* feat(router): continue chat streams on fallback after a mid-stream break A chat-completions stream that breaks after content has been delivered was re-raised and the fallback deployment never ran (#40404), while the Responses-API path already continues via a prefilled assistant turn. Add the same for chat completions behind `enable_mid_stream_fallback_continuation` (opt-in, async-only), so a post-content break re-enters the fallback chain with the partial text as an assistant prefill instead of surfacing the error. Continuation is only attempted when it is safe: the stream emitted plain assistant text (no tool/function calls, thinking blocks, reasoning items, audio or images), the request is not constrained output (response_format or a forced tool_choice) and not merge-reasoning mode, and the fallback target's model supports assistant prefill. The target check runs as a deployment pre-call filter, so a chain with no prefill-capable deployment empties and the original error is surfaced rather than a duplicated or rejected request being sent. Plain reasoning_content is treated as out-of-band and does not block a continuation, matching the Responses-API path; Anthropic thinking is excluded because its signed thinking blocks cannot ride a text-only prefill. CustomStreamWrapper now latches whether a disqualifying delta was streamed and carries it on MidStreamFallbackError so the router can decide without re-scanning chunks. Default behavior is unchanged. * fix(router): harden mid-stream continuation eligibility and prefill folding Address review of the mid-stream continuation: - keep response_format={"type": "text"} eligible; only json_object / json_schema and other structured formats decline, since "text" is the unconstrained default - fold a new partial into an existing trailing assistant prefill instead of appending a second one, so a nested mid-stream break stays a single prefill turn even on providers that do not merge consecutive assistant messages - split the deployment prefill-capability lookup into two readable steps - cover the merge_reasoning decline branch, the text response_format pass, and the prefill-folding path with tests * fix(router): address review of mid-stream continuation - register the continuation deployment filter as a process-global singleton instead of tracking it per router, so discarding one router no longer removes the type-deduplicated filter that other live routers still depend on - disqualify reasoning_content: it reaches the caller as visible reasoning that a text-only prefill cannot carry, so a reasoning-capable fallback would re-derive it and produce an incoherent response - move MID_STREAM_CONTINUATION_KWARG to constants and lazy-import the filter class in the router, breaking the module-level import cycle CodeQL flagged - trim the added docstrings to the repository comment policy * fix(router): keep mid-stream continuation within the type-discipline budget The LIT* type-discipline gate counts mutable-collection use the ruff pass does not see. Annotate the reads with read-only Sequence/Mapping views, compare response_format against a frozen MappingProxyType sentinel, and mark the genuinely mutable litellm message and deployment-list boundaries with mutable-ok reasons, so LIT001 and LIT002 stay under their limits. * fix(router): clear basedpyright operator error and the import-cycle alert - narrow the accumulated stream delta content to str before appending, so the shared helper no longer trips reportOperatorIssue (str += object) - keep the continuation marker in the pre-call-check module and lazy-import it at the two router call sites instead of routing it through constants, so the router has no module-level dependency that closes an import cycle * fix(router): make the mid-stream continuation marker unforgeable The deployment filter is process-global and read the continuation marker as a truthy value from request_kwargs. Since the proxy can forward arbitrary request-body fields into the router, a client could send `"_mid_stream_continuation": true` on a normal request to filter a mixed model group down to prefill-capable deployments and steer their prompt onto that provider. Set a private sentinel object internally and check it by type instead of truthiness: a JSON request body cannot construct one, so a forged flag is ignored. Adds a regression test that forged client values (true, "true", 1, a dict) leave the deployment list untouched. * feat(router): honor per-deployment model_info for continuation prefill capability The deployment filter only read supports_assistant_prefill from the cost map, so a model configured with `model_info: {supports_assistant_prefill: true}` on the deployment (the usual way to declare a capability for a model that is not in the cost map, or to override it) was wrongly skipped. Check the deployment's model_info first (True or False both authoritative), then fall back to the cost map. Adds tests for the override in both directions. * fix(router): bound mid-stream continuation to the caller's output allowance A continuation handed the fallback the full max_tokens / max_completion_tokens even though part of the answer had already streamed, so the total could exceed the caller's limit and repeated interruptions could re-grant the allowance on every hop, amplifying spend. Reduce each configured ceiling by the tokens already emitted before re-entry, and decline the continuation (surface the original error) when the allowance is exhausted. The reductions compound across hops because the trimmed ceiling is what the next hop sees. Also add the missing explanatory comment on the model_info fall-through except. * refactor(router): extract mid-stream decline to stay within the complexity budget The output-ceiling branch pushed stream_with_fallbacks past the C901 limit. Both decline paths (ineligible after content, and exhausted allowance) re-raised the original provider error the same way, so pull that into _raise_original_mid_stream_error. It removes the duplicated branching, drops the function back under the complexity ceiling, and reads clearer. * fix(cost-map): mark Claude Sonnet 4.6 as not supporting assistant prefill The Anthropic API and Bedrock both reject an assistant-last message on claude-sonnet-4-6 with "This model does not support assistant message prefill", so the continuation filter must not route a mid-stream continuation to it. Flip the flag on every claude-sonnet-4-6 entry and on databricks' opus-4-6 entry, whose anthropic sibling already says false. The prefill check tests now register synthetic cost-map entries instead of pinning real models, which broke when claude-3-opus left the map. * refactor(router): type the streaming fallback kwargs and drop narration comments Removes an unused mutable-ok marker (LIT013) and the explanatory comments Greptile flagged, and types initial_kwargs on both streaming fallback iterators as dict[str, Any] like their Responses siblings so the new continuation helpers take a typed mapping and the basedpyright budget stays at or below main. * fix(router): run post_call_rules over the joined text of a continued stream Each provider stream wrapper validates only the fragment it produced, so a rule that trips on the primary's prefix plus the continuation's text never fired. The router now feeds litellm.post_call_rules the emitted text plus every continuation chunk before yielding it. Also drops a narrating test-helper docstring. * refactor(router): read a deployment's declared prefill support without an empty except * test(router): cover _raise_original_mid_stream_error directly for the router coverage gate * fix(router): fold the continuation prefill into a trailing assistant turn A request that already ends in an assistant message took the partial output as a second assistant turn, which prefill providers reject. The partial now extends that turn in place, with prefix set, so the continuation request never ends in two assistant messages. * fix(router): keep content blocks on a trailing assistant turn when extending it with the partial output A trailing assistant message whose content is a list of blocks was stringified before the partial output was appended, so the fallback received the Python repr of the blocks as its prefill. The partial now lands as one more text block, and a content shape that cannot be extended surfaces the original stream error instead of a garbled continuation. * fix(router): continue the trailing text block in place when extending a prefill with content blocks Anthropic strips trailing whitespace per content block, so appending the partial output as a new text block after an assistant turn that ends in "Sure, " would send the prefill as "Sure,here". The continuation now extends the last text block itself and only opens a new text block when the trailing block is not text (an image, say), so the prefill reads exactly as the text the caller already received * test(router): type the prefill check's deployment helper * fix(router): keep a continued stream on the primary's identity and widen what can continue Continuation chunks now keep the primary stream's id and created time and drop the fallback's second role delta. Requests with n > 1 no longer continue. Prefill support reads model_info.base_model and litellm_params.base_model before the deployment model. enable_mid_stream_fallback_continuation is runtime-updatable through update_settings and registers the prefill filter. The bridge rebuild of MidStreamFallbackError keeps the inner stream's disqualifier. A fallback that repeats the prefill is not doubled in the continuation input. * fix(router): decline mid-stream continuation after a content filter, merged reasoning, or a plain trailing assistant turn Also count the partial stream's completion tokens in the continued stream's usage, accept string values for enable_mid_stream_fallback_continuation, and list the new router helpers in the router coverage check * fix(router): drop re-emitted whitespace at the continuation join and sum both legs' usage consistently * fix(router): keep the full prefill so a nested break keeps the separator * fix(router): bill both calls of a continued stream and fix Bedrock Converse, Databricks, and Vertex DeepSeek prefill routes * test(router): integration cells for mid-stream fallback continuation Covers the continued stream the caller gets, the prefill turn and reduced max_tokens the fallback receives, the prefill-capability filter, the runtime toggle, repeated requests through the response cache, and the spend row of a continued stream * fix(router): log a continued stream under the caller's id, price each cut on its own prompt, and keep prefill flags per deployment * fix(router): price and log each cut leg before its continuation reuses the logging object Price the cut stream's partial and let its failure log finish (bounded) before the fallback overwrites a shared proxy logging object, and skip continuation when an output guardrail is registered or a request fallback carries its own messages. * test(router): integration cells for the output-guardrail and request-fallback declines and the cut call's failure log Cover a registered post_call guardrail and a request fallback carrying its own messages keeping the original error, an input-only guardrail leaving continuation on, and the cut call's failure event naming its own deployment and price. * fix(router): skip mid-stream continuation when a request fallback overrides request params A request-body fallback entry that sets anything besides model (stream, messages, max_tokens) changes the request the prefill continuation relies on, so a stream: false entry ended the answer with no error. * fix(router): skip mid-stream continuation for a fallback group target that overrides request params The override check read only top-level fallback entries, so a target inside a group's list, such as {"primary": [{"model": "backup", "stream": false}]} in the request, the config, or a key's router settings, still ended the answer with no error. * fix(router): check only the request's own fallback chain for request param overrides Scanning every group's chain turned continuation off for all requests when one unrelated group's target overrode a param. Resolve the chain the router will use for this request, the same way the fallback path does. * fix(router): keep the original error when request fallbacks are malformed The request-param override check resolved a standard-shape chain outside the router's own error handling, so an empty entry or a non-list chain raised StopIteration or TypeError and replaced the original mid-stream error. Skip empty entries and treat a non-list chain as no chain. * fix(router): read deployment-configured constraints, decline deployment-id fallbacks without prefill, strip only the last Bedrock text block * fix(router): read a deployment's tool_choice ahead of router defaults in the continuation check, and restore the renamed prefill test names * fix(router): filter continuation deployments on every routing strategy, read extra_body and fallback deployments' own params The deployment filter now also runs on the sync selection path that usage-based-routing v1 and custom strategies use, one predicate reads n, response_format, tool_choice and merge_reasoning_content_in_choices with extra_body laid over them, fallback deployments whose own config constrains the output are skipped, and continuation declines when the cut deployment's id is not in the router (per-request credential deployments) * fix(router): decline a cut mid-echo, reduce extra_body output limits, and check post_call_rules once on nested continuations --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|---|---|---|
| .. | ||
| _support | ||
| authorization | ||
| caching | ||
| compatibility | ||
| configuration | ||
| cost_calculation | ||
| database | ||
| management | ||
| mcp | ||
| messages_endpoint | ||
| observability | ||
| pricing | ||
| providers | ||
| routing | ||
| sandbox | ||
| sdk | ||
| security | ||
| spend | ||
| streaming | ||
| translation | ||
| __init__.py | ||
| AGENTS.md | ||
| conftest.py | ||
| coordination_redis_proxy_config.yaml | ||
| mcp_coverage.toml | ||
| oci_proxy_test_config.yaml | ||
| proxy_config.yaml | ||
| README.md | ||
| run.py | ||
| test_oci_integration.py | ||
| test_oci_proxy_integration.py | ||
Integration contracts
These tests exercise a running gateway, PostgreSQL and Redis with an owned local upstream. CircleCI owns this suite. Tests are grouped by behavior, with no automatic test retries or fallback to paid provider calls
The ROI database contracts in database/test_roi_observed.py run as plain pytest outside run_integration.sh in CircleCI's roi-database Postgres job. The job uploads coverage with the roi-postgres flag. These contracts own temporary databases and script only the external provider transport
The Redis cluster IAM contracts in sdk/test_redis_cluster_iam_auth.py start their own redis-server and mock the cloud credential clients, so they run in the GitHub Actions redis-compat matrix against every supported redis-py major rather than in run_integration.sh
The cost group is driven by the CostTrackingTestCase literals under cost_calculation/cases/<provider>.py (gathered by cost_calculation/catalog.py), with the scripted cost map in cost_calculation/cost_map.py. Each case has a name, contract ID, cost-map model, optional deployment overrides, request body, tagged response and exact or recount expectations. Request bodies use $MODEL for the registered proxy model, while responses use $REQUEST_ID for the per-run scenario ID. To add a case, add a cost-map entry when the model is new, add the request body and exact provider response data, and add hand-computed expected values. The upstream serves each stored response for any path under /<scenario_id>, while the test-owned cost map is served over loopback through LITELLM_MODEL_COST_MAP_URL
Use tests/integration/run.py management, accounting, database, providers, extensions, mcp, sdk or cost to run a selected group. The group to directory mapping is the GROUPS literal at the top of run.py; a new directory needs a GROUPS entry and an OWNED_DIRECTORIES entry in _support/manifest.py. Set INTEGRATION_WORKERS above 1 to run a group under pytest-xdist. Every group run by more than one worker gives each worker a private database, Redis, scripted upstream process, fake provider and proxy, with a peer and read-only database role where required. There is no opt-in list and no shared proxy, upstream, database or Redis in that mode: run_integration.sh does not start them and does not hand their addresses to the run, so a test can only reach its own worker's services. The pytest controller owns these services and closes them after worker failures. Their cases use pytest-xdist load groups inside the files selected by CircleCI timing splits. Module and class fixtures are grouped automatically, so authors do not need scheduling markers. Function fixtures remain independently schedulable. Tests that own an independent mutable sink for every case should use function fixtures, so a shared module fixture does not serialize them or share pending observations. Nested harness probes discard the parent run's shard, worker and result settings, then supply their own selections. MCP keeps its explicit load groups. Automatic group suffixes are removed from JUnit and execution records to preserve case identities. Owned proxy helpers wait for a healthy response from every configured, live worker before yielding. Serial runs keep the supplied deployment, including routing parity runs. Set INTEGRATION_PROXY_URL, INTEGRATION_UPSTREAM_URL, INTEGRATION_MASTER_KEY and DATABASE_URL to an isolated test deployment. When that deployment runs more than one proxy worker, set INTEGRATION_PROXY_WORKERS to the count so a test that writes a model and then calls it waits out the config reload interval, the only cross-worker convergence bound the wire exposes. The runner selects the new domain directories explicitly; the legacy OCI and sandbox selections remain separate
Management, MCP and accounting also require INTEGRATION_PEER_URL, REDIS_HOST and REDIS_PORT. Under several workers each worker gets a second directly addressed proxy sharing only that worker's stores, and a single-worker run uses the two proxies run_integration.sh starts. The test-only CLI wrapper supplies enterprise route entitlement, following the existing behavior suite's convention. It does not qualify license validation; run it with one worker and no reload
The generated lifecycle models use 20 examples, eight steps, generation and shrinking, with isolated resources per example. HTTP operation caps include generation and shrinking and exempt cleanup. Local qualification defaults to seed 4106601 and canonical order; CircleCI derives exploration and ordering seeds from the checked-out revision and workflow ID. The ordering seed shuffles files, scoped fixture configurations and cases within each configuration. Ordering keeps shared module and class configurations together where their dependencies permit it. Dependent fixtures with their own module parameters can still rebuild an outer configuration, with every case retained
CircleCI uses its built-in circleci tests split --split-by=timings --timings-type=filename to assign test files using the uploaded JUnit timings. Each file stays on one node, preserving its module and parametrized fixtures. Jobs default to one node. Parallelism should use the smallest node count that keeps the complete job, including setup and cleanup, within twenty minutes. A group that already finishes within that target on one node stays on one node. Management, accounting, providers and management replica currently use four nodes. Extensions uses eight nodes; database and MCP use two, and fast suites use one. No job is configured above eight nodes. A single slow file can still determine a suite's runtime; split such a file along independent fixture boundaries rather than adding more nodes
Every node collects the same candidate files before applying CircleCI's assigned file list. Its execution record retains the candidate inventory and the selected, passed and skipped cases. An empty assigned file list produces an empty shard, not a full-suite fallback. Every parallel group has a dependent census job that rejects an empty candidate inventory, missing shards, omitted cases and duplicate execution. Standard and replica runs keep separate workspace records
Future change-based selection belongs before timing splitting. Pass the selected group files or node IDs to run.py <group> --list to list their files, then give those filenames to CircleCI. Run the same candidate selection on every node with --shard-files <CircleCI-output-path> --shards <count> --shard-index <index>. The census compares execution with the candidate inventory, while full-suite runs remain the default. CircleCI determines scheduling from timing history; timing data never selects or omits candidates. Use --seed and --order-seed to reproduce test generation and order. The installed Hypothesis version, settings, seeds and collected order are recorded beside the execution manifest
A future selector must explicitly skip a group when no candidates apply; omitting positional candidates means the full group. Keep full runs on the default branch and scheduled workflows, and select the full affected groups when shared fixtures, CI configuration or an unknown dependency changes
Reuse the existing canned provider handlers through _support/upstream.py. It rejects internal request fields and exposes actual received requests for independent assertions. Register every created resource for cleanup immediately, keep expected values independent of production calculations, and assert readback plus the runtime effect of a change
Owned proxies disable .env loading by default. A contract testing dotenv behavior can explicitly set PYTHON_DOTENV_DISABLED=0 in its owned environment. The runner drops inherited *_API_KEY variables, so a contract that needs one sets a synthetic value in its owned environment. An explicit scratch writer database drops an inherited reader with a different database name; pass both database URLs when the contract needs a paired reader. Database relays close listeners, active connections and their event loops on teardown. Upstream startup failures reap the child process before returning the failure. Custom subprocesses, direct SQL and background tasks still need an explicit owner in the test
Owned proxy workers configure a 32-thread executor before application startup, preserving additional worker startup hooks. Held synchronous provider calls must not consume a CPU-dependent executor limit before the rest of a fault burst can start. The proxy entrypoint imports LiteLLM inside main, so spawned workers begin supervision before importing the application. Worker healthchecks have a five-second deadline by default, so uvicorn kills a worker that stays paused longer than that. Tests never signal proxy processes themselves. OwnedProxy.kill_worker SIGKILLs a worker and returns once its replacement answers readiness with its own pid, replacing_worker does the same for a kill that has to land mid-burst, and suspended pauses a worker or the supervisor, which only works on a proxy launched with healthcheck=WorkerHealthcheck.LENIENT. Helper processes that are not the proxy stop through stop_child, stop_processes and stop_process_group and pause through paused. scripts/check_test_quality.py rule TQ010 rejects a raw os.kill, SIGKILL / SIGSTOP / SIGCONT, .kill(), .terminate(), .suspend() or .send_signal() anywhere under tests/integration outside _support, and TQ011 rejects an assertion that caps an elapsed time with a fixed number. Bound timings with _support/timing.py instead, relative to a measured control or to the injected delay. run.py measures how long this box takes to import the proxy application before it starts pytest, records it in boot-calibration.json beside the results and exports it as INTEGRATION_IMPORT_SECONDS. Readiness deadlines, graceful stops and the default per-test timeout are multiples of that measurement (_support/budget.py), so a slower box gets longer budgets and a two-worker proxy gets twice the readiness deadline of a one-worker one. Readiness requires responsive worker identities that are still alive and a positively identified owned listener. Unreadable socket records cannot establish ownership. Crash tests own their client tasks with TaskGroup, release held peers in finally and verify that the intended worker dies. A test requiring traffic on both workers prepares that traffic explicitly instead of assuming OS load balancing, for example by sending each half while the other worker is suspended
Any port the harness picks before the server that listens on it has started comes from allocate_port() in _support/ports.py. That covers owned proxies, scripted upstreams, fake providers, OTLP sinks, database relays and Redis. A server that binds port 0 itself and keeps that socket, such as wire_server without a port, needs no allocation. Each pytest process claims a block of 200 ports between 10000 and 32767 by holding an exclusive lock file per block in the system temp directory, so two runs on one machine, such as parallel worktrees, never share a block, and the OS drops the lock when the process exits. The range sits above the fixed service ports and below the Linux and macOS ephemeral ranges, so a port-0 bind or an outbound connection never lands in a block. Ports inside a block go out in order and are never handed out twice in a run, a port that something outside the harness already holds is skipped, and a process that uses up its block claims the next free one. A test that restarts a server on the same port allocates that port up front instead of reading it back from the first server. TQ012 in scripts/check_test_quality.py rejects reading a port back from a port-0 bind anywhere under tests/integration
The CircleCI workflow starts its own database and Redis, restricts test-phase egress to its owned services and writes JUnit plus an executed-node manifest. Missing setup, failed cleanup or a selected test with neither a passed call nor a skip fail qualification. Skipped nodes are listed under skipped in execution.json, so the skip reasons double as the open bug list. GITHUB_FILES in run.py lists the files excluded from the run_integration.sh selection
There is no hand-maintained list of test cases. A positional argument is a file of the group or a pytest node id inside one (path::test[param]), so one cell of a parametrized file can run alone. The runner fails only when pytest fails, when collection errors, or when a selected file collects zero tests. Older tests still carry @pytest.mark.covers(...) decorators; the marker stays registered so they collect, but the IDs are not checked against anything and new tests should not use it. The GitHub Actions coverage census reads the GROUPS literal in run.py and treats every tests/integration/<directory>/test_*.py file in a scheduled group as owned by CircleCI
Provider sentinels currently use the controlled server, not live recordings. The provider shard also runs the existing strict replay controls for changed requests, exhausted interactions, leftover interactions and no provider connection. Future recorded scenarios must use that replay-only implementation; missing recordings cannot fall back to a real provider. The observation endpoint is destructive and the current selection runs serially against one owned upstream
Translation tests in translation/ compare exact provider requests and LiteLLM responses against a shared fake provider; translation/README.md has their rules
Fixtures must contain synthetic data only. Keep private incident records and source documents out of code, fixtures, logs and PR descriptions
Database cases own their temporary schemas, roles, constraints and proxy processes. They prove reader-versus-writer execution with PostgreSQL lock observations, exercise real transaction wait limits and verify rollback after a reached database failure
Accounting cases compare persisted input and output cost components against literal rates, including zero and default prices. Cache state models assert actual upstream calls, response identity and every persisted charge. Generated accounting tests have a 180-second test limit to accommodate the asynchronous spend writer
Provider contracts exercise actual TCP requests with synthetic credentials and local protocol peers. The S3 verifier uses independently implemented equations, a published known-answer vector, a fixed signing clock and deliberately invalid signed requests. Bedrock cases clear ambient AWS credential sources and check the literal model path, loaded role references, STS requests and bearer-only behavior
CircleCI runs providers on four isolated nodes using its file timing splitter. Each node owns its services. The dependent providers coverage job verifies all four execution records against the candidate case inventory and rejects missing, duplicate, failed or incomplete execution. The node's assigned filenames are saved in node-files.txt beside its execution record
Streaming checks send real HTTP transfer chunks, including one-byte partitions, fragmented tools, incomplete transfers and a cancellation barrier. They assert meaningful text, tool arguments, final usage and persisted cost. The Redis recovery case owns a separate database and Redis process, uses the supported one-second circuit-breaker recovery setting, waits for the real subscriber and verifies response data in Redis after restart. CircleCI reuses its existing Redis image for that extra process; it never pulls an image during tests
The messages_endpoint/ directory holds /v1/messages endpoint contracts: native-provider backends under providers/ (anthropic, bedrock, gemini) and the translation bridges (responses_bridge, chat_bridge) at the top level. It runs in the providers shard; run.py selects test files recursively under each scheduled directory
The sdk shard exercises the SDK's own HTTP clients against local protocol peers with no gateway in the path, so a case here fails only when the client library or its wire behavior changes. The HTTP/2 case runs a hypercorn TLS peer offering h2 and http/1.1 over ALPN, drives the sync and async httpx handlers at it with LITELLM_HTTP2 off and on, and asserts the version both the client and the peer observed on the wire. Put a test here only when it needs no proxy or database. CircleCI starts a local Redis for this shard like the others, so SDK-side caching cases that need a real Redis server belong here too; a case that reaches the gateway belongs in one of the other shards
The extensions shard uses the built-in generic callback and guardrail transports. It checks callback correlation and credential exclusion, guardrail rewriting and denial, retained OpenAI consumers and A2A wire versions. CircleCI runs it on eight xlarge nodes using its file timing splitter. Each node runs its assigned files with four pytest workers, each owning its database, Redis, upstream and proxy. The dependent coverage job verifies all eight execution records against the candidate case inventory. Tests must not assume a particular set of sibling files
The security shard uses four pytest workers on an xlarge machine, each with its own isolated services like every other multi-worker group. Route sweeps use a new HTTP client for every call and share only the TLS verification context, so authentication and response cookies cannot cross callers. The canary rig supplies owned OpenAI and Anthropic endpoints and synthetic credentials and rejects attempted external egress
The two mcp nodes own separate services and use the same case census as providers and extensions. Their coverage data is combined into one MCP report after both nodes finish. Each node runs the MCP gateway against SDK peers owned by each test (_support/mcp.py): streamable HTTP, SSE and stdio peers, an OpenAPI-spec app, and an OAuth 2.1 authorization-server double. Every peer records the requests it receives so a test can assert what reached the peer, not only what the proxy answered. The shard runs with INTEGRATION_WORKERS set and with INTEGRATION_COVERAGE=1, which starts every worker's proxy and peer under coverage run --parallel-mode limited to the MCP modules and stores coverage.txt plus an HTML report with the job artifacts. mcp_coverage.toml measures lines through sys.monitoring, because the CPython 3.12 trace function that branch measurement needs made a covered proxy take about four times as long to become ready. A test that fails because the product is wrong is skipped with pytest.skip("BUG: <symptom>") so the skip list in execution.json is the open MCP bug list
Browser contracts live in tests/e2e/ui/tests/integrationCritical and run only through tests/e2e/ui/integration.config.ts. The expected browser results are listed in expected.json in that directory and checked by .circleci/scripts/verify_integration_browser.py. The CircleCI browser shard builds the checked-out dashboard, starts the owned proxy with that build, and verifies one exact browser result without retries or skips. The default Playwright selection excludes this directory. The focused project flow asserts the submitted create and clear values, fresh SQL state and actual blocked/restored serving while preserving model restrictions
Two always-on -replica CircleCI jobs (management, database) run their groups in replica mode, where every proxy connects through a real litellm_writer role and a real read-only litellm_reader role against the same PostgreSQL. Nothing is captured there: the job passes when the tests pass, and a write routed to the read-only reader fails the test that issued it. A deeper check runs on demand as the routing_parity workflow, triggered through the CircleCI API v2 pipeline endpoint on the PR branch with {"parameters": {"routing_parity_base": "<40-hex merge-base sha>"}}. The workflow fans out over the seven groups, and each routing-parity-<group> job runs its own group twice against the same test harness, once with litellm/, enterprise/, and litellm-proxy-extras/ checked out from the base revision and once from the head, with a pytest plugin snapshotting pg_stat_statements into routing-observed.json per side. The check step then compares the two observations and writes routing-diff.txt: a statement seen on both sides fails when its role set changed, globally or for the same test (per-test capture is skipped under xdist), unless it is listed in tests/integration/routing/either_role.json, where each entry names the statement and a one-line reason it legitimately runs on whichever role asks for it, printed under == either role ==. Queries seen on only one side are listed, never failed, pg_stat_statements evictions and a role that never ran a statement are failures