mirror of
https://github.com/BerriAI/litellm.git
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* test: migrate local_testing SDK and provider tests out of build_and_test * test: cover sagemaker region, hf template and nova paths end to end Region rows now go through litellm.completion on the sagemaker/ handler that the legacy tests exercised, the prompt template test mocks the Hugging Face tokenizer config instead of switching to custom_prompt_dict, streaming tests assert role, finish reason and body, and Nova single turn and streaming run through litellm.completion with a recorded request body * test: tighten migrated integration tests for local OpenAI routes, timeouts and air-gapped boot Split the catch-all providers migration file by behavior. The fake endpoint route tests now hit the owned upstream directly, as the legacy harness tests did. LM Studio asserts the outbound key, path and stripped model. The embedding timeout test asserts the proxy maps a deployment timeout to a 408 and forwards the read timeout to the provider client, instead of timing out the test client The Azure streaming tool-call test also asserts the second identical stream is served from the Redis cache with the same reassembled tool call The Docker network test always skipped in CI because the security job has no litellm/litellm image and no egress to pull one, and it tested a published image rather than the checkout. It now boots the checkout proxy with every outbound HTTP connection refused and asserts readiness, the bundled cost map fallback and that the cost map host is the only egress attempted * test: tighten the migrated e2e rows for local_testing SDK and provider tests Drop the duplicated Anthropic covers marker and the Anthropic cell wrongly claimed by the Bedrock and Vertex cache tests. Keep the file-wide Anthropic model as it is on main. Send the 2023-06-01 version header to Anthropic through the deployment's extra_headers so the header actually reaches the provider, and mark the creation-token case 1h then 5m like the legacy test did Reuse the Bedrock file's own registration for the pydantic response test, swap the hand-built PNGs for the shared cat.jpg fixture, assert the SageMaker Nova image answer names the cat and that top_logprobs=3 is honored, and register the SageMaker Nova opt-in markers the same way as the other opt-in markers * test: restore lost assertions in migrated test_main tests Restore the role alternation check in test_completion_anthropic_hanging, the embedding and streaming response-header checks, the logit_bias drop check and the gemini system and safety settings checks. Add an azure 429 retry-after test for test_exception_with_headers, trigger the router fallback with mock_timeout like the legacy test, and stop the mock timeout tests sleeping 3s * test: restore lost legacy assertions in migrated vertex ai unit tests * test: tighten migrated cost, streaming and embedding tests and scope the hosted mock guard * test: strengthen migrated anthropic, azure, bedrock and cohere provider tests Assert full request bodies and usage instead of presence checks, restore the dummy-tool and custom_llm_provider assertions the legacy tests made, add the async and per-model variants the legacy parametrization covered, split streamed tool arguments across deltas, and move the Azure chat streaming tests to the azure.py mirror file * test: tighten migrated llms provider tests and cover legacy intents lost in the move Strengthen the migrated fireworks, gemini, mistral, together, openai text completion, openrouter, perplexity and openai error tests so they assert what the legacy tests proved (cost, provider tag, usage-only-on-last-chunk, function_call rebuild, reasoning param, sync/async/stream error fields). Replace the huggingface and jina tests that doubled litellm code with respx end-to-end tests. Add the tests the pre-existing mapped tests never covered: cohere 400 mapping, token-array text completion, hosted_vllm/llamafile/lm_studio env api base embeddings, watsonx embedding auth, ollama ssl_verify client and ollama vision prompt * test: cover residual legacy paths for anthropic tool streams, watsonx async stream, ollama http images and caller async embedding clients * test: restore single request assertions in the deep_infra and azure_ai embedding tests * test: drop a no-op streaming cost flag from the openai streaming cost test * test: cover residual legacy-test lines in caching, main, utils, replicate, vertex and bedrock invoke * test: cover streamed audio assembly, choice membership, untranslated responses events and the stream log guard * test: pin cost rates in unit tests, use sdk for cohere e2e, drop vertex llama e2e * test: send the vertex maps e2e request through the openai sdk * test: drop the local_testing jobs that select no tests after the migrations * test: wait for the streamed cache entry and keep custom Mistral rates test-local * test: keep untouched Mistral test lines as they were --------- Co-authored-by: yuneng <yuneng@berri.ai>
325 lines
16 KiB
Python
325 lines
16 KiB
Python
"""Generic configuration for live e2e tests against a running LiteLLM proxy.
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Shared by every e2e suite under tests/e2e/. Values come from the
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environment so the same tests run against localhost or a deployed proxy.
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"""
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from __future__ import annotations
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import os
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import socket
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from dataclasses import dataclass
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import time
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import uuid
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from pathlib import Path
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from typing import Final
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from dotenv import load_dotenv
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from e2e_metadata import step
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from fixture_mode import deterministic_marker, parse_fixture_mode, registration_owner
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from provider_edge import provider_edge_api_base
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from pydantic import TypeAdapter
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# Local runs keep provider / DataDog keys in tests/e2e/.env (see CONTRIBUTING.md).
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# Compose injects them into the proxy container, but pytest on the host does not
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# inherit that file unless we load it. override=False so a real shell export wins.
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load_dotenv(Path(__file__).resolve().parent / ".env", override=False)
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PROXY_BASE_URL = os.environ.get("LITELLM_PROXY_URL", "http://localhost:4000").rstrip("/")
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MASTER_KEY = os.environ["LITELLM_MASTER_KEY"]
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# Control-plane (management/admin) base URL. Defaults to PROXY_BASE_URL so a
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# single path-routing host (stage ALB, compose monolith) works for both planes.
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# Set LITELLM_CONTROL_PLANE_URL only when management is a different base than
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# the LLM host and you are not going through an ingress that path-routes.
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CONTROL_PLANE_BASE_URL = os.environ.get(
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"LITELLM_CONTROL_PLANE_URL", PROXY_BASE_URL
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).rstrip("/")
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def split_replica_urls(raw: str) -> tuple[str, ...]:
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return tuple(dict.fromkeys(url.strip().rstrip("/") for url in raw.split(",") if url.strip()))
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def parse_replica_urls(raw: str, fallback: str) -> tuple[str, ...]:
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return split_replica_urls(raw) or (fallback,)
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def parse_control_plane_replica_urls(
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raw: str, *, control_plane_base_url: str, base_url: str, replica_urls: tuple[str, ...]
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) -> tuple[str, ...]:
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"""The replicas a management read-back polls. LITELLM_CONTROL_PLANE_REPLICA_URLS
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names them outright; unset, they follow the two base URLs: every data-plane
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replica when the planes share a base (a monolith serves every route from every
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replica) and the control-plane base alone when they differ. A stack sets it when
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LITELLM_PROXY_REPLICA_URLS names gateway pods behind a shared router base, since
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a gateway trims the management routes at startup and answers them 404."""
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explicit: Final = split_replica_urls(raw)
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if explicit:
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return explicit
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return replica_urls if control_plane_base_url == base_url else (control_plane_base_url,)
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PROXY_REPLICA_URLS: Final = parse_replica_urls(os.environ.get("LITELLM_PROXY_REPLICA_URLS", ""), PROXY_BASE_URL)
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CONTROL_PLANE_REPLICA_URLS: Final = parse_control_plane_replica_urls(
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os.environ.get("LITELLM_CONTROL_PLANE_REPLICA_URLS", ""),
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control_plane_base_url=CONTROL_PLANE_BASE_URL,
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base_url=PROXY_BASE_URL,
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replica_urls=PROXY_REPLICA_URLS,
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)
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@dataclass(frozen=True, slots=True)
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class StackEndpoints:
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base_url: str
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control_plane_base_url: str
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replica_urls: tuple[str, ...]
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control_replica_urls: tuple[str, ...]
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def control_replica_urls_for(
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self, *, base_url: str, control_plane_base_url: str, replica_urls: tuple[str, ...]
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) -> tuple[str, ...]:
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"""The control replicas a client built for these endpoints polls when its caller names none:
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this stack's own list for this stack's endpoints, since an exported list describes one stack only,
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and the base-URL rule for any other proxy."""
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if (base_url, control_plane_base_url, replica_urls) == (
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self.base_url,
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self.control_plane_base_url,
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self.replica_urls,
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):
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return self.control_replica_urls
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return parse_control_plane_replica_urls(
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"", control_plane_base_url=control_plane_base_url, base_url=base_url, replica_urls=replica_urls
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)
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ENV_STACK: Final = StackEndpoints(
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base_url=PROXY_BASE_URL,
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control_plane_base_url=CONTROL_PLANE_BASE_URL,
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replica_urls=PROXY_REPLICA_URLS,
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control_replica_urls=CONTROL_PLANE_REPLICA_URLS,
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)
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UI_USERNAME = os.environ.get("E2E_UI_USERNAME", "admin")
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UI_PASSWORD = os.environ.get("E2E_UI_PASSWORD", MASTER_KEY)
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# Dashboard base for playwright. Defaults to PROXY_BASE_URL so one ALB/monolith
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# host covers /ui as well. Override E2E_UI_BASE_URL only if the UI is elsewhere.
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UI_BASE_URL = os.environ.get("E2E_UI_BASE_URL", PROXY_BASE_URL).rstrip("/")
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CHEAP_ANTHROPIC_MODEL = os.environ.get("E2E_CHEAP_ANTHROPIC_MODEL", "claude-haiku-4-5")
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CHEAP_OPENAI_MODEL = os.environ.get("E2E_CHEAP_OPENAI_MODEL", "gpt-5.5")
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S3_PARTITION_GRANULARITY = os.environ.get("E2E_S3_PARTITION_GRANULARITY", "day")
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LINEAR_MCP_URL = os.environ.get("E2E_LINEAR_MCP_URL", "https://mcp.linear.app/mcp")
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LINEAR_STORAGE_STATE = os.environ.get("E2E_LINEAR_STORAGE_STATE", "")
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LINEAR_READONLY_TOOL: Final = "list_teams" # as listed by tools/list on mcp.linear.app when PR #33787 landed
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# Jaeger query API of the compose stack's OTEL trace destination (the `jaeger`
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# service in docker-compose.yml maps it to host 16686). Trace-completeness tests
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# read exported spans back through it.
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OTEL_QUERY_URL = os.environ.get("E2E_OTEL_QUERY_URL", "http://localhost:16686").rstrip("/")
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OTEL_EXPORTER_ENDPOINT = os.environ.get("E2E_OTEL_EXPORTER_ENDPOINT", "")
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# Real-DataDog read-back (no local sink - destination fakes cannot be deployed
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# on the cluster): the proxy delivers with DD_API_KEY as in production, and the
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# tests read ingested events back through the DataDog Logs Search API, which
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# additionally needs an application key. On the cluster the secret manager
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# injects both; locally tests/e2e/.env provides them.
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DD_SITE = os.environ.get("DD_SITE", "datadoghq.com").strip()
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DD_API_KEY = os.environ.get("DD_API_KEY", "").strip()
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DD_APP_KEY = os.environ.get("DD_APP_KEY", "").strip()
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# After the first event is searchable, keep watching this long for a late
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# duplicate before the exactly-one assertion: real-DataDog ingestion jitter can
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# make one call's two events searchable tens of seconds apart, and a duplicate
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# that surfaces late IS the bug (LIT-4447), so one poll interval is not enough.
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DD_SETTLE_SECONDS = float(os.environ.get("E2E_DD_SETTLE_SECONDS", "30"))
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# DataDog Logs Search `from` window (relative to now). Wide enough for a suite
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# run plus ingestion lag; override if a long CI queue needs a wider lookback.
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DD_SEARCH_FROM = os.environ.get("E2E_DD_SEARCH_FROM", "now-30m").strip() or "now-30m"
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# The Logs Search API budget is tight - 2 requests per 10s org-wide
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# (x-ratelimit-name logs_public_search_api) - so read-backs pace their search
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# calls at this interval instead of POLL_INTERVAL, and back off when a 429
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# still slips through (the budget is shared with anything else searching).
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DD_SEARCH_INTERVAL = float(os.environ.get("E2E_DD_SEARCH_INTERVAL", "10"))
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# Writes on the proxy are eventually consistent (e.g. spend rows flush on
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# proxy_batch_write_at, ~60s). Read-backs poll to this deadline, never sleep-once.
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POLL_TIMEOUT = float(os.environ.get("E2E_POLL_TIMEOUT", "120"))
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POLL_INTERVAL = float(os.environ.get("E2E_POLL_INTERVAL", "5"))
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REQUEST_TIMEOUT = float(os.environ.get("E2E_REQUEST_TIMEOUT", "60"))
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SLOW_PROVIDER_TIMEOUT_SECONDS = float(os.environ.get("E2E_SLOW_PROVIDER_TIMEOUT", "180"))
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# How long a control-plane write (/model/new, /guardrails, /v1/agents) may take to
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# reach EVERY replica. Distinct from POLL_TIMEOUT, which is sized for spend-row
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# flush; this one is sized for the proxy's config reload
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# (`proxy_config_reload_interval_seconds`, 30s by default and 7s on the e2e stack)
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# plus margin.
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#
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# The barriers below wait this out on top of polling /v1/models on every replica in
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# PROXY_REPLICA_URLS: that poll proves each addressed gateway converged, but not the
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# workers behind it, and behind a load balancer (PROXY_REPLICA_URLS unset) a
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# successful read only proves ONE replica converged, because every request opens a
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# fresh connection and the next call re-rolls. See ProxyClient._await_model_servable.
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PROPAGATION_TIMEOUT = float(os.environ.get("E2E_PROPAGATION_TIMEOUT", "15"))
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# Record/replay fixture selection (see fixture_mode.py and provider_edge.py).
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# The raw mode value is parsed and validated there; "live" (the default, also
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# for empty values) means the harness behaves exactly as before this knob
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# existed.
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FIXTURE_MODE_RAW = os.environ.get("E2E_FIXTURE_MODE", "live")
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FIXTURE_DIR = Path(
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os.environ.get("E2E_FIXTURE_DIR", "").strip()
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or str(Path(__file__).resolve().parent / ".fixtures")
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)
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# Where the provider-edge server binds, and the host name edge api_base URLs
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# advertise to the proxy. They differ when the proxy runs in a container and
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# reaches the pytest host via a gateway name like host.docker.internal.
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PROVIDER_EDGE_BIND_HOST = os.environ.get("E2E_PROVIDER_EDGE_BIND_HOST", "").strip() or "127.0.0.1"
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PROVIDER_EDGE_ADVERTISE_HOST = (
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os.environ.get("E2E_PROVIDER_EDGE_ADVERTISE_HOST", "").strip() or PROVIDER_EDGE_BIND_HOST
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)
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# Deliberately modest concurrency. The suite shares its proxy with every other
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# suite in the run, and 750 users at spawn rate 50 saturated the request path hard
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# enough to distort latency-sensitive neighbours (and to spend real provider money
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# fast).
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LOAD_USERS = int(os.environ.get("E2E_LOAD_USERS", "200"))
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LOAD_SPAWN_RATE = float(os.environ.get("E2E_LOAD_SPAWN_RATE", "20"))
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LOAD_DURATION_SECONDS = float(os.environ.get("E2E_LOAD_DURATION_SECONDS", "60"))
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LOAD_MAX_FAILURE_RATIO = float(os.environ.get("E2E_LOAD_MAX_FAILURE_RATIO", "0.01"))
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# The throughput floor is derived per replica instead of being an absolute fleet
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# number, so the verdict does not depend on how many replicas happen to be warm.
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# One closed-loop user only ever occupies one replica at a time, so a short serial
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# pass measures a single replica's request path: its throughput is 1/latency, and
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# the concurrent phase then has to reach at least that much no matter how large
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# the fleet is. An absolute floor instead asserted replicas x per-replica rate,
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# which reactive autoscaling decides rather than the request path.
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LOAD_BASELINE_SECONDS = float(os.environ.get("E2E_LOAD_BASELINE_SECONDS", "15"))
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LOAD_MAX_SERIAL_LATENCY_SECONDS = float(os.environ.get("E2E_LOAD_MAX_SERIAL_LATENCY_SECONDS", "0.5"))
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LOAD_MIN_CONCURRENCY_EFFICIENCY = float(os.environ.get("E2E_LOAD_MIN_CONCURRENCY_EFFICIENCY", "0.8"))
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WEEKLY_ANOMALY_OPT_IN_ENV = "E2E_WEEKLY_ANOMALY"
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MANAGED_FILES_OPT_IN_ENV = "E2E_MANAGED_FILES_STACK"
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PROMPT_CACHING_OPT_IN_ENV = "E2E_PROMPT_CACHING_STACK"
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REDIS_CHAOS_OPT_IN_ENV = "E2E_REDIS_CHAOS"
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CLI_DETERMINISM_OPT_IN_ENV = "E2E_CLI_DETERMINISM"
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MCP_OAUTH_LIVE_OPT_IN_ENV: Final = "E2E_MCP_OAUTH_LIVE"
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PROVIDER_EDGE_HOST_OPT_IN_ENV: Final = "E2E_PROVIDER_EDGE_HOST_REACHABLE"
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OWNED_GATEWAY_OPT_IN_ENV: Final = "E2E_OWNED_GATEWAY"
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OTEL_V2_OPT_IN_ENV: Final = "E2E_OTEL_V2"
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OTEL_TLS_OPT_IN_ENV: Final = "E2E_OTEL_EXPORTER_ENDPOINT"
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SECRET_MANAGER_OPT_IN_ENV: Final = "E2E_SECRET_MANAGER"
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SAGEMAKER_NOVA_OPT_IN_ENV: Final = "SAGEMAKER_NOVA_ENDPOINT"
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SAGEMAKER_NOVA2_LITE_OPT_IN_ENV: Final = "SAGEMAKER_NOVA2_LITE_ENDPOINT"
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ANOMALY_SESSIONS = int(os.environ.get("E2E_ANOMALY_SESSIONS", "6"))
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ANOMALY_TURNS_PER_SESSION = int(os.environ.get("E2E_ANOMALY_TURNS_PER_SESSION", "6"))
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ANOMALY_TURN_ATTEMPTS = int(os.environ.get("E2E_ANOMALY_TURN_ATTEMPTS", "3"))
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ANOMALY_MAX_ERROR_RATIO = float(os.environ.get("E2E_ANOMALY_MAX_ERROR_RATIO", "0.05"))
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ANOMALY_MIN_WARM_CACHE_READ_SHARE = float(
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os.environ.get("E2E_ANOMALY_MIN_WARM_CACHE_READ_SHARE", "0.65")
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)
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ANOMALY_MAX_P95_TURN_SECONDS = float(
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os.environ.get("E2E_ANOMALY_MAX_P95_TURN_SECONDS", "30")
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)
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ANOMALY_MAX_KEY_SPEND_USD = float(
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os.environ.get("E2E_ANOMALY_MAX_KEY_SPEND_USD", "0.60")
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)
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ANOMALY_SPEND_SETTLE_SECONDS = float(
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os.environ.get("E2E_ANOMALY_SPEND_SETTLE_SECONDS", "75")
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)
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MEMORY_REQUESTS_PER_PHASE = int(os.environ.get("E2E_MEMORY_REQUESTS_PER_PHASE", "300"))
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MEMORY_RETRIES_PER_REQUEST = int(os.environ.get("E2E_MEMORY_RETRIES_PER_REQUEST", "2"))
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MEMORY_TRANSCRIPT_TURNS = int(os.environ.get("E2E_MEMORY_TRANSCRIPT_TURNS", "40"))
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MEMORY_CONCURRENCY = int(os.environ.get("E2E_MEMORY_CONCURRENCY", "4"))
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MEMORY_RSS_SETTLE_SAMPLES = int(os.environ.get("E2E_MEMORY_RSS_SETTLE_SAMPLES", "15"))
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MEMORY_RSS_SAMPLE_INTERVAL_SECONDS = float(os.environ.get("E2E_MEMORY_RSS_SAMPLE_INTERVAL_SECONDS", "1"))
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MEMORY_RSS_BUDGET_MB = float(os.environ.get("E2E_MEMORY_RSS_BUDGET_MB", "48"))
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MEMORY_IDLE_RSS_BUDGET_MB = float(os.environ.get("E2E_MEMORY_IDLE_RSS_BUDGET_MB", "768"))
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MEMORY_STORED_REQUEST_BUDGET_KB = float(os.environ.get("E2E_MEMORY_STORED_REQUEST_BUDGET_KB", "64"))
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def ws_base_url() -> str:
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"""PROXY_BASE_URL with its scheme swapped for the websocket one, so a suite
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opening a socket points at the same proxy every HTTP suite uses."""
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for scheme, ws_scheme in (("https://", "wss://"), ("http://", "ws://")):
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if PROXY_BASE_URL.startswith(scheme):
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return ws_scheme + PROXY_BASE_URL[len(scheme) :]
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return PROXY_BASE_URL
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def datadog_mcp_url(*, toolsets: str = "core") -> str:
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"""Regional Datadog remote MCP endpoint for this process's DD_SITE.
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US1 is mcp.datadoghq.com; every other site is mcp.<site> (e.g. us5 ->
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mcp.us5.datadoghq.com). A fixed mcp.datadoghq.com URL 403s when the keys
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belong to a non-US1 org.
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"""
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site = (
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os.environ.get("DD_SITE", DD_SITE) or "datadoghq.com"
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).strip().removeprefix("https://").removeprefix("http://").rstrip("/")
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site = site.removeprefix("app.")
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host = "mcp.datadoghq.com" if site in ("", "datadoghq.com") else f"mcp.{site}"
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base = f"https://{host}/v1/mcp"
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return f"{base}?toolsets={toolsets}" if toolsets else base
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def provider_edge_base(mount: str) -> str | None:
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"""The api_base an edge-wired deployment should register with, using this
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process's fixture-mode and edge-host configuration: None in live mode, the
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shared edge server's mount URL in record and replay, and with the shared
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cache on, the cache edge's mount URL scoped to the node that owns the
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deployment: the running test, or the module or class whose fixture is
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setting it up."""
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return provider_edge_api_base(
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mount,
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mode_raw=FIXTURE_MODE_RAW,
|
|
bundle_dir=FIXTURE_DIR,
|
|
bind_host=PROVIDER_EDGE_BIND_HOST,
|
|
advertise_host=PROVIDER_EDGE_ADVERTISE_HOST,
|
|
test_key=registration_owner(),
|
|
forward_timeout=REQUEST_TIMEOUT,
|
|
)
|
|
|
|
|
|
STREAM_MIN_LEAD_SECONDS: Final = 1.0
|
|
|
|
|
|
def provider_paces_stream() -> bool:
|
|
return parse_fixture_mode(FIXTURE_MODE_RAW) != "replay"
|
|
|
|
|
|
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. In record
|
|
and replay modes the token is deterministic per test instead, so a replay
|
|
run regenerates the exact requests the record run sent."""
|
|
if parse_fixture_mode(FIXTURE_MODE_RAW) in ("record", "replay"):
|
|
return deterministic_marker()
|
|
return uuid.uuid4().hex[:12]
|
|
|
|
|
|
INHERITED_ENV_PREFIXES: Final = ("REDIS_", "MICROSOFT_", "GOOGLE_", "GENERIC_", "PROXY_")
|
|
|
|
|
|
def available_port() -> int:
|
|
with socket.socket() as listener:
|
|
listener.bind(("127.0.0.1", 0))
|
|
return TypeAdapter(tuple[str, int]).validate_python(listener.getsockname())[1]
|
|
|
|
|
|
@step("Wait for the last control-plane write to reach every proxy replica")
|
|
def settle_propagation(written_at: float) -> None:
|
|
"""Block until PROPAGATION_TIMEOUT has elapsed since `written_at`, a
|
|
`time.monotonic()` stamp taken the moment a control-plane write returned.
|
|
|
|
Callers that already polled for the object still need this: the poll proves one
|
|
replica has it, not all of them. Waiting out the config-reload budget is what
|
|
makes the object safe to use on whichever replica the next request lands on.
|
|
"""
|
|
remaining = PROPAGATION_TIMEOUT - (time.monotonic() - written_at)
|
|
if remaining > 0:
|
|
time.sleep(remaining)
|