/deploy/ce/config.sh new file mode 100755 index 0000000..95322cb --- /dev/null +++ b/deploy/ce/config.sh @@ -0,0 +1,111 @@ +#!/bin/bash +# ============================================================ +# Shared config for deploying VAKRA to IBM Code Engine + COS. +# +# Mirrors the team's existing Code Engine deploy conventions so +# everything lands in the SAME account/region/project/registry you already use. +# This is an ADDITIONAL, admin-only path — it never touches the local +# docker-compose flow or any existing CE app / COS bucket. +# +# Override anything via env, e.g.: COS_BUCKET=my-bucket ./1_create_bucket_and_pds.sh +# ============================================================ + +# ---- Account / region / project (reused from the routing account) ---------- +export REGION="${REGION:-us-east}" +export RESOURCE_GROUP_NAME="${RESOURCE_GROUP_NAME:-routing}" +export CE_PROJECT_NAME="${CE_PROJECT_NAME:-ce-project-routing}" + +# ---- Container registry (global icr.io — us-east has no regional endpoint) --- +export REGISTRY_HOST="${REGISTRY_HOST:-icr.io}" +export REGISTRY_NAMESPACE="${REGISTRY_NAMESPACE:-routing_namespace}" +export REGISTRY_SECRET_NAME="${REGISTRY_SECRET_NAME:-icr-secret-1}" +export IMAGE_REPO="${REGISTRY_HOST}/${REGISTRY_NAMESPACE}/vakra-benchmark" +export IMAGE_REF="${IMAGE_REF:-${IMAGE_REPO}:latest}" +export EXPLORER_IMAGE_REPO="${REGISTRY_HOST}/${REGISTRY_NAMESPACE}/vakra-explorer" +export EXPLORER_IMAGE_REF="${EXPLORER_IMAGE_REF:-${EXPLORER_IMAGE_REPO}:latest}" + +# ---- Object Storage (new bucket in your existing COS instance) -------------- +# COS_CREDS_JSON points at a COS *service-credential* JSON (create it in IBM Cloud with +# "Include HMAC Credential" enabled). It must contain credentials.{apikey, +# resource_instance_id, cos_hmac_keys.{access_key_id,secret_access_key}}. +export COS_CREDS_JSON="${COS_CREDS_JSON:-$HOME/.cos_creds.json}" +# NEW bucket, dedicated to VAKRA. Globally-unique name — change if taken. +export COS_BUCKET="${COS_BUCKET:-vakra-benchmark-data-$REGION}" +export COS_ENDPOINT="${COS_ENDPOINT:-https://s3.$REGION.cloud-object-storage.appdomain.cloud}" +# CE HMAC secret (for the persistent data store) + the data store name. +export COS_ACCESS_SECRET_NAME="${COS_ACCESS_SECRET_NAME:-vakra-cos-access}" +export PDS_NAME="${PDS_NAME:-vakra-store}" + +# ---- Code Engine apps: one per capability (all from the same image) --------- +# name -> CAPABILITY_ID +export APP_CAP1="${APP_CAP1:-vakra-cap1}" +export APP_CAP2="${APP_CAP2:-vakra-cap2}" +export APP_CAP3="${APP_CAP3:-vakra-cap3}" +export APP_CAP4="${APP_CAP4:-vakra-cap4}" +export APP_EXPLORER="${APP_EXPLORER:-vakra-explorer}" + +# Data delivery on CE: mount = COS pds mount (default, recommended) +# sync = download COS -> ephemeral disk at startup (fallback) +export DATA_SOURCE="${DATA_SOURCE:-mount}" + +# Sizing. Capabilities 1-3 are light; capability 4 loads embeddings + ChromaDB. +export CPU="${CPU:-1}" +export MEMORY="${MEMORY:-4G}" +export CAP4_CPU="${CAP4_CPU:-2}" +export CAP4_MEMORY="${CAP4_MEMORY:-8G}" +# Ephemeral storage: tiny for mount mode; must exceed the dataset for sync mode. +if [ "$DATA_SOURCE" = "sync" ]; then + export EPHEMERAL="${EPHEMERAL:-30G}" + export CAP4_EPHEMERAL="${CAP4_EPHEMERAL:-40G}" + # sync needs enough memory headroom to hold the ephemeral tier; bump if needed. + export MEMORY="${MEMORY_SYNC:-$MEMORY}" +else + export EPHEMERAL="${EPHEMERAL:-2G}" + export CAP4_EPHEMERAL="${CAP4_EPHEMERAL:-4G}" +fi + +# Keep >=1 instance warm so endpoints never cold-start. MIN_SCALE=0 -> scale-to-zero. +export MIN_SCALE="${MIN_SCALE:-1}" +export MAX_SCALE="${MAX_SCALE:-1}" +export BRIDGE_PORT="${BRIDGE_PORT:-8080}" + +# Repo root (two levels up from deploy/ce/). +export APP_ROOT="$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )/../.." &> /dev/null && pwd )" +export CE_DIR="$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )" +export URLS_ENV_FILE="${URLS_ENV_FILE:-$CE_DIR/.ce_urls.env}" + +# ---- Pull COS creds (apikey + CRN + HMAC) out of the credential JSON -------- +if [[ -f "$COS_CREDS_JSON" ]]; then + export COS_API_KEY="$(python3 -c "import json;c=json.load(open('$COS_CREDS_JSON'))['credentials'];print(c['apikey'])" 2>/dev/null)" + export COS_INSTANCE_CRN="$(python3 -c "import json;c=json.load(open('$COS_CREDS_JSON'))['credentials'];print(c['resource_instance_id'])" 2>/dev/null)" + export COS_HMAC_ACCESS_KEY_ID="$(python3 -c "import json;c=json.load(open('$COS_CREDS_JSON'))['credentials'];print(c['cos_hmac_keys']['access_key_id'])" 2>/dev/null)" + export COS_HMAC_SECRET_ACCESS_KEY="$(python3 -c "import json;c=json.load(open('$COS_CREDS_JSON'))['credentials'];print(c['cos_hmac_keys']['secret_access_key'])" 2>/dev/null)" +fi + +# ---- Helpers --------------------------------------------------------------- +function require_login() { + if ! ibmcloud target -o json 2>/dev/null | python3 -c "import sys,json;json.load(sys.stdin)" >/dev/null 2>&1; then + echo "Not logged in. Run: ibmcloud login --sso (then re-run)"; exit 1 + fi +} + +function ce_target() { + ibmcloud target -r "$REGION" -g "$RESOURCE_GROUP_NAME" >/dev/null + ibmcloud ce project select --name "$CE_PROJECT_NAME" >/dev/null +} + +# Admin gate: this path can create cloud resources. Require an explicit opt-in. +function admin_guard() { + if [[ "${VAKRA_CE_ADMIN:-}" != "1" ]]; then + echo "Refusing to run: this is the admin-only Code Engine path." + echo "Set VAKRA_CE_ADMIN=1 to proceed, e.g.: VAKRA_CE_ADMIN=1 $0" + exit 1 + fi + if [[ "${1:-}" == "-y" || "${YES:-}" == "1" ]]; then return 0; fi + echo "About to act on:" + echo " region=$REGION group=$RESOURCE_GROUP_NAME project=$CE_PROJECT_NAME" + echo " registry=$IMAGE_REPO" + echo " bucket=$COS_BUCKET data-source=$DATA_SOURCE" + read -r -p "Proceed? [y/N] " ans + [[ "$ans" == "y" || "$ans" == "Y" ]] || { echo "Aborted."; exit 1; } +} diff --git a/deploy/ce/index.html b/deploy/ce/index.html new file mode 100644 index 0000000..acb350c --- /dev/null +++ b/deploy/ce/index.html @@ -0,0 +1,382 @@ + + + + + +VAKRA on Code Engine — start here + + + + +
+
+
vakra · code engine
+ +
+
+ +
+
+ 4 / 4 capabilities live on Code Engine +
Enterprise tool-calling benchmark · IBM Code Engine + COS
+

The VAKRA benchmark environment, running in the cloud.

+

Four capability servers on IBM Code Engine expose their tools over MCP-HTTP, backed by ~35 GB of data in IBM COS. Try it in the browser, benchmark against it with one config flag, or deploy your own — start below.

+
+ Open the tool explorer + Read the runbook +
+
+
+ + +
+
+

What this is

+

VAKRA is an enterprise benchmark: an agent is given a set of domain tools (SQL/REST APIs, retrievers, BPO services) and must answer questions by calling them. This deployment moves that tool environment onto Code Engine and its data into COS, so no one has to run containers or download 35 GB locally. Two things get bridged for the cloud, and nothing about the local setup changes:

+ + + +
+ ↳ + Per-domain scoping is preserved. A connection to /mcp/california_schools only ever sees that domain's tools — the bridge pins MCP_DOMAIN per request, exactly like the local docker exec -e path. +
+
+
+ + +
+
+

Choose your path

+

Pick the row that matches you. Each links to the full guide.

+
+ +
+

Try it — zero setup

live
+

Open the hosted explorer, pick a capability and a domain, and browse or invoke the tools right in your browser. No clone, no install, no keys.

+ Open the explorer → · first click: cap 2 → california_schools +
+ +
+

Benchmark against it

dev
+

Run the usual VAKRA runner — the only change from a local run is the MCP config. Add a provider key (OpenAI or watsonx) for a real agent run.

+ 
# after: source deploy/ce/.ce_urls.env
+python benchmark_runner.py --capability_id 2 \
+  --domain california_schools \
+  --mcp-config benchmark/mcp_connection_config.ce.yaml
+ Full instructions → USING.md +
+ +
+

Deploy your own

admin
+

Push data to COS, build the image, and roll out the four apps. Admin-gated, idempotent, and fully additive — existing deployments are untouched.

+ 
python deploy/ce/0_push_data_to_cos.py --stream
+cd deploy/ce
+VAKRA_CE_ADMIN=1 YES=1 ./1_create_bucket_and_pds.sh
+VAKRA_CE_ADMIN=1 YES=1 ./2_build_push_image.sh
+VAKRA_CE_ADMIN=1 YES=1 ./3_deploy_apps.sh
+ Full runbook → RUNBOOK.md +
+ +
+

Understand it

how
+

How the stdio→HTTP bridge keeps tools domain-scoped, how COS is mounted, and every issue we hit (and its fix) while standing this up.

+ Architecture + gotchas → RUNBOOK.md · quick reference → CHEATSHEET.md +
+ +
+
+
+ + +
+
+

The four capabilities

+

Each capability is its own app and MCP endpoint. Tool counts below are from the live smoke test.

+
+ + + + + + + + +
AppCapabilityServesExample domainsTools
vakra-cap1bi_apis — slot-fill / selectionRouterMCP toolsaddress, …9
vakra-cap2dashboard_apis — SQL / RESTM3 REST toolscalifornia_schools, financial, formula_1, movie139
vakra-cap3multihop_reasoningBPO or M3 REST (by domain)bpo, …32
vakra-cap4multiturn — REST + retrieverM3 REST + semantic retrieveraddress, …144
+
+

Valid --domain values are the task-file names under data/test/capability_<id>_*/input/. Browse them per capability in the explorer.

+
+
+ + +
+
+

The endpoint contract

+

Any MCP client can talk to a deployed app over streamable HTTP. Get the real URLs from deploy/ce/.ce_urls.env (an admin has them).

+
+
basehttps://vakra-cap<1–4>.<hash>.us-east.codeengine.appdomain.cloud
+
MCP<base>/mcp/<domain>  — streamable HTTP; scoped to one domain
+
health<base>/healthz  → {"status":"ok","capability_id":"N"}
+
+
+ ! + These endpoints are public and unauthenticated. Keep the URLs within the team; add a bearer-token gate in mcp_http_bridge.py if you need to lock them down. +
+
+
+ + +
+
+

At a glance

+
+
Region · Project
us-east · ce-project-routing
+
Image
icr.io/routing_namespace/ vakra-benchmark:latest
+
Data
COS mount (default) · ~35 GB
+
MCP
mcp==1.27.0 · /mcp/<domain>
+
+
+
+ + +
+
+

The docs

+
+
RUNBOOK.md
Reproduce from scratch — every step, every gotcha + fix. The source of truth.
 +
USING.md
Use the deployed endpoints — MCP client, benchmark runner, or explorer.
 +
CHEATSHEET.md
One-page command reference: deploy · verify · benchmark · use · operate.
 +
README.md
Index + architecture, and which doc to read for what.
 +
+
+
+ +
+
+ VAKRA on IBM Code Engine + COS — additive, admin-gated, all resources prefixed vakra-*. + Internal preview · keep links within the team. +
+
+ + + + diff --git a/deploy/ce/teardown.sh b/deploy/ce/teardown.sh new file mode 100755 index 0000000..47669c3 --- /dev/null +++ b/deploy/ce/teardown.sh @@ -0,0 +1,43 @@ +#!/bin/bash +# ============================================================ +# Teardown — remove ONLY the vakra-* Code Engine resources this path created. +# Never touches other apps, other buckets, or the shared COS instance. +# +# By default the COS bucket + its 32 GB of data are KEPT (redeploy is cheap). +# Pass --delete-bucket to also empty and delete the bucket. +# ============================================================ +set -euo pipefail +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +source "${SCRIPT_DIR}/config.sh" +admin_guard "${1:-}" +require_login +ce_target + +DELETE_BUCKET=0 +for a in "$@"; do [[ "$a" == "--delete-bucket" ]] && DELETE_BUCKET=1; done + +echo "Deleting Code Engine apps ..." +for name in "$APP_CAP1" "$APP_CAP2" "$APP_CAP3" "$APP_CAP4" "$APP_EXPLORER"; do + ibmcloud ce app delete --name "$name" -f >/dev/null 2>&1 && echo " deleted app $name" || echo " (no app $name)" +done + +echo "Deleting persistent data store '$PDS_NAME' ..." +ibmcloud ce pds delete --name "$PDS_NAME" -f >/dev/null 2>&1 && echo " deleted pds" || echo " (no pds)" + +echo "Deleting HMAC secret '$COS_ACCESS_SECRET_NAME' ..." +ibmcloud ce secret delete --name "$COS_ACCESS_SECRET_NAME" -f >/dev/null 2>&1 && echo " deleted secret" || echo " (no secret)" + +rm -f "$URLS_ENV_FILE" 2>/dev/null || true + +if [[ "$DELETE_BUCKET" == "1" ]]; then + echo "Emptying and deleting bucket '$COS_BUCKET' ..." + ibmcloud cos config crn --crn "$COS_INSTANCE_CRN" >/dev/null 2>&1 || true + # Delete all objects, then the bucket. (Requires the cos plugin.) + ibmcloud cos objects-delete-all --bucket "$COS_BUCKET" --region "$REGION" --force >/dev/null 2>&1 || true + ibmcloud cos bucket-delete --bucket "$COS_BUCKET" --region "$REGION" --force >/dev/null 2>&1 \ + && echo " deleted bucket" || echo " (could not delete bucket — delete manually if needed)" +else + echo "Kept bucket '$COS_BUCKET' (pass --delete-bucket to remove it)." +fi + +echo "Teardown complete." diff --git a/docker/Dockerfile.unified b/docker/Dockerfile.unified index 929d122..fc09eb1 100644 --- a/docker/Dockerfile.unified +++ b/docker/Dockerfile.unified @@ -83,6 +83,14 @@ RUN chmod +x entrypoint.sh # --- MCP dispatcher (single entrypoint for all tasks, routed by TASK_ID) --- COPY docker/mcp_dispatch.py mcp_dispatch.py +# --- Optional MCP stdio->HTTP bridge + COS sync (used only for Code Engine) --- +# Dormant in the default local docker-exec flow. The bridge needs a recent mcp for +# StreamableHTTPSessionManager (upgrades only within the mcp 1.x line, no server +# behaviour change); boto3 is used by cos_sync.py when DATA_SOURCE=sync. +RUN pip install --no-cache-dir "mcp==1.27.0" boto3 +COPY docker/mcp_http_bridge.py mcp_http_bridge.py +COPY docker/cos_sync.py cos_sync.py + # Volume mount points (data mounted at runtime, not baked in) VOLUME /app/db VOLUME /app/environment/configs diff --git a/docker/cos_sync.py b/docker/cos_sync.py new file mode 100644 index 0000000..e638a81 --- /dev/null +++ b/docker/cos_sync.py @@ -0,0 +1,95 @@ +#!/usr/bin/env python3 +""" +cos_sync.py — pull a COS bucket prefix to a local directory (S3 / HMAC). + +Used ONLY when the container runs with DATA_SOURCE=sync (the fallback to the +default COS pds mount). It downloads the benchmark data from the VAKRA bucket to +the container's local (ephemeral) disk at startup, giving the servers full +local-filesystem semantics — useful if the s3fs mount proves too slow, or for the +writable ChromaDB path in capability 4. + +Reads from env (set by deploy/ce/3_deploy_apps.sh via the COS access secret): + COS_ENDPOINT e.g. https://s3.us-east.cloud-object-storage.appdomain.cloud + COS_BUCKET e.g. vakra-benchmark-data-us-east + COS_ACCESS_KEY_ID HMAC access key id + COS_SECRET_ACCESS_KEY HMAC secret access key + +Usage: + python cos_sync.py --prefix databases --dest /app/db + python cos_sync.py --prefix configs --dest /app/environment/configs +""" +import argparse +import os +import sys +from pathlib import Path + + +def _client(): + import boto3 # from ibm COS S3-compatible endpoint; boto3 is installed in the image + from botocore.client import Config + + endpoint = os.environ["COS_ENDPOINT"] + key = os.environ["COS_ACCESS_KEY_ID"] + secret = os.environ["COS_SECRET_ACCESS_KEY"] + return boto3.client( + "s3", + endpoint_url=endpoint, + aws_access_key_id=key, + aws_secret_access_key=secret, + config=Config(signature_version="s3v4"), + ) + + +def sync(prefix: str, dest: str) -> None: + bucket = os.environ["COS_BUCKET"] + prefix = prefix.strip("/") + "/" + dest_root = Path(dest) + dest_root.mkdir(parents=True, exist_ok=True) + + client = _client() + paginator = client.get_paginator("list_objects_v2") + + n_files = 0 + n_bytes = 0 + n_skipped = 0 + for page in paginator.paginate(Bucket=bucket, Prefix=prefix): + for obj in page.get("Contents", []): + key = obj["Key"] + if key.endswith("/"): + continue + rel = key[len(prefix):] + if not rel: + continue + local_path = dest_root / rel + local_path.parent.mkdir(parents=True, exist_ok=True) + # Skip if same size already present (cheap resume). + if local_path.exists() and local_path.stat().st_size == obj["Size"]: + n_skipped += 1 + continue + client.download_file(bucket, key, str(local_path)) + n_files += 1 + n_bytes += obj["Size"] + if n_files % 25 == 0: + print(f" [{prefix}] {n_files} files, {n_bytes / 1e9:.2f} GB ...", flush=True) + + print(f" [{prefix}] done: downloaded {n_files} file(s) ({n_bytes / 1e9:.2f} GB), " + f"skipped {n_skipped} already-present.", flush=True) + + +def main() -> None: + ap = argparse.ArgumentParser(description="Sync a COS prefix to a local dir") + ap.add_argument("--prefix", required=True, help="Bucket prefix, e.g. 'databases'") + ap.add_argument("--dest", required=True, help="Local destination directory") + args = ap.parse_args() + + for var in ("COS_ENDPOINT", "COS_BUCKET", "COS_ACCESS_KEY_ID", "COS_SECRET_ACCESS_KEY"): + if not os.environ.get(var): + print(f"cos_sync: missing env {var}", file=sys.stderr) + sys.exit(1) + + print(f"cos_sync: {os.environ['COS_BUCKET']}/{args.prefix} -> {args.dest}", flush=True) + sync(args.prefix, args.dest) + + +if __name__ == "__main__": + main() diff --git a/docker/entrypoint-unified.sh b/docker/entrypoint-unified.sh index 3100344..5a1b580 100644 --- a/docker/entrypoint-unified.sh +++ b/docker/entrypoint-unified.sh @@ -3,6 +3,22 @@ set -e echo "=== M3 Unified Container Starting ===" +# --- Optional: pull data from COS to local disk (DATA_SOURCE=sync) --- +# Default (unset) or DATA_SOURCE=mount -> data is provided by a COS pds mount (or a +# local bind mount) at the paths below; nothing to download here. +# DATA_SOURCE=sync -> download from COS to ephemeral disk before starting servers +# (fallback path; gives full local-fs semantics, e.g. writable ChromaDB for cap 4). +if [ "$DATA_SOURCE" = "sync" ]; then + echo "DATA_SOURCE=sync -> pulling data from COS to local disk (this can take a while)..." + python /app/cos_sync.py --prefix databases --dest /app/db + python /app/cos_sync.py --prefix configs --dest /app/environment/configs + if [ "$CAPABILITY_ID" = "4" ]; then + python /app/cos_sync.py --prefix indexed_documents --dest /app/retrievers/chroma_data + python /app/cos_sync.py --prefix queries --dest /app/retrievers/queries || true + fi + echo "DATA_SOURCE=sync -> data ready." +fi + # --- Start M3 REST FastAPI on port 8000 --- echo "Starting M3 REST FastAPI on port 8000..." cd /app/m3-rest @@ -53,7 +69,18 @@ if [ "$RETRIEVER_AVAILABLE" = "true" ]; then done fi -echo "=== All services running. Container ready for exec. ===" +echo "=== All services running. ===" -# Keep container alive for docker exec -i usage -exec tail -f /dev/null +# --- Serve mode --- +# SERVE_MODE=http -> start the MCP stdio->HTTP bridge (Code Engine / remote clients). +# The FastAPI backends above stay up (the MCP servers call them); +# the bridge exposes MCP over HTTP at /mcp/ on BRIDGE_PORT. +# (unset/default) -> keep the container alive for `docker exec -i` (local benchmark flow). +if [ "$SERVE_MODE" = "http" ]; then + echo "SERVE_MODE=http -> starting MCP HTTP bridge on port ${BRIDGE_PORT:-8080} (endpoint: /mcp/)" + exec python /app/mcp_http_bridge.py --port "${BRIDGE_PORT:-8080}" +else + echo "Container ready for exec." + # Keep container alive for docker exec -i usage + exec tail -f /dev/null +fi diff --git a/docker/mcp_http_bridge.py b/docker/mcp_http_bridge.py new file mode 100644 index 0000000..0829d89 --- /dev/null +++ b/docker/mcp_http_bridge.py @@ -0,0 +1,204 @@ +#!/usr/bin/env python3 +""" +mcp_http_bridge.py — stdio → streamable-HTTP MCP bridge (OPT-IN, Code Engine only). + +Why this exists +--------------- +Locally, benchmark clients reach the MCP servers via `docker exec -i -e MCP_DOMAIN= + python /app/mcp_dispatch.py` — i.e. MCP over **stdio**, with the domain +injected as an env var into a freshly-spawned server process. Code Engine has no +`docker exec`, so the servers must be reachable over **HTTP**. + +This bridge fronts the *unchanged* `mcp_dispatch.py`. It reproduces the exact +per-domain tool scoping: + + HTTP client connects to -> https:///mcp/ + bridge spawns -> python /app/mcp_dispatch.py (env MCP_DOMAIN=, + CAPABILITY_ID inherited) + bridge proxies -> initialize / list_tools / call_tool + +A client that connects to /mcp/address gets ONLY the address tools — the subprocess +behind that path was launched with a single MCP_DOMAIN, so list_tools() is scoped +exactly as it is under docker exec. `verify_checksum(capability_id, domain, tools)` +on the client passes unchanged. No MCP server file is modified. + +Only runs when the container is started with SERVE_MODE=http (see entrypoint-unified.sh). +The default (docker-exec / local) path is untouched. + +Requires: mcp>=1.9 (StreamableHTTPSessionManager), starlette, uvicorn — all in the image. +""" +from __future__ import annotations + +import argparse +import asyncio +import contextlib +import logging +import os +import sys +from contextvars import ContextVar +from typing import Dict, Optional + +import uvicorn +from starlette.types import Receive, Scope, Send + +from mcp import ClientSession, StdioServerParameters +from mcp.client.stdio import stdio_client +from mcp.server.lowlevel import Server +from mcp.server.streamable_http_manager import StreamableHTTPSessionManager + +logging.basicConfig( + level=os.environ.get("BRIDGE_LOG_LEVEL", "INFO"), + format="%(asctime)s bridge[%(levelname)s] %(message)s", +) +log = logging.getLogger("mcp_http_bridge") + +CAPABILITY_ID = os.environ.get("CAPABILITY_ID", "").strip() +# Overridable for local testing (point at a dummy stdio MCP server). +DISPATCH = os.environ.get("BRIDGE_DISPATCH", "/app/mcp_dispatch.py") + +# Domain for the request currently being handled. Set by the ASGI wrapper before +# delegating to the session manager; read by the proxied list_tools/call_tool +# handlers. anyio copies the current context into the per-request task the session +# manager spawns, so the value propagates correctly. +_current_domain: ContextVar[str] = ContextVar("current_domain", default="") + + +# --------------------------------------------------------------------------- +# Downstream backend: a fresh stdio subprocess (mcp_dispatch.py) pinned to a +# single MCP_DOMAIN, created AND torn down within the calling request's own task +# scope. We deliberately do NOT cache/share sessions across requests — a +# ClientSession's internal task group belongs to the task that created it, and +# reusing it from another request task trips anyio's cancel-scope bookkeeping +# ("attempted to exit a cancel scope that isn't the current task's"). +# --------------------------------------------------------------------------- +@contextlib.asynccontextmanager +async def spawn_backend(domain: str): + env = os.environ.copy() + if domain: + env["MCP_DOMAIN"] = domain + params = StdioServerParameters(command=sys.executable, args=[DISPATCH], env=env) + async with stdio_client(params) as (read, write): + async with ClientSession(read, write) as sess: + await sess.initialize() + yield sess + + +# --------------------------------------------------------------------------- +# The single low-level proxy Server. Its handlers forward each request to a +# fresh domain-pinned subprocess (domain from the contextvar set per request). +# --------------------------------------------------------------------------- +proxy = Server(f"vakra-capability-{CAPABILITY_ID or '?'}") + + +@proxy.list_tools() +async def _list_tools(): + domain = _current_domain.get() + async with spawn_backend(domain) as sess: + tools = (await sess.list_tools()).tools + log.info("list_tools domain=%r -> %d tools", domain, len(tools)) + return tools + + +@proxy.call_tool() +async def _call_tool(name: str, arguments: dict): + domain = _current_domain.get() + async with spawn_backend(domain) as sess: + result = await sess.call_tool(name, arguments or {}) + # Forward the downstream content blocks verbatim. + return result.content + + +session_manager = StreamableHTTPSessionManager( + app=proxy, + event_store=None, + json_response=True, # plain JSON responses — no SSE plumbing needed for the benchmark + stateless=True, # each request self-contained; domain is re-derived from the path +) + + +# --------------------------------------------------------------------------- +# Minimal ASGI app: /healthz + /mcp//... (domain -> contextvar -> manager) +# --------------------------------------------------------------------------- +async def _send_json(send: Send, status: int, body: bytes) -> None: + await send({ + "type": "http.response.start", + "status": status, + "headers": [(b"content-type", b"application/json")], + }) + await send({"type": "http.response.body", "body": body}) + + +async def app(scope: Scope, receive: Receive, send: Send) -> None: + if scope["type"] == "lifespan": + # Keep the session manager's task group alive for the whole app lifetime, + # and tear down any spawned subprocesses on shutdown. + while True: + message = await receive() + if message["type"] == "lifespan.startup": + try: + cm = session_manager.run() + await cm.__aenter__() + scope.setdefault("state", {})["_mgr_cm"] = cm + await send({"type": "lifespan.startup.complete"}) + except Exception as e: # noqa: BLE001 + await send({"type": "lifespan.startup.failed", "message": str(e)}) + elif message["type"] == "lifespan.shutdown": + cm = scope.get("state", {}).get("_mgr_cm") + if cm is not None: + with contextlib.suppress(Exception): + await cm.__aexit__(None, None, None) + await send({"type": "lifespan.shutdown.complete"}) + return + + if scope["type"] != "http": + return + + path = scope.get("path", "") + + if path in ("/healthz", "/health"): + import json as _json + body = _json.dumps({ + "status": "ok", + "capability_id": CAPABILITY_ID, + }).encode() + await _send_json(send, 200, body) + return + + # Expect /mcp/[/...] + parts = [p for p in path.split("/") if p != ""] + if len(parts) >= 2 and parts[0] == "mcp": + domain = parts[1] + token = _current_domain.set(domain) + try: + await session_manager.handle_request(scope, receive, send) + finally: + _current_domain.reset(token) + return + + import json as _json + await _send_json( + send, 404, + _json.dumps({ + "error": "not found", + "hint": "connect to /mcp/ (e.g. /mcp/address); health at /healthz", + }).encode(), + ) + + +def main() -> None: + parser = argparse.ArgumentParser(description="VAKRA MCP stdio->HTTP bridge") + parser.add_argument("--port", type=int, default=int(os.environ.get("BRIDGE_PORT", "8080"))) + parser.add_argument("--host", type=str, default=os.environ.get("BRIDGE_HOST", "0.0.0.0")) + args = parser.parse_args() + + if CAPABILITY_ID not in {"1", "2", "3", "4"}: + log.error("CAPABILITY_ID must be one of 1..4; got %r", CAPABILITY_ID) + sys.exit(1) + + log.info("MCP HTTP bridge starting: capability=%s on %s:%d (endpoint: /mcp/)", + CAPABILITY_ID, args.host, args.port) + uvicorn.run(app, host=args.host, port=args.port, log_level="info") + + +if __name__ == "__main__": + main() diff --git a/pyproject.toml b/pyproject.toml index c59eeb8..bc6e063 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,7 @@ dependencies = [ "jinja2", "dotenv", "pyyaml", + "sentence-transformers>=5.6.1", ] [project.optional-dependencies] diff --git a/tools_explorer/app.py b/tools_explorer/app.py index 1e2cd7c..694cc97 100644 --- a/tools_explorer/app.py +++ b/tools_explorer/app.py @@ -12,6 +12,7 @@ import json import logging +import os import sys import traceback from pathlib import Path @@ -46,7 +47,13 @@ def _load_configs(): from benchmark.mcp_client import load_mcp_config - config_path = PROJECT_ROOT / "benchmark" / "mcp_connection_config.yaml" + # MCP_CONFIG lets the explorer point at Code Engine instead of local containers, + # e.g. MCP_CONFIG=benchmark/mcp_connection_config.ce.yaml (after sourcing + # deploy/ce/.ce_urls.env). Defaults to the local docker-exec config. + override = os.environ.get("MCP_CONFIG") + config_path = Path(override) if override else PROJECT_ROOT / "benchmark" / "mcp_connection_config.yaml" + if not config_path.is_absolute(): + config_path = PROJECT_ROOT / config_path return load_mcp_config(str(config_path)) diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..18b7c15 --- /dev/null +++ b/uv.lock @@ -0,0 +1,6554 @@ +version = 1 +revision = 2 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.14' and sys_platform == 'win32'", + "python_full_version >= '3.14' and sys_platform == 'emscripten'", + "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version == '3.13.*' and sys_platform == 'win32'", + "python_full_version == '3.12.*' and sys_platform == 'win32'", + "python_full_version == '3.13.*' and sys_platform == 'emscripten'", + "python_full_version == '3.12.*' and sys_platform == 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