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Author SHA1 Message Date
yuneng-jiang
65e36b0298
Merge pull request #45011 from BerriAI/litellm_pgb_bump_1103
chore(docker): bump pgbouncer to 1.26.0
2026-10-07 10:32:50 -07:00
yuneng
497a3b406b chore(docker): bump pgbouncer to 1.26.0 2026-10-07 06:53:40 +00:00
yuneng-jiang
68b1fe1b66
Merge pull request #44776 from BerriAI/litellm_chore_8a10a6
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chore(release): refresh dependencies on stable/1.103.x and cut 1.103.4
2026-10-05 22:27:42 -07:00
Yuneng Jiang
0e6c47f8d1
chore: refresh uv.lock for 1.103.4 2026-10-05 18:54:46 -07:00
Yuneng Jiang
d040262bf8
bump: version 1.103.3 → 1.103.4 2026-10-05 18:54:27 -07:00
Yuneng Jiang
dc36db371c
chore(deps): bump source-map-js in the vscode-extension lockfile 2026-10-05 18:52:52 -07:00
Yuneng Jiang
7679ae853f
chore(deps): bump source-map-js and smol-toml in the dashboard lockfile 2026-10-05 18:52:52 -07:00
Yuneng Jiang
0c1ed2e155
chore(deps): bump next, moment and brace-expansion in the dashboard 2026-10-05 18:52:51 -07:00
Yuneng Jiang
eb91e815c0
chore(deps): bump werkzeug to 3.1.9 2026-10-05 18:51:41 -07:00
Yuneng Jiang
9bfde413b3
chore(deps): bump multidict to 6.9.1 2026-10-05 18:51:40 -07:00
Yuneng Jiang
1f388e5221
chore(deps): bump mako to 1.4.2 2026-10-05 18:51:40 -07:00
Yuneng Jiang
0cc25f2f18
chore(deps): bump langgraph-sdk to 0.4.4 2026-10-05 18:51:39 -07:00
Yuneng Jiang
6db4026e27
chore(deps): bump oauthlib to 4.0.0 2026-10-05 18:51:39 -07:00
Yuneng Jiang
41017f478d
chore(deps): bump fsspec to 2026.6.0 2026-10-05 18:51:38 -07:00
yuneng-jiang
ecae261b10
Merge pull request #44437 from BerriAI/litellm_chore_bba82d
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test(e2e): backport Together structured-output and text-completion fixes to stable/1.103.x
2026-10-03 14:11:07 -07:00
yuneng
ff6578183b test(e2e): align completion, SAIL, and spend-log fixtures with supported contracts (#43902)
Partial backport to stable/1.103.x: only the text completion endpoint test moves off the retired gpt-3.5-turbo-instruct to openai/gpt-5.4-nano with reasoning off. This line predates the OpenAI SDK rewrite of the test, so reasoning_effort goes through EndpointsClient.text_completions instead of extra_body. The SAIL, spend-log and coverage registry repairs are not needed for this line's e2e suite

(cherry picked from commit e61733b170)
2026-10-03 21:07:17 +00:00
yuneng
3896240d3b test(ci): repair stale tests and flaky CI infrastructure (#43983)
Partial backport to stable/1.103.x: only the Together AI structured-output e2e case moves to the hybrid reasoning backend with reasoning off, since the reasoning-only model it picked returned no content. The CI infrastructure and other test repairs are not needed for this line's e2e suite

(cherry picked from commit 6ca90b927c)
2026-10-03 21:07:17 +00:00
yuneng-jiang
8a7280ee1b
Merge pull request #44404 from BerriAI/litellm_chore_35b6b0
chore(release): backport #44341, #44346 to stable/1.103.x
2026-10-03 12:00:31 -07:00
devin-ai-integration[bot]
94d97b26f0
fix(responses): merge bridged tool calls into the same choice as the text (#44346)
* revert(responses): revert "fix(responses): keep gpt-5.4/5.5 tool calls on chat and merge bridged tool calls into one choice" (#44295)

This reverts commit ca1994e403.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(responses): merge bridged tool calls into the same choice as the text

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
(cherry picked from commit 5724117116)
2026-10-03 11:20:16 -07:00
devin-ai-integration[bot]
dabf756927
fix(proxy): stamp the client alias on a copy of each streamed chunk so pricing sees the deployment model (#44341)
* fix(proxy): stamp the client alias on a copy of each streamed chunk so pricing sees the deployment model

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(spend): streamed alias matching a capability rule bills the deployment price

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(spend): assert every streamed chunk carries the client alias

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(logging): log the client alias on the priced streamed response, the same as non-streamed

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
(cherry picked from commit 7b432d78d2)
2026-10-03 11:20:16 -07:00
yuneng-jiang
b74a2496c1
Merge pull request #44352 from BerriAI/litellm_chore_db5a8b
chore(deps): bump pyjwt, pypdf, tornado, urllib3 and gitpython for stable/1.103.x
2026-10-03 00:17:34 -07:00
yuneng
008bacc53f chore(deps): bump pyjwt, pypdf, tornado, urllib3 and gitpython in uv.lock for advisories
Lock-only bumps inside the existing pyproject ranges, each already at or below the version
main resolves: pyjwt 2.13.0 -> 2.15.0, pypdf 6.16.2 -> 6.19.0, tornado 6.5.8 -> 6.5.9,
urllib3 2.7.0 -> 2.8.0, gitpython 3.1.61 -> 3.1.62
2026-10-03 07:12:16 +00:00
yuneng-jiang
121ce723f5
Merge pull request #44309 from BerriAI/litellm_chore_ff7ad3
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chore(release): backport #42643 to stable/1.103.x
2026-10-02 19:03:44 -07:00
yuneng-jiang
0893321abf
chore(docker): bump wolfi-base digest to pick up glibc 2.44-r6 (#42643)
The pinned base's /etc/apk/world locks glibc-2.44=2.44-r1, so the apk upgrade in the runtime stage cannot move it. The new digest ships 2.44-r6 on amd64 and arm64

(cherry picked from commit bc911abdbb)
2026-10-02 18:58:46 -07:00
yuneng-jiang
79691289df
Merge pull request #44286 from BerriAI/litellm_fix_cbfd1b
fix(proxy-extras): stop the migration sanity check from building the hand-built SpendLogs indexes and cut 1.103.3
2026-10-02 17:15:54 -07:00
Yuneng Jiang
21995f87a4
chore(release): bump litellm 1.103.2 -> 1.103.3 for stable/1.103.x 2026-10-02 16:58:30 -07:00
Yuneng Jiang
4d245e1d9c
fix(proxy-extras): keep the post-migration sanity check from building the hand-built SpendLogs indexes
schema.prisma still declares the LiteLLM_SpendLogs (api_key, startTime) and (litellm_call_id) indexes while their migrations are now SELECT 1, so the v1 resolver's drift script recreated both with a blocking CREATE INDEX at boot. The drift script now drops those two statements before it is applied, matching filter_request_log_index_diff on main. The key metadata recovery fixture builds its index directly and the schema sync test exempts the two indexes.
2026-10-02 16:58:30 -07:00
yuneng-jiang
3e32c0cd8e
Merge pull request #44225 from BerriAI/litellm_stable1103_extras_post1
chore(release): bump litellm-proxy-extras 0.4.100 -> 0.4.100.post1 for stable/1.103.x
2026-10-02 12:32:35 -07:00
yuneng
00b77ec8b5 chore(release): bump litellm-proxy-extras 0.4.100 -> 0.4.100.post1 for stable/1.103.x 2026-10-02 19:21:25 +00:00
yuneng-jiang
b0c4d5b6d4
Merge pull request #44205 from BerriAI/litellm_stable_1_103_x_enforce_migration_check_noop_index_migrations
fix(proxy): enforce the migration check by default and stop building SpendLogs indexes in migrations (stable/1.103.x)
2026-10-02 12:14:27 -07:00
yassin
6e65828d7f fix(proxy): enforce the migration check by default and stop building SpendLogs indexes in migrations
ENFORCE_PRISMA_MIGRATION_CHECK now defaults to true in both the proxy CLI and the standalone migration entrypoint, with ENFORCE_PRISMA_MIGRATION_CHECK=false or --no-enforce_prisma_migration_check as the opt-out. The two LiteLLM_SpendLogs index migrations become SELECT 1 so operators build those indexes online by hand.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-10-02 17:20:02 +00:00
yuneng-jiang
f69b2103df
Merge pull request #43984 from BerriAI/litellm_backport_lit9020_stable_1_103_x
fix(proxy): backport #43962 to stable/1.103.x
2026-09-30 22:40:24 -07:00
yuneng-jiang
2869a6f482
fix(proxy): restore pre-config-wins handling of pass-through endpoints (#43962)
* fix(proxy): restore pre-config-wins handling of pass-through endpoints

Config-wins (#41779) made general_settings.pass_through_endpoints a config-owned key. The DB reader then got the config list back as if it were DB rows, re-registered each entry without forward_headers on every DB sync, and the stripped copy won the route lookup, so a config pass-through with forward_headers: true stopped forwarding Authorization. UI create, update and delete of pass-throughs were also rejected while the config declared any.

This puts pass-throughs back on their pre-#41779 path: the settings store no longer lets the config own the key, the config list is captured env-resolved at load_config, each DB sync merges DB entries with config entries on paths the DB does not declare, and /config/field/info reads the stored rows only. A UI pass-through write re-applies that merge immediately so the config entries stay served until the next sync.

* fix(proxy): keep config pass-throughs in every reload of the merged list

get_config now returns DB pass-throughs plus config ones on other paths,
each DB sync republishes that merged list, and /config/field/info reads
pass_through_endpoints from the DB row so a UI write never drops stored
entries when models are not stored in the DB

* fix(proxy): keep serving pass-throughs while the config file reloads

load_yaml cleared the runtime pass-through list, so auth: false routes
answered 401 while get_config awaited the database

* fix(proxy): read stored pass-throughs from the writer before a UI write

A lagging read replica could return an older list, and the UI create and
edit flows write the whole field back

* fix(proxy): apply config file pass-through auth changes on reload

The kept runtime list was merged as if it were DB entries, so an edited
config entry on the same path was dropped. Merge the stored DB row with
the fresh config instead, and give the field-info test mock a writer

* fix(proxy): keep pass-throughs served while a DB sync reads the database

get_config resets the stored DB rows before reading them again, which
cleared the served pass-through list and made auth: false routes answer
401 for the length of the read

* refactor(proxy): move the settings store reload out of the loop

basedpyright rejects a Final variable assigned inside a loop

(cherry picked from commit 2eb2bf130b)
2026-09-30 22:23:33 -07:00
Mateo Wang
afbda352f1
Merge pull request #43662 from BerriAI/litellm_backport_safeguards_stable_1_103_x
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fix(anthropic): backport #42152 and #42288 to stable/1.103.x
2026-09-30 16:40:30 -07:00
Mateo Wang
f14625652a
Merge pull request #43897 from BerriAI/litellm_backport_usage_attribution_stable_1_103_x
fix(proxy): backport #40541, #43642, and #43656 to stable/1.103.x for v1.103.2
2026-09-30 16:30:56 -07:00
mateo-berri
fe872527f1 chore(release): bump litellm-enterprise 0.1.69 -> 0.1.69.post1 for stable/1.103.x 2026-09-30 15:02:08 -07:00
mateo-berri
1bbc9ee1f9 test(integration): register the daily activity key metadata contracts on stable/1.103.x 2026-09-30 12:35:46 -07:00
mateo-berri
460d51fd85 bump: version 1.103.2 2026-09-30 12:03:00 -07:00
devin-ai-integration[bot]
97f670a942 fix(proxy): look up hashed key names with two spend log rows per key (#43656)
Backport of #43656 to stable/1.103.x.
Cherry-picked from 61a73c59b0 (main).
2026-09-30 12:02:36 -07:00
devin-ai-integration[bot]
00b8664bbd fix(proxy): recover session key owners from daily spend for usage attribution (#43642)
Backport of #43642 to stable/1.103.x.
Cherry-picked from f5a1c9f1f1 (main).
2026-09-30 11:56:46 -07:00
yuneng-jiang
74952e95ac test(integration): add the scratch_database harness helper
Hand-ported prerequisite for the #43642 backport to stable/1.103.x.
Taken from dd636373229b1ab3bfb2ed5b9b17b0ebd68b3ac7 (#43288, main), scratch_database only.
2026-09-30 11:56:46 -07:00
Mateo Wang
a746ac2462 fix(spend): attribute CLI session spend to the per-user cli-session alias instead of the hashed session token (#40541)
Backport of #40541 to stable/1.103.x.
Cherry-picked from 25fb7810c2 (main).
2026-09-30 11:43:02 -07:00
yuneng-jiang
a32e70a196
Merge pull request #43824 from BerriAI/litellm_sync_stable_1_103_x
chore(release): sync stable/1.103.x to v1.103.1
2026-09-30 11:00:07 -07:00
yuneng-jiang
580bde9a2d
Merge pull request #13 from BerriAI/litellm_session_token_1_103_x
refactor(auth): bind UI/CLI session tokens to their own AES-GCM context (stable/1.103.x)
2026-09-29 15:39:29 -07:00
Yuneng Jiang
d3bf006613
chore(lint): scope a TRY004 suppression to the bearer-token salt key check
This line's ruff strict budget has no headroom for the one TRY004 the
backport adds; the raise reports missing configuration, not a bad type.
2026-09-29 15:34:35 -07:00
Yuneng Jiang
a80eacacee
refactor(auth): bind UI/CLI session tokens to their own AES-GCM context
Backport of BerriAI/litellm-private#5 (12981f93d3) onto stable/1.103.x, applied as
the PR's net diff so main-only intermediate refactors stay out.
2026-09-29 15:17:24 -07:00
mateo-berri
3b00260b86 fix(azure_ai): add the dangerous-tool-use beta when Foundry gets safeguards
The proxy never forwards client anthropic-beta headers to azure_ai, so Foundry
400s on safeguards without the beta. Add it on the provider side when the request
carries safeguards, the way the Vertex path does.
2026-09-28 22:48:03 -07:00
mateo-berri
44115c5f2b fix(anthropic): forward the dangerous-tool-use beta to Azure AI Foundry
Foundry answers safeguards without the dangerous-tool-use-2026-09-03 beta
with a 400, and the azure_ai beta map dropped that beta, so Claude Code auto
mode requests through the gateway turned from 200 into 400 once safeguards
started passing through
2026-09-28 22:25:13 -07:00
mateo-berri
4982a1e111 chore(test): keep the backported Vertex safeguards test within the line's test-quality budget
Adds a test-quality-ok marker on the one patch.object the picked Vertex test needs, since the GCP token exchange runs before the faked HTTP boundary. Test-only, no runtime change.
2026-09-28 21:15:27 -07:00
Mateo Wang
594f0d1eaa fix(anthropic): forward Claude Code safeguards and dangerous-tool-use beta to Bedrock Invoke and Vertex on /v1/messages (#42288)
Backport of #42288 to stable/1.103.x.
Cherry-picked from fc82f6e8fa (main, first parent). Its Bedrock Mantle beta map and Mantle-only test are left out, since this line has no bedrock_mantle beta map and its Mantle messages path reuses the Bedrock Invoke one.
2026-09-28 20:07:52 -07:00
Yassin Kortam
e0850bab88 fix(anthropic): forward safeguards and anthropic-beta unchanged on native /v1/messages (#42152)
Backport of #42152 to stable/1.103.x.
Cherry-picked from e912ebe999 (main, first parent).
2026-09-28 20:02:24 -07:00
yuneng-jiang
e7d8bbc5de
Merge pull request #6 from BerriAI/litellm_bump_1_103_1
chore: bump litellm 1.103.0 -> 1.103.1
2026-09-28 17:38:24 -07:00
Yuneng Jiang
bf02f06913
bump: litellm 1.103.0 -> 1.103.1 2026-09-28 15:07:12 -07:00
yuneng-jiang
c991f4b01f
fix(proxy): unregister logging callbacks removed from the stored config (#43429)
* fix(proxy): unregister logging callbacks removed from the stored config

POST /config/callback/delete saved the config and resynced, but the resync only
ever added callbacks, so a deleted callback kept exporting and kept showing in
/get/config/callbacks as read-only on every worker.

ProxyConfig now tracks which callback list entries each DB config sync
registered and unregisters them once the stored config stops listing them.
Callbacks it did not register (YAML, code) are never touched, and a failed
config load skips the sync instead of treating the config as empty.

* refactor(proxy): keep callback sync comprehensions to one for clause
2026-09-27 00:50:16 -07:00
yuneng-jiang
cc111d1ae5
fix(streaming): backport text-completion usage fix and e2e provider-flake tolerance to rc/1.103.0 (#43400)
* test(e2e): tolerate provider-side flakes on five full-suite cells (#42628)

* test(e2e): tolerate provider-side flakes on five full-suite cells

Mistral OCR retries a provider-relayed 429 with backoff, the Vertex vision
probe turns reasoning off so its 32 tokens go to the answer, the Vertex
cache cell spaces eight never-seen prefixes 15s apart around Google's
nondeterministic minimum-token rejection and prices the cached tokens
instead of prompt_tokens, and the Azure content-policy cell resends the
jailbreak prompt while Azure skips its filter

* test(e2e): shorten the new helper docstrings

* test(e2e): accept a relayed provider 429 on the rust OCR cells

The gateway already retries a provider 429 three times per call and the
Mistral key is shared across pipelines, so a throttle can hold across all
four attempts of the OCR cell. After the bounded retries the cell now
accepts the gateway's faithful relay of the provider's 429 (throttling_error,
code 429) as its second expected outcome; the gateway's own 429 and any
other error still fail the cell at once.

* test(e2e): drop the harness unit tests, the live cells cover the helpers

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
(cherry picked from commit 41ca4656cd)

* fix(streaming): keep litellm Usage on text-completion usage chunks (#43047)

* fix(streaming): keep litellm Usage on text-completion usage chunks

* fix(streaming): convert provider usage to litellm Usage instead of dropping it

(cherry picked from commit be35b22dfc)

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-09-26 19:12:06 -07:00
yuneng-jiang
4dbbe6eddd
test(ci): fix the e2e and integration reds left on rc/1.103.0 after #43382 and #43388 (#43391)
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The batch cleanup leftover warning used a class defined in a test-directory module. The xdist controller cannot import it, so an uncaught leftover warning crashed the whole e2e run. It is now a plain UserWarning.

The integration harness backport missed the workers option and Gateway.request headers that the OTel conversation id tests use.
2026-09-26 17:54:12 -07:00
yuneng-jiang
8aca86a571
test(e2e): clear the two rc/1.103.0 e2e reds owned by upstream providers (#43388)
Backports the batch cleanup half of #43321 so an Azure cancel still in progress after 120s leaves a warning instead of a teardown error, and points the MCP Tools UI test at DeepWiki's renamed ask_wiki_question tool.
2026-09-26 17:18:10 -07:00
yuneng-jiang
e640c0eb41
test(integration): make rc/1.103.0 integration groups collect and pass again (#43382)
Adds the OwnedProxy harness the #42486 backport's OTel test imports, registers the #43029 backport's spend flush test in contracts.json with its covers marker, and aligns the MCP tool failure assertion with main.
2026-09-26 17:00:41 -07:00
yuneng-jiang
10e77ce406
fix(caching): stand default cache points down when extra_body hides a direct client mark (#43342)
* fix(caching): stand default cache points down when extra_body hides a direct client mark

On native /v1/messages the extra_body envelope is dropped, so a client tool mark or root cache_control reaches Anthropic even when extra_body overrides it. The stand-down check only counted the envelope-merged view and injected two default marks on top of the client's.

(cherry picked from commit 01ef7c4725)

* fix(caching): keep chat completions on the envelope-merged mark count for the default stand-down

Chat completions merge extra_body over the request, so a direct tool mark that extra_body replaces never reaches the provider there. Only /v1/messages, where the native transforms drop the envelope, needs to count marks on both sides.

(cherry picked from commit a9c5fa760e)
2026-09-26 16:45:26 -07:00
yuneng-jiang
6076c0a058
fix(jwt,otel): backport session conversation id and JWT team header selection to rc/1.103.0 (#43343)
* feat(otel): emit gen_ai.conversation.id from the caller's session id on v2 LLM spans (#42486)

* feat(otel): emit gen_ai.conversation.id from the caller's session id on v2 LLM spans

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): keep the caller's header session under missing_session_id: generate and read replayed payload session ids

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): drop only the proxy-minted session id so a caller id on the other metadata key survives

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): keep a replayed session id hidden when it only echoes the payload trace id

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): keep a replayed session id even when the payload trace id fell back to it

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(otel): stop reading the replayed payload's session id, the generated marker does not survive replay

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(integration): audit gen_ai.conversation.id on otel v2 spans through a real proxy, sink and postgres

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(integration): keep otel conversation rigs alive for the whole session so shuffled shards do not reboot the proxy per test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(otel): stop the audit rig proxies from probing sibling test peers for model info

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(otel): record accepted OTLP batches in the sink instead of mutating the collector

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(otel): guard the accepted batch deque so snapshots cannot race sink appends

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: mrinal <mrinal@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng <yucheng@berri.ai>
(cherry picked from commit a3196907e4)

* fix(jwt): accept a team alias in x-litellm-team-id (#42445)

* fix(jwt): accept a team alias in x-litellm-team-id

The header only matched canonical team ids, so a JWT caller selecting one of their teams by its alias got a 403 even though they belonged to it. The header value is now resolved through the existing alias lookup before the JWT allowed-team check and the DB membership fallback, while a value that is already a team id never costs an alias lookup and denials keep naming the value the caller sent

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(jwt): only alias a header team id the database provably lacks

Under fallback_to_db_teams a header value whose team row read fails for any reason other than TeamNotFoundError now keeps the membership denial instead of falling through to the alias lookup, so a degraded read cannot select a different team that carries the value as an alias. Drops the HeaderTeam docstring that only restated its fields

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: ryan <ryan@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
(cherry picked from commit 071cb49d32)

* fix(jwt): say x-litellm-team-id matched no team id or alias in the 403 (#42495)

* fix(jwt): say x-litellm-team-id matched no team id or alias in the 403

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(jwt): tell the caller when x-litellm-team-id names an alias shared by several teams

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(jwt): deny a shared x-litellm-team-id alias exactly like an unknown value

A distinct 403 for an alias several teams share was raised before the
allowed-teams check, so any JWT could probe which aliases exist. The
alias lookup now treats the duplicate as a miss, and both denials say
the value does not resolve to a team id or a unique team alias, which
is true for unknown, unauthorized and duplicate values alike

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: ryan <ryan@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
(cherry picked from commit 08639fcf42)

* fix(jwt): let x-litellm-team-id select DB membership teams when the token also carries a team claim (#43206)

* fix(jwt): let x-litellm-team-id select DB membership teams when the token also carries a team claim

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* docs(jwt): describe header team selection under fallback_to_db_teams

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>
(cherry picked from commit 7b4fd47c6e)

---------

Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mrinal <mrinal@berri.ai>
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: ryan <ryan@berri.ai>
Co-authored-by: yassin <yassin@berri.ai>
2026-09-26 15:03:25 -07:00
yuneng-jiang
6bfc987349
chore: update Next.js build artifacts (2026-09-26 18:18 UTC, node v24.19.0) (#43328) 2026-09-26 11:48:11 -07:00
yuneng-jiang
6397b3603d
fix: backport five regression fixes to rc/1.103.0 (#43331)
* fix: apply configured cache_control_injection_points beside client cache_control marks (#41956)

(cherry picked from commit d8267d507d)

* fix(token_counter): count replayed redacted_thinking blocks so prompt_caching keeps pinning (#42069)

(cherry picked from commit 0e7cf5113e)

* fix(mcp): return camelCase tool keys from /v1/mcp/tools after the SDK 2 upgrade (#42352)

(cherry picked from commit 5eb4e30f29)

* fix(rust_bridge): keep the Messages route on Python until the Rust path is ready (#42517)

rc/1.103.0 has no token counter or tokenizer routes in the catalog, so only the Messages rule moves to PYTHON_ONLY

(cherry picked from commit 85ed18e8f2)

* fix(proxy): stop leaking periodic tasks on every DB config reload (#42784)

(cherry picked from commit fc87a06f00)

---------

Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-26 11:47:22 -07:00
yuneng-jiang
4d08789101
fix(proxy): pass team member spend rows as jsonb so a $0 flush cannot poison the pool connection (#43029) (#43323)
Prisma types a raw array parameter from the first batch a connection sees. After a flush in
which every member cost was a whole number (a free model), the connection's cached statement
expected int8[] and every later fractional batch on it failed with "improper binary format in
array element", so member spend silently stopped landing while team spend kept rising.

The rows now travel as one JSON document unpacked by jsonb_to_recordset with the column types
declared in SQL, so Postgres types the numbers and the batch shape no longer matters.

(cherry picked from commit 5e4b1b9df0)

Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
2026-09-26 11:15:05 -07:00
yuneng-jiang
a78a439c68
revert(usage): remove the top-N aggregated key cap and daily global spend rollup code from rc/1.103.0 (#43326)
Reverts the code from #41324 (merge 87694c26ef) and #41293 (merge 2e46b10320).
The LiteLLM_DailyGlobalSpend model and migration stay so databases that applied
rc.1 keep a consistent table and rollup marker when the feature returns.
2026-09-26 11:14:53 -07:00
Mateo Wang
ed9ae4fc8c
Merge pull request #42658 from BerriAI/litellm_backport_42607_rc_1_103_0
fix(bedrock): backport the /v1/messages Invoke streaming pass-through to rc/1.103.0 (#42607)
2026-09-23 11:11:02 -07:00
devin-ai-integration[bot]
4a00468f38 fix(bedrock): stream /v1/messages Invoke bytes through instead of holding them in a 1024-byte chunker (#42607)
* fix(bedrock): stream /v1/messages Invoke bytes through instead of holding them in a 1024-byte chunker

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(bedrock): apply ruff format to invoke messages stream passthrough

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* style(bedrock): drop drive-by reformat of existing invoke messages tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(bedrock): collect streamed chunks into a tuple in passthrough regression test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(bedrock): give the passthrough regression test a 10s first-chunk budget

* test(bedrock): type the eventstream frame helper's payload as Mapping[str, object]

* test(bedrock): take the gated byte stream's chunks as an immutable Sequence

---------

Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
(cherry picked from commit 975bd28549)
2026-09-22 20:03:14 -07:00
yuneng-jiang
ccf5e8c93a
Merge pull request #42081 from BerriAI/litellm_skip_bedrock_govcloud_batch_e2e
test(batches): skip the Bedrock GovCloud batch e2e until its secrets are provisioned
2026-09-19 20:08:52 -07:00
Yuneng Jiang
379d256eb9
test(batches): skip the Bedrock GovCloud batch e2e until its secrets are provisioned
The test resolves four AWS_GOVCLOUD_* values through os.environ/ references on
the deployment, and none of them is injected into the e2e stack, so the upload
returns 500 "S3 bucket_name is required" and the test fails on configuration
rather than on the GovCloud partition behavior it guards.

The runner podSpec mounts 29 individual secretKeyRef entries from
litellm-provider-keys with no envFrom, and the string "govcloud" appears
nowhere in project-releaser, so nothing supplies these values today. The
commercial-partition Bedrock batch tests resolve their own os.environ/ bucket
and pass, which rules out the reference syntax and leaves the absent secrets as
the only cause.

Skipped rather than weakened, matching the LIT-5027 and LIT-4820 markers in
this file: the assertions stay as the correct contract and the marker names the
condition for removing it.

Reports 1 skipped instead of 1 failed.
2026-09-19 19:55:07 -07:00
yuneng-jiang
cc449198c7
Merge pull request #42076 from BerriAI/litellm_rc_1_103_0_gcs_autorouter_golden
test(logging): add autorouter estimate keys to the GCS pub/sub spend-log golden
2026-09-19 19:26:01 -07:00
yuneng-jiang
840f033f8c
Merge pull request #42075 from BerriAI/litellm_rc_1_103_0_mcp2_test_helpers
test(mcp): migrate the mcp test helpers to the mcp 2.x MCPServer API
2026-09-19 19:25:25 -07:00
Yuneng Jiang
dcd6e0def7
test(logging): add autorouter estimate keys to the GCS pub/sub spend-log golden
The spend-log payload now carries metadata.autorouter_savings_estimate and
metadata.autorouter_baseline_observation, but the golden this suite compares
against does not list them, so the exact-match check reports them as extra
keys and logging_testing goes red on the release candidate.

This backports the golden verbatim from main, where the same change landed in
09e14a485c after rc/1.103.0 was cut.

tests/logging_callback_tests/test_gcs_pub_sub.py::test_async_gcs_pub_sub_v1:
1 failed before, 1 passed after.
2026-09-19 19:25:17 -07:00
Yuneng Jiang
9f79a59a41
test(mcp): migrate the mcp test helpers to the mcp 2.x MCPServer API
pyproject pins mcp>=2.2.0,<3, where FastMCP was renamed to MCPServer and
stateless_http, json_response, transport_security, host and port moved off
the constructor onto streamable_http_app() and run(). The two helpers still
imported mcp.server.fastmcp, so every module reaching them died at collection
and integration-extensions went red on the release candidate.

This ports the helpers verbatim from main, where the same migration already
landed in 479360ae87 after rc/1.103.0 was cut. Only the two helper files are
taken; the rest of that commit restores unrelated test surface.

Collection on the four affected modules: 4 errors and 0 tests before, 0
errors and 6 tests after.
2026-09-19 19:09:46 -07:00
420 changed files with 9691 additions and 3338 deletions

View file

@ -1,16 +1,16 @@
# syntax=docker/dockerfile:1.7
# Base image for building
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
# Runtime image
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
# Pinned by digest like the other base images; bump explicitly on Node upgrades.
ARG UI_BUILD_IMAGE=node:24.19-alpine3.24@sha256:d32cdf619f63fe0471182d08996dd516c6275bb5fd31ae06e55a570bd9e1ad43
# Checksum from https://www.pgbouncer.org/downloads/ (the Wolfi repo only carries 1.24.x)
ARG PGBOUNCER_VERSION=1.25.2
ARG PGBOUNCER_SHA256=924ad35113fd0a71c8e2dbe85b5d03445532e2b7b37a9f8a48983beea238b332
ARG PGBOUNCER_VERSION=1.26.0
ARG PGBOUNCER_SHA256=afd25dd61ee6775d37b40629b87ce08736b3e6955f3057bb212e410fbf21c71d
FROM $UV_IMAGE AS uvbin

View file

@ -1,5 +1,5 @@
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
FROM $UV_IMAGE AS uvbin

View file

@ -1,16 +1,16 @@
# syntax=docker/dockerfile:1.7
# Base image for building
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
# Runtime image
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
# Pinned by digest like the other base images; bump explicitly on Node upgrades.
ARG UI_BUILD_IMAGE=node:24.19-alpine3.24@sha256:d32cdf619f63fe0471182d08996dd516c6275bb5fd31ae06e55a570bd9e1ad43
# Checksum from https://www.pgbouncer.org/downloads/ (the Wolfi repo only carries 1.24.x)
ARG PGBOUNCER_VERSION=1.25.2
ARG PGBOUNCER_SHA256=924ad35113fd0a71c8e2dbe85b5d03445532e2b7b37a9f8a48983beea238b332
ARG PGBOUNCER_VERSION=1.26.0
ARG PGBOUNCER_SHA256=afd25dd61ee6775d37b40629b87ce08736b3e6955f3057bb212e410fbf21c71d
FROM $UV_IMAGE AS uvbin

View file

@ -1,15 +1,15 @@
# syntax=docker/dockerfile:1.7
# Base images
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG PROXY_EXTRAS_SOURCE=published
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
# Pinned by digest like the other base images; bump explicitly on Node upgrades.
ARG UI_BUILD_IMAGE=node:24.19-alpine3.24@sha256:d32cdf619f63fe0471182d08996dd516c6275bb5fd31ae06e55a570bd9e1ad43
# Checksum from https://www.pgbouncer.org/downloads/ (the Wolfi repo only carries 1.24.x)
ARG PGBOUNCER_VERSION=1.25.2
ARG PGBOUNCER_SHA256=924ad35113fd0a71c8e2dbe85b5d03445532e2b7b37a9f8a48983beea238b332
ARG PGBOUNCER_VERSION=1.26.0
ARG PGBOUNCER_SHA256=afd25dd61ee6775d37b40629b87ce08736b3e6955f3057bb212e410fbf21c71d
FROM $UV_IMAGE AS uvbin

View file

@ -10,6 +10,7 @@ from typing import TYPE_CHECKING, Final, List, Literal, Optional, Tuple, cast
from litellm._logging import verbose_proxy_logger
from litellm._uuid import uuid
from litellm.constants import (
CLI_SESSION_KEY_PREFIX,
MANAGED_OBJECT_STALENESS_CUTOFF_DAYS,
MAX_OBJECTS_PER_POLL_CYCLE,
)
@ -112,10 +113,12 @@ class CheckBatchCost:
verbose_proxy_logger.error(f"CheckBatchCost: could not look up user {user_id} for batch {batch_id}: {e}")
return {}
async def _get_key_alias(self, batch_id: str, api_key: str | None) -> str | None:
async def _get_key_alias(self, batch_id: str, api_key: str | None, created_by: str | None) -> str | None:
"""Resolve the creating virtual key's alias from its hashed token."""
if not api_key:
return None
if created_by and api_key == f"{CLI_SESSION_KEY_PREFIX}-{created_by}":
return api_key
try:
key_row: prisma_models.LiteLLM_VerificationToken | None = (
await self.prisma_client.db.litellm_verificationtoken.find_unique(
@ -204,7 +207,7 @@ class CheckBatchCost:
**(await self._get_user_info(batch_id, job.created_by)),
}
key_alias = await self._get_key_alias(batch_id, api_key)
key_alias = await self._get_key_alias(batch_id, api_key, job.created_by)
if key_alias is not None:
metadata["user_api_key_alias"] = key_alias
team_alias = await self._get_team_alias(team_id)

View file

@ -50,6 +50,7 @@ from litellm.proxy._types import (
ProxyException,
UserAPIKeyAuth,
)
from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
from litellm.proxy.openai_files_endpoints.common_utils import (
BATCH_CREATE_HIDDEN_PARAM,
FILE_LIST_CONTINUATION_CHUNK_SIZE,
@ -359,7 +360,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
from prisma import Json
api_key = user_api_key_dict.api_key or None
api_key = LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict) or None
attribution_columns = (
{
**({"api_key": api_key} if api_key is not None else {}),

View file

@ -1,6 +1,6 @@
[project]
name = "litellm-enterprise"
version = "0.1.69"
version = "0.1.69.post1"
description = "Package for LiteLLM Enterprise features"
readme = "README.md"
requires-python = ">=3.9"
@ -26,7 +26,7 @@ required-version = ">=0.10.9"
module-root = ""
[tool.commitizen]
version = "0.1.69"
version = "0.1.69.post1"
version_files = [
"pyproject.toml:^version",
"../pyproject.toml:litellm-enterprise==",

View file

@ -1,9 +1,9 @@
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:1d95114038f76513a9ace6fca107d5582b08c65981f81f61cb56bf7fd2ef216d
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
# Checksum from https://www.pgbouncer.org/downloads/ (the Wolfi repo only carries 1.24.x)
ARG PGBOUNCER_VERSION=1.25.2
ARG PGBOUNCER_SHA256=924ad35113fd0a71c8e2dbe85b5d03445532e2b7b37a9f8a48983beea238b332
ARG PGBOUNCER_VERSION=1.26.0
ARG PGBOUNCER_SHA256=afd25dd61ee6775d37b40629b87ce08736b3e6955f3057bb212e410fbf21c71d
FROM $UV_IMAGE AS uvbin

View file

@ -1,2 +1 @@
-- CreateIndex
CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogs_api_key_startTime_idx" ON "LiteLLM_SpendLogs"("api_key", "startTime");
SELECT 1;

View file

@ -1,12 +1 @@
-- CreateIndex (CONCURRENTLY)
--
-- Disclaimer:
-- - CREATE INDEX CONCURRENTLY cannot run inside a transaction. This migration must stay a
-- single statement so Prisma Migrate on PostgreSQL can apply it outside a transaction.
-- - Builds are slower and use more I/O than a blocking CREATE INDEX; if the build is
-- interrupted, Postgres may leave an INVALID index that must be dropped and recreated.
-- - Do not edit this file after it has been applied to any database: Prisma checksums
-- migrations; add a new migration instead.
-- - Requires PostgreSQL that supports CONCURRENTLY with IF NOT EXISTS (use a new migration
-- without IF NOT EXISTS if you must support older versions).
CREATE INDEX CONCURRENTLY IF NOT EXISTS "LiteLLM_SpendLogs_litellm_call_id_idx" ON "LiteLLM_SpendLogs"("litellm_call_id");
SELECT 1;

View file

@ -115,6 +115,17 @@ _SPEND_LOGS_PK_CLAUSE_RE = re.compile(
re.IGNORECASE,
)
HAND_BUILT_SPEND_LOGS_INDEXES: Final = frozenset(
{
"LiteLLM_SpendLogs_api_key_startTime_idx",
"LiteLLM_SpendLogs_litellm_call_id_idx",
}
)
_CREATE_INDEX_RE: Final = re.compile(
r'^\s*CREATE\s+(?:UNIQUE\s+)?INDEX\s+(?:CONCURRENTLY\s+)?(?:IF\s+NOT\s+EXISTS\s+)?"(?P<index>[^"]+)"\s+ON\b',
re.IGNORECASE,
)
PARTITIONED_SPEND_LOGS_PUSH_ERROR = (
"LiteLLM_SpendLogs is a partitioned table (see db_scripts/partition_spend_logs.sql), "
"so its primary key must include the partition key (\"startTime\"). `prisma db push` "
@ -165,6 +176,21 @@ def filter_partitioned_spend_logs_diff(diff_sql: str) -> str:
return "".join(f"{statement};\n\n" for statement in kept)
def filter_hand_built_spend_logs_index_diff(diff_sql: str) -> str:
"""The `prisma migrate diff` script without the statements that create the
LiteLLM_SpendLogs indexes schema.prisma declares but the migrations deliberately
leave for operators to build online."""
kept: Final = tuple(
statement for statement in diff_sql.split(";") if not _creates_hand_built_spend_logs_index(statement)
)
return ";".join(kept) if any(part.strip() for part in kept) else ""
def _creates_hand_built_spend_logs_index(statement: str) -> bool:
match: Final = _CREATE_INDEX_RE.match(_without_sql_comments(statement))
return match is not None and match["index"] in HAND_BUILT_SPEND_LOGS_INDEXES
def _migration_timestamp(name: str) -> int:
"""Extract the leading `YYYYMMDDHHMMSS` timestamp from a migration name.
@ -433,6 +459,20 @@ class ProxyExtrasDBManager:
return True
return False
@staticmethod
def _filter_drift_script(diff_sql: str) -> str:
"""The drift script without the hand-built SpendLogs indexes and, when
LiteLLM_SpendLogs is partitioned, without its primary-key rewrite and
partitioning artifacts."""
without_indexes: Final = filter_hand_built_spend_logs_index_diff(diff_sql)
if not ProxyExtrasDBManager.spend_logs_is_partitioned():
return without_indexes
logger.info(
"LiteLLM_SpendLogs is partitioned; removed its primary-key "
"rewrite and partitioning artifacts from the drift script"
)
return filter_partitioned_spend_logs_diff(without_indexes)
@staticmethod
def _resolve_all_migrations(
migrations_dir: str, schema_path: str, mark_all_applied: bool = True
@ -513,21 +553,14 @@ class ProxyExtrasDBManager:
return
logger.info(f"Migration diff created at {diff_sql_path}")
if ProxyExtrasDBManager.spend_logs_is_partitioned():
filtered_sql = filter_partitioned_spend_logs_diff(
diff_sql_path.read_text()
)
diff_sql_path.write_text(filtered_sql)
logger.info(
"LiteLLM_SpendLogs is partitioned; removed its primary-key "
"rewrite and partitioning artifacts from the drift script"
)
if not filtered_sql.strip():
logger.info("Drift script is empty after filtering; nothing to apply")
if not mark_all_applied:
return
ProxyExtrasDBManager._mark_migrations_applied(migrations_dir)
filtered_sql: Final = ProxyExtrasDBManager._filter_drift_script(diff_sql_path.read_text())
diff_sql_path.write_text(filtered_sql)
if not filtered_sql.strip():
logger.info("Drift script is empty after filtering; nothing to apply")
if not mark_all_applied:
return
ProxyExtrasDBManager._mark_migrations_applied(migrations_dir)
return
# 2. Run prisma db execute to apply the migration
applied_ok = False

View file

@ -1,6 +1,6 @@
[project]
name = "litellm-proxy-extras"
version = "0.4.100"
version = "0.4.100.post1"
description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
readme = "README.md"
requires-python = ">=3.9"
@ -26,7 +26,7 @@ required-version = ">=0.10.9"
module-root = ""
[tool.commitizen]
version = "0.4.100"
version = "0.4.100.post1"
version_files = [
"pyproject.toml:^version",
"../pyproject.toml:litellm-proxy-extras==",

View file

@ -11,6 +11,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": "context-management-2025-06-27",
"dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03",
"effort-2025-11-24": "effort-2025-11-24",
"fast-mode-2026-02-01": "fast-mode-2026-02-01",
"files-api-2025-04-14": "files-api-2025-04-14",
@ -44,6 +45,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": "context-management-2025-06-27",
"dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03",
"effort-2025-11-24": "effort-2025-11-24",
"fast-mode-2026-02-01": null,
"files-api-2025-04-14": "files-api-2025-04-14",
@ -76,6 +78,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": null,
"dangerous-tool-use-2026-09-03": null,
"effort-2025-11-24": "effort-2025-11-24",
"fast-mode-2026-02-01": null,
"files-api-2025-04-14": null,
@ -109,6 +112,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": "context-management-2025-06-27",
"dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03",
"effort-2025-11-24": "effort-2025-11-24",
"fast-mode-2026-02-01": null,
"files-api-2025-04-14": null,
@ -142,6 +146,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": "context-management-2025-06-27",
"dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03",
"effort-2025-11-24": null,
"fast-mode-2026-02-01": null,
"files-api-2025-04-14": null,
@ -175,6 +180,7 @@
"computer-use-2025-11-24": "computer-use-2025-11-24",
"context-1m-2025-08-07": "context-1m-2025-08-07",
"context-management-2025-06-27": "context-management-2025-06-27",
"dangerous-tool-use-2026-09-03": null,
"effort-2025-11-24": "effort-2025-11-24",
"fast-mode-2026-02-01": "fast-mode-2026-02-01",
"files-api-2025-04-14": "files-api-2025-04-14",

View file

@ -188,7 +188,7 @@ def _reasoning_items_from_output_items(output_items: Sequence[object]) -> tuple[
def _as_chat_reasoning_items(
reasoning_items: Sequence[_BuiltReasoningItem],
reasoning_items: Sequence[_BuiltReasoningItem | ChatCompletionReasoningItem],
) -> list[ChatCompletionReasoningItem] | None:
if not reasoning_items:
return None
@ -782,7 +782,32 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
else:
pass # don't fail request if item in list is not supported
# If we accumulated tool calls, create a single choice with all of them
if accumulated_tool_calls and choices:
last_choice: Final = choices[-1]
last_reasoning_content: Final = getattr(last_choice.message, "reasoning_content", None)
last_reasoning_items: Final = getattr(last_choice.message, "reasoning_items", None)
merged_reasoning_content: Final = (
" ".join(value for value in (last_reasoning_content, reasoning_content) if value) or None
)
merged_reasoning_items: Final = _as_chat_reasoning_items(
(
*(last_reasoning_items or ()),
*(() if pending_reasoning_item is None else (pending_reasoning_item,)),
)
)
merged_message: Final = Message(
role=last_choice.message.role,
content=last_choice.message.content,
annotations=getattr(last_choice.message, "annotations", None),
tool_calls=accumulated_tool_calls,
reasoning_content=merged_reasoning_content,
reasoning_items=merged_reasoning_items,
)
return [
*choices[:-1],
Choices(message=merged_message, finish_reason="tool_calls", index=last_choice.index),
]
if accumulated_tool_calls:
msg = Message(
content=None,

View file

@ -1861,6 +1861,7 @@ SPEND_LOG_KEY_METADATA_CACHE_TTL: Final = 600
SPEND_LOG_KEY_METADATA_MISS_CACHE_TTL: Final = 30
SPEND_LOG_KEY_METADATA_CACHE_MAX_ITEMS: Final = 10000
SPEND_LOG_KEY_METADATA_QUERY_TIMEOUT_MS: Final = 5000
SPEND_LOG_KEY_METADATA_ROWS_PER_PROBE: Final = 100
# Short TTL for negative MCP access-group existence lookups. Keeps unauthenticated
# callers from forcing a DB query per request for unknown names, while bounding
# staleness so a transient DB error (which surfaces as an empty list) cannot
@ -2084,16 +2085,12 @@ MCP_SPEND_LOG_MODEL_PREFIX: Final[str] = "MCP: "
PTU_SENTINEL_API_KEY: Final[str] = "__ptu_flat_cost__"
PTU_ROLLUP_JOB_ID: Final[str] = "ptu_flat_cost_rollup_job"
PTU_ROLLUP_LOCK_TTL_SECONDS: Final[int] = 900
USAGE_TOP_API_KEYS_LIMIT: Final[int] = int(os.getenv("USAGE_TOP_API_KEYS_LIMIT", "100"))
# Furthest back the catch-up pass looks for unpriced PTU days when a deployment
# declares no ptu_effective_from, bounding the scan for an open-ended window.
PTU_ROLLUP_MAX_BACKFILL_DAYS: Final[int] = 90
# Deployments named in the lapsed-window alert before it is truncated, so a fleet-wide
# expiry cannot produce an alert too large for the channel delivering it.
PTU_LAPSED_ALERT_LIMIT: Final[int] = 10
DAILY_GLOBAL_SPEND_RECONCILE_JOB_ID: Final[str] = "daily_global_spend_reconcile_job"
DAILY_GLOBAL_SPEND_RECONCILE_LOCK_TTL_SECONDS: Final[int] = 3600
DAILY_GLOBAL_SPEND_RECONCILED_THROUGH_PARAM: Final[str] = "daily_global_spend_reconciled_through"
# Slack allowed when deciding a sentinel row is stale. The row's updated_at and the
# run's cutoff are stamped by different hosts, so clock skew between them must not let
# one run delete a charge another just wrote. A stale row is hours old and a concurrent

View file

@ -114,6 +114,7 @@ class SlackAlerting(CustomBatchLogger):
self.default_webhook_url = default_webhook_url
self.flush_lock = asyncio.Lock()
self.periodic_started = False
self._periodic_flush_task: asyncio.Task[None] | None = None
self.hanging_request_check = AlertingHangingRequestCheck(
slack_alerting_object=self,
)
@ -125,6 +126,12 @@ class SlackAlerting(CustomBatchLogger):
self.digest_lock = asyncio.Lock()
super().__init__(**kwargs, flush_lock=self.flush_lock)
def _ensure_periodic_flush_task(self) -> None:
if self.periodic_started and (self._periodic_flush_task is None or not self._periodic_flush_task.done()):
return
self._periodic_flush_task = asyncio.create_task(self.periodic_flush())
self.periodic_started = True
def update_values(
self,
alerting: list | None = None,
@ -137,17 +144,14 @@ class SlackAlerting(CustomBatchLogger):
):
if alerting is not None:
self.alerting = alerting
asyncio.create_task(self.periodic_flush())
self.periodic_started = True
self._ensure_periodic_flush_task()
if alerting_threshold is not None:
self.alerting_threshold = alerting_threshold
if alert_types is not None:
self.alert_types = alert_types
if alerting_args is not None:
self.alerting_args = SlackAlertingArgs(**alerting_args)
if not self.periodic_started:
asyncio.create_task(self.periodic_flush())
self.periodic_started = True
self._ensure_periodic_flush_task()
if alert_type_config is not None:
for key, val in alert_type_config.items():
self.alert_type_config[key] = AlertTypeConfig(**val) if isinstance(val, dict) else val
@ -1442,9 +1446,8 @@ Model Info:
return
# Start periodic flush if not already started
if not self.periodic_started and self.alerting is not None and len(self.alerting) > 0:
asyncio.create_task(self.periodic_flush())
self.periodic_started = True
if self.alerting is not None and len(self.alerting) > 0:
self._ensure_periodic_flush_task()
if "webhook" in self.alerting and alert_type == "budget_alerts" and user_info is not None:
await self.send_webhook_alert(webhook_event=user_info)

View file

@ -36,6 +36,7 @@ from litellm.types.integrations.anthropic_cache_control_hook import (
CacheControlMessageInjectionPoint,
)
from litellm.types.llms.anthropic import (
ANTHROPIC_TOOL_SEARCH_TOOL_TYPES,
AllAnthropicToolsValues,
AnthropicSystemMessageContent,
)
@ -124,6 +125,16 @@ def _carries_cache_breakpoint(block: object) -> bool:
return isinstance(block, dict) and any(block.get(key) is not None for key in CACHE_BREAKPOINT_KEYS)
def _tool_carries_cache_breakpoint(tool: object) -> bool:
return _carries_cache_breakpoint(tool) or (
isinstance(tool, dict) and _carries_cache_breakpoint(tool.get("function"))
)
def _chat_transform_drops_tool_cache_control(tool: object) -> bool:
return isinstance(tool, dict) and tool.get("type") in ANTHROPIC_TOOL_SEARCH_TOOL_TYPES
def _accepts_prompt_cache_breakpoint(block: object) -> bool:
return isinstance(block, dict) and block.get("type") in OPENAI_PROMPT_CACHE_BREAKPOINT_BLOCK_TYPES
@ -134,6 +145,8 @@ def _accepts_prompt_cache_breakpoint(block: object) -> bool:
# rather than spending them on a list that is still missing some of their targets.
CARRY_UNMATCHED_MESSAGE_POINTS: Final = "_litellm_carry_unmatched_cache_control_points"
EXTERNAL_BREAKPOINTS_STAMP: Final = "_litellm_external_breakpoints"
class AnthropicCacheControlHook(CustomPromptManagement):
@staticmethod
@ -199,19 +212,13 @@ class AnthropicCacheControlHook(CustomPromptManagement):
# Create a deep copy of messages to avoid modifying the original list
processed_messages = copy.deepcopy(messages)
# Separate message-level and non-message-level injection points
message_points: Final[list[CacheControlMessageInjectionPoint]] = []
remaining_points: Final[list[CacheControlInjectionPoint]] = []
for point in injection_points:
if point.get("location") == "message":
message_points.append(cast(CacheControlMessageInjectionPoint, point))
else:
remaining_points.append(point)
message_points: Final = tuple(
cast(CacheControlMessageInjectionPoint, point)
for point in injection_points
if point.get("location") == "message"
)
remaining_points: Final = tuple(point for point in injection_points if point.get("location") != "message")
# Non-message points (currently Bedrock tool_config) are handled in the
# provider transform, where each tool_config point appends at most one
# cachePoint to the tools. That block also counts toward Anthropic's
# limit, so reserve a slot for it here to leave room.
stamped_dialect: Final = injection_points[0].get("_litellm_openai_dialect")
openai_dialect: Final = (
stamped_dialect
@ -236,8 +243,10 @@ class AnthropicCacheControlHook(CustomPromptManagement):
if carry_unmatched
else tuple(message_points)
)
reserved_blocks: Final = (
1 if not openai_dialect and any(p.get("location") == "tool_config" for p in remaining_points) else 0
stamped_external: Final = injection_points[0].get(EXTERNAL_BREAKPOINTS_STAMP)
external_breakpoints: Final = stamped_external if isinstance(stamped_external, int) else 0
reserved_blocks: Final = AnthropicCacheControlHook._blocks_reserved_outside_messages(
remaining_points, external_breakpoints, openai_dialect
)
breakpoints_before: Final = AnthropicCacheControlHook.count_request_cache_breakpoints(processed_messages)
processed_messages = self._apply_message_injections(
@ -254,14 +263,19 @@ class AnthropicCacheControlHook(CustomPromptManagement):
# Points this pass did not place: non-message ones for the provider transform, and
# the deferred role-targeted ones. Deferring is what reaches the Responses API's
# `instructions`, which is only a system message once the bridge builds one. The
# judged stamp is what makes it safe: the next pass must not re-judge points
# against messages this pass already marked (see `_should_stand_down`).
carried_points: Final[Sequence[CacheControlInjectionPoint]] = (*remaining_points, *carried_message_points)
# `instructions`, which is only a system message once the bridge builds one. A later
# pass re-applies them safely: a target that already carries a mark is skipped and
# the census counts every mark on the wire, litellm's own included.
carried_points: Final[Sequence[CacheControlInjectionPoint]] = (
*AnthropicCacheControlHook._points_with_a_slot_left(
remaining_points,
AnthropicCacheControlHook.count_request_cache_breakpoints(processed_messages) + external_breakpoints,
openai_dialect,
),
*carried_message_points,
)
if carried_points:
non_default_params["cache_control_injection_points"] = AnthropicCacheControlHook._stamped_as_judged(
carried_points
)
non_default_params["cache_control_injection_points"] = list(carried_points)
return model, processed_messages, non_default_params
@ -296,6 +310,72 @@ class AnthropicCacheControlHook(CustomPromptManagement):
)
return system_blocks + sum(AnthropicCacheControlHook._count_cache_control_blocks(msg) for msg in messages)
@staticmethod
def count_external_cache_breakpoints(
tools: Iterable[object] | None, cache_control: object = None, request_kwargs: object = None
) -> int:
"""Client breakpoints outside messages and system that the provider cap still counts.
A tool carries its mark at the top level (Anthropic shape) or under ``function``
(OpenAI shape). A top-level ``cache_control`` is Anthropic's automatic caching,
which places one breakpoint of its own on top of the explicit ones. The
``extra_body`` envelope of ``request_kwargs`` is merged over the request on the
wire, so a ``tools`` or ``cache_control`` it carries replaces the direct value
and is counted in its place. Callers pass only the tools whose mark reaches the
provider on their path.
"""
extra_body: Final = (
_validated_object_mapping(AnthropicCacheControlHook._request_value(request_kwargs, "extra_body")) or {}
)
wire_cache_control: Final = extra_body.get("cache_control", cache_control)
wire_tools: Final = _validated_object_list(extra_body["tools"]) if "tools" in extra_body else tools
tool_blocks: Final = sum(1 for tool in wire_tools or () if _tool_carries_cache_breakpoint(tool))
envelope_blocks: Final = AnthropicCacheControlHook.count_request_cache_breakpoints(
_validated_object_list(extra_body.get("messages")) or (), extra_body.get("system")
)
return int(wire_cache_control is not None) + tool_blocks + envelope_blocks
@staticmethod
def count_external_cache_breakpoints_on_messages_route(
tools: Iterable[object] | None, cache_control: object, request_kwargs: object
) -> int:
"""The /v1/messages census before the route splits.
The native messages transforms drop the ``extra_body`` envelope while the
chat bridge merges it, so the cap reserves for whichever census is larger
rather than letting an envelope that unmarks a direct tool free a slot the
provider still counts.
"""
return max(
AnthropicCacheControlHook.count_external_cache_breakpoints(tools, cache_control),
AnthropicCacheControlHook.count_external_cache_breakpoints(tools, cache_control, request_kwargs),
)
@staticmethod
def _blocks_reserved_outside_messages(
remaining_points: Sequence[CacheControlInjectionPoint], external_breakpoints: int, openai_dialect: bool
) -> int:
"""Slots of the provider cap that the message census cannot see.
The client's breakpoints on tools and its automatic top-level ``cache_control``
are already on the wire, and a ``tool_config`` point becomes one more cachePoint
in the Bedrock converse transform. OpenAI's cap counts only its own block markers.
"""
if openai_dialect:
return 0
tool_config_blocks: Final = 1 if any(p.get("location") == "tool_config" for p in remaining_points) else 0
return external_breakpoints + tool_config_blocks
@staticmethod
def _points_with_a_slot_left(
remaining_points: Sequence[CacheControlInjectionPoint], breakpoints_on_wire: int, openai_dialect: bool
) -> tuple[CacheControlInjectionPoint, ...]:
"""A ``tool_config`` point becomes a cachePoint the Bedrock converse transform never
counts against the cap, so it is forwarded only while the wire still has a slot."""
if openai_dialect or breakpoints_on_wire < MAX_CACHE_CONTROL_BLOCKS:
return tuple(remaining_points)
return tuple(point for point in remaining_points if point.get("location") != "tool_config")
@staticmethod
def _apply_message_injections(
points: Sequence[CacheControlMessageInjectionPoint],
@ -476,11 +556,16 @@ class AnthropicCacheControlHook(CustomPromptManagement):
def apply_to_anthropic_messages_request(
messages: list[dict],
system: str | list | None,
injection_points: list[CacheControlInjectionPoint],
injection_points: Sequence[CacheControlInjectionPoint],
openai_dialect: bool = False,
external_breakpoints: int = 0,
) -> tuple[list[dict], str | list | None, list[CacheControlInjectionPoint]]:
"""Apply cache control injection for the Anthropic-native v1/messages endpoint.
``external_breakpoints`` is the client's breakpoint count outside ``messages`` and
``system`` (see ``count_external_cache_breakpoints``); it shrinks the budget so
the request never exceeds the provider cap.
Returns (messages, system, remaining_non_message_points).
"""
if not injection_points:
@ -489,22 +574,17 @@ class AnthropicCacheControlHook(CustomPromptManagement):
processed_messages: list[dict] = copy.deepcopy(messages)
processed_system = copy.deepcopy(system) if system is not None else None
message_points: Final[list[CacheControlMessageInjectionPoint]] = []
system_points: Final[list[CacheControlMessageInjectionPoint]] = []
remaining_points: Final[list[CacheControlInjectionPoint]] = []
role_points: Final = tuple(
cast(CacheControlMessageInjectionPoint, point)
for point in injection_points
if point.get("location") == "message"
)
system_points: Final = tuple(point for point in role_points if point.get("role") == "system")
message_points: Final = tuple(point for point in role_points if point.get("role") != "system")
remaining_points: Final = tuple(point for point in injection_points if point.get("location") != "message")
for point in injection_points:
if point.get("location") == "message":
msg_point = cast(CacheControlMessageInjectionPoint, point)
if msg_point.get("role") == "system":
system_points.append(msg_point)
else:
message_points.append(msg_point)
else:
remaining_points.append(point)
reserved_blocks: Final = (
1 if not openai_dialect and any(p.get("location") == "tool_config" for p in remaining_points) else 0
reserved_blocks: Final = AnthropicCacheControlHook._blocks_reserved_outside_messages(
remaining_points, external_breakpoints, openai_dialect
)
max_blocks: Final = MAX_CACHE_CONTROL_BLOCKS - reserved_blocks
@ -541,8 +621,14 @@ class AnthropicCacheControlHook(CustomPromptManagement):
max_blocks=max_blocks - system_blocks,
openai_dialect=openai_dialect,
)
forwarded_points: Final = AnthropicCacheControlHook._points_with_a_slot_left(
remaining_points,
AnthropicCacheControlHook.count_request_cache_breakpoints(processed_messages, processed_system)
+ external_breakpoints,
openai_dialect,
)
return processed_messages, processed_system, remaining_points
return processed_messages, processed_system, list(forwarded_points)
@staticmethod
def _default_control() -> ChatCompletionCachedContent:
@ -559,31 +645,26 @@ class AnthropicCacheControlHook(CustomPromptManagement):
return ChatCompletionCachedContent(type="ephemeral")
@staticmethod
def _stamped_as_judged(points: Sequence[CacheControlInjectionPoint]) -> Sequence[Mapping[str, object]]:
"""Mark written-back points as having passed the client cache_control judgment.
Builds copies because config-owned point dicts are shared across
requests; mutating them would leak the stamp into future requests.
"""
return AnthropicCacheControlHook._stamped(points, "_litellm_judged", True)
@staticmethod
def _judged_configured_points(
def _stamped_for_prompt_hook(
points: Sequence[CacheControlInjectionPoint],
messages: list[AllMessageValues],
tools: list[object] | None,
cache_control: object,
external_breakpoints: int,
model: str,
custom_llm_provider: str | None,
api_base: object,
prompt_cache_options: object,
request_kwargs: object,
) -> Sequence[Mapping[str, object]] | None:
if AnthropicCacheControlHook._should_stand_down(points, messages, None, tools, cache_control, request_kwargs):
return None
return AnthropicCacheControlHook._stamped_with_dialect(
) -> Sequence[Mapping[str, object]]:
"""Carry onto the points what the prompt-management hook never receives.
The hook sees neither the tools nor the request kwargs, so the target dialect
and the client's breakpoint count outside the message list ride on the points.
Builds copies because config-owned point dicts are shared across requests.
"""
with_dialect: Final = AnthropicCacheControlHook._stamped_with_dialect(
points, model, custom_llm_provider, api_base, prompt_cache_options
)
if external_breakpoints == 0:
return with_dialect
return AnthropicCacheControlHook._stamped(with_dialect, EXTERNAL_BREAKPOINTS_STAMP, external_breakpoints)
@staticmethod
def _stamped_with_dialect(
@ -604,35 +685,9 @@ class AnthropicCacheControlHook(CustomPromptManagement):
)
@staticmethod
def _stamped(
points: Sequence[CacheControlInjectionPoint], key: str, value: object
) -> Sequence[Mapping[str, object]]:
def _stamped(points: Sequence[Mapping[str, object]], key: str, value: object) -> Sequence[Mapping[str, object]]:
return [{**point, key: value} for point in points]
@staticmethod
def _should_stand_down(
points: Sequence[CacheControlInjectionPoint],
messages: list[AllMessageValues],
system: str | list | None,
tools: list | None,
cache_control: object = None,
request_kwargs: object = None,
) -> bool:
"""Whether configured injection points must yield to client-set cache_control.
Points that a prior pass over this request already judged and wrote
back carry the internal judged stamp; any re-entry (acompletion
re-entering completion, the async-to-sync /v1/messages dispatch,
interceptor sub-calls reusing the request kwargs) must not re-judge
them, because by then the messages carry litellm's own injected marks
and the judgment would misread those as client breakpoints.
"""
if all(point.get("_litellm_judged") for point in points):
return False
return AnthropicCacheControlHook._request_has_cache_control(
messages, system, tools, cache_control, request_kwargs
)
@staticmethod
def _request_has_cache_control(
messages: list[AllMessageValues],
@ -640,28 +695,24 @@ class AnthropicCacheControlHook(CustomPromptManagement):
tools: list | None = None,
cache_control: object = None,
request_kwargs: object = None,
on_messages_route: bool = False,
) -> bool:
"""Client breakpoints own caching in both the request and its extra_body envelope."""
bodies: Final = (
{"messages": messages, "system": system, "tools": tools, "cache_control": cache_control},
_validated_object_mapping(AnthropicCacheControlHook._request_value(request_kwargs, "extra_body")) or {},
)
return any(
body.get("cache_control") is not None
or AnthropicCacheControlHook.count_request_cache_breakpoints(
_validated_object_list(body.get("messages")) or (), body.get("system")
"""Return True if the request already carries any client-supplied cache_control.
Only the automatic defaults stand down on it: a client that marks its own
breakpoints (Claude Code does) has a caching strategy the defaults would
clash with, whether the marks sit in the request or in its ``extra_body``
envelope. Configured injection points are an explicit instruction and are
applied alongside the client's marks, bounded by the provider cap.
"""
external_breakpoints: Final = (
AnthropicCacheControlHook.count_external_cache_breakpoints_on_messages_route(
tools, cache_control, request_kwargs
)
> 0
or any(
AnthropicCacheControlHook._request_value(tool, "cache_control") is not None
or AnthropicCacheControlHook._request_value(
AnthropicCacheControlHook._request_value(tool, "function"), "cache_control"
)
is not None
for tool in (_validated_object_list(body.get("tools")) or ())
)
for body in bodies
if on_messages_route
else AnthropicCacheControlHook.count_external_cache_breakpoints(tools, cache_control, request_kwargs)
)
return AnthropicCacheControlHook.count_request_cache_breakpoints(messages, system) + external_breakpoints > 0
@staticmethod
def get_default_injection_points(
@ -673,6 +724,7 @@ class AnthropicCacheControlHook(CustomPromptManagement):
enable_prompt_caching: bool | None = None,
cache_control: object = None,
request_kwargs: object = None,
on_messages_route: bool = False,
) -> list[CacheControlInjectionPoint]:
"""Default breakpoints when ``litellm.enable_anthropic_prompt_caching`` is on.
@ -693,7 +745,9 @@ class AnthropicCacheControlHook(CustomPromptManagement):
if not supports_anthropic_cache_control(model, custom_llm_provider):
return []
if AnthropicCacheControlHook._request_has_cache_control(messages, system, tools, cache_control, request_kwargs):
if AnthropicCacheControlHook._request_has_cache_control(
messages, system, tools, cache_control, request_kwargs, on_messages_route
):
return []
if is_claude_code_one_shot_subagent_request(
@ -769,34 +823,30 @@ class AnthropicCacheControlHook(CustomPromptManagement):
) -> None:
"""For /chat/completions: resolve the injection points the request should carry.
Configured injection points win over the automatic defaults, but stand
down entirely when the client already marked its own cache_control
breakpoints (messages or tools): injecting alongside them clashes with
the client's caching strategy and can exceed the provider's four-block
limit. The judgment happens once per request; points a prior pass
wrote back carry the judged stamp and are never re-judged (see
``_should_stand_down``). Seeding the param lets the existing
prompt-management gate and the AnthropicCacheControlHook run
unchanged.
Configured injection points win over the automatic defaults and are applied
even when the client marked its own cache_control elsewhere in the request;
the provider's four-block cap bounds them, counting the client's marks on
messages, tools and the top-level ``cache_control``. Only the defaults stand
down on client marks. Seeding the param lets the existing prompt-management
gate and the AnthropicCacheControlHook run unchanged.
"""
import litellm
if non_default_params.get("cache_control_injection_points"):
judged: Final = AnthropicCacheControlHook._judged_configured_points(
non_default_params["cache_control_injection_points"],
messages,
tools,
non_default_params.get("cache_control"),
configured: Final = non_default_params.get("cache_control_injection_points")
if configured:
tools_keeping_marks: Final = tuple(
tool for tool in tools or () if not _chat_transform_drops_tool_cache_control(tool)
)
non_default_params["cache_control_injection_points"] = AnthropicCacheControlHook._stamped_for_prompt_hook(
configured,
AnthropicCacheControlHook.count_external_cache_breakpoints(
tools_keeping_marks, non_default_params.get("cache_control"), non_default_params
),
model,
custom_llm_provider,
api_base,
non_default_params.get("prompt_cache_options"),
non_default_params,
)
if judged is None:
non_default_params.pop("cache_control_injection_points")
else:
non_default_params["cache_control_injection_points"] = judged
return
points: Final = AnthropicCacheControlHook.get_default_injection_points(
messages=messages,
@ -897,15 +947,14 @@ class AnthropicCacheControlHook(CustomPromptManagement):
) -> tuple[list[dict], str | list | None]:
"""Extract cache_control_injection_points from kwargs and apply if present.
Configured points stand down entirely when the client already marked
its own cache_control breakpoints anywhere in the request. The
judgment happens once per request; points a prior pass wrote back
carry the judged stamp and are never re-judged (see
``_should_stand_down``). When none are configured but
Configured points are applied even when the client marked its own
cache_control elsewhere in the request, bounded by the provider cap,
which counts the client's marks on messages, system, tools and the
top-level ``cache_control``. When none are configured but
``litellm.enable_anthropic_prompt_caching`` or the per-request
``enable_prompt_caching`` kwarg (stamped from key metadata) is on,
synthesize default breakpoints for the native /v1/messages path. Pops
both keys from kwargs;
synthesize default breakpoints for the native /v1/messages path; those
defaults alone stand down on client marks. Pops both keys from kwargs;
if remaining (non-message) points exist they are written back so
downstream transforms can handle them.
"""
@ -917,13 +966,8 @@ class AnthropicCacheControlHook(CustomPromptManagement):
configured: Final = cast( # cast-ok: kwargs is untyped; this key only holds the documented injection-point list
list[CacheControlInjectionPoint] | None, kwargs.pop("cache_control_injection_points", None)
)
if configured and AnthropicCacheControlHook._should_stand_down(
configured, typed_messages, system, tools, cache_control, kwargs
):
return messages, system
injection_points: list[CacheControlInjectionPoint] = configured or []
if not injection_points and model is not None:
injection_points = AnthropicCacheControlHook.get_default_injection_points(
injection_points: Final[Sequence[CacheControlInjectionPoint]] = configured or (
AnthropicCacheControlHook.get_default_injection_points(
messages=typed_messages,
system=system,
tools=tools,
@ -932,7 +976,11 @@ class AnthropicCacheControlHook(CustomPromptManagement):
enable_prompt_caching=enable_prompt_caching,
cache_control=cache_control,
request_kwargs=kwargs,
on_messages_route=True,
)
if model is not None
else ()
)
if not injection_points:
return messages, system
@ -945,6 +993,9 @@ class AnthropicCacheControlHook(CustomPromptManagement):
system=system,
injection_points=injection_points,
openai_dialect=openai_dialect,
external_breakpoints=AnthropicCacheControlHook.count_external_cache_breakpoints_on_messages_route(
tools, cache_control, kwargs
),
)
breakpoints_added: Final = (
AnthropicCacheControlHook.count_request_cache_breakpoints(messages, system) - breakpoints_before
@ -953,7 +1004,7 @@ class AnthropicCacheControlHook(CustomPromptManagement):
if openai_dialect and breakpoints_added > 0:
kwargs.setdefault("prompt_cache_options", PromptCacheOptions(mode="explicit"))
if remaining:
kwargs["cache_control_injection_points"] = AnthropicCacheControlHook._stamped_as_judged(remaining)
kwargs["cache_control_injection_points"] = remaining
return messages, system
@property

View file

@ -561,6 +561,7 @@ class OpenTelemetryV2(CustomLogger):
time_to_first_chunk_seconds=call.time_to_first_chunk_seconds,
request_route=request_root_http_route(),
trace=call.trace,
session_id=call.session_id,
)
end_time_ns: Final = to_ns(end_time)
if carrier is not None and carrier.span is not None:

View file

@ -43,6 +43,7 @@ class GenAIMapper:
GenAI.OPERATION_NAME: lambda d: d.operation.value,
GenAI.PROVIDER_NAME: lambda d: d.provider or None,
GenAI.OUTPUT_TYPE: lambda d: d.output_type.value if d.output_type else None,
GenAI.CONVERSATION_ID: lambda d: d.session_id,
GenAI.REQUEST_MODEL: lambda d: d.request_model or None,
GenAI.REQUEST_TEMPERATURE: lambda d: d.request_params.temperature,
GenAI.REQUEST_TOP_P: lambda d: d.request_params.top_p,

View file

@ -41,7 +41,7 @@ from dataclasses import dataclass, field
from types import MappingProxyType
from typing import TYPE_CHECKING, Any, Final, cast
from litellm.constants import LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL
from litellm.constants import LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL, SESSION_ID_GENERATED_METADATA_KEY
from litellm.integrations.otel.model.semconv import resolve_operation
from litellm.integrations.otel.model.trace_controls import TraceControls, caller_trace_controls
from litellm.integrations.otel.model.utils import as_str, as_str_mapping, to_seconds
@ -226,6 +226,7 @@ class LLMCallEvent:
provisional_span_name: str
time_to_first_chunk_seconds: float | None
trace: TraceControls
session_id: str | None
@classmethod
def from_dict(cls, kwargs: Mapping[str, Any]) -> LLMCallEvent:
@ -233,6 +234,7 @@ class LLMCallEvent:
payload: Final = cast("StandardLoggingPayload", raw_payload) if raw_payload else None
operation: Final = resolve_operation(as_str(kwargs.get("call_type")))
model: Final = as_str(kwargs.get("model")) or ""
trace: Final = caller_trace_controls(kwargs)
return cls(
call_id=_call_id(payload, kwargs),
payload=payload,
@ -242,10 +244,40 @@ class LLMCallEvent:
upstream_started=kwargs.get("api_call_start_time") is not None,
provisional_span_name=f"{operation.value} {model}".strip(),
time_to_first_chunk_seconds=time_to_first_chunk_seconds(kwargs),
trace=caller_trace_controls(kwargs),
trace=trace,
session_id=caller_session_id(kwargs, trace),
)
def caller_session_id(kwargs: Mapping[str, object], trace: TraceControls) -> str | None:
"""The conversation id the caller sent (``litellm_session_id``, else the
``session_id`` trace control); ``None`` when the request carried none.
``get_litellm_params`` back-fills ``litellm_session_id`` from ``metadata.trace_id``
(which the proxy stamps with the OTel trace id) and ``missing_session_id: generate``
mints one into the body; neither is a caller conversation, so both are ignored,
while a ``langfuse_session_id`` header still counts under the generate policy.
``StandardLoggingPayload.session_id`` is never read: the payload drops the
generated marker, so a replayed minted id would pass for a caller's."""
params: Final[Mapping[str, object]] = as_str_mapping(kwargs.get("litellm_params")) or MappingProxyType({})
bodies: Final = tuple(
metadata
for key in ("metadata", "litellm_metadata")
if (metadata := as_str_mapping(params.get(key))) is not None
)
from_body: Final = tuple(session for body in bodies if (session := as_str(body.get("session_id"))))
minted: Final = frozenset(
session
for body in bodies
if body.get(SESSION_ID_GENERATED_METADATA_KEY) and (session := as_str(body.get("session_id")))
)
if minted:
return next((session for session in (trace.session_id, *from_body) if session and session not in minted), None)
explicit: Final = as_str(params.get("litellm_session_id"))
echoes_trace_id: Final = explicit is not None and any(as_str(body.get("trace_id")) == explicit for body in bodies)
return (None if echoes_trace_id else explicit) or trace.session_id or None
def time_to_first_chunk_seconds(kwargs: Mapping[str, Any]) -> float | None:
"""Seconds from the upstream request being issued (``api_call_start_time``)
to the first streamed chunk (``completion_start_time``); ``None`` for

View file

@ -407,6 +407,7 @@ class LLMCallSpanData:
call_type: str | None = None
request_route: str | None = None
trace: TraceControls = field(default_factory=TraceControls)
session_id: str | None = None
embedding_output: EmbeddingOutput | None = None
@classmethod
@ -417,6 +418,7 @@ class LLMCallSpanData:
time_to_first_chunk_seconds: float | None = None,
request_route: str | None = None,
trace: TraceControls | None = None,
session_id: str | None = None,
) -> LLMCallSpanData:
params: Final = cast(Mapping[str, object], payload.get("model_parameters") or {})
# The single parse of the request's metadata — the request-vs-provider
@ -463,6 +465,7 @@ class LLMCallSpanData:
call_type=call_type or None,
request_route=request_route or context.identity.request_route,
trace=trace or TraceControls(),
session_id=session_id or None,
embedding_output=embedding_output if capture_content else None,
)

View file

@ -2553,6 +2553,7 @@ class PrometheusLogger(CustomLogger):
from litellm.litellm_core_utils.litellm_logging import (
StandardLoggingPayloadSetup,
)
from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
status_code: Final = self._extract_status_code(exception=original_exception)
@ -2571,7 +2572,9 @@ class PrometheusLogger(CustomLogger):
end_user=user_api_key_dict.end_user_id,
user=user_api_key_dict.user_id,
user_email=user_api_key_dict.user_email,
hashed_api_key=None if status_code == 401 else user_api_key_dict.api_key,
hashed_api_key=None
if status_code == 401
else LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict),
api_key_alias=user_api_key_dict.key_alias,
team=user_api_key_dict.team_id,
team_alias=user_api_key_dict.team_alias,

View file

@ -1638,7 +1638,7 @@ class WebSearchInterceptionLogger(CustomLogger):
return { # mutable-ok: litellm's metadata channel is a plain dict its logging path reads and enriches
**user_api_key_metadata,
"model_group": search_tool_name,
"user_api_key": user_api_key_auth.api_key,
"user_api_key": LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_auth),
"user_api_key_auth": user_api_key_auth,
}

View file

@ -610,6 +610,9 @@ class Logging(LiteLLMLoggingBaseClass):
self.truncated_messages_for_logging: str | list | dict | None = None # mutable-ok: logged messages shape
## TIME TO FIRST TOKEN LOGGING ##
self.completion_start_time: datetime.datetime | None = None
# The model the proxy shows the client on streamed chunks. The logged streamed response carries it
# once that response is priced, the same way a non-streamed response is logged
self.client_facing_stream_model: str | None = None
self._llm_caching_handler: LLMCachingHandler | None = None
# INITIAL LITELLM_PARAMS
@ -2279,6 +2282,15 @@ class Logging(LiteLLMLoggingBaseClass):
setattr(result, "usage", transformed_usage)
return result
def _with_client_facing_stream_model(
self,
response: ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse,
) -> ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse:
model: Final = self.client_facing_stream_model
if model is None or getattr(response, "model", None) in (None, model):
return response
return response.model_copy(update={"model": model})
def _success_handler_helper_fn(
self,
result=None,
@ -2592,9 +2604,11 @@ class Logging(LiteLLMLoggingBaseClass):
result=complete_streaming_response
)
self._merge_hidden_params_from_response_into_metadata(complete_streaming_response)
logged_streaming_response: Final = self._with_client_facing_stream_model(complete_streaming_response)
self.model_call_details["complete_streaming_response"] = logged_streaming_response
## STANDARDIZED LOGGING PAYLOAD
self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload(
complete_streaming_response, start_time, end_time
logged_streaming_response, start_time, end_time
)
standard_logging_payload: Final[StandardLoggingPayload | None] = self.model_call_details.get(
"standard_logging_object"
@ -3130,10 +3144,13 @@ class Logging(LiteLLMLoggingBaseClass):
await self._prepare_baseline_cache_estimate(complete_streaming_response)
logged_streaming_response: Final = self._with_client_facing_stream_model(complete_streaming_response)
self.model_call_details["async_complete_streaming_response"] = logged_streaming_response
## STANDARDIZED LOGGING PAYLOAD
try:
self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload(
complete_streaming_response, start_time, end_time
logged_streaming_response, start_time, end_time
)
except Exception: # noqa: BLE001 # payload build must never block later callbacks (slot release)
verbose_logger.exception(

View file

@ -1504,8 +1504,11 @@ class CustomStreamWrapper:
self.tool_call = True
if hasattr(chunk, "usage") and chunk.usage is not None:
model_response.usage = chunk.usage
chunk_usage: Final = getattr(chunk, "usage", None)
if isinstance(chunk_usage, Usage):
model_response.usage = chunk_usage
elif isinstance(chunk_usage, BaseModel):
model_response.usage = Usage(**chunk_usage.model_dump())
## RETURN ARG
result: Final = self.return_processed_chunk_logic(

View file

@ -46,6 +46,8 @@ from litellm.types.llms.openai import (
AllMessageValues,
ChatCompletionDocumentObject,
ChatCompletionNamedToolChoiceParam,
ChatCompletionRedactedThinkingBlock,
ChatCompletionThinkingBlock,
ChatCompletionToolParam,
OpenAIMessageContentListBlock,
)
@ -854,6 +856,8 @@ def _count_content_list(
content_list: str
| Iterable[
OpenAIMessageContentListBlock
| ChatCompletionThinkingBlock
| ChatCompletionRedactedThinkingBlock
| AnthropicMessagesTextParam
| AnthropicMessagesImageParam
| AnthropicMessagesDocumentParam
@ -898,9 +902,9 @@ def _count_content_list(
use_default_image_token_count,
default_token_count,
)
elif c["type"] == "thinking":
elif c["type"] in ("thinking", "redacted_thinking"):
# Claude extended thinking content block
# Count the thinking text and skip signature (opaque signature blob)
# Count the thinking text and skip the opaque blobs (signature, redacted data)
thinking_text = str(c.get("thinking", ""))
if thinking_text:
num_tokens += count_function(thinking_text)
@ -920,7 +924,8 @@ def _count_content_list(
raise ValueError(
f"Invalid content item type: {content_type}. "
f"Expected str or dict with 'type' field "
f"(text, image_url, image, document, file, tool_use, tool_result, thinking, tool_reference)."
f"(text, image_url, image, document, file, tool_use, tool_result, thinking, redacted_thinking, "
f"tool_reference)."
)
return num_tokens
except Exception as e:

View file

@ -35,7 +35,7 @@ if TYPE_CHECKING:
from litellm.router import Router
# Anthropic-only keys already mapped by the translator; strip on extra_kwargs re-merge.
ANTHROPIC_ONLY_REQUEST_KEYS: Final[frozenset[str]] = frozenset({"output_config"})
ANTHROPIC_ONLY_REQUEST_KEYS: Final[frozenset[str]] = frozenset({"output_config", "safeguards"})
_AnthropicMessages: TypeAlias = "list[dict[str, object]]"
_AnthropicSystem: TypeAlias = "str | list[dict[str, object]] | None"

View file

@ -79,10 +79,14 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
"speed",
"output_config",
"reasoning_effort",
"safeguards",
# TODO: Add Anthropic `metadata` support
# "metadata",
]
def should_filter_anthropic_beta_headers(self) -> bool:
return self._resolved_provider != "anthropic"
def _remove_scope_from_cache_control(self, anthropic_messages_request: dict) -> None:
"""
Remove `scope` field from cache_control blocks.

View file

@ -2,14 +2,18 @@
Azure Anthropic messages transformation config - extends AnthropicMessagesConfig with Azure authentication
"""
from collections.abc import Mapping
from typing import Any, Final
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
AnthropicMessagesConfig,
)
from litellm.llms.azure.common_utils import BaseAzureLLM
from litellm.types.llms.anthropic import ANTHROPIC_BETA_HEADER_VALUES
from litellm.types.router import GenericLiteLLMParams
DANGEROUS_TOOL_USE_BETA: Final = ANTHROPIC_BETA_HEADER_VALUES.DANGEROUS_TOOL_USE_2026_09_03.value
class AzureAnthropicMessagesConfig(AnthropicMessagesConfig):
"""
@ -71,7 +75,7 @@ class AzureAnthropicMessagesConfig(AnthropicMessagesConfig):
messages=messages,
)
return headers, api_base
return _with_dangerous_tool_use_beta_for_safeguards(headers, optional_params), api_base
def get_complete_url(
self,
@ -164,3 +168,14 @@ class AzureAnthropicMessagesConfig(AnthropicMessagesConfig):
self._normalize_system_role_messages(anthropic_messages_request, model=model)
self._remove_scope_from_cache_control(anthropic_messages_request)
return anthropic_messages_request
def _with_dangerous_tool_use_beta_for_safeguards(
headers: Mapping[str, str], optional_params: Mapping[str, object]
) -> dict[str, str]:
if optional_params.get("safeguards") is None:
return dict(headers)
existing: Final = ",".join(value for key, value in headers.items() if key.lower() == "anthropic-beta")
betas: Final = {piece.strip() for piece in existing.split(",") if piece.strip()}
others: Final = {key: value for key, value in headers.items() if key.lower() != "anthropic-beta"}
return {**others, "anthropic-beta": ",".join(sorted(betas | {DANGEROUS_TOOL_USE_BETA}))}

View file

@ -530,6 +530,9 @@ class AmazonAnthropicClaudeMessagesConfig(
if anthropic_model_info.is_eager_input_streaming_used(tools):
beta_set.add(ANTHROPIC_FINE_GRAINED_TOOL_STREAMING_BETA_HEADER)
if anthropic_messages_optional_request_params.get("safeguards") is not None:
beta_set.add(ANTHROPIC_BETA_HEADER_VALUES.DANGEROUS_TOOL_USE_2026_09_03.value)
self._filter_context_management_for_bedrock_invoke(
anthropic_messages_request=anthropic_messages_request,
beta_set=beta_set,
@ -759,9 +762,7 @@ class AmazonAnthropicClaudeMessagesConfig(
aws_decoder: Final = AmazonAnthropicClaudeMessagesStreamDecoder(
model=model,
)
completion_stream: Final = aws_decoder.aiter_bytes(
httpx_response.aiter_bytes(chunk_size=aws_decoder.DEFAULT_CHUNK_SIZE)
)
completion_stream: Final = aws_decoder.aiter_bytes(httpx_response.aiter_bytes())
# Convert decoded Bedrock events to Server-Sent Events expected by Anthropic clients.
return self.bedrock_sse_wrapper(
completion_stream=completion_stream,
@ -908,16 +909,6 @@ class AmazonAnthropicClaudeMessagesConfig(
class AmazonAnthropicClaudeMessagesStreamDecoder(AWSEventStreamDecoder):
def __init__(
self,
model: str,
) -> None:
"""
Iterator to return Bedrock invoke response in anthropic /messages format
"""
super().__init__(model=model)
self.DEFAULT_CHUNK_SIZE = 1024
def _chunk_parser(self, chunk_data: dict) -> GChunk | ModelResponseStream | dict:
"""
Parse the chunk data into anthropic /messages format

View file

@ -108,6 +108,9 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
if anthropic_model_info.is_tool_search_used(tools):
beta_values.add(get_tool_search_beta_header("vertex_ai"))
if optional_params.get("safeguards") is not None:
beta_values.add(ANTHROPIC_BETA_HEADER_VALUES.DANGEROUS_TOOL_USE_2026_09_03.value)
if beta_values:
headers["anthropic-beta"] = ",".join(beta_values)

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View file

@ -1,4 +1,4 @@
:HL["/litellm-asset-prefix/_next/static/chunks/1kid9zr1--h6y.css","style"]
:HL["/litellm-asset-prefix/_next/static/chunks/3146e697tym4_.css","style"]
:HL["/litellm-asset-prefix/_next/static/media/83afe278b6a6bb3c-s.p.2bn3s6zvc0dyp.woff2","font",{"crossOrigin":"","type":"font/woff2"}]
0:{"tree":{"name":"","param":null,"prefetchHints":4176,"slots":{"children":{"name":"(dashboard)","param":null,"prefetchHints":4192,"slots":{"children":{"name":"__PAGE__","param":null,"prefetchHints":4256,"slots":null}}}}},"staleTime":300,"buildId":"kXnLzJ6ylsRPmgSkCkCKM"}
0:{"tree":{"name":"","param":null,"prefetchHints":4176,"slots":{"children":{"name":"(dashboard)","param":null,"prefetchHints":4192,"slots":{"children":{"name":"__PAGE__","param":null,"prefetchHints":4256,"slots":null}}}}},"staleTime":300,"buildId":"RvBoD6No6gfcqg-cP5_LO"}

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View file

@ -16,7 +16,7 @@ f:I[363178,["/litellm-asset-prefix/_next/static/chunks/1kpvojzxb_2ce.js","/litel
6:X
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