litellm/tests/e2e/e2e_config.py
mubashir1osmani fdf380d0e3
test(e2e): harden stage flakes for batches, UI, and MCP (#33831)
* test(e2e): harden stage flakes for batches, UI, and MCP

Unique batch model names avoid load-balancing onto stale azure-batch
deployments that still pointed at the retired gpt-4.1-mini-batch, which
only the managed/unified path was hitting. Retry batch retrieve on 500
and /ui/api-keys navigation on ERR_ABORTED. Skip the MCP key-access suite
when the compose-only mcp-upstream is unreachable on stage k8s

* test(e2e): cover Datadog remote MCP via search_datadog_logs

Register the regional Datadog MCP endpoint with DD-API-KEY /
DD-APPLICATION-KEY static headers (CI-safe header auth; browser OAuth is
not headless-automatable). Seed a chat completion marked e2e-datadog-mcp-*,
assert the proxy shipped it, list tools, call search_datadog_logs for the
marker, and delete the server on teardown. Math-upstream key-access tests
only skip when that compose service is unreachable

* test(e2e): drop compose math MCP upstream; use Datadog only

Key-access denial and happy-path MCP e2e both register the real regional
Datadog remote MCP server with DD-API-KEY / DD-APPLICATION-KEY headers.
Remove the mcp-upstream compose service and FastMCP add/multiply fixture

* docs(e2e): require real Datadog MCP for all mcp suite tests

Document that tests/e2e/mcp must register via datadog_mcp helpers against
mcp.<site>/v1/mcp and must not introduce compose or fake MCP upstreams

* chore: restore mcp_e2e_upstream_server.py

Keep the FastMCP fixture file; e2e no longer wires it in compose, but the
module itself is not part of the Datadog-only cleanup

* fix(e2e): load tests/e2e/.env and fix datadog_reader importlib load

pytest on the host never inherited compose env_file keys, so DD_API_KEY
stayed empty. load_dotenv tests/e2e/.env in e2e_config. Register the
dynamically loaded datadog_reader module in sys.modules so dataclasses
do not crash under Python 3.12

* test(e2e/batches): harden azure/vertex unified lifecycle flakes

Put the provider deployment name in every JSONL body so Azure does not
depend on a perfect model rewrite. Retry create/retrieve/cancel on
transient statuses with backoff. Drop cancel assertions for azure and
vertex (registry only has a shared basic cell; create+retrieve prove
routing, cancel stays best-effort cleanup)

* test(e2e/ui): treat api-keys shell as success after SPA ERR_ABORTED

Post-login client redirects abort the first /ui/api-keys/ goto on stage.
Wait off /ui/login after cookie set, then accept the page once Create New
Key is visible even if goto raised ERR_ABORTED

* test(e2e): drop flaky key models dropdown Playwright suite

API management e2e already covers key generate/update persistence. The
UI Models-dropdown sentinel cases only added SPA ERR_ABORTED noise and
no unique product signal. Remove the suite and unused browser fixtures
2026-07-18 19:11:54 +00:00

102 lines
5.1 KiB
Python

"""Generic configuration for live e2e tests against a running LiteLLM proxy.
Shared by every e2e suite under tests/e2e/. Values come from the
environment so the same tests run against localhost or a deployed proxy.
"""
from __future__ import annotations
import os
import uuid
from pathlib import Path
from dotenv import load_dotenv
# Local runs keep provider / DataDog keys in tests/e2e/.env (see CONTRIBUTING.md).
# Compose injects them into the proxy container, but pytest on the host does not
# inherit that file unless we load it. override=False so a real shell export wins.
load_dotenv(Path(__file__).resolve().parent / ".env", override=False)
PROXY_BASE_URL = os.environ.get("LITELLM_PROXY_URL", "http://localhost:4000").rstrip("/")
MASTER_KEY = os.environ.get("LITELLM_MASTER_KEY", "sk-1234")
# Control-plane (management/admin) base URL. Defaults to PROXY_BASE_URL so a
# single path-routing host (stage ALB, compose monolith) works for both planes.
# Set LITELLM_CONTROL_PLANE_URL only when management is a different base than
# the LLM host and you are not going through an ingress that path-routes.
CONTROL_PLANE_BASE_URL = os.environ.get(
"LITELLM_CONTROL_PLANE_URL", PROXY_BASE_URL
).rstrip("/")
UI_USERNAME = os.environ.get("E2E_UI_USERNAME", "admin")
UI_PASSWORD = os.environ.get("E2E_UI_PASSWORD", MASTER_KEY)
# Dashboard base for playwright. Defaults to PROXY_BASE_URL so one ALB/monolith
# host covers /ui as well. Override E2E_UI_BASE_URL only if the UI is elsewhere.
UI_BASE_URL = os.environ.get("E2E_UI_BASE_URL", PROXY_BASE_URL).rstrip("/")
CHEAP_ANTHROPIC_MODEL = os.environ.get("E2E_CHEAP_ANTHROPIC_MODEL", "claude-haiku-4-5")
CHEAP_OPENAI_MODEL = os.environ.get("E2E_CHEAP_OPENAI_MODEL", "gpt-5.5")
# Jaeger query API of the compose stack's OTEL trace destination (the `jaeger`
# service in docker-compose.yml maps it to host 16686). Trace-completeness tests
# read exported spans back through it.
OTEL_QUERY_URL = os.environ.get("E2E_OTEL_QUERY_URL", "http://localhost:16686").rstrip("/")
# Real-DataDog read-back (no local sink - destination fakes cannot be deployed
# on the cluster): the proxy delivers with DD_API_KEY as in production, and the
# tests read ingested events back through the DataDog Logs Search API, which
# additionally needs an application key. On the cluster the secret manager
# injects both; locally tests/e2e/.env provides them.
DD_SITE = os.environ.get("DD_SITE", "datadoghq.com").strip()
DD_API_KEY = os.environ.get("DD_API_KEY", "").strip()
DD_APP_KEY = os.environ.get("DD_APP_KEY", "").strip()
# After the first event is searchable, keep watching this long for a late
# duplicate before the exactly-one assertion: real-DataDog ingestion jitter can
# make one call's two events searchable tens of seconds apart, and a duplicate
# that surfaces late IS the bug (LIT-4447), so one poll interval is not enough.
DD_SETTLE_SECONDS = float(os.environ.get("E2E_DD_SETTLE_SECONDS", "30"))
# DataDog Logs Search `from` window (relative to now). Wide enough for a suite
# run plus ingestion lag; override if a long CI queue needs a wider lookback.
DD_SEARCH_FROM = os.environ.get("E2E_DD_SEARCH_FROM", "now-30m").strip() or "now-30m"
# The Logs Search API budget is tight - 2 requests per 10s org-wide
# (x-ratelimit-name logs_public_search_api) - so read-backs pace their search
# calls at this interval instead of POLL_INTERVAL, and back off when a 429
# still slips through (the budget is shared with anything else searching).
DD_SEARCH_INTERVAL = float(os.environ.get("E2E_DD_SEARCH_INTERVAL", "10"))
# Writes on the proxy are eventually consistent (e.g. spend rows flush on
# proxy_batch_write_at, ~60s). Read-backs poll to this deadline, never sleep-once.
POLL_TIMEOUT = float(os.environ.get("E2E_POLL_TIMEOUT", "120"))
POLL_INTERVAL = float(os.environ.get("E2E_POLL_INTERVAL", "5"))
REQUEST_TIMEOUT = float(os.environ.get("E2E_REQUEST_TIMEOUT", "60"))
LOAD_USERS = int(os.environ.get("E2E_LOAD_USERS", "750"))
LOAD_SPAWN_RATE = float(os.environ.get("E2E_LOAD_SPAWN_RATE", "50"))
LOAD_DURATION_SECONDS = float(os.environ.get("E2E_LOAD_DURATION_SECONDS", "60"))
LOAD_MIN_RPS = float(os.environ.get("E2E_LOAD_MIN_RPS", "355"))
LOAD_MAX_FAILURE_RATIO = float(os.environ.get("E2E_LOAD_MAX_FAILURE_RATIO", "0.01"))
def datadog_mcp_url(*, toolsets: str = "core") -> str:
"""Regional Datadog remote MCP endpoint for this process's DD_SITE.
US1 is mcp.datadoghq.com; every other site is mcp.<site> (e.g. us5 ->
mcp.us5.datadoghq.com). A fixed mcp.datadoghq.com URL 403s when the keys
belong to a non-US1 org.
"""
site = (
os.environ.get("DD_SITE", DD_SITE) or "datadoghq.com"
).strip().removeprefix("https://").removeprefix("http://").rstrip("/")
if site.startswith("app."):
site = site[len("app.") :]
host = "mcp.datadoghq.com" if site in ("", "datadoghq.com") else f"mcp.{site}"
base = f"https://{host}/v1/mcp"
return f"{base}?toolsets={toolsets}" if toolsets else base
def unique_marker() -> str:
"""A short unique token per call/run, so concurrent runs and the shared
response cache never collide on prompts, tags, or customer ids."""
return uuid.uuid4().hex[:12]