A provider read timeout after the 200 was already committed on a streamed
/v1/messages request used to run the success logging path, so the failure
callbacks never fired and the failure metrics stayed flat. The pass-through
stream handler and the Bedrock relay iterator now dispatch the failure
handlers instead, with the usage and cost of the chunks already delivered
stashed on the logging object so the failure row still bills them.
`/team/info` access_group_details now carries mcp_server_ids and agent_ids per
group next to models, so the dashboard can say which group granted a server or
agent. The Object Permissions rows drop the Inherited badge and the row tooltip
reads "Granted via access group <name>. Full ID: <id>", listing every group
when more than one grants the same id and falling back to "an access group"
when the proxy did not say.
Claude-Session: https://claude.ai/code/session_01QvQzYztinxj8ZuD5YxbVdL
The auto-bridge that moves gpt-5.4+ requests carrying function tools and no
reasoning_effort onto /v1/responses only fired when the resolved api_base was
the literal https://api.openai.com/v1, so a deployment pointed at an OpenAI
PrivateLink hostname (<region>.privatelink.api.openai.com) or a port-qualified
or trailing-slash default stayed on Chat Completions and got OpenAI's 400 back.
Gate on the resolved URL's hostname instead: api.openai.com or any subdomain of
it bridges, every other custom base still stays on chat
test_router_timeout, test_timeout_streaming and test_openai_embedding_timeouts
asked api.openai.com for a response in 10 to 100 microseconds and asserted the
resulting exception was a timeout. No connect can finish in that window, so
socket.create_connection always walked the whole address list, and because it
re-raises only the LAST address's error, the assertion was decided by the order
getaddrinfo happened to return.
api.openai.com is dual-stack and the CI container has no usable IPv6, so a
trailing AAAA record made the last attempt fail with an OSError. httpcore maps
socket.timeout to ConnectTimeout but OSError to ConnectError, so the expected
APITimeoutError arrived as APIConnectionError and the job went red. The three
tests were really measuring DNS ordering, not litellm.
Point them at the fake OpenAI endpoint the suite already runs, ask for the
slow-endpoint model it already delays on, and give them a timeout comfortably
under that delay. The embeddings route did not honour slow-endpoint yet, so it
now delays the same way chat and text completions already do.
Each test also gained a failure on the success path. Without it a request that
returned instead of timing out fell out of the try block and the test passed on
a result it was written to reject.
Regenerating a key repointed ?key= at the rotated hash with a pushed history
entry, so pressing the browser Back button landed on the hash that had just
been revoked. /key/info answers 404 for it and the page shows "Key not found
in database".
The rotated hash now replaces the current entry instead of pushing a new one,
so Back from a just-regenerated key returns to the key list. Opening a key
from the table still pushes, so Back from a normally opened key is unchanged.
* feat(auto-router): support classifier reasoning effort
* fix(auto-router): harden classifier reasoning effort
* fix(ui): satisfy classifier config lint limits
* refactor(auto-router): simplify classifier effort support
* fix(auto-router): clear frontend-lint and type-discipline gates, trim LOC
---------
Co-authored-by: Tin Chi Lo <tin@berri.ai>
* fix(ui): clearing the organization picker no longer sends organization_id="" on key create
* fix(proxy): paginate Request Logs by conversation and aggregate session type counts and models server-side
* fix(proxy): keep access groups in sync when a model is renamed or deleted
* fix(proxy): cap the Request Logs conversation total like the row total
* fix(proxy): judge access group backing by the database for db models
A worker whose router has not polled the database yet still lists a sibling under its old
name, so a delete or rename handled there kept the stale name in every access group. Only
config-sourced deployments count as router backing now; db models are counted in the table.
* fix(ui): keep the conversation badge when an MCP call represents a conversation
A conversation that straddles the bounded page window can be represented by one of its MCP
rows, which showed a plain MCP badge and hid the session counts. The badge now reads the
server aggregates whenever the conversation has more than one call.
* fix(proxy): list every model of a conversation in Request Logs and keep the conversation badge for MCP representatives
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): type session spend aggregates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): satisfy request logs lint budget
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): cap per-session model aggregation in request logs
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: ratchet type-discipline budget after staging merge
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): send an explicit null when the key edit form clears the organization
Clearing the Organization picker in the key edit form wrote undefined into
the form value, and JSON.stringify drops undefined-valued keys, so
/key/update never saw the field and the key kept its old organization.
Writing null instead survives serialization, and the backend's
model_dump(exclude_unset=True) preserves it, so the column is set to NULL.
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Historical dirty spend on large installs was still unlabeled when the
matching token sat past the first page. Keep scanning until the digest
matches or the table ends.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* feat(cli): enable Claude Code gateway model discovery by default in lite claude
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cli): build agent env declaratively and document discovery key for lite up
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cli): keep build_agent_env within LIT002 type-discipline budget
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Required lint failed ruff format on the ternary that unwraps a polars DataFrame or list before alias recovery
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Key Activity charts already fell back to user_email. The top-keys tables
and usage export still printed '-' or a truncated hash. They now use the
same alias-then-email label.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Recovery already resolved the owner email for double-hashed spend keys,
then Key Activity dropped it. The Usage payload now carries user_email
and the key label falls back to that email before key-hash-...
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
The Python 3.10 smoke check imports the proxy without prisma, so PrismaError
is loaded only inside the DB helper. Recovery now returns frozen mappings
and ReadOnly TypedDict fields so the type-discipline budget stays put.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
The Usage recovery path was adding four BLE001 hits and failing the
strict-rule budget. Soft-fail only on PrismaError so a down token table
still falls through to SpendLogs.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Lint CI failed because ruff format splits the Set alias import and collapses a couple of long lines.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Recovery now resolves the key owner's email from UserTable via the
recovered token user_id, and SpendLogsMetadata keeps user_api_key_user_email
so new batch/export consumers see email without a separate user join.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Extract the Usage reverse-hash / SpendLogs alias recovery into a shared
helper and apply it when CloudZero and Focus export DailyUserSpend rows,
so BI pulls get api_key_alias back for historical v1.99 double-hashed keys
instead of null.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Callback log replay also omitted user_api_key_hash, so it could double-hash
spend rows the same way batch costing did. On the read path, Usage key
metadata now reverse-hashes orphaned DailyUserSpend.api_key values against
VerificationToken and falls back to SpendLogs metadata so historical dirty
rows show their api_key_alias again instead of key-hash-...
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Batch cost attribution and the legacy queue endpoint already store the
VerificationToken hash in user_api_key, but omitted user_api_key_hash.
Since v1.99 the spend-log writer re-hashes any key without that provenance
flag, so DailyUserSpend.api_key no longer joins VerificationToken and Usage
shows key-hash-... rows with null api_key_alias / user_email.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
prisma's `delete` returns None when the `where` clause matched no row
instead of raising, and the handler never looked at the return value. It
went straight on to filter an in-memory list that never held the name and
answered 200 "Credential deleted successfully", so an operator scripting
credential cleanup could not tell a real deletion from a typo.
Look at what the repository returned and answer 404 with the name, the
same rejection PATCH /credentials/{credential_name} already gives. A
credential that only exists in the config yaml is never written to the
table, so it now answers 404 too, which is honest: reporting success for
it is the same lie, since it comes back on the next proxy boot.
Adds regression tests for the delete 404, the still-working delete, the
config-yaml-only credential, and for the raise-not-return fix on both
DELETE /credentials/{credential_name} and GET /credentials, which
serialized a rejection as the 200 response body.
The config stub shared one list object between save_config and get_config, so the
DB overlay handed the endpoint back the very list it had just appended to and both
tests passed with the product fix reverted. Store the settings as JSON the way the
litellm_config row does, and check the duplicate guard against a list that only
ever existed in the DB.
The monitor reads the queue on its first pass, before it ever waits on a
request, so dropping a request made while spend_log_flush_requested is still
None delays nothing. Reordering the loop to wait first would turn that drop
into a real delay for the Responses chaining flow, and now fails this test.
`POST /v1/agents/{id}/make_public` appended the agent id to
`litellm.public_agent_groups` and only then called `get_config()`, which
re-applies the DB's `litellm_settings` over the module globals and threw the
append away. The config it saved was therefore a no-op: the endpoint answered
200 with an empty `public_agent_groups`, the agent never reached
`GET /public/agent_hub`, and re-publishing never hit the "already public" 400.
Read the config first, derive the new list from the refreshed globals, save it,
then update the global
Also fixes the e2e model hub spec, which is flaky for a second reason: the
"Make Models Public" modal preselects the groups that are already public, so a
blind click on "Select All" cleared them and left "Next" disabled for the full
15s action timeout. Check the box instead of toggling it, and wait for "Next"
to be enabled before clicking
Covers the reintroduction of a second module-level cache for the guardrail
translation mappings: remapping the loader between two pre-call hooks must
change which handler runs, and the module must expose no assignable map of
its own.
Streaming /v1/messages against a model served through the chat-completions
bridge (every non-Anthropic provider other than OpenAI) minted its msg_ id
inside the stream wrapper, so the spend row landed under the provider's own
completion id and the caller could not find the call by the only id it saw.
The wrapper now mints the id once in its constructor and hands it to the
logging object, the same way the Responses-API bridge does.
`PrismaClient.spend_log_flush_requested` was an `asyncio.Event` built at
import time, so it bound to whichever event loop first awaited it and every
later loop got `RuntimeError: ... is bound to a different event loop` out of
`_wait_for_spend_log_flush_request`. The queue monitor's blanket `except
Exception` swallowed that into its error logger, so the flush silently never
happened and the row sat in the worker's queue until the next poll.
The monitor now creates its own Event inside the loop that awaits it and
hands it to the client, and `request_spend_log_flush` signals through the
client instead of the class. A request that arrives before the monitor is
running is dropped and loses nothing, because the monitor reads the queue on
its first pass before it ever waits.
In CI this showed up as the proxy-endpoints shard flaking on
test_monitor_spend_logs_queue_flushes_as_soon_as_one_is_requested whenever
--dist=loadscope put the health-endpoint tests, which boot a proxy TestClient
and start a monitor, on the same worker ahead of the spend-log tests.
TestStreamingScanDedup restored the reduced module-level translation
mapping on teardown via monkeypatch, so under --dist=loadscope the
worker that ran only that class carried the reduced mapping into the
streaming block test modules. Tag routing tests now assert the eligible
deployment set directly instead of sampling ten random picks. The
liveliness latency check measures steady-state polls after a warm-up
request rather than the first request through a fresh app.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
