From 9008fbd512dbf2fff53fedbbfce48cc6d0900a2f Mon Sep 17 00:00:00 2001 From: mo Date: Tue, 21 Jul 2026 23:20:24 +0000 Subject: [PATCH] feat: Authentik login + switchable GPU prod target Add OIDC auth for Command Center and runtime GPU endpoint selection pointed at atc-gpu-prod (10.0.10.106), matching what is currently deployed. --- api/Dockerfile | 2 +- api/agent_activity.py | 4 +- api/agent_ops.py | 58 +- api/auth.py | 229 ++ api/etl_offload.py | 14 +- api/gpu_config.py | 304 ++ api/lab_context.py | 34 +- api/main.py | 391 ++- api/node_ops.py | 19 + api/node_registry.py | 18 +- api/pii_catalog.py | 257 +- api/platform_context.py | 29 +- api/presentation.py | 17 +- api/presentation_static.py | 4 +- api/requirements.txt | 2 + api/topology_views.py | 17 +- api/workload.py | 31 +- caddy/Caddyfile | 3 + config/command-center/atc.env.example | 4 +- config/command-center/docker-compose.yml | 8 +- docker-compose.dockhand.yml | 6 +- docker-compose.yml | 16 +- ui/package-lock.json | 2868 +++++++++++++++++ ui/src/App.tsx | 18 + ui/src/components/features/GpuMatrixPanel.tsx | 218 +- ui/src/components/features/LoginView.tsx | 47 + ui/src/components/layout/TopBar.tsx | 22 +- ui/src/hooks/useAuth.ts | 42 + ui/src/lib/api.ts | 66 +- ui/src/lib/infraCatalog.ts | 10 +- ui/src/types.ts | 48 + 31 files changed, 4667 insertions(+), 139 deletions(-) create mode 100644 api/auth.py create mode 100644 api/gpu_config.py create mode 100644 ui/package-lock.json create mode 100644 ui/src/components/features/LoginView.tsx create mode 100644 ui/src/hooks/useAuth.ts diff --git a/api/Dockerfile b/api/Dockerfile index 9a13ba6..8d831a8 100644 --- a/api/Dockerfile +++ b/api/Dockerfile @@ -4,7 +4,7 @@ WORKDIR /app RUN apt-get update && apt-get install -y --no-install-recommends curl && rm -rf /var/lib/apt/lists/* COPY requirements.txt . RUN pip install --no-cache-dir -r requirements.txt -COPY main.py lab_context.py agent_terminal.py workload.py node_registry.py node_ops.py topology_views.py supervisor.py approval_service.py db.py dockhand_envs.py presentation.py database_inventory.py presentation_upload.py presentation_static.py storage_s3.py elasticsearch_api.py sql_console.py hdfs_api.py ssh_terminal.py pipeline_ops.py hadoop_analytics.py agent_ops.py cdc_consumer.py movements.py dataflow.py streaming_ops.py spark_workbench.py hadoop_sql.py hdfs_kafka.py webhdfs_util.py pii_catalog.py platform_context.py trino_federated.py etl_offload.py agent_activity.py lake_meta.py lineage.py dq_monitor.py observability.py catalog_governance.py hive_bench_seed.json . +COPY main.py auth.py lab_context.py agent_terminal.py workload.py node_registry.py node_ops.py topology_views.py supervisor.py approval_service.py db.py dockhand_envs.py presentation.py database_inventory.py presentation_upload.py presentation_static.py storage_s3.py elasticsearch_api.py sql_console.py hdfs_api.py ssh_terminal.py pipeline_ops.py hadoop_analytics.py agent_ops.py cdc_consumer.py movements.py dataflow.py streaming_ops.py spark_workbench.py hadoop_sql.py hdfs_kafka.py webhdfs_util.py pii_catalog.py platform_context.py trino_federated.py etl_offload.py agent_activity.py lake_meta.py lineage.py dq_monitor.py observability.py catalog_governance.py gpu_config.py hive_bench_seed.json . RUN mkdir -p /data ENV DATABASE_URL=sqlite:////data/atc-agents.db EXPOSE 3201 diff --git a/api/agent_activity.py b/api/agent_activity.py index 7e86e86..2a4a868 100644 --- a/api/agent_activity.py +++ b/api/agent_activity.py @@ -24,6 +24,7 @@ TRINO_USER = os.getenv("TRINO_USER", "mo") HDFS_NN_URL = os.getenv("HDFS_NN_URL", "http://10.0.21.61:9870").rstrip("/") YARN_URL = os.getenv("YARN_URL", "http://10.0.21.62:8088").rstrip("/") DOCKHAND_URL = os.getenv("DOCKHAND_URL", "http://10.0.21.45:8082").rstrip("/") +DOCKHAND_API_TOKEN = os.getenv("DOCKHAND_API_TOKEN", "") OBJECTSCALE_URL = os.getenv("OBJECTSCALE_URL", os.getenv("S3_ENDPOINT", "http://10.0.20.111:9020")).rstrip("/") TICK_SECONDS = float(os.getenv("AGENT_ACTIVITY_TICK_SECONDS", "8")) @@ -142,7 +143,8 @@ async def _infra_sentinel() -> None: async with httpx.AsyncClient(timeout=4.0) as client: async def _one(name: str, eid: int): try: - r = await client.get(f"{DOCKHAND_URL}/api/containers", params={"env": eid}) + hdr = {"Authorization": f"Bearer {DOCKHAND_API_TOKEN}"} if DOCKHAND_API_TOKEN else {} + r = await client.get(f"{DOCKHAND_URL}/api/containers", params={"env": eid}, headers=hdr) if r.status_code >= 400: return None d = r.json() diff --git a/api/agent_ops.py b/api/agent_ops.py index b4d1f1f..07fc43c 100644 --- a/api/agent_ops.py +++ b/api/agent_ops.py @@ -364,10 +364,36 @@ _CUST_INTERVAL = float(os.getenv("CUSTODIAN_OFFLOAD_INTERVAL_SECONDS", "120")) _CUST_BATCH = int(os.getenv("CUSTODIAN_OFFLOAD_BATCH", "200")) _CUST_TARGETS = [ {"label": "postgres sales_orders", "src": "postgres_sales.public.sales_orders", - "target": "iceberg.hadoop.sales_orders_offload"}, + "target": "iceberg.hadoop.sales_orders_offload", + "create_sql": ( + "CREATE TABLE iceberg.hadoop.sales_orders_offload AS " + "SELECT * FROM postgres_sales.public.sales_orders WHERE 1=0" + ), + "insert_sql": ( + "INSERT INTO iceberg.hadoop.sales_orders_offload " + "SELECT * FROM postgres_sales.public.sales_orders LIMIT {batch}" + )}, {"label": "mysql employee_events", "src": "mysql_hr.hr.employee_events", - "target": "iceberg.hadoop.employee_events_offload"}, + "target": "iceberg.hadoop.employee_events_offload", + "create_sql": ( + "CREATE TABLE iceberg.hadoop.employee_events_offload AS SELECT " + "event_id, employee_id, department, role_name, region, event_type, " + "CAST(salary_change AS double) AS salary_change, " + "CAST(event_ts AS timestamp(6)) AS event_ts, notes, " + "employee_name, employee_email, employee_phone, national_id, home_address, " + "CAST(date_of_birth AS date) AS date_of_birth " + "FROM mysql_hr.hr.employee_events WHERE 1=0" + ), + "insert_sql": ( + "INSERT INTO iceberg.hadoop.employee_events_offload SELECT " + "event_id, employee_id, department, role_name, region, event_type, " + "CAST(salary_change AS double), CAST(event_ts AS timestamp(6)), notes, " + "employee_name, employee_email, employee_phone, national_id, home_address, " + "CAST(date_of_birth AS date) " + "FROM mysql_hr.hr.employee_events LIMIT {batch}" + )}, ] + _custodian_state: dict[str, Any] = { "enabled": os.getenv("CUSTODIAN_OFFLOAD_ENABLED", "1") not in ("0", "false", "False", ""), "interval": _CUST_INTERVAL, @@ -385,12 +411,28 @@ async def _custodian_offload_once(idx: int | None = None) -> dict[str, Any]: i = _custodian_state["idx"] if idx is None else idx tgt = _CUST_TARGETS[i % len(_CUST_TARGETS)] _custodian_state["idx"] = i + 1 - ddl = f"CREATE TABLE IF NOT EXISTS {tgt['target']} AS SELECT * FROM {tgt['src']} WHERE 1=0" - dml = f"INSERT INTO {tgt['target']} SELECT * FROM {tgt['src']} LIMIT {_CUST_BATCH}" - await _term(DML_AGENT, f"$ trino --catalog iceberg # Hadoop offload: {tgt['label']} → {tgt['target']}", - level="cmd", phase="offload") - await _term(DML_AGENT, f" {ddl};", level="cmd", phase="offload") - await _trino_collect(ddl, 1) + await _trino_collect("CREATE SCHEMA IF NOT EXISTS iceberg.hadoop", 1) + probe = await _trino_collect(f"SELECT 1 FROM {tgt['target']} WHERE 1=0", 1) + if not probe.get("ok"): + ddl = tgt["create_sql"] + await _term(DML_AGENT, f"$ trino --catalog iceberg # Hadoop offload: {tgt['label']} → {tgt['target']}", + level="cmd", phase="offload") + await _term(DML_AGENT, f" {ddl};", level="cmd", phase="offload") + created = await _trino_collect(ddl, 1) + if not created.get("ok"): + err = created.get("error") + await _term(DML_AGENT, f" ✗ offload failed: {str(err)[:140]}", level="err", phase="offload") + await _emit(f"[custodian-offload] {tgt['label']} failed: {str(err)[:120]}", "err") + _custodian_state["runs_total"] += 1 + _custodian_state["last"] = { + "target": tgt["target"], "src": tgt["src"], "ok": False, + "rows": 0, "ts": datetime.now(timezone.utc).isoformat(), "error": err, + } + return _custodian_state["last"] + else: + await _term(DML_AGENT, f"$ trino --catalog iceberg # Hadoop offload: {tgt['label']} → {tgt['target']}", + level="cmd", phase="offload") + dml = tgt["insert_sql"].format(batch=_CUST_BATCH) await _term(DML_AGENT, f" {dml};", level="cmd", phase="offload") ins = await _trino_collect(dml, 1) ok = bool(ins.get("ok")) diff --git a/api/auth.py b/api/auth.py new file mode 100644 index 0000000..b8e926c --- /dev/null +++ b/api/auth.py @@ -0,0 +1,229 @@ +"""Authentik OIDC login and session cookie for Command Center.""" + +from __future__ import annotations + +import logging +import os +from typing import Any +from urllib.parse import quote, urlencode + +import httpx +from authlib.common.security import generate_token +from authlib.integrations.starlette_client import OAuth +from authlib.oauth2.rfc7636 import create_s256_code_challenge +from fastapi import FastAPI, HTTPException, Request +from fastapi.responses import JSONResponse, RedirectResponse +from starlette.middleware.sessions import SessionMiddleware + +log = logging.getLogger("atc-agents.auth") + +AUTH_ENABLED = os.getenv("AUTH_ENABLED", "true").lower() in ("1", "true", "yes") +AUTHENTIK_ISSUER = os.getenv( + "AUTHENTIK_ISSUER", + "http://atc-mgt01.dell-atc.lan:9000/application/o/command-center/", +).rstrip("/") + "/" +AUTHENTIK_CLIENT_ID = os.getenv("AUTHENTIK_CLIENT_ID", "") +AUTHENTIK_CLIENT_SECRET = os.getenv("AUTHENTIK_CLIENT_SECRET", "") +AUTHENTIK_REDIRECT_URI = os.getenv( + "AUTHENTIK_REDIRECT_URI", + "http://10.0.21.33/auth/callback", +) +SESSION_SECRET = os.getenv("SESSION_SECRET", "dev-insecure-change-me") +SESSION_COOKIE = "cc_session" + +oauth = OAuth() +_oauth_ready = False + +PUBLIC_PREFIXES = ( + "/auth/", + "/api/health", + "/api/auth/me", +) + + +def is_auth_enabled() -> bool: + return AUTH_ENABLED + + +def build_session_user(claims: dict[str, Any]) -> dict[str, Any]: + name = claims.get("name") or claims.get("preferred_username") or claims.get("email") or "user" + email = claims.get("email") or "" + username = claims.get("preferred_username") or claims.get("nickname") or email or str(claims.get("sub") or "user") + return { + "sub": claims.get("sub"), + "email": email, + "name": name, + "preferred_username": username, + } + + +def get_session_user(request: Request) -> dict[str, Any] | None: + if not AUTH_ENABLED: + return { + "sub": "dev:local", + "email": "", + "name": "Dev User", + "preferred_username": "dev", + "dev": True, + } + user = request.session.get("user") + return user if isinstance(user, dict) else None + + +def auth_me_payload(request: Request) -> dict[str, Any]: + user = get_session_user(request) + if not user: + raise HTTPException(status_code=401, detail="Not authenticated") + return { + "user": user.get("sub"), + "email": user.get("email"), + "name": user.get("name"), + "preferred_username": user.get("preferred_username"), + "auth_enabled": AUTH_ENABLED, + } + + +def _ensure_oauth() -> None: + global _oauth_ready + if _oauth_ready or not AUTH_ENABLED: + return + if not AUTHENTIK_CLIENT_ID or not AUTHENTIK_CLIENT_SECRET: + log.warning("AUTH_ENABLED but Authentik client credentials missing") + return + meta_url = AUTHENTIK_ISSUER + ".well-known/openid-configuration" + oauth.register( + name="authentik", + client_id=AUTHENTIK_CLIENT_ID, + client_secret=AUTHENTIK_CLIENT_SECRET, + server_metadata_url=meta_url, + client_kwargs={"scope": "openid profile email"}, + ) + _oauth_ready = True + + +def _is_public_path(path: str) -> bool: + return any(path == p or path.startswith(p) for p in PUBLIC_PREFIXES) + + +async def auth_guard_middleware(request: Request, call_next): + if not AUTH_ENABLED: + return await call_next(request) + path = request.url.path + if _is_public_path(path): + return await call_next(request) + if path.startswith("/api/"): + if get_session_user(request) is None: + return JSONResponse({"detail": "Not authenticated"}, status_code=401) + return await call_next(request) + + +def init_auth_middleware(app: FastAPI) -> None: + """Session must wrap auth guard so request.session is populated first.""" + app.middleware("http")(auth_guard_middleware) + app.add_middleware( + SessionMiddleware, + secret_key=SESSION_SECRET, + session_cookie=SESSION_COOKIE, + max_age=86400 * 7, + same_site="lax", + https_only=False, + ) + + +def setup_auth(app: FastAPI) -> None: + _ensure_oauth() + _register_routes(app) + + +def _token_endpoint() -> str: + return AUTHENTIK_ISSUER.rstrip("/").rsplit("/application/o/", 1)[0] + "/application/o/token/" + + +def _userinfo_endpoint() -> str: + return AUTHENTIK_ISSUER.rstrip("/").rsplit("/application/o/", 1)[0] + "/application/o/userinfo/" + + +async def _exchange_code_for_userinfo(code: str, code_verifier: str | None) -> dict[str, Any]: + data = { + "grant_type": "authorization_code", + "code": code, + "redirect_uri": AUTHENTIK_REDIRECT_URI, + "client_id": AUTHENTIK_CLIENT_ID, + "client_secret": AUTHENTIK_CLIENT_SECRET, + } + if code_verifier: + data["code_verifier"] = code_verifier + async with httpx.AsyncClient(timeout=20.0) as client: + tok = await client.post(_token_endpoint(), data=data) + if tok.status_code >= 400: + log.warning("Token exchange failed: %s %s", tok.status_code, tok.text[:300]) + tok.raise_for_status() + payload = tok.json() + access = payload.get("access_token") + if not access: + raise RuntimeError("No access_token in token response") + ui = await client.get( + _userinfo_endpoint(), + headers={"Authorization": f"Bearer {access}"}, + ) + if ui.status_code >= 400: + log.warning("Userinfo failed: %s %s", ui.status_code, ui.text[:300]) + ui.raise_for_status() + return ui.json() + + +def _register_routes(app: FastAPI) -> None: + @app.get("/api/auth/me") + async def api_auth_me(request: Request): + return auth_me_payload(request) + + @app.get("/auth/login") + async def auth_login(request: Request): + if not AUTH_ENABLED: + return RedirectResponse("/", status_code=302) + _ensure_oauth() + if not _oauth_ready: + raise HTTPException(503, "Authentik not configured") + code_verifier = generate_token(48) + request.session["pkce_code_verifier"] = code_verifier + return await oauth.authentik.authorize_redirect( + request, + AUTHENTIK_REDIRECT_URI, + code_challenge=create_s256_code_challenge(code_verifier), + code_challenge_method="S256", + code_verifier=code_verifier, + ) + + @app.get("/auth/callback") + async def auth_callback(request: Request): + if not AUTH_ENABLED: + return RedirectResponse("/", status_code=302) + err = request.query_params.get("error") + if err: + desc = request.query_params.get("error_description") or err + log.warning("OIDC provider error: %s — %s", err, desc) + return RedirectResponse(f"/?error={quote(desc)}", status_code=302) + code = request.query_params.get("code") + if not code: + return RedirectResponse("/?error=missing_code", status_code=302) + state = request.query_params.get("state") + if state: + request.session.pop(f"_state_authentik_{state}", None) + code_verifier = request.session.pop("pkce_code_verifier", None) + try: + userinfo = await _exchange_code_for_userinfo(code, code_verifier) + except Exception as e: + log.warning("OIDC callback failed: %s", e) + return RedirectResponse("/?error=login_failed", status_code=302) + request.session["user"] = build_session_user(userinfo or {}) + return RedirectResponse("/", status_code=302) + + @app.get("/auth/logout") + async def auth_logout(request: Request): + request.session.clear() + if not AUTH_ENABLED: + return RedirectResponse("/", status_code=302) + end_session = AUTHENTIK_ISSUER + "end-session/" + post_logout = "http://10.0.21.33/" + params = urlencode({"post_logout_redirect_uri": post_logout}) + return RedirectResponse(f"{end_session}?{params}", status_code=302) diff --git a/api/etl_offload.py b/api/etl_offload.py index d73b7ac..bc65d44 100644 --- a/api/etl_offload.py +++ b/api/etl_offload.py @@ -24,6 +24,7 @@ Endpoints: from __future__ import annotations import io +import os import json import random import threading @@ -46,9 +47,9 @@ DATASETS = [ _lock = threading.Lock() _state: dict[str, Any] = { - "enabled": True, - "interval_s": 60.0, - "chunk": 5000, + "enabled": os.getenv("ETL_OFFLOAD_ENABLED", "1") not in ("0", "false", "False"), + "interval_s": float(os.getenv("ETL_OFFLOAD_INTERVAL_SECONDS", "30")), + "chunk": int(os.getenv("ETL_OFFLOAD_CHUNK", "20000")), "running_cycle": False, "started_at": None, "last_cycle_ts": 0.0, @@ -440,8 +441,11 @@ def _loop() -> None: try: if _state["enabled"]: run_cycle() - except Exception: - pass + except Exception as exc: + try: + _feed(f"cycle error: {str(exc)[:160]}", level="err") + except Exception: + pass time.sleep(max(10.0, float(_state["interval_s"]))) diff --git a/api/gpu_config.py b/api/gpu_config.py new file mode 100644 index 0000000..dad7c73 --- /dev/null +++ b/api/gpu_config.py @@ -0,0 +1,304 @@ +"""Runtime GPU / LLM endpoint selection with DB override above env defaults.""" + +from __future__ import annotations + +import os +from datetime import datetime, timezone +from typing import Any +from urllib.parse import urlparse + +import httpx +from sqlalchemy import Column, DateTime, String, Text, select +from sqlalchemy.orm import DeclarativeBase + +from db import SessionLocal, engine + +GPU_UI_PORT = int(os.getenv("GPU_UI_PORT", "9000")) +LLM_PORT = int(os.getenv("LLM_PORT", "8001")) +LLM_PATH = os.getenv("LLM_PATH", "/v1") + +ENV_GPU_URL = os.getenv("GPU_URL", "http://10.0.10.106:9000") +ENV_GPU_UI_URL = os.getenv("GPU_UI_URL", ENV_GPU_URL) +ENV_LLM_URL = os.getenv("LLM_URL", "http://10.0.10.106:8001/v1") + + +class _Base(DeclarativeBase): + pass + + +class SystemSetting(_Base): + __tablename__ = "system_settings" + + key = Column(String(64), primary_key=True) + value = Column(Text, nullable=False, default="") + updated_at = Column(DateTime(timezone=True), nullable=True) + + +GPU_PRESETS: list[dict[str, Any]] = [ + { + "id": "gpu-prod", + "label": "atc-gpu-prod (VM306)", + "vm": "atc-gpu-prod", + "vmid": 306, + "host": "10.0.10.106", + "gpu_ui_port": 9000, + "llm_port": 8001, + "description": "4× V100 — shared production GPU lab", + }, + { + "id": "gpu-dev", + "label": "atc-gpu-dev (VM303, legacy)", + "vm": "atc-gpu-dev", + "vmid": 303, + "host": "10.0.20.106", + "gpu_ui_port": 9000, + "llm_port": 8001, + "description": "Legacy dev VM — GPU passthrough removed", + }, + { + "id": "gpu-bart", + "label": "atc-gpu-bart (VM301)", + "vm": "atc-gpu-bart", + "vmid": 301, + "host": "10.0.11.66", + "gpu_ui_port": 9000, + "llm_port": 8001, + "description": "Bart GPU VM — 2× V100", + }, +] + + +def _ensure_table() -> None: + SystemSetting.metadata.create_all(engine, tables=[SystemSetting.__table__]) + + +def _get_setting(key: str) -> str | None: + _ensure_table() + with SessionLocal() as db: + row = db.get(SystemSetting, key) + return row.value if row else None + + +def _set_settings(values: dict[str, str]) -> None: + _ensure_table() + now = datetime.now(timezone.utc) + with SessionLocal() as db: + for key, value in values.items(): + row = db.get(SystemSetting, key) + if row: + row.value = value + row.updated_at = now + else: + db.add(SystemSetting(key=key, value=value, updated_at=now)) + db.commit() + + +def _clear_settings(keys: list[str]) -> None: + _ensure_table() + with SessionLocal() as db: + for key in keys: + row = db.get(SystemSetting, key) + if row: + db.delete(row) + db.commit() + + +def _build_urls(host: str, gpu_ui_port: int, llm_port: int) -> dict[str, str]: + host = host.strip().replace("http://", "").replace("https://", "").split("/")[0] + if ":" in host: + base_host = host.split(":")[0] + else: + base_host = host + gpu_url = f"http://{base_host}:{gpu_ui_port}" + llm_url = f"http://{base_host}:{llm_port}{LLM_PATH}" + return { + "host": base_host, + "gpu_url": gpu_url, + "gpu_ui_url": gpu_url, + "llm_url": llm_url, + } + + +def _env_defaults() -> dict[str, Any]: + parsed = urlparse(ENV_GPU_URL) + host = parsed.hostname or "10.0.10.106" + return { + "source": "env", + "preset_id": "env", + "label": "Environment default", + **_build_urls(host, parsed.port or GPU_UI_PORT, LLM_PORT), + "env_gpu_url": ENV_GPU_URL, + "env_llm_url": ENV_LLM_URL, + } + + +def get_gpu_urls() -> dict[str, str]: + """Effective GPU/LLM URLs — DB override wins over env.""" + cfg = get_gpu_config() + return { + "gpu_url": cfg["gpu_url"], + "gpu_ui_url": cfg["gpu_ui_url"], + "llm_url": cfg["llm_url"], + "host": cfg["host"], + } + + +def resolve_gpu_identity(gpu: dict[str, Any] | None = None) -> dict[str, Any]: + """Canonical GPU host/VM/URLs for topology, registry links, and presentation.""" + urls = get_gpu_urls() + cfg = get_gpu_config() + g = gpu or {} + host = str(g.get("ip") or g.get("host") or urls["host"]).strip() + preset_id = g.get("preset_id") or cfg.get("preset_id") + preset = next((p for p in GPU_PRESETS if p["id"] == preset_id), None) + if preset is None: + preset = next((p for p in GPU_PRESETS if p["host"] == host), None) + if preset is None: + preset = GPU_PRESETS[0] + ui_url = str(g.get("ui_url") or urls["gpu_ui_url"]) + llm_url = str(g.get("vllm_url") or urls["llm_url"]) + return { + "host": host, + "ip": host, + "vm": preset.get("vm") or "atc-gpu-prod", + "vmid": preset.get("vmid") or 306, + "ui_url": ui_url, + "llm_url": llm_url, + "preset_id": preset.get("id") or preset_id or "gpu-prod", + "label": preset.get("label") or cfg.get("label") or preset.get("vm"), + } + + +def get_gpu_config() -> dict[str, Any]: + override_host = _get_setting("gpu_host") + if not override_host: + return _env_defaults() + + preset_id = _get_setting("gpu_preset_id") or "custom" + gpu_ui_port = int(_get_setting("gpu_ui_port") or GPU_UI_PORT) + llm_port = int(_get_setting("llm_port") or LLM_PORT) + urls = _build_urls(override_host, gpu_ui_port, llm_port) + preset = next((p for p in GPU_PRESETS if p["id"] == preset_id), None) + return { + "source": "override", + "preset_id": preset_id, + "label": preset["label"] if preset else f"Custom ({override_host})", + **urls, + "env_gpu_url": ENV_GPU_URL, + "env_llm_url": ENV_LLM_URL, + "updated_at": _get_setting("gpu_updated_at"), + } + + +def get_gpu_config_payload() -> dict[str, Any]: + cfg = get_gpu_config() + return { + "active": cfg, + "presets": GPU_PRESETS, + "defaults": _env_defaults(), + } + + +def save_gpu_config( + *, + preset_id: str | None = None, + host: str | None = None, + gpu_ui_port: int | None = None, + llm_port: int | None = None, +) -> dict[str, Any]: + if preset_id and preset_id != "custom": + preset = next((p for p in GPU_PRESETS if p["id"] == preset_id), None) + if not preset: + raise ValueError(f"Unknown preset: {preset_id}") + host = preset["host"] + gpu_ui_port = preset.get("gpu_ui_port", GPU_UI_PORT) + llm_port = preset.get("llm_port", LLM_PORT) + if not host: + raise ValueError("host is required for custom GPU target") + + gpu_ui_port = gpu_ui_port or GPU_UI_PORT + llm_port = llm_port or LLM_PORT + now = datetime.now(timezone.utc).isoformat() + _set_settings( + { + "gpu_host": host.strip(), + "gpu_ui_port": str(gpu_ui_port), + "llm_port": str(llm_port), + "gpu_preset_id": preset_id or "custom", + "gpu_updated_at": now, + } + ) + return get_gpu_config() + + +def reset_gpu_config() -> dict[str, Any]: + _clear_settings(["gpu_host", "gpu_ui_port", "llm_port", "gpu_preset_id", "gpu_updated_at"]) + return _env_defaults() + + +async def test_gpu_target( + host: str | None = None, + gpu_ui_port: int | None = None, + llm_port: int | None = None, + preset_id: str | None = None, +) -> dict[str, Any]: + if preset_id and preset_id != "custom": + preset = next((p for p in GPU_PRESETS if p["id"] == preset_id), None) + if preset: + host = preset["host"] + gpu_ui_port = preset.get("gpu_ui_port", GPU_UI_PORT) + llm_port = preset.get("llm_port", LLM_PORT) + if not host: + cfg = get_gpu_config() + host = cfg["host"] + gpu_ui_port = gpu_ui_port or GPU_UI_PORT + llm_port = llm_port or LLM_PORT + + urls = _build_urls(host, gpu_ui_port or GPU_UI_PORT, llm_port or LLM_PORT) + result: dict[str, Any] = { + "ok": False, + "host": urls["host"], + "gpu_url": urls["gpu_url"], + "llm_url": urls["llm_url"], + "metrics_ok": False, + "llm_ok": False, + "gpu_count": 0, + "inference_active": False, + "active_model": None, + "errors": [], + } + + async with httpx.AsyncClient(timeout=8.0) as client: + try: + mr = await client.get(f"{urls['gpu_url']}/api/gpu/metrics") + if mr.status_code == 200: + result["metrics_ok"] = True + gpus = mr.json().get("current", {}).get("gpus", []) + result["gpu_count"] = len(gpus) + else: + result["errors"].append(f"metrics HTTP {mr.status_code}") + except Exception as exc: + result["errors"].append(f"metrics: {exc}") + + try: + model_r = await client.get(f"{urls['gpu_url']}/api/active-model") + if model_r.status_code == 200: + md = model_r.json() + result["inference_active"] = bool(md.get("inference_active")) + result["active_model"] = md.get("name") + except Exception as exc: + result["errors"].append(f"active-model: {exc}") + + try: + lr = await client.get(f"{urls['llm_url']}/models") + if lr.status_code == 200: + result["llm_ok"] = True + else: + result["errors"].append(f"llm HTTP {lr.status_code}") + except Exception as exc: + result["errors"].append(f"llm: {exc}") + + result["ok"] = result["metrics_ok"] and ( + result["gpu_count"] > 0 or result["inference_active"] or result["llm_ok"] + ) + return result diff --git a/api/lab_context.py b/api/lab_context.py index ead9f5e..0cb4980 100644 --- a/api/lab_context.py +++ b/api/lab_context.py @@ -17,6 +17,14 @@ from database_inventory import collect_database_inventory from node_registry import NODE_REGISTRY DOCKHAND_URL = os.getenv("DOCKHAND_URL", "http://10.0.21.45:8082") +DOCKHAND_API_TOKEN = os.getenv("DOCKHAND_API_TOKEN", "") + + +def _dockhand_headers() -> dict[str, str]: + if DOCKHAND_API_TOKEN: + return {"Authorization": f"Bearer {DOCKHAND_API_TOKEN}"} + return {} + HDFS_NN_URL = os.getenv("HDFS_NN_URL", "http://10.0.21.61:9870") LAKEHOUSE_HOST = os.getenv("LAKEHOUSE_HOST", "10.0.21.50") AIRFLOW_URL = os.getenv("AIRFLOW_URL", "http://10.0.21.55:8080") @@ -24,7 +32,12 @@ KAFKA_UI_URL = os.getenv("KAFKA_UI_URL", "http://10.0.21.36:9000") KAFKA_CONNECT_URL = os.getenv("KAFKA_CONNECT_URL", f"http://{LAKEHOUSE_HOST}:8083") TRINO_URL = os.getenv("TRINO_URL", f"http://{LAKEHOUSE_HOST}:8089") SPARK_UI_URL = os.getenv("SPARK_UI_URL", f"http://{LAKEHOUSE_HOST}:8080") -GPU_URL = os.getenv("GPU_URL", "http://10.0.20.106:9000") +try: + from gpu_config import get_gpu_urls as _get_gpu_urls +except Exception: + _get_gpu_urls = None # type: ignore + +GPU_URL = os.getenv("GPU_URL", "http://10.0.10.106:9000") OBJECTSCALE_URL = os.getenv("OBJECTSCALE_URL", "http://10.0.20.111:9020") YARN_URL = os.getenv("YARN_URL", "http://10.0.21.62:8088") @@ -110,7 +123,7 @@ async def dockhand_containers( await _log(log, "cmd", "fetch", f"$ GET {url}") t0 = time.monotonic() try: - r = await client.get(f"{DOCKHAND_URL}/api/containers", params={"env": env_id}, timeout=8.0) + r = await client.get(f"{DOCKHAND_URL}/api/containers", params={"env": env_id}, headers=_dockhand_headers(), timeout=8.0) ms = int((time.monotonic() - t0) * 1000) r.raise_for_status() data = r.json() @@ -407,11 +420,20 @@ async def collect_objectscale(client: httpx.AsyncClient, log: TerminalLogFn | No async def collect_gpu_metrics(client: httpx.AsyncClient, log: TerminalLogFn | None = None) -> dict[str, Any]: - await _log(log, "info", "fetch", "▸ GPU Lab metrics") - base = {"ok": False, "host": GPU_URL, "ui_url": GPU_URL} + gpu_url = GPU_URL + host = GPU_URL + if _get_gpu_urls is not None: + try: + u = _get_gpu_urls() + gpu_url = u["gpu_url"] + host = u["host"] + except Exception: + pass + await _log(log, "info", "fetch", f"▸ GPU Lab metrics @ {host}") + base = {"ok": False, "host": host, "ui_url": gpu_url} try: - metrics_url = f"{GPU_URL}/api/gpu/metrics" - model_url = f"{GPU_URL}/api/active-model" + metrics_url = f"{gpu_url}/api/gpu/metrics" + model_url = f"{gpu_url}/api/active-model" await _log(log, "cmd", "fetch", f"$ GET {metrics_url}") await _log(log, "cmd", "fetch", f"$ GET {model_url}") t0 = time.monotonic() diff --git a/api/main.py b/api/main.py index bdab09b..0c91a15 100644 --- a/api/main.py +++ b/api/main.py @@ -15,6 +15,7 @@ import httpx import redis.asyncio as aioredis from fastapi import Body, FastAPI, File, UploadFile, WebSocket, WebSocketDisconnect from fastapi.middleware.cors import CORSMiddleware +import auth as cockpit_auth from agent_terminal import ( get_all_terminals, get_terminal_lines, @@ -77,6 +78,14 @@ from db import SessionLocal, db_health, init_database from supervisor import mirror_terminal_line, mirror_to_supervisors from workload import build_workload_payload +from gpu_config import ( + get_gpu_config, + get_gpu_config_payload, + get_gpu_urls, + reset_gpu_config, + save_gpu_config, + test_gpu_target, +) _workload_cache: dict[str, Any] = {"ts": 0.0, "data": None} _presentation_cache: dict[str, Any] = {"ts": 0.0, "data": None} @@ -89,12 +98,130 @@ from sqlalchemy.orm import DeclarativeBase REDIS_URL = os.getenv("REDIS_URL", "redis://redis:6379/0") DOCKHAND_URL = os.getenv("DOCKHAND_URL", "http://10.0.21.45:8082") -GPU_URL = os.getenv("GPU_URL", "http://10.0.20.106:9000") +DOCKHAND_API_TOKEN = os.getenv("DOCKHAND_API_TOKEN", "") + + +def _dockhand_headers() -> dict[str, str]: + if DOCKHAND_API_TOKEN: + return {"Authorization": f"Bearer {DOCKHAND_API_TOKEN}"} + return {} + +GPU_URL = os.getenv("GPU_URL", "http://10.0.10.106:9000") GPU_UI_URL = os.getenv("GPU_UI_URL", GPU_URL) -LLM_URL = os.getenv("LLM_URL", "http://10.0.20.106:8001/v1") +LLM_URL = os.getenv("LLM_URL", "http://10.0.10.106:8001/v1") LLM_MODEL = os.getenv("LLM_MODEL", "gpt-4o") LLM_API_KEY = os.getenv("LLM_API_KEY", "sk-local") LLM_TIMEOUT = float(os.getenv("LLM_TIMEOUT", "120")) +# Llama-3-70B GPTQ on V100 is capped at 4096; keep a hard safety budget. +LLM_MAX_MODEL_LEN = int(os.getenv("LLM_MAX_MODEL_LEN", "4096")) +# Conservative estimate: Llama tokenizers often use ~2.2–2.8 chars/token on English+lab text. +LLM_CHARS_PER_TOKEN = float(os.getenv("LLM_CHARS_PER_TOKEN", "2.4")) +LLM_CONTEXT_MARGIN = int(os.getenv("LLM_CONTEXT_MARGIN", "160")) +LLM_MAX_OUTPUT = int(os.getenv("LLM_MAX_OUTPUT", "256")) +LLM_MAX_CONTEXT_CHARS = int(os.getenv("LLM_MAX_CONTEXT_CHARS", "5500")) + + +def _estimate_tokens(text: str) -> int: + # Slightly inflate so we never underestimate vs vLLM's tokenizer. + return max(1, int(len(text) / LLM_CHARS_PER_TOKEN) + 32) + + +def _compact_lab_context(context: str) -> str: + """Keep primary section + short per-domain summaries; drop verbose inventory lines.""" + lines = context.splitlines() + out: list[str] = [] + in_full = False + detail = 0 + max_detail = 4 + for line in lines: + if line.startswith("=== FULL LAB"): + in_full = True + out.append(line) + continue + if line.startswith("=== PRIMARY"): + in_full = False + detail = 0 + out.append(line) + continue + if line.startswith("--- "): + detail = 0 + out.append(line) + continue + # Drop long platform-capabilities essays if present — keep a one-liner marker + if line.startswith("=== PLATFORM CAPABILITIES"): + out.append(line) + out.append(" (see Command Center UI for full feature list)") + continue + if out and out[-1].startswith(" (see Command Center"): + if line.startswith("===") or line.startswith("--- ") or line.startswith("=== AGENTS") or line.startswith("=== DATA MASKING") or line.startswith("=== PII MASKING"): + pass + else: + continue + # Always keep masking / PII evidence sections in full (demo-critical) + if line.startswith("=== DATA MASKING") or line.startswith("=== PII MASKING"): + # flush remaining lines of this section without detail limits by marking + out.append(line) + continue + # Limit bullet detail in general lab dump, but keep masking evidence intact + keep_full = any(s in "\n".join(out[-5:]) for s in ("=== DATA MASKING", "=== PII MASKING")) + if (line.startswith(" - ") or line.startswith(" - ")) and not keep_full: + detail += 1 + if detail > max_detail: + if detail == max_detail + 1: + out.append(" …") + continue + out.append(line) + return "\n".join(out) + + +def _truncate_for_llm(context: str, max_chars: int) -> str: + context = _compact_lab_context(context) + if len(context) <= max_chars: + return context + # Prefer keeping PRIMARY section; cut FULL LAB first + primary_end = context.find("=== FULL LAB") + if primary_end > 200: + head = context[:primary_end].rstrip() + tail_budget = max(400, max_chars - len(head) - 80) + tail = context[primary_end: primary_end + tail_budget] + trimmed = head + "\n" + tail + else: + trimmed = context[:max_chars] + if len(trimmed) > max_chars: + trimmed = trimmed[: max_chars - 60].rsplit("\n", 1)[0] + if len(context) > len(trimmed): + trimmed += f"\n\n[… truncated for {LLM_MAX_MODEL_LEN}-token model window …]" + return trimmed + + +def _fit_llm_payload(system_rules: str, context: str, user_message: str) -> tuple[str, int]: + """Fit prompt+completion into the served model length with a safety margin.""" + user_tok = _estimate_tokens(user_message) + rules_tok = _estimate_tokens(system_rules) + budget = LLM_MAX_MODEL_LEN - LLM_CONTEXT_MARGIN + max_out = min(LLM_MAX_OUTPUT, 256) + + # Absolute char cap first (independent of estimate errors) + context = _truncate_for_llm(context, LLM_MAX_CONTEXT_CHARS) + + for _ in range(6): + ctx_budget_tok = budget - user_tok - rules_tok - max_out + if ctx_budget_tok < 200: + max_out = max(64, max_out // 2) + continue + ctx_max_chars = max(600, int(ctx_budget_tok * LLM_CHARS_PER_TOKEN * 0.85)) + fitted = _truncate_for_llm(context, ctx_max_chars) + total = rules_tok + _estimate_tokens(fitted) + user_tok + max_out + if total <= budget: + return fitted, max_out + # Still too big — shrink context harder, then output + context = fitted + LLM_MAX = max(800, int(len(fitted) * 0.7)) + context = _truncate_for_llm(context, LLM_MAX) + max_out = max(64, max_out - 32) + + return _truncate_for_llm(context, 800), 64 + AGENTS = [ { @@ -247,7 +374,11 @@ ZONES = [ ] INTENT_KEYWORDS: dict[str, list[str]] = { - "data-custodian": ["database", "postgres", "postgresql", "mysql", "mongo", "mongodb", "cassandra", "neo4j", "sql", "db "], + "data-custodian": [ + "database", "postgres", "postgresql", "mysql", "mongo", "mongodb", "cassandra", "neo4j", "sql", "db ", + "pii", "mask", "masked", "masking", "email", "e-mail", "phone", "iban", "address", "customer", + "employee", "gdpr", "privacy", "sensitive", "personal", "name", "ssn", "national_id", + ], "lakehouse-ops": ["trino", "spark", "lakehouse", "iceberg", "query", "table"], "hadoop-ranger": [ "hadoop", "hdfs", "yarn", "datanode", "namenode", "replicatie", "replication", @@ -327,10 +458,24 @@ class ApprovalDecision(BaseModel): def route_agent(message: str) -> str: lower = message.lower() + # PII / privacy questions always go to Data Custodian (masking demo path) + pii_words = ( + "pii", "mask", "masked", "masking", "email", "e-mail", "mail adres", "mail address", + "phone", "telefoon", "iban", "address", "adres", "customer name", "employee", + "gdpr", "privacy", "sensitive", "personal", "national_id", "ssn", "gevoelig", + ) + if any(w in lower for w in pii_words): + return "data-custodian" # Storage/data questions default to Hadoop unless clearly about databases - if any(w in lower for w in ("data", "opslag", "gb", "replicatie", "replication", "hdfs", "hadoop")): - if not any(w in lower for w in ("postgres", "mysql", "mongo", "database", "sql", "neo4j", "cassandra")): + if any(w in lower for w in ("opslag", "gb", "replicatie", "replication", "hdfs", "hadoop", "datanode", "namenode")): + if not any(w in lower for w in ("postgres", "mysql", "mongo", "database", "sql", "neo4j", "cassandra", "pii", "email")): return "hadoop-ranger" + if any(w in lower for w in ("gpu", "vllm", "llm", "nvidia", "inference", "vram", "model")): + return "infra-sentinel" + if any(w in lower for w in ("kafka", "airflow", "debezium", "connector", "etl", "pipeline", "dag")): + return "etl-guardian" + if any(w in lower for w in ("trino", "spark", "iceberg", "lakehouse")): + return "lakehouse-ops" scores = {aid: sum(1 for kw in kws if kw in lower) for aid, kws in INTENT_KEYWORDS.items()} best = max(scores, key=scores.get) if scores[best] == 0: @@ -338,13 +483,34 @@ def route_agent(message: str) -> str: return best + +def _is_pii_question(message: str) -> bool: + lower = message.lower() + return any(w in lower for w in ( + "pii", "mask", "masked", "masking", "unmask", "visible", "email", "e-mail", "phone", + "iban", "address", "adres", "customer", "employee", "privacy", "gdpr", "sensitive", + "personal", "gevoelig", "name", "telefoon", "mail", "data flow", "national_id", + "ssn", "bsn", "geboorte", "birth", + )) + + +async def _pii_evidence_block(message: str, log: Any | None = None) -> str: + """Live policy + samples synced with Data Flow masking toggles.""" + try: + from pii_catalog import build_policy_evidence + return build_policy_evidence() + except Exception as exc: + return f"=== PII MASKING EVIDENCE ===\n(unavailable: {exc})" + + async def gather_agent_context( agent_id: str, status: dict[str, Any], log: Any | None = None, + message: str | None = None, ) -> str: """Full lab snapshot for vLLM — all domains, agent's primary domain highlighted.""" - snapshot = await collect_full_lab_context(gpu_data=status.get("gpu"), log=log) + snapshot = await collect_full_lab_context(gpu_data=status.get("gpu"), log=log, include_inventory=False) snapshot["domains_summary"] = status.get("domains", {}) ctx = format_context_for_agent(agent_id, snapshot) agent_lines = ["", "=== AGENTS & SUPERVISORS ==="] @@ -353,10 +519,24 @@ async def gather_agent_context( agent_lines.append(f" - {a['name']} ({a['id']}){sup}: {a['role']}") ctx = ctx + "\n".join(agent_lines) try: - from platform_context import build_llm_addendum - ctx = ctx + "\n\n" + build_llm_addendum() + from platform_context import build_masking_section + # Fresh policy so chat mirrors Data Flow toggles (skip huge business catalog). + ctx = ctx + "\n\n" + build_masking_section(fresh=True) except Exception: - pass + try: + from platform_context import build_llm_addendum + ctx = ctx + "\n\n" + build_llm_addendum() + except Exception: + pass + if message and _is_pii_question(message): + try: + evidence = await _pii_evidence_block(message, log=log) + ctx = ctx + "\n\n" + evidence + if log: + await log("ok", "fetch", "▸ PII masking evidence attached (synced with Data Flow)") + except Exception as exc: + if log: + await log("warn", "fetch", f"▸ PII evidence skipped: {exc}") if log: await log("info", "fetch", f"▸ Context assembled: {len(ctx)} chars for LLM") return ctx @@ -369,34 +549,44 @@ async def ask_llm( log: Any | None = None, ) -> str | None: agent = next(a for a in AGENTS if a["id"] == agent_id) - system = f"""You are {agent['name']}, an autonomous ops agent in the Dell ATC data lab. -Specialization: {agent['role']}. -Motto: {agent.get('motto', '')}. + # Deterministic PII path: always mirror Data Flow masked vs visible toggles. + if _is_pii_question(message): + try: + from pii_catalog import format_pii_chat_answer + answer = format_pii_chat_answer(message) + if log: + await log("ok", "pii", "▸ Returning Data Flow–synced masking answer (masked + visible)") + return answer + except Exception as exc: + if log: + await log("warn", "pii", f"▸ PII answer builder failed: {exc}") + rules = f"""You are {agent['name']} ({agent['role']}) in the Dell ATC data lab. +Answer in English, briefly (max ~8 sentences). Use ONLY the live data below — never invent hosts/ports/numbers. +If data is missing or DOWN, say so. -You respond on behalf of your domain but have visibility into the FULL lab stack: Docker, databases, lakehouse (Trino/Spark/Kafka Connect), ETL (Airflow/Kafka), Hadoop HDFS, and GPU/vLLM. +PII / masking rules (critical — synced with Data Flow tab): +- MASKED columns: NEVER reveal raw values; quote the token 🔒 MASKED when present. +- VISIBLE columns (operator opted out in Data Flow): you MAY report the real sample values and say they are visible by policy. +- Never invent emails, phones, names, IBANs, or addresses that are not in the live samples. +- If asked what is masked vs visible, list columns from the DATA MASKING POLICY / PII EVIDENCE sections. -Rules: -- Always respond in English. -- You have full visibility into the entire cluster: all VMs, zones, connectors, GPU, Hadoop, ObjectScale and Command Center. -- Use ONLY the live data below — do not invent hosts, ports, numbers or connector names. -- Use exact container/connector names from the data (e.g. mysql-hr-connector, not "Debezium"). -- If something is DOWN or 0 GB, say so honestly. -- Respect the data masking policy: NEVER reveal, guess or reconstruct raw values of MASKED columns (they arrive as the token 🔒 MASKED). You MUST still answer helpfully — confirm the column is masked for privacy/governance, explain why, and you may use non-sensitive aggregates/counts over it. -- You are fully aware of all latest platform changes via the section PLATFORM CAPABILITIES & RECENT CHANGES below; use it to answer questions about recent changes, the Spark Workbench, the Hadoop pipeline, the Data Flow pulse switch and the autonomous agents (DML, ETL, Custodian Hadoop offload). -- Be concise and helpful (max ~10 sentences); bullet lists are fine when they aid clarity. - ---- LIVE LAB DATA (primary domain first, then full stack) --- -{context} -""" +--- LIVE LAB DATA ---""" + fitted_ctx, max_tokens = _fit_llm_payload(rules, context, message) + system = rules + "\n" + fitted_ctx + urls = get_gpu_urls() + llm_url = urls["llm_url"] if log: - await log("info", "llm", f"▸ Querying vLLM model={LLM_MODEL}") - await log("cmd", "llm", f"$ POST {LLM_URL.rstrip('/')}/chat/completions") + est = _estimate_tokens(system) + _estimate_tokens(message) + await log("info", "llm", f"▸ Querying vLLM model={LLM_MODEL} @ {urls['host']} (~{est}+{max_tokens} tok)") + if len(context) > len(fitted_ctx): + await log("warn", "llm", f" context trimmed {len(context)} → {len(fitted_ctx)} chars") + await log("cmd", "llm", f"$ POST {llm_url.rstrip('/')}/chat/completions") await log("info", "llm", f" user: {message[:160]}{'…' if len(message) > 160 else ''}") try: async with httpx.AsyncClient(timeout=LLM_TIMEOUT) as client: t0 = time.monotonic() r = await client.post( - f"{LLM_URL.rstrip('/')}/chat/completions", + f"{llm_url.rstrip('/')}/chat/completions", headers={ "Authorization": f"Bearer {LLM_API_KEY}", "Content-Type": "application/json", @@ -407,7 +597,7 @@ Rules: {"role": "system", "content": system}, {"role": "user", "content": message}, ], - "max_tokens": 800, + "max_tokens": max_tokens, "temperature": 0.25, }, ) @@ -422,15 +612,78 @@ Rules: return content if log: await log("warn", "llm", f"← Empty or invalid LLM output ({ms}ms)") + except httpx.HTTPStatusError as exc: + detail = exc.response.text[:200] if exc.response is not None else str(exc) + if log: + await log("err", "llm", f"✗ vLLM HTTP {exc.response.status_code}: {detail}") + # One hard retry with a minimal context if we blew the window. + if exc.response is not None and exc.response.status_code == 400 and "maximum context length" in detail: + tiny = _truncate_for_llm(context, 1200) + system2 = rules + "\n" + tiny + max2 = 128 + if log: + await log("warn", "llm", f" retry with tiny context ({len(tiny)} chars, max_tokens={max2})") + try: + async with httpx.AsyncClient(timeout=LLM_TIMEOUT) as client: + r2 = await client.post( + f"{llm_url.rstrip('/')}/chat/completions", + headers={ + "Authorization": f"Bearer {LLM_API_KEY}", + "Content-Type": "application/json", + }, + json={ + "model": LLM_MODEL, + "messages": [ + {"role": "system", "content": system2}, + {"role": "user", "content": message}, + ], + "max_tokens": max2, + "temperature": 0.25, + }, + ) + r2.raise_for_status() + content2 = r2.json()["choices"][0]["message"]["content"].strip() + if content2: + if log: + await log("ok", "llm", f"← vLLM retry OK {len(content2)} chars") + return content2 + except Exception as exc2: + if log: + await log("err", "llm", f"✗ vLLM retry failed: {exc2}") except Exception as exc: if log: await log("err", "llm", f"✗ vLLM error: {exc}") return None -def fallback_answer(agent_id: str, context: str) -> str: +def fallback_answer(agent_id: str, context: str, user_message: str = "") -> str: agent_name = next(a["name"] for a in AGENTS if a["id"] == agent_id) - return f"**{agent_name}** (offline LLM — ruwe data):\n\n{context}" + if user_message and _is_pii_question(user_message): + try: + from pii_catalog import format_pii_chat_answer + return f"**{agent_name}**\n\n" + format_pii_chat_answer(user_message) + except Exception: + marker = "=== PII MASKING EVIDENCE" + if marker in context: + return ( + f"**{agent_name}** — masking policy (synced with Data Flow):\n\n" + + context[context.index(marker):].strip() + ) + preview_lines: list[str] = [] + for line in context.splitlines(): + if line.startswith(("=== PRIMARY", "Health summary", "ATC Lab", "--- ")): + preview_lines.append(line) + if len(preview_lines) >= 14: + break + hint = "\n".join(preview_lines) if preview_lines else "Lab snapshot collected; LLM unavailable." + q = f"\n\nYour question: _{user_message[:200]}_" if user_message else "" + return ( + f"**{agent_name}** — I could not get a reply from the GPU LLM " + f"(context window or vLLM error).{q}\n\n" + "Try a short, specific question " + "(e.g. *How many GPUs are online?* or *Is Kafka healthy?*).\n\n" + f"Quick snapshot:\n{hint}" + ) async def publish_event(event: dict[str, Any]) -> None: @@ -480,7 +733,11 @@ def add_feed(agent_id: str, message: str, level: str = "info") -> dict: async def dockhand_env_containers(env_id: int) -> list[dict]: try: async with httpx.AsyncClient(timeout=8.0) as client: - r = await client.get(f"{DOCKHAND_URL}/api/containers", params={"env": env_id}) + r = await client.get( + f"{DOCKHAND_URL}/api/containers", + params={"env": env_id}, + headers=_dockhand_headers(), + ) r.raise_for_status() return r.json() except Exception: @@ -497,15 +754,26 @@ async def probe_url(url: str) -> bool: async def collect_gpu() -> dict[str, Any]: - host = GPU_URL.replace("http://", "").replace("https://", "").split("/")[0] - base = {"ok": False, "host": host, "ui_url": GPU_UI_URL} + urls = get_gpu_urls() + cfg = get_gpu_config() + gpu_url = urls["gpu_url"] + host = urls["host"] + base = { + "ok": False, + "host": host, + "ip": host, + "ui_url": urls["gpu_ui_url"], + "config_source": cfg.get("source", "env"), + "preset_id": cfg.get("preset_id"), + "config_label": cfg.get("label"), + } try: async with httpx.AsyncClient(timeout=6.0) as client: metrics_r, model_r, integration_r = await asyncio.gather( - client.get(f"{GPU_URL}/api/gpu/metrics"), - client.get(f"{GPU_URL}/api/active-model"), - client.get(f"{GPU_URL}/api/integration"), + client.get(f"{gpu_url}/api/gpu/metrics"), + client.get(f"{gpu_url}/api/active-model"), + client.get(f"{gpu_url}/api/integration"), return_exceptions=True, ) @@ -667,12 +935,12 @@ async def run_agent_task(agent_id: str, message: str, prompt_id: str) -> str: await log("info", "fetch", f"[{prompt_id}] Collecting live lab metrics…") status = await collect_status() - context = await gather_agent_context(agent_id, status, log=log) + context = await gather_agent_context(agent_id, status, log=log, message=message) answer = await ask_llm(agent_id, message, context, log=log) if not answer: await log("warn", "llm", "LLM fallback — returning raw context") - answer = fallback_answer(agent_id, context) + answer = fallback_answer(agent_id, context, message) if not approval_created: proposed = detect_agent_proposed_action(answer, message) @@ -784,6 +1052,10 @@ app.add_middleware( allow_headers=["*"], ) +# Authentik OIDC session + API guard +cockpit_auth.init_auth_middleware(app) +cockpit_auth.setup_auth(app) + @app.get("/api/health") async def health(): @@ -983,6 +1255,41 @@ async def get_status(): async def get_gpu(): return await collect_gpu() +@app.get("/api/gpu/config") +async def get_gpu_config_endpoint(): + return get_gpu_config_payload() + + +@app.post("/api/gpu/config") +async def post_gpu_config(body: dict[str, Any]): + try: + saved = save_gpu_config( + preset_id=body.get("preset_id"), + host=body.get("host"), + gpu_ui_port=body.get("gpu_ui_port"), + llm_port=body.get("llm_port"), + ) + return {"ok": True, "active": saved, "presets": get_gpu_config_payload()["presets"]} + except ValueError as exc: + return JSONResponse({"ok": False, "detail": str(exc)}, status_code=400) + + +@app.post("/api/gpu/config/test") +async def post_gpu_config_test(body: dict[str, Any]): + return await test_gpu_target( + preset_id=body.get("preset_id"), + host=body.get("host"), + gpu_ui_port=body.get("gpu_ui_port"), + llm_port=body.get("llm_port"), + ) + + +@app.delete("/api/gpu/config") +async def delete_gpu_config(): + active = reset_gpu_config() + return {"ok": True, "active": active} + + def agent_stats() -> dict[str, dict[str, Any]]: stats: dict[str, dict[str, Any]] = {a["id"]: {"tasks": 0, "last_active": None, "alerts": 0} for a in AGENTS} @@ -1053,11 +1360,11 @@ async def run_node_ask_task(node_id: str, message: str) -> None: await terminal_log(node_id, f"→ Routing to agent {agent_id}", level="info", phase="ask") log = make_logger(node_id) status = await collect_status() - context = await gather_agent_context(agent_id, status, log=log) + context = await gather_agent_context(agent_id, status, log=log, message=message) node_ctx = f"\n\n=== FOCUSED NODE: {meta['label']} ({meta['ip']}) ===\n{meta.get('description', '')}\n" answer = await ask_llm(agent_id, message, context + node_ctx, log=log) if not answer: - answer = fallback_answer(agent_id, context) + answer = fallback_answer(agent_id, context, message) await terminal_log(node_id, f"◆ {answer}", level="llm", phase="answer") await publish_event({"type": "node_ask_result", "node_id": node_id, "agent_id": agent_id, "answer": answer}) diff --git a/api/node_ops.py b/api/node_ops.py index 264cfbd..cd8ec28 100644 --- a/api/node_ops.py +++ b/api/node_ops.py @@ -153,6 +153,25 @@ def build_node_detail(node_id: str, snap: dict[str, Any], workload_node: dict | wn = workload_node or {} agent_id = NODE_AGENT.get(node_id, "infra-sentinel") + if node_id == "gpu": + try: + from gpu_config import resolve_gpu_identity + gid = resolve_gpu_identity(snap.get("gpu") if isinstance(snap, dict) else None) + meta["ip"] = gid["ip"] + meta["vm"] = gid["vm"] + meta["vmid"] = gid["vmid"] + meta["ssh"] = f"ssh root@{gid['ip']}" + meta["links"] = [ + {"label": "GPU Lab UI", "url": gid["ui_url"]}, + {"label": "vLLM API", "url": gid["llm_url"]}, + ] + meta["endpoints"] = [ + {"name": "gpu-lab", "host": gid["ip"], "port": "9000", "proto": "http"}, + {"name": "vllm", "host": gid["ip"], "port": "8001", "proto": "http"}, + ] + except Exception: + pass + detail: dict[str, Any] = { "id": node_id, "agent_id": agent_id, diff --git a/api/node_registry.py b/api/node_registry.py index 0f057f2..b5a6901 100644 --- a/api/node_registry.py +++ b/api/node_registry.py @@ -183,21 +183,21 @@ NODE_REGISTRY: dict[str, dict[str, Any]] = { }, "gpu": { "label": "GPU Lab", - "vm": "atc-gpu-dev", - "vmid": 303, + "vm": "atc-gpu-prod", + "vmid": 306, "pve": "atc-gpu", - "ip": "10.0.20.106", - "ssh": "ssh root@10.0.20.106", + "ip": "10.0.10.106", + "ssh": "ssh root@10.0.10.106", "role": "inference", "color": "#3fb950", - "description": "4× V100 GPU lab. vLLM serves the active model (Llama 3 70B GPTQ) — powers agent reasoning in this Command Center.", + "description": "4× V100 GPU lab (VM306). vLLM serves the active model (Llama 3 70B GPTQ) — powers agent reasoning in this Command Center.", "links": [ - {"label": "GPU Lab UI", "url": "http://10.0.20.106:9000"}, - {"label": "vLLM API", "url": "http://10.0.20.106:8001/v1"}, + {"label": "GPU Lab UI", "url": "http://10.0.10.106:9000"}, + {"label": "vLLM API", "url": "http://10.0.10.106:8001/v1"}, ], "endpoints": [ - {"name": "gpu-lab", "host": "10.0.20.106", "port": "9000", "proto": "http"}, - {"name": "vllm", "host": "10.0.20.106", "port": "8001", "proto": "http"}, + {"name": "gpu-lab", "host": "10.0.10.106", "port": "9000", "proto": "http"}, + {"name": "vllm", "host": "10.0.10.106", "port": "8001", "proto": "http"}, ], "commands": ["gpu metrics", "model status", "vram usage"], }, diff --git a/api/pii_catalog.py b/api/pii_catalog.py index d5a149e..11277a0 100644 --- a/api/pii_catalog.py +++ b/api/pii_catalog.py @@ -34,6 +34,7 @@ POLICY_PATH = Path(os.getenv("MASKING_POLICY_PATH", "/data/masking_policy.json") DEFAULT_MASKED = True MASK_TOKEN = "🔒 MASKED (masking policy ON)" _policy_cache: dict[str, bool] | None = None +_policy_mtime: float = -1.0 # Datasets we surface in the PII overlay. node_id matches dataflow.py node ids. # om_fqn = OpenMetadata table FQN (service.database.schema.table) for tag lookup. @@ -77,21 +78,42 @@ DATASET_BY_KEY = {ds["key"]: ds for ds in DATASETS} def _load_policy() -> dict[str, bool]: - global _policy_cache - if _policy_cache is None: + """Load policy from disk; re-read when the file mtime changes (Data Flow toggles).""" + global _policy_cache, _policy_mtime + try: + mtime = POLICY_PATH.stat().st_mtime + except Exception: + mtime = 0.0 + if _policy_cache is None or mtime != _policy_mtime: try: _policy_cache = {k: bool(v) for k, v in json.loads(POLICY_PATH.read_text()).items()} except Exception: - _policy_cache = {} + if _policy_cache is None: + _policy_cache = {} + _policy_mtime = mtime return _policy_cache def _save_policy(p: dict[str, bool]) -> None: - global _policy_cache + global _policy_cache, _policy_mtime _policy_cache = p try: POLICY_PATH.parent.mkdir(parents=True, exist_ok=True) POLICY_PATH.write_text(json.dumps(p, indent=2)) + _policy_mtime = POLICY_PATH.stat().st_mtime + except Exception: + _policy_mtime = time.time() + + +def invalidate_pii_caches() -> None: + """Force catalog rebuild so chat/Data Flow see the same mask flags immediately.""" + _cache["data"] = None + _cache["ts"] = 0.0 + try: + import trino_federated as tf + if hasattr(tf, "_dict_cache"): + tf._dict_cache["data"] = None + tf._dict_cache["at"] = 0.0 except Exception: pass @@ -325,10 +347,235 @@ async def set_policy(body: MaskPolicyRequest) -> JSONResponse: for col in cols: p[f"{key}.{col}"] = bool(body.masked) _save_policy(p) - _cache["data"] = None # force rebuild so masked flags reflect the new policy + invalidate_pii_caches() # chat + Data Flow must reflect the toggle immediately return JSONResponse({"ok": True, "key": key, "columns": cols, "masked": bool(body.masked)}) +def policy_column_lists(*, use_cache: bool = False) -> dict[str, Any]: + """Live masked vs visible PII columns — same source as the Data Flow tab.""" + catalog = get_pii(use_cache=use_cache) + masked: list[dict[str, str]] = [] + visible: list[dict[str, str]] = [] + for d in catalog.get("datasets", []): + key = d.get("key") or "" + label = d.get("label") or key + locked = bool(d.get("masked_layer") or d.get("policy_locked")) + for c in d.get("pii_columns", []): + entry = { + "key": key, + "label": label, + "column": c.get("name") or "", + "category": c.get("category") or "PII", + "locked": locked, + } + (masked if c.get("masked") else visible).append(entry) + summ = catalog.get("summary") or {} + return { + "catalog": catalog, + "masked": masked, + "visible": visible, + "summary": summ, + "mask_token": MASK_TOKEN, + } + + +def _interest_categories(message: str) -> list[str]: + lower = (message or "").lower() + cat_map = [ + (("email", "e-mail", "mail"), "EMAIL"), + (("phone", "telefoon", "mobile"), "PHONE"), + (("name", "naam"), "NAME"), + (("iban", "bank", "card"), "FINANCIAL"), + (("ssn", "bsn", "national", "passport"), "NATIONAL_ID"), + (("address", "adres"), "ADDRESS"), + (("birth", "dob", "geboorte"), "DOB"), + (("ip",), "IP"), + ] + out: list[str] = [] + for words, cat in cat_map: + if any(w in lower for w in words): + out.append(cat) + return out + + +def _sample_rows_for_chat( + *, + categories: list[str] | None = None, + max_datasets: int = 2, + rows_per: int = 2, +) -> list[dict[str, Any]]: + """Fetch a few live rows; values already policy-masked.""" + catalog = get_pii(use_cache=False) + prefer = ["mysql", "postgres", "mongodb", "cassandra", "neo4j", "curated"] + samples: list[dict[str, Any]] = [] + for key in prefer: + dset = next((d for d in catalog.get("datasets", []) if d.get("key") == key), None) + if not dset or not dset.get("pii_columns"): + continue + ds = DATASET_BY_KEY.get(key) + if not ds: + continue + pii_cols = dset["pii_columns"] + if categories: + focus = [c for c in pii_cols if c.get("category") in categories] + # Always keep one id-like visible column for context when focusing + ids = [c for c in pii_cols if c.get("category") == "IDENTIFIER" and not c.get("masked")] + pick = (ids[:1] + focus) if focus else pii_cols + else: + pick = pii_cols + if not pick: + continue + # de-dupe preserving order + seen: set[str] = set() + select_cols: list[str] = [] + masked_map: dict[str, bool] = {} + for c in pick: + name = c["name"] + if name in seen: + continue + seen.add(name) + select_cols.append(name) + masked_map[name] = bool(c.get("masked")) + if len(select_cols) >= 6: + break + name_col = next((c["name"] for c in pii_cols if c.get("category") == "NAME"), None) + try: + cols, rows = _lookup_rows(ds, select_cols, name_col, None, rows_per) + except Exception: + continue + if not rows: + continue + rendered = [] + for row in rows[:rows_per]: + rendered.append({ + cname: (MASK_TOKEN if masked_map.get(cname) else val) + for cname, val in zip(cols, row) + }) + samples.append({ + "key": key, + "label": dset.get("label", key), + "table": ds.get("table"), + "rows": rendered, + "masked_cols": [c for c, m in masked_map.items() if m], + "visible_cols": [c for c, m in masked_map.items() if not m], + }) + if len(samples) >= max_datasets: + break + return samples + + +def build_policy_evidence(*, max_datasets: int = 2, rows_per: int = 2) -> str: + """Compact internal evidence for LLM context (not shown raw to users).""" + snap = policy_column_lists(use_cache=False) + masked = snap["masked"] + visible = snap["visible"] + summ = snap["summary"] + lines = [ + "=== PII POLICY (Data Flow synced) ===", + f"Masked {summ.get('masked_columns', len(masked))}/{summ.get('pii_columns', 0)} · " + f"visible {summ.get('unmasked_columns', len(visible))}. Token: {MASK_TOKEN}", + "Masked: " + ", ".join(f"{m['key']}.{m['column']}" for m in masked[:25]) + ( + f" …(+{len(masked)-25})" if len(masked) > 25 else "" + ), + "Visible: " + (", ".join(f"{v['key']}.{v['column']}" for v in visible[:25]) or "(none)"), + ] + for s in _sample_rows_for_chat(max_datasets=max_datasets, rows_per=rows_per): + lines.append(f"Sample {s['label']}:") + for row in s["rows"]: + lines.append(" " + " | ".join(f"{k}={v}" for k, v in row.items())) + return "\n".join(lines) + + +def format_pii_chat_answer(message: str = "") -> str: + """Short personal reply: masked → say masked; visible → show values. Never list field names.""" + snap = policy_column_lists(use_cache=False) + masked = snap["masked"] + visible = snap["visible"] + lower = (message or "").lower() + interest = _interest_categories(message) + greeting = any(w in lower for w in ("hi", "hello", "hey", "hallo", "goedemorgen", "goedemiddag")) + hi = "Hi! " if greeting else "" + + label = { + "EMAIL": "email", + "PHONE": "phone number", + "NAME": "name", + "FINANCIAL": "bank / IBAN details", + "NATIONAL_ID": "national ID", + "ADDRESS": "address", + "DOB": "date of birth", + "IP": "IP address", + } + + # No specific PII type asked — keep it vague, never enumerate columns + if not interest: + if any(w in lower for w in ("mask", "pii", "sensitive", "privacy", "personal")): + return ( + f"{hi}Personal data is protected by the masking policy. " + f"Ask for something specific (an email, a phone number, a name…) and I'll tell you " + f"whether I can share it — or only `{MASK_TOKEN}`." + ) + return ( + f"{hi}I can't share personal data that's masked. " + f"Ask me for an email, phone number, or name if you want to check." + ) + + topic = ", ".join(label.get(c, c.lower()) for c in interest) + interested_masked = [c for c in masked if c["category"] in interest] + interested_visible = [c for c in visible if c["category"] in interest] + + # Collect visible sample *values* only (no column names in the reply) + values: list[str] = [] + if interested_visible: + samples = _sample_rows_for_chat(categories=interest, max_datasets=2, rows_per=2) + for s in samples: + for row in s["rows"]: + for col in interested_visible: + if col["column"] in row: + val = row[col["column"]] + if val is None or val == "" or val == MASK_TOKEN: + continue + values.append(str(val)) + # unique, preserve order + seen: set[str] = set() + uniq: list[str] = [] + for v in values: + if v not in seen: + seen.add(v) + uniq.append(v) + values = uniq[:5] + + # Fully masked for this ask + if interested_masked and not interested_visible: + return ( + f"{hi}No — that {topic} is masked (`{MASK_TOKEN}`). " + "I can't share it." + ) + + # Fully visible + if interested_visible and not interested_masked: + if values: + listed = ", ".join(values) + return f"{hi}Sure — here's what I can share: {listed}." + return f"{hi}That {topic} isn't masked, but I don't have a sample value right now." + + # Mixed: some sources masked, some visible — still don't name columns + if interested_visible and interested_masked: + if values: + listed = ", ".join(values) + return ( + f"{hi}Some of that is masked (`{MASK_TOKEN}`); " + f"what I can share: {listed}." + ) + return ( + f"{hi}Some of that {topic} is masked (`{MASK_TOKEN}`). " + "I can't share the protected parts." + ) + + return f"{hi}I don't have that personal data available." + + + def _lookup_rows(ds: dict[str, Any], select: list[str], name_col: str | None, search: str | None, limit: int) -> tuple[list[str], list[list[Any]]]: """Fetch rows from the source. Native DB queries (fast, early LIMIT) for diff --git a/api/platform_context.py b/api/platform_context.py index e34ae4f..3b9b651 100644 --- a/api/platform_context.py +++ b/api/platform_context.py @@ -90,15 +90,15 @@ def build_platform_section() -> str: return "\n".join(lines) -def build_masking_section() -> str: +def build_masking_section(fresh: bool = False) -> str: """Exact masking policy + strict guidance so the LLM can answer about masked - data without ever revealing masked raw values.""" - lines: list[str] = ["=== DATA MASKING POLICY (enforced) ==="] + data without ever revealing masked raw values. Synced with Data Flow toggles.""" + lines: list[str] = ["=== DATA MASKING POLICY (enforced — synced with Data Flow) ==="] masked: list[str] = [] unmasked: list[str] = [] try: from pii_catalog import get_pii # type: ignore - data = get_pii() + data = get_pii(use_cache=not fresh) for d in data.get("datasets", []): for c in d.get("pii_columns", []): tag = f"{d.get('label')}.{c.get('name')} [{c.get('category')}]" @@ -112,22 +112,27 @@ def build_masking_section() -> str: lines.append(f"(masking catalog unavailable: {exc})") if masked: - lines.append("MASKED columns (raw values are withheld — token 🔒 MASKED):") + lines.append("MASKED columns (raw values withheld — token 🔒 MASKED):") for m in masked[:40]: lines.append(f" - {m}") + else: + lines.append("MASKED columns: (none)") if unmasked: - lines.append("Visible PII columns (operator opted out of masking):") + lines.append("VISIBLE columns (operator opted out of masking in Data Flow — real values OK):") for u in unmasked[:40]: lines.append(f" - {u}") + else: + lines.append("VISIBLE columns: (none — all PII masked)") lines += [ "", - "How to handle masked data when answering:", - " 1. NEVER reveal, guess, reconstruct or print the raw value of a MASKED column. If a value comes in as '🔒 MASKED', keep it masked.", - " 2. DO still answer helpfully: confirm the column exists and is masked for privacy/governance, and explain why (PII protection policy).", - " 3. You MAY use and report non-sensitive aggregates, counts, distributions and derived metrics over masked columns (e.g. 'there are N distinct customers') as long as no individual raw value is exposed.", - " 4. Tell the operator they can unmask a specific column from the Data Flow PII overlay if they have the authority, and that the curated/masked Iceberg layer is physically masked and cannot be unmasked.", - " 5. Unmasked PII columns may be shown, but flag that they are sensitive.", + "How to handle masked vs visible data when answering:", + " 1. MASKED: NEVER reveal, guess, or reconstruct raw values. Quote '🔒 MASKED' when present.", + " 2. VISIBLE: you MAY show the real sample values and state that the operator made them visible in Data Flow.", + " 3. DO still answer helpfully: confirm which columns are masked vs visible from the lists above.", + " 4. You MAY use non-sensitive aggregates/counts over masked columns without exposing individuals.", + " 5. Curated/masked Iceberg layers are physically masked and cannot be unmasked from the UI.", + " 6. Never invent PII that is not in the live samples.", ] return "\n".join(lines) diff --git a/api/presentation.py b/api/presentation.py index 6b73627..e08ea84 100644 --- a/api/presentation.py +++ b/api/presentation.py @@ -276,6 +276,17 @@ def build_presentation_payload(snap: dict[str, Any]) -> dict[str, Any]: )) gpus = gpu.get("gpus") or snap.get("gpu", {}).get("gpus") or [] + try: + from gpu_config import resolve_gpu_identity + gpu_id = resolve_gpu_identity(snap.get("gpu") or gpu) + except Exception: + host = (snap.get("gpu") or gpu).get("host") or "10.0.10.106" + gpu_id = { + "vm": "atc-gpu-prod", + "vmid": 306, + "ui_url": f"http://{host}:9000", + "llm_url": f"http://{host}:8001/v1", + } gpu_lines = [ f"GPU{g['index']}: {g.get('util_gpu', 0):.0f}% util, " f"{g.get('memory_used_mib', 0):.0f}/{g.get('memory_total_mib', 0):.0f} MiB" @@ -284,11 +295,11 @@ def build_presentation_payload(snap: dict[str, Any]) -> dict[str, Any]: slides.append(_slide( "gpu", "GPU Lab & GenAI", - f"{gpu.get('model') or 'vLLM'} on atc-gpu-dev (VM 303)", + f"{gpu.get('model') or 'vLLM'} on {gpu_id['vm']} (VM {gpu_id['vmid']})", [ f"Inference: {'ON' if gpu.get('inference_active') else 'OFF'}", - f"API: {snap.get('gpu', {}).get('vllm_url') or 'http://10.0.20.106:8001/v1'}", - "GPU Lab UI: http://10.0.20.106:9000", + f"API: {gpu_id['llm_url']}", + f"GPU Lab UI: {gpu_id['ui_url']}", "Kibana/Elastic: http://10.0.21.46:5601", *gpu_lines, ], diff --git a/api/presentation_static.py b/api/presentation_static.py index edc9630..fbeac0e 100644 --- a/api/presentation_static.py +++ b/api/presentation_static.py @@ -151,7 +151,7 @@ MODERN_DECKS: dict[str, dict[str, Any]] = { "bullets": [ "Supervisor + field operators on Command Center", "Each agent sees live workload, GPU, databases, topology", - "LLM: Llama 3 70B GPTQ via vLLM (10.0.20.106:8001)", + "LLM: Llama 3 70B GPTQ via vLLM (10.0.10.106:8001)", "Approval workflow for sensitive operations", ], }, @@ -161,7 +161,7 @@ MODERN_DECKS: dict[str, dict[str, Any]] = { "subtitle": "Dell ATC cluster — key IPs", "bullets": [ "Command Center VM304: 10.0.21.33 (this dashboard)", - "GPU Lab VM303: 10.0.20.106 — 7× V100, vLLM, model manager", + "GPU Lab VM306: 10.0.10.106 — 4× V100, vLLM, model manager", "DB Vault: 10.0.21.51 · Lakehouse: 10.0.21.50 · Elastic: 10.0.21.46", "Docling UI: http://10.0.21.33:5001/ui/", ], diff --git a/api/requirements.txt b/api/requirements.txt index 545379e..21f2db5 100644 --- a/api/requirements.txt +++ b/api/requirements.txt @@ -17,3 +17,5 @@ boto3==1.35.99 paramiko==3.5.0 aiokafka==0.12.0 pyarrow==18.1.0 +authlib==1.4.1 +itsdangerous==2.2.0 diff --git a/api/topology_views.py b/api/topology_views.py index 7c015ba..468057b 100644 --- a/api/topology_views.py +++ b/api/topology_views.py @@ -537,13 +537,24 @@ def _build_architecture( 1, 1, "📓", ) gpu_ok = bool(gpu.get("ok")) + try: + from gpu_config import resolve_gpu_identity + gpu_id = resolve_gpu_identity(gpu) + except Exception: + host = gpu.get("ip") or gpu.get("host") or "10.0.10.106" + gpu_id = {"vm": "atc-gpu-prod", "ip": host} ml = _arch_node( "cons-ml", "ML / GenAI", "vLLM cluster", C_CON, 70, "#bc8cff", "consumers", - "ok" if gpu_ok else "warn", "atc-gpu-dev", "10.0.20.106", + "ok" if gpu_ok else "warn", gpu_id["vm"], gpu_id["ip"], [gpu.get("active_model") or "offline"], - [{"name": gpu.get("active_model") or "vllm", "state": "running" if gpu.get("inference_active") else "down", "image": "vllm", "ports": ["8001"]}], + [{"name": gpu.get("active_model") or "vllm", "state": "running" if gpu.get("inference_active") else "down", "image": "vllm", "ports": ["8001", "9000"]}], gpu.get("gpu_count", 0) or 0, max(gpu.get("gpu_count", 4) or 4, 1), "🤖", - {"model": gpu.get("active_model"), "util": round(sum(g.get("util_gpu", 0) for g in gpu.get("gpus", [])) / max(len(gpu.get("gpus", [])), 1), 1)}, + {"model": gpu.get("active_model"), "util": round(sum(g.get("util_gpu", 0) for g in gpu.get("gpus", [])) / max(len(gpu.get("gpus", [])), 1), 1), + "ui_url": gpu_id.get("ui_url"), "vllm_url": gpu_id.get("llm_url"), + "links": [ + {"label": "GPU Lab UI", "url": gpu_id.get("ui_url") or f"http://{gpu_id['ip']}:9000"}, + {"label": "vLLM API", "url": gpu_id.get("llm_url") or f"http://{gpu_id['ip']}:8001/v1"}, + ]}, ) nodes = [ diff --git a/api/workload.py b/api/workload.py index 6ae2329..56a4d5d 100644 --- a/api/workload.py +++ b/api/workload.py @@ -63,6 +63,18 @@ def build_workload_payload(snap: dict[str, Any]) -> dict[str, Any]: gpu = snap.get("gpu", {}) objectscale = snap.get("objectscale", {}) command = snap.get("command_center", {}) + try: + from gpu_config import resolve_gpu_identity + gpu_id = resolve_gpu_identity(gpu) + except Exception: + host = gpu.get("ip") or gpu.get("host") or "10.0.10.106" + gpu_id = { + "vm": "atc-gpu-prod", + "ip": host, + "ui_url": gpu.get("ui_url") or f"http://{host}:9000", + "llm_url": gpu.get("vllm_url") or f"http://{host}:8001/v1", + "vmid": 306, + } docker_apps = [_app_row(c) for c in docker.get("containers", [])] db_apps = [_app_row(c) for c in databases.get("containers", [])] @@ -221,6 +233,18 @@ def build_workload_payload(snap: dict[str, Any]) -> dict[str, Any]: } if extra: row.update(extra) + if nid == "gpu": + row["vm"] = gpu_id["vm"] + row["ip"] = gpu_id["ip"] + row["vmid"] = gpu_id.get("vmid", row.get("vmid")) + row["links"] = [ + {"label": "GPU Lab UI", "url": gpu_id["ui_url"]}, + {"label": "vLLM API", "url": gpu_id["llm_url"]}, + ] + row["endpoints"] = [ + {"name": "gpu-lab", "host": gpu_id["ip"], "port": "9000", "proto": "http"}, + {"name": "vllm", "host": gpu_id["ip"], "port": "8001", "proto": "http"}, + ] return row connect_running = 1 if connect_app and connect_app.get("state") == "running" else 0 @@ -247,10 +271,11 @@ def build_workload_payload(snap: dict[str, Any]) -> dict[str, Any]: _node("hadoop", "Hadoop HDFS", "atc-hadoop-m01", "10.0.21.61", 50, 52, "#39ff14", "ok" if hdfs_ok else "warn", "parallel", zones[-1]["apps"], hadoop.get("live_datanodes", 0), zones[-1]["total"], {"hdfs_used_gb": hadoop.get("capacity_used_gb"), "hdfs_total_gb": hadoop.get("capacity_total_gb")}), - _node("gpu", "GPU Lab", "atc-gpu-dev", "10.0.20.106", 88, 52, "#76b900", "ok" if gpu.get("ok") else "down", "inference", - [{"name": gpu.get("active_model") or "vLLM", "state": "running" if gpu.get("inference_active") else "down", "image": "vllm", "ports": ["8001"]}], + _node("gpu", "GPU Lab", gpu_id["vm"], gpu_id["ip"], 88, 52, "#76b900", "ok" if gpu.get("ok") else "down", "inference", + [{"name": gpu.get("active_model") or "vLLM", "state": "running" if gpu.get("inference_active") else "down", "image": "vllm", "ports": ["8001", "9000"]}], gpu.get("gpu_count", 0), gpu.get("gpu_count", 0) or 4, - {"model": gpu.get("active_model"), "util": round(sum(g.get("util_gpu", 0) for g in gpu.get("gpus", [])) / max(len(gpu.get("gpus", [])), 1), 1)}), + {"model": gpu.get("active_model"), "util": round(sum(g.get("util_gpu", 0) for g in gpu.get("gpus", [])) / max(len(gpu.get("gpus", [])), 1), 1), + "ui_url": gpu_id["ui_url"], "vllm_url": gpu_id["llm_url"]}), _node("command", "Command Center", "MCP · VM304", "10.0.21.33", 50, 78, "#00f0ff", _level(command.get("running", 0), command.get("total", 1) or 1), "hub", command.get("containers") and [_app_row(c) for c in command.get("containers", [])] or [ diff --git a/caddy/Caddyfile b/caddy/Caddyfile index 519744f..5f356db 100644 --- a/caddy/Caddyfile +++ b/caddy/Caddyfile @@ -8,6 +8,9 @@ handle_path /dq/* { reverse_proxy dq-api:5010 } + handle /auth/* { + reverse_proxy api:3201 + } handle /api/* { reverse_proxy api:3201 } diff --git a/config/command-center/atc.env.example b/config/command-center/atc.env.example index 2b16e59..7396bd7 100644 --- a/config/command-center/atc.env.example +++ b/config/command-center/atc.env.example @@ -8,8 +8,8 @@ S3_REGION=us-east-1 JUPYTER_TOKEN=choose-a-strong-token -GPU_URL=http://10.0.20.106:9000 -LLM_URL=http://10.0.20.106:8001/v1 +GPU_URL=http://10.0.10.106:9000 +LLM_URL=http://10.0.10.106:8001/v1 LLM_MODEL=gpt-4o LLM_API_KEY=sk-local diff --git a/config/command-center/docker-compose.yml b/config/command-center/docker-compose.yml index e1cc2f7..66cbafc 100644 --- a/config/command-center/docker-compose.yml +++ b/config/command-center/docker-compose.yml @@ -32,9 +32,9 @@ services: SQLITE_FALLBACK_PATH: /data/atc-agents.db DOCLING_URL: http://docling-serve:5001 PRESENTATIONS_DIR: /data/presentations - GPU_URL: http://10.0.20.106:9000 - GPU_UI_URL: http://10.0.20.106:9000 - LLM_URL: http://10.0.20.106:8001/v1 + GPU_URL: http://10.0.10.106:9000 + GPU_UI_URL: http://10.0.10.106:9000 + LLM_URL: http://10.0.10.106:8001/v1 LLM_MODEL: gpt-4o LLM_API_KEY: sk-local LAKEHOUSE_HOST: 10.0.21.50 @@ -87,7 +87,7 @@ services: CHROMA_HOST: chromadb CHROMA_PORT: 8000 DOCLING_URL: http://docling-serve:5001 - LLM_URL: http://10.0.20.106:8001/v1 + LLM_URL: http://10.0.10.106:8001/v1 LLM_MODEL: gpt-4o LLM_API_KEY: sk-local RAG_DATA_DIR: /data diff --git a/docker-compose.dockhand.yml b/docker-compose.dockhand.yml index cb4e669..61120bd 100644 --- a/docker-compose.dockhand.yml +++ b/docker-compose.dockhand.yml @@ -30,9 +30,9 @@ services: DOCKHAND_URL: http://10.0.21.45:8082 DATABASE_URL: postgresql+psycopg2://atc:atc-agents-pg@postgres:5432/atc_agents SQLITE_FALLBACK_PATH: /data/atc-agents.db - GPU_URL: http://10.0.20.106:9000 - GPU_UI_URL: http://10.0.20.106:9000 - LLM_URL: http://10.0.20.106:8001/v1 + GPU_URL: http://10.0.10.106:9000 + GPU_UI_URL: http://10.0.10.106:9000 + LLM_URL: http://10.0.10.106:8001/v1 LLM_MODEL: qwen2.5-32b-gptq LLM_API_KEY: sk-local LAKEHOUSE_HOST: 10.0.21.50 diff --git a/docker-compose.yml b/docker-compose.yml index 3dc7022..b121c89 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -32,9 +32,9 @@ services: SQLITE_FALLBACK_PATH: /data/atc-agents.db DOCLING_URL: http://docling-serve:5001 PRESENTATIONS_DIR: /data/presentations - GPU_URL: http://10.0.20.106:9000 - GPU_UI_URL: http://10.0.20.106:9000 - LLM_URL: http://10.0.20.106:8001/v1 + GPU_URL: http://10.0.10.106:9000 + GPU_UI_URL: http://10.0.10.106:9000 + LLM_URL: http://10.0.10.106:8001/v1 LLM_MODEL: gpt-4o LLM_API_KEY: sk-local LAKEHOUSE_HOST: 10.0.21.50 @@ -44,10 +44,6 @@ services: OPENMETADATA_URL: ${OPENMETADATA_URL:-http://10.0.21.47:8585} KAFKA_UI_URL: http://10.0.21.36:9000 HDFS_NN_URL: http://10.0.21.61:9870 - S3_ENDPOINT: ${S3_ENDPOINT:-http://10.0.20.111:9020} - S3_ACCESS_KEY: ${S3_ACCESS_KEY:-object_admin1} - S3_SECRET_KEY: ${S3_SECRET_KEY} - S3_REGION: ${S3_REGION:-us-east-1} ELASTICSEARCH_URL: ${ELASTICSEARCH_URL:-https://10.0.21.46:9200} KIBANA_URL: ${KIBANA_URL:-http://10.0.21.46:5601} ELASTIC_USER: ${ELASTIC_USER:-elastic} @@ -94,7 +90,7 @@ services: CHROMA_HOST: chromadb CHROMA_PORT: 8000 DOCLING_URL: http://docling-serve:5001 - LLM_URL: http://10.0.20.106:8001/v1 + LLM_URL: http://10.0.10.106:8001/v1 LLM_MODEL: gpt-4o LLM_API_KEY: sk-local RAG_DATA_DIR: /data @@ -124,10 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useCommandCenter } from './hooks/useCommandCenter' @@ -27,6 +29,7 @@ import { resolveInfraNode } from './lib/infraCatalog' import { cn } from './lib/utils' export default function App() { + const auth = useAuth() const clock = useClock() const cc = useCommandCenter() const [gpuChatActive, setGpuChatActive] = useState(false) @@ -53,6 +56,19 @@ export default function App() { return 'Lab' })() + if (auth.status === 'loading') { + return ( +
+ Checking session… +
+ ) + } + if (auth.status === 'anon') { + return + } + + const userLabel = auth.user?.name || auth.user?.preferred_username || auth.user?.email || 'Signed in' + return (
{ window.location.href = '/auth/logout' }} />
diff --git a/ui/src/components/features/GpuMatrixPanel.tsx b/ui/src/components/features/GpuMatrixPanel.tsx index d64b334..eb058be 100644 --- a/ui/src/components/features/GpuMatrixPanel.tsx +++ b/ui/src/components/features/GpuMatrixPanel.tsx @@ -1,7 +1,7 @@ import { useEffect, useMemo, useState } from 'react' -import { Activity, ChevronDown, ChevronUp, Cpu, ExternalLink, Zap } from 'lucide-react' -import { fetchGpu } from '../../lib/api' -import type { GpuDevice, GpuStatus } from '../../types' +import { Activity, ChevronDown, ChevronUp, Cpu, ExternalLink, Settings2, Zap } from 'lucide-react' +import { fetchGpu, fetchGpuConfig, resetGpuConfig, saveGpuConfig, testGpuConfig } from '../../lib/api' +import type { GpuConfigPayload, GpuConfigTestResult, GpuDevice, GpuStatus } from '../../types' import type { GpuLiveMetrics } from '../../hooks/useLiveMetrics' import { cn } from '../../lib/utils' @@ -53,6 +53,13 @@ export function GpuMatrixPanel({ gpu, live, boost = false, onSelectGpu }: Props) const [localGpu, setLocalGpu] = useState(gpu) const [lastPoll, setLastPoll] = useState(null) const [expanded, setExpanded] = useState(false) + const [showSettings, setShowSettings] = useState(false) + const [gpuConfig, setGpuConfig] = useState(null) + const [selectedPreset, setSelectedPreset] = useState('gpu-prod') + const [customHost, setCustomHost] = useState('') + const [configBusy, setConfigBusy] = useState(false) + const [testResult, setTestResult] = useState(null) + const [configMsg, setConfigMsg] = useState(null) useEffect(() => { setLocalGpu(gpu) @@ -62,6 +69,19 @@ export function GpuMatrixPanel({ gpu, live, boost = false, onSelectGpu }: Props) if (boost) setExpanded(true) }, [boost]) + useEffect(() => { + if (!showSettings) return + fetchGpuConfig().then((cfg) => { + if (!cfg) return + setGpuConfig(cfg) + const active = cfg.active + setSelectedPreset(active.preset_id === 'env' ? 'gpu-prod' : active.preset_id) + if (active.preset_id === 'custom' || active.source === 'override') { + setCustomHost(active.host) + } + }) + }, [showSettings]) + useEffect(() => { const poll = async () => { const g = await fetchGpu() @@ -76,6 +96,49 @@ export function GpuMatrixPanel({ gpu, live, boost = false, onSelectGpu }: Props) return () => clearInterval(iv) }, [boost]) + const handleTestTarget = async () => { + setConfigBusy(true) + setTestResult(null) + setConfigMsg(null) + const body = + selectedPreset === 'custom' + ? { preset_id: 'custom', host: customHost.trim() } + : { preset_id: selectedPreset } + const result = await testGpuConfig(body) + setTestResult(result) + setConfigBusy(false) + } + + const handleSaveTarget = async () => { + setConfigBusy(true) + setConfigMsg(null) + const body = + selectedPreset === 'custom' + ? { preset_id: 'custom', host: customHost.trim() } + : { preset_id: selectedPreset } + const res = await saveGpuConfig(body) + setConfigBusy(false) + if (res?.active) { + setConfigMsg(`Saved → ${res.active.label}`) + const g = await fetchGpu() + if (g) setLocalGpu(g) + } else { + setConfigMsg(res?.detail || 'Save failed') + } + } + + const handleResetTarget = async () => { + setConfigBusy(true) + await resetGpuConfig() + setSelectedPreset('gpu-prod') + setCustomHost('') + setTestResult(null) + setConfigMsg('Reset to environment default') + const g = await fetchGpu() + if (g) setLocalGpu(g) + setConfigBusy(false) + } + const g = localGpu const devices = g?.gpus || [] const inferenceOn = g?.ok && g.inference_active @@ -102,7 +165,31 @@ export function GpuMatrixPanel({ gpu, live, boost = false, onSelectGpu }: Props)

GPU Matrix

-

GPU Lab offline

+

+ GPU Lab offline{g?.host ? ` · ${g.ip || g.host}` : ''} +

+ + {showSettings && gpuConfig && ( + + )} ) } @@ -130,6 +217,17 @@ export function GpuMatrixPanel({ gpu, live, boost = false, onSelectGpu }: Props) )} )} ) } + +type GpuTargetSettingsProps = { + gpuConfig: GpuConfigPayload + selectedPreset: string + customHost: string + configBusy: boolean + testResult: GpuConfigTestResult | null + configMsg: string | null + onPresetChange: (id: string) => void + onCustomHostChange: (host: string) => void + onTest: () => void + onSave: () => void + onReset: () => void +} + +function GpuTargetSettings({ + gpuConfig, + selectedPreset, + customHost, + configBusy, + testResult, + configMsg, + onPresetChange, + onCustomHostChange, + onTest, + onSave, + onReset, +}: GpuTargetSettingsProps) { + return ( +
+

GPU Target

+ + {selectedPreset === 'custom' && ( + onCustomHostChange(e.target.value)} + placeholder="10.0.x.x" + className="w-full rounded border border-border bg-surface px-1.5 py-1 font-mono text-[9px] text-foreground" + /> + )} +
+ + + +
+ {testResult && ( +

+ {testResult.ok + ? `OK · ${testResult.gpu_count} GPU(s) · ${testResult.active_model || 'no model'}` + : `Failed · ${testResult.errors.join('; ') || 'unreachable'}`} +

+ )} + {configMsg &&

{configMsg}

} +

+ Active: {gpuConfig.active.label} ({gpuConfig.active.host}) +

+
+ ) +} diff --git a/ui/src/components/features/LoginView.tsx b/ui/src/components/features/LoginView.tsx new file mode 100644 index 0000000..4551dc2 --- /dev/null +++ b/ui/src/components/features/LoginView.tsx @@ -0,0 +1,47 @@ +import { Box, LogIn } from 'lucide-react' +import { useMemo } from 'react' + +export function LoginView() { + const error = useMemo(() => { + try { + const p = new URLSearchParams(window.location.search) + const err = p.get('error') + if (!err) return null + if (err === 'login_failed') return 'Sign-in failed — try again.' + return err + } catch { + return null + } + }, []) + + return ( + + ) +} diff --git a/ui/src/components/layout/TopBar.tsx b/ui/src/components/layout/TopBar.tsx index 99f7cb7..0337434 100644 --- a/ui/src/components/layout/TopBar.tsx +++ b/ui/src/components/layout/TopBar.tsx @@ -1,4 +1,4 @@ -import { Activity, Bot, Box, Clock, ShieldAlert } from 'lucide-react' +import { Activity, Bot, Box, Clock, LogOut, ShieldAlert } from 'lucide-react' import type { Agent, Approval, StatusData, WorkloadData } from '../../types' import { Badge } from '../ui/Badge' import { ThemeToggle } from './ThemeToggle' @@ -11,9 +11,11 @@ type Props = { agents: Agent[] approvals: Approval[] onApprovalsClick: () => void + userLabel?: string + onLogout?: () => void } -export function TopBar({ clock, workload, agents, approvals, onApprovalsClick }: Props) { +export function TopBar({ clock, workload, agents, approvals, onApprovalsClick, userLabel, onLogout }: Props) { const pipelineOk = workload?.totals?.pipeline_active ?? false const running = workload?.totals?.apps_running ?? 0 const total = workload?.totals?.apps_total ?? 0 @@ -53,6 +55,22 @@ export function TopBar({ clock, workload, agents, approvals, onApprovalsClick }:
+ {userLabel ? ( + + {userLabel} + + ) : null} + {onLogout ? ( + + ) : null}
diff --git a/ui/src/hooks/useAuth.ts b/ui/src/hooks/useAuth.ts new file mode 100644 index 0000000..95eb83f --- /dev/null +++ b/ui/src/hooks/useAuth.ts @@ -0,0 +1,42 @@ +import { useCallback, useEffect, useState } from 'react' + +export type AuthUser = { + user?: string + email?: string + name?: string + preferred_username?: string + auth_enabled?: boolean +} + +type AuthState = + | { status: 'loading'; user: null } + | { status: 'anon'; user: null } + | { status: 'authed'; user: AuthUser } + +export function useAuth(): AuthState & { refresh: () => Promise } { + const [state, setState] = useState({ status: 'loading', user: null }) + + const refresh = useCallback(async () => { + try { + const r = await fetch('/api/auth/me', { credentials: 'same-origin' }) + if (r.status === 401) { + setState({ status: 'anon', user: null }) + return + } + if (!r.ok) { + setState({ status: 'anon', user: null }) + return + } + const me = (await r.json()) as AuthUser + setState({ status: 'authed', user: me }) + } catch { + setState({ status: 'anon', user: null }) + } + }, []) + + useEffect(() => { + void refresh() + }, [refresh]) + + return { ...state, refresh } +} diff --git a/ui/src/lib/api.ts b/ui/src/lib/api.ts index 4d684c6..b92a2a7 100644 --- a/ui/src/lib/api.ts +++ b/ui/src/lib/api.ts @@ -6,6 +6,8 @@ import type { CdcStats, DataflowGraph, FeedEntry, + GpuConfigPayload, + GpuConfigTestResult, GpuStatus, Movement, PiiDataset, @@ -21,7 +23,7 @@ async function fetchJson(url: string, timeoutMs = 10000): Promise { const ctrl = new AbortController() const timer = setTimeout(() => ctrl.abort(), timeoutMs) try { - const r = await fetch(url, { signal: ctrl.signal }) + const r = await fetch(url, { signal: ctrl.signal, credentials: 'same-origin' }) if (!r.ok) return null return (await r.json()) as T } catch { @@ -62,6 +64,54 @@ export async function fetchGpu(): Promise { return fetchJson('/api/gpu', 8000) } +export async function fetchGpuConfig(): Promise { + return fetchJson('/api/gpu/config', 8000) +} + +export async function saveGpuConfig(body: { + preset_id?: string + host?: string + gpu_ui_port?: number + llm_port?: number +}) { + const r = await fetch('/api/gpu/config', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify(body), + }) + return r.json() +} + +export async function testGpuConfig(body: { + preset_id?: string + host?: string + gpu_ui_port?: number + llm_port?: number +}): Promise { + const ctrl = new AbortController() + const timer = setTimeout(() => ctrl.abort(), 12000) + try { + const r = await fetch('/api/gpu/config/test', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify(body), + signal: ctrl.signal, + }) + if (!r.ok) return null + return (await r.json()) as GpuConfigTestResult + } catch { + return null + } finally { + clearTimeout(timer) + } +} + +export async function resetGpuConfig() { + const r = await fetch('/api/gpu/config', { method: 'DELETE' , credentials: 'same-origin' }) + return r.json() +} + + export async function fetchTerminals(): Promise> { const j = await fetchJson<{ terminals?: Record }>('/api/terminals', 8000) return j?.terminals || {} @@ -77,7 +127,7 @@ export async function fetchNodeDetail(nodeId: string) { } export function probeNode(nodeId: string) { - return fetch(`/api/nodes/${nodeId}/probe`, { method: 'POST' }) + return fetch(`/api/nodes/${nodeId}/probe`, { method: 'POST' , credentials: 'same-origin' }) } export function askNode(nodeId: string, message: string) { @@ -207,19 +257,19 @@ export function triggerStreamingJob(jobId: string, conf?: Record