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33 commits
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moe-berri
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467847b2e9
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fix(ui): restore Z.AI credential fields in provider catalog (#49325)
Carry the Z.AI catalog fix from #40088 and move its regression into the mapped unit test file. Co-authored-by: Chaitanya Laxman <chaitanyalaxman118@gmail.com> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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moe-berri
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0382f134e7
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fix(ui): add Meta Model API to the Add Model provider dropdown (#49314)
* test(ui): cover separate Meta Model API provider onboarding Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): add Meta Model API provider onboarding Co-authored-by: lostmartian <sahilgangurde08@gmail.com> Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(ui): align Meta coverage with provider keys and listed registry Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): show Meta model placeholder Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: lostmartian <sahilgangurde08@gmail.com> |
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quietjules
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d302096b5a
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feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex (#48949)
* feat(lite): offer each model group's reasoning efforts in pi, OpenCode and Codex lite pi, lite opencode and lite codex now read supported_reasoning_efforts from /model_group/info and write them into each client's model config. pi gets reasoning and a thinkingLevelMap, OpenCode gets reasoning_options plus one variant per effort, and Codex fallback entries get supported_reasoning_levels with a default level. The proxy-served Codex catalog on /v1/models?client_version= offers the same levels Codex before 0.138.0 fails the whole catalog on an effort it cannot name, so those releases, and an unreadable version, get only the six efforts every release parses. A group with unknown efforts keeps today's output, and a group with none is written as non-reasoning The strength order and nearest_declared_reasoning_effort move to an SDK-free module so the lite CLI, which loads without initializing the SDK, can import the Codex catalog * fix(lite): describe team models by their public name and keep Codex's none default /model_group/info now looks up a team's own deployments when the caller's team serves the requested name, so a team model reports its reasoning levels. Codex fallback entries default to none when the group lists it, and the proxy builds the Codex catalog in a worker thread * fix(lite): round Codex's default level down and describe a team's shared-name model from its own deployments Move the reasoning strength helper to litellm_core_utils so lite and the Codex catalog import it without the SDK or the router, and let make lint-format-check-changed diff the working tree so a staged rename passes. * fix(lite): keep pi's system role on reasoning model groups pi switches its system prompt to the developer role for any model marked reasoning, so an operator's cache_control_injection_points entry for role system stopped matching on Claude groups. lite pi now sets compat.supportsDeveloperRole false on those entries, so pi sends system as it did before. * fix(codex): treat a client_version too long to parse as an old Codex and keep undescribed stock levels A client_version past Python's integer digit limit made the Codex catalog answer 500. It now gets the levels every Codex parses. A stock Codex level with no description validates again, as on base, and lite codex treats undecodable codex --version output as an unknown version * fix(lite): keep REASONING_EFFORT_STRENGTH_ORDER importable from router_utils and skip the Codex sync on undecodable debug models output --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Juan V.
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60601ca995
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feat(pass-through): add eu/jev decision API pass-through with spend tracking (#46875)
* feat(pass-through): add eu/jev decision API pass-through with spend tracking
Adds a /eu_jev/{endpoint:path} pass-through route for eu/jev, an EU-hosted
decision API that speaks the same POST /v1/systemone contract as TypeSafe.
It reads EU_JEV_API_KEY and EU_JEV_API_BASE (defaults to
https://jev.bevel.software), books spend through the shared decision logging
handler, and prices eu_jev/eu-jeff-1.0.0 and eu_jev/eu-jeff-latest from the
cost map
* fix(pass-through): default eu_jev to its canonical eu-jev.com origin
* fix(pass-through): reject custom_body on the eu_jev route
A key limited to other models could send an eu/jev request through
custom_body, because auth checks the outer body while the shared
pass-through forwards custom_body upstream. The route now answers 400
before anything is forwarded, the same way validate_oss_request guards
the laya and bespoke routes
* fix(pass-through): give the eu_jev route request and 200 response schemas
The OpenAPI docs gate flagged POST /eu_jev/{endpoint} for OA001 and
OA003. The route now documents the eu/jev System One request body and
its 200 answer, usage and meta shape, taken from the eu/jev OpenAPI
document. The lazy OpenAPI snapshot and the dashboard API types are
regenerated with python -m litellm.proxy._lazy_openapi_snapshot and
npm run gen:api
* fix(pass-through): reject streaming on the eu_jev route
A body with stream=true switched the route to streaming, which skips the
decision spend tracking. Reject it with a 400, as validate_oss_request does
for laya and bespoke.
* fix(pass-through): type the eu_jev request body like the other decision routes
* fix(pass-through): check eu_jev decisions against the model eu/jev runs
Serve only POST /eu_jev/v1/systemone, eu/jev's one endpoint, resolve an omitted
model and the legacy names to eu-jeff-latest for key model checks and pricing,
check scopes under eu_jev/<model> like Laya and Bespoke, and answer 503 when
EU_JEV_API_KEY is unset
* fix(pass-through): apply eu_jev key limits, register eu_jev, price unlisted releases
Pre-call hooks and guardrails now see the body model as eu_jev/<release>, so
model_rpm_limit and model_tpm_limit set on eu_jev/eu-jeff-latest apply, and
upstream still gets the client's exact body. eu_jev is a registered decisions
provider, so access groups, config deployments, /v1/systemone and /v1/decisions
accept it, and the Admin UI can add it. A release without its own cost map row
is priced as eu-jeff-latest instead of $0
* fix(eu_jev): use the pass-through deployment's api_base and accept provider-prefixed models
* fix(eu_jev): declare /v1/systemone on the eu/jev cost map entries so the generated endpoint table keeps it
* fix(eu_jev): take pass-through credentials only from proxy-wide deployments
The eu/jev route now ignores team-scoped deployments when it picks the
upstream key and base, so one team's deployment can no longer redirect
another team's calls, and a base ending in /v1 is not doubled
* fix(eu_jev): let a configured pass-through at /eu_jev/v1/systemone keep serving it
Scope the mapped pass-through and gateway allowlist entries to the decision
route instead of the whole /eu_jev prefix, so custom routes under /eu_jev keep
their auth, metering, and gateway behavior from before this PR
* fix(eu_jev): treat /eu_jev/v1/systemone as a provider route only while the built-in route serves it
Drop the decision path from the mapped pass-through list and classify it with one
check that asks the pass-through registry, so an operator's own pass-through at that
path keeps its auth, metering, LLM-route status and litellm_user_api_key handling
from before this PR. The built-in route now yields on a per-request root path and
on any configured method, and the gateway keeps only the exact decision path
* fix(eu_jev): find a configured route at the decision path with or without a trailing slash, and stop a deleted one forwarding
* test(eu_jev): annotate new test variables with Final
* fix(proxy): keep eu/jev pass-through routing stable during updates and method mismatches
Swap an updated pass-through's routes with no await between removal and
re-registration, so the built-in eu/jev route never sees the path as
unconfigured mid-update. The built-in eu/jev handler no longer takes a
configured route's target, and the built-in route also yields on a
method-only match, so GET and PUT on the no-slash form of a slash route
redirect again.
* test(pass-through): annotate the route-swap test's locals as Final
* fix(pass-through): keep an updated auth route's LLM API route checks on the updating worker
* fix(eu_jev): leave a null model out of the upstream decision request
A JSON model of null is limited and counted as eu-jeff-latest, so send the
request upstream without a model field, the way an omitted model goes, since
eu/jev answers a null model with 400 Unknown model
* fix(pass-through): keep route checks on a path another auth endpoint still serves after an update
Forward a non-string eu/jev model unchanged so eu/jev rejects it, and drop only a null or missing one
* test(eu_jev): keep the non-string model test in the eu/jev route test file so a CI shard runs it
* refactor(eu_jev): build the scoped pass-through body as a new dict instead of updating it in place
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
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Nate Armstrong
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ead221995e
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refactor(router): move router callers onto the entry points and invert the proxy imports (#48847)
Code outside the router now reaches it only through the entry points (registry, settings, health, select, apply, observe, register_plugin, retire) or the endpoint methods; the outside-member allowlist shrinks from 139 to 45. litellm/router.py no longer imports litellm.proxy: it asks the installed RouterHost (litellm/router_host.py) for vertex pass-through credentials, member auto-router authorization and auto-router prompt compression, and the proxy installs its host on import. Call sites where a model name can be missing keep the old answer instead of reaching an entry point with None. |
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Mateo Wang
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77064d6c70
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feat(vector_stores): add OpenSearch k-NN search as a vector store provider (#47759)
* feat(vector_stores): add Amazon OpenSearch as a vector store provider * feat(ui): add Amazon OpenSearch to the vector store provider dropdown * feat(vector_stores): add OpenSearch k-NN search as a vector store provider * test(vector_stores): hold the OpenSearch provider tests alone for the first review The provider source comes back in the next commits on this PR * ci(tests): run the OpenSearch vector store unit tests * fix(vector_stores): sign on.aws and FIPS OpenSearch hosts and reject missing AWS credentials before embedding * fix(vector_stores): regenerate provider endpoint support for opensearch * fix(vector_stores): keep opensearch retrieve, update, and delete off the index and refuse half-set AWS keys and per-account endpoints * fix(vector_stores): return only scalar opensearch attributes and keep credential source output out of 401s * test(vector_stores): inject a failing opensearch credential source instead of running a shell * fix(vector_stores): sign opensearch for the endpoint's region, refuse list, add opensearch_index_name, honor drop_params * fix(vector_stores): refuse a caller-chosen opensearch_index_name on search and rag query * fix(vector_stores): refuse opensearch_index_name only on OpenSearch stores, keep the old 400 text Other providers drop the key again as they did before OpenSearch support, and the four embedding keys keep their original error sentence. * fix(vector_stores): refuse a caller index on slash-form OpenSearch stores |
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zoveki
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c87a25a357
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feat(proxy)!: general_settings.claude_code_marketplace_auth_required puts the Claude Code marketplace behind a LiteLLM key (#48980)
* test(proxy): require a key for the Claude Code marketplace when configured and keep exception text out of its 500s * feat(proxy): general_settings.claude_code_marketplace_auth_required requires a LiteLLM key for the Claude Code marketplace When true, GET /claude-code/marketplace.json answers 401 without a key in Authorization, x-litellm-api-key, the litellm_key_header_name header, or ?key=, and GET /public/skill_hub returns an empty list. Both routes' 500 bodies carry a fixed message instead of the exception text. * fix(proxy): refuse ?key= and send WWW-Authenticate when the Claude Code marketplace requires a key * fix(proxy): close the marketplace key gate's outage, quoted-setting, and dashboard gaps Refuse the database-outage fallback identity with a 401, read a quoted "true" as on and an unreadable value as on, keep the skill hub's 500 detail a fixed string, and have the dashboard setup tab show a settings snippet with a key header when the marketplace requires a key * fix(proxy): keep the no-database 500, validate the marketplace key setting at boot, and show the key snippet until the probe answers * fix(claude-code): read the marketplace key setting from the UI config and answer database outages with 503 * fix(claude-code): keep the no-database hint on skill_hub and warn that the remove step uninstalls plugins --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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AaronHowell
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904c092ffe
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feat(providers): add BigModel support and model pricing (#48563)
* feat: add BigModel provider with native Chat, Responses, and Messages APIs Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com> * test(providers): make BigModel unit tests a package Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com> * docs(providers): clarify BigModel parameter interface Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com> * fix(bigmodel): keep the Coding Plan base, surface Responses auth errors, and scope routes Chat Completions keeps a GLM Coding Plan api_base. Responses raises the status from BigModel's success=false body instead of returning an empty 200, and a JSON body answering a stream request is replayed as a one-shot stream. Messages streams keep ping and [DONE] lines. bigmodel leaves openai_compatible_providers so speech, image, and transcription routes send it no request * fix(responses): replay a JSON body on a stream request only when it has a Content-Length A gateway that labels a chunked SSE stream as application/json kept streaming before the replay, so only a sized body is read in full * fix(bigmodel): scope the JSON stream replay to BigModel, map its business error codes, and echo requested tools * fix(bigmodel): forward Codex's include and parallel_tool_calls, keep the OpenAI org header off BigModel, and pass unchanged Messages stream events through * fix(bigmodel): map disabled thinking to low effort, keep Messages temperature, raise context window and content policy errors, and default parallel_tool_calls to true * fix(bigmodel): keep the caller's reasoning_effort when Messages rewrites disabled thinking * fix(bigmodel): keep context-window and content-policy errors on streamed Responses replays --------- Co-authored-by: Bytechoreographer <Bytechoreographer@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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kailian zhou
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3a350cacc9
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feat!: add StreamLake provider metadata (#41006)
* feat: add StreamLake provider metadata * fix(streamlake): complete provider discovery and test request flows * test(streamlake): assert cost and tool-param invariants instead of pinning vendor prices * fix(streamlake): accept tools and reasoning on endpoint ids and match the current price page Endpoint ids have no cost-map row, so tools and reasoning_effort were rejected before reaching StreamLake. The provider now declares both capabilities, and named non-reasoning rows opt out explicitly. The rows now follow StreamLake's 2026-09-17 price page: drop the KAT-Coder and Qwen3 rows it no longer serves, add the served models that had no price, drop account-level rpm and tpm, and fill missing context windows. StreamLake is also registered for streamlake/* wildcards and its messages and responses support. * fix(streamlake): regenerate the endpoint matrix and type the new tests The backup endpoint matrix advertised chat only while the root map listed Messages and Responses, so /public/endpoints hid both. Regenerating with scripts/generate_provider_endpoints_support.py makes the two files match. Types the StreamLake tests and sets the Add Model test's API key with fireEvent.change, per the dashboard test guide. * fix(streamlake): drop the retired max_tokens field from the StreamLake cost-map rows * fix(streamlake): price the four served models StreamLake publishes rates for and add the Qwen3.8 cache prices * fix(streamlake): send token caps as max_completion_tokens and mark image models StreamLake ignores max_tokens on kimi-k2.6, kimi-k2.7-code, qwen3.6-27b and qwen3.6-35b-a3b, while every served model honors max_completion_tokens, so the JSON provider now maps max_tokens to max_completion_tokens instead of the reverse. Rows whose models read an image in a live probe set supports_vision, and the Qwen3.8 rows drop the explicit cache write price, which this route never uses since cache_control is dropped * fix(streamlake): keep cache_control marks, price explicit cache reads, and use API input limits StreamLake reads cache_control, so the provider keeps the marks through a preserve_cache_control flag. Qwen3.8 explicit cache hits now use their own read price, rows with a cache read price declare prompt caching, three models StreamLake serves without reasoning drop reasoning_effort, and max_input_tokens follows the limits the API reports. * fix(utils): warn when a custom_provider_map name matches a built-in provider --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Amaan
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7c7304c22b
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feat(providers): add ZeroGPU as an OpenAI-compatible provider (#43874)
* feat(providers): add ZeroGPU as an OpenAI-compatible provider Registers zerogpu through the JSON provider registry so zerogpu/<model> routes to https://api.zerogpu.ai/v1/chat/completions with ZEROGPU_API_KEY and an optional ZEROGPU_API_BASE. Adds LlmProviders.ZEROGPU, the constants.py provider and endpoint lists, cost map entries for the 10 ZeroGPU text generation models, the endpoint matrix, the Add Model form fields, the README row and the dashboard provider entry * feat(zerogpu): add capability flags verified against the live API Live calls to https://api.zerogpu.ai/v1/chat/completions confirmed tools, tool_choice and json_schema response_format on 8 of the 10 catalog text models, cached token reporting on deepseek-v4.1-flash, gpt-4.1-mini, gpt-5.4-nano and gpt-5.6-luna, and reasoning_effort on gpt-5.6-luna. LFM2.5-1.2B-Instruct answers stream requests with plain JSON instead of SSE and LFM2.5-1.2B-Thinking returns 500 on every request, so both stay out of the cost map until the API serves them correctly * feat(zerogpu): price LFM2.5-1.2B-Instruct Adds zerogpu/LFM2.5-1.2B-Instruct to the cost map with the catalog prices and context window. It gets no capability flags because the live API ignores tools, response_format and max_completion_tokens for this model, so LiteLLM drops tool params for it instead of sending them. LFM2.5-1.2B-Thinking stays out of the cost map * fix(zerogpu): reject transcription requests before calling the upstream API ZeroGPU only serves chat completions, so drop it from the OpenAI transcription transport set. A zerogpu transcription request now fails locally instead of hitting an /audio/transcriptions endpoint that does not exist * test(zerogpu): cover the responses and messages bridges Both endpoints reach ZeroGPU through chat completions, so assert the request each one sends upstream and the reply it returns * refactor(zerogpu): move zerogpu out of the provider list tails New upstream providers append to the end of openai_compatible_endpoints, openai_compatible_providers and providers.json, so an entry at the tail conflicts with every one of them. Placing zerogpu next to long-stable entries keeps those merges clean. No behavior change * fix(zerogpu): price cached input for qwen3-30b-a3b-fp8 The ZeroGPU model catalog (https://docs.zerogpu.ai/docs/model-catalog, checked 2026-10-09) lists cached input for qwen3-30b-a3b-fp8 at $0.05 per 1M tokens. Without cache_read_input_token_cost, cached tokens were billed at the full $0.10 input rate * revert(zerogpu): leave the audio transcription provider set unchanged Per review, keep OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS as upstream defines it. This PR only covers chat completions, and ZeroGPU now serves /audio/transcriptions anyway, so the local refusal and its test are removed * fix(zerogpu): add max_tokens so trim_messages can size ZeroGPU history trim_messages reads max_tokens as the fallback for max_input_tokens and evaluates it eagerly, so without it the lookup raised, got swallowed, and the full history came back untrimmed. max_tokens matches each model's maxTokens in ZeroGPU's models API (https://api-dashboard.zerogpu.ai/api/models, checked 2026-10-10) * test(zerogpu): record mocked requests on a recorder object The mock handler appended to a list the caller passed in, which AGENTS.md forbids. A recorder now owns the captured requests as a tuple * fix(zerogpu): cap max_tokens at each model's output limit Each cap is the max_output_tokens ZeroGPU stores for the model in its production models table (read 2026-10-20), the same column its /v1/models serves as max_length. That gives 65536 for deepseek-v4.1-flash, 32768 for gpt-4.1-mini and gpt-oss-120b, 128000 for gpt-5.4-nano and gpt-5.6-luna, 8192 for LFM2.5-1.2B-Instruct and llama-3.1-8b-instruct-fast, and 16384 for qwen3-30b-a3b-fp8. glm-5.3-flash is stored as 32786, which reads as a typo for 32768, so that row uses 32768 trim_messages sizes history from max_input_tokens, so lowering max_tokens leaves it unaffected * fix(zerogpu): flag prompt caching on glm-5.3-flash Repeating the same ~4.3K-token prompt against ZeroGPU on 2026-10-20 returned cached_tokens of 4320 on some glm-5.3-flash calls. gpt-oss-120b and llama-3.1-8b-instruct-fast returned 0 on all nine calls, and qwen3-30b-a3b-fp8 never returned cached_tokens, so they stay unflagged. Their cached prices stay as ZeroGPU publishes them, so any cache hit is still billed at the right rate * fix(zerogpu): set gpt-5.4-nano context window to 272000 ZeroGPU accepts a 271001-token gpt-5.4-nano prompt and rejects 273000 tokens as over the context window (checked 2026-10-21), so max_input_tokens is 272000 rather than the 400000 its catalog lists * fix(zerogpu): list zerogpu models for zerogpu/* wildcards zerogpu had no models_by_provider entry, so get_provider_models("zerogpu") returned None and a zerogpu/* wildcard listed no models. zerogpu_models is now filled from the cost map rows like openinfer_models and registered in models_by_provider * fix(zerogpu): flag gpt-5.4-nano as a reasoning model ZeroGPU honors reasoning_effort on gpt-5.4-nano (checked 2026-10-21). Without it the model spends 0 reasoning tokens, and with low or high it spends 32 or more. LiteLLM only treated it as a reasoning model by falling back to OpenAI's bare gpt-5.4-nano row, so get_model_info and /model/info reported supports_reasoning as null. The row now carries the flag itself * fix(zerogpu): flag deepseek, glm, gpt-oss and qwen3 as reasoning models ZeroGPU's /v1/models marks these four as reasoning models and accepts reasoning_effort on all of them (checked 2026-10-21), but LiteLLM rejected the param with UnsupportedParamsError because their rows had no supports_reasoning flag. glm reports reasoning_tokens under reasoning_effort, and gpt-oss and qwen3 spend hidden reasoning tokens on every reply. The gpt-oss test case now expects reasoning_effort to reach ZeroGPU * fix(zerogpu): set gpt-oss-120b context window to 128000 ZeroGPU routes gpt-oss-120b across several upstream backends, and at least one of them returns 413 past a 128000-token window, so max_input_tokens uses that as the safe floor. The backends reached on 2026-10-21 accepted up to about 131K prompt tokens, so this only gives up a little headroom on the larger ones * feat(zerogpu): call ZeroGPU's Responses API natively ZeroGPU serves /v1/responses for all nine catalog models, so LiteLLM no longer bridges Responses requests through chat completions. Native calls return ZeroGPU's reasoning output items for glm, gpt-oss and qwen3, which the bridge dropped. Checked live on 2026-10-22 through litellm.responses for every model, non-streaming and streaming, plus a gpt-oss tool call. LFM2.5-1.2B-Instruct streams correctly now that ZeroGPU's text_generation lane emits Responses SSE * fix(zerogpu): stop inferring the zerogpu provider from api_base alone Listing https://api.zerogpu.ai/v1 in openai_compatible_endpoints rerouted bare model names on that api_base from openai to zerogpu. A bare gpt-5.6-luna call with verbosity used to return 200 and started raising UnsupportedParamsError. Drop the entry and its api_base-alone test, so zerogpu is only selected through the zerogpu/ prefix * fix(zerogpu): price gpt-6-luna, llama-3.2-3b, LFM2.5-1.2B-Thinking and qwen3.6 A zerogpu/* wildcard served these four chat models with no cost-map row, so their calls logged $0 spend. Add rows at ZeroGPU's catalog prices from https://api-dashboard.zerogpu.ai/api/models, with context windows and output caps from ZeroGPU's models table. LFM2.5-1.2B-Thinking has no cached price, like LFM2.5-1.2B-Instruct. gpt-6-luna is flagged supports_reasoning because LiteLLM already routes gpt-6 names as reasoning models. Checked live on 2026-10-28, all four now report nonzero response_cost * fix(zerogpu): drop the retired max_tokens field from the zerogpu rows Upstream #48471 retired max_tokens from the cost map in favor of max_input_tokens and max_output_tokens, and test_no_row_carries_the_retired_max_tokens_field failed on all 13 zerogpu rows. Every row already carries the same value in max_output_tokens, so nothing is lost. The zerogpu limits test now checks that each row's output limit fits its context window * chore(zerogpu): regenerate provider endpoint support for zerogpu Upstream #48619 generates provider_endpoints_support.json from the cost map and checks it in CI, and the hand-written zerogpu entry no longer matched. Regenerated with scripts/generate_provider_endpoints_support.py. Only the zerogpu entry changed, and it now matches what the generator emits for other JSON-registry providers such as openinfer * fix(zerogpu): flag tools, json_schema and prompt caching on gpt-6-luna ZeroGPU serves function calling, tool_choice, json_schema response_format and prompt caching on gpt-6-luna, so set supports_function_calling, supports_tool_choice, supports_response_schema and supports_prompt_caching on its row in both cost maps. Checked live on 2026-10-28, a weather tool call came back with the right arguments, json_schema output validated, and repeated prompts reported 3260 of 3263 tokens cached * fix(zerogpu): set qwen3.6-35b-a3b context to 262144 and flag its tools and reasoning ZeroGPU accepts up to 262,144 input tokens on qwen3.6-35b-a3b and serves tools, tool_choice, json_schema response_format and reasoning_effort on it. Raise max_input_tokens from 16384 and set supports_function_calling, supports_tool_choice, supports_response_schema and supports_reasoning in both cost maps. Before this, LiteLLM rejected tools and reasoning_effort for the model. Checked live on 2026-10-28, a 209,905-token prompt succeeded, an oversized one was refused with a 262144-token limit, and tool calls, json_schema output and reasoning_effort all worked * fix(zerogpu): flag vision on gpt-6-luna and qwen3.6-35b-a3b ZeroGPU reads image inputs on gpt-6-luna and qwen3.6-35b-a3b, so set supports_vision on both rows in both cost maps. Checked live on 2026-10-28, both models named the animal in an image_url photo, and the image showed up in their prompt token counts |
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Mateo Wang
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0a1dbc0fb4
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refactor(mcp): drop the experimental label from the MCP server and client paths (#48513)
* refactor(mcp): drop the experimental label from the MCP server and client paths Move litellm/proxy/_experimental/mcp_server to litellm/proxy/mcp_server and litellm/experimental_mcp_client to litellm/mcp_client, with the mirrored tests moved under tests/unit/proxy/mcp_server and tests/unit/mcp_client. Both old packages stay as shims that warn with DeprecationWarning, re-export the new package's public names and alias every submodule in sys.modules so deep imports keep resolving to the same objects. The OpenAPI docs gate now puts the merge base's enterprise package on PYTHONPATH so its base counts do not mix the checked-out enterprise code with the base litellm tree Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci(mcp): keep tests/unit/proxy/_experimental as a sharded root for the shim tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): alias namespace subpackages and bind attributes in the deprecated MCP shims pkgutil.walk_packages skipped mcp_server/auth because it has no __init__.py, so old imports of litellm.proxy._experimental.mcp_server.auth.* failed, and sys.modules entries alone left litellm.experimental_mcp_client.tools unreachable as an attribute. Walk the package on disk and setattr each alias on its old parent. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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yucheng-berri
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f7e6ddec66
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feat(proxy): add LITELLM_OFFLINE_MODE, one switch for the fetches LiteLLM makes on its own (#48096)
* feat(proxy): add LITELLM_OFFLINE_MODE to stop every request the proxy makes on its own * fix(ui): name LITELLM_OFFLINE_MODE where the cost map panel says local mode is forced * test: isolate the offline-mode tokenizer tests from the local Hugging Face cache * test: cover the offline policy templates and the cached Kimi K3 tokenizer * test(integration): count Kimi K3 tokens in the offline-mode egress test * refactor(token_counter): skip non-bundled tokenizers in offline mode instead of listing downloaded ones --------- Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com> |
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jesus-berri
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c8f7e0de7d
|
feat(model hub): show admin-defined custom tags and metadata from model_info (#46064)
* feat(model hub): show admin-defined custom tags and metadata from model_info Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(router): move model hub custom field merging into router_utils Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(model hub): share the custom tag badge list between the column and details Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(model hub): cover public hub, patch, null, hostile, forwarding, and killed-worker paths for custom fields Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(model hub): drop custom_metadata entries with non-string keys or non-finite numbers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(model hub): use isinstance narrowing instead of TypeGuard for custom_metadata values Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(model hub): build custom tags and metadata in the proxy instead of the router Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(model hub): serve custom tags and metadata on model_group_alias rows Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * remove docstring from model_group_custom_fields.py * style(model hub): fix lint and format in custom metadata tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(model hub): drop leading blank line in custom fields helper Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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michelligabriele
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1c6d55c7e8
|
fix(proxy): show the newest health check per model group on the model hub (#47552) | ||
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Mateo Wang
|
8a2782e41c
|
feat(router): route batch creates to mode batch deployments and expose supported_endpoints on /model_group/info (#47376)
* feat(router): expose supported_endpoints on /model_group/info * feat(router): route batch creates to mode batch deployments in mixed model groups * fix(router): prefer batch deployments after eligibility filters and in group-name credential lookups * fix(router): keep group-name credential lookups on the first deployment and prefer batch deployments before cooldown Model-encoded ids carry only the group name, so preferring the batch deployment there moved ids created before the upgrade onto its credentials. Batch creates now pick batch-capable deployments before health checks and cooldown, routing and group info share one batch-capable check, the cost map's /v1/batch is dropped only for Azure, and /model/info applies the same per-deployment rule * test(router): map _listed_endpoints to its /model/info tests in the router coverage check * fix(router): skip only Azure chat deployments for batch creates and list batch support per caller team Narrow the batch create filter to Azure and azure_ai deployments that are not mode batch, so OpenAI groups keep their chat deployments during cooldown and under tag filters. Mark batch deployments by mode batch only, since stored endpoint lists from older Admin UI saves copy the cost map. Leave /model/info unchanged so the Admin UI never saves a computed endpoint list, and pass the caller's team into /model_group/info. * test(proxy): let the model hub router fakes take the caller's team_id * fix(router): gate batch-create routing on deployments the caller's team may use and list only /v1/batch for Azure batch deployments * fix(router): skip a malformed model_info.supported_endpoints instead of failing group info and chat * fix(router): apply the batch create filter after cooldown, managed files, and tags The batch filter ran before health checks and cooldown, so a batch create on a mixed Azure group answered with a router 429 or 401 when cooldown, tags, or a managed file's targets left no batch deployment, where main sends the create on and returns Azure's 400. The filter now runs right before order filtering, after every eligibility filter, so those cases answer as main does and creates still skip Azure chat deployments whenever a batch deployment is left * test(router): annotate the batch routing test assignments with Final |
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joshua-berri
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6d0d0bb68b
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feat: add Nace Drex decisions provider (#46523)
* feat: add Nace Drex decisions provider * fix: expose Nace in dashboard provider metadata * ci: include Nace tests in the provider shard * fix: complete Nace provider catalog and preserve OpenRouter tests * test: mark Nace test directories as packages * fix: share Drex score parsing across decision providers --------- Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> |
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devin-ai-integration[bot]
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da2f5a498f
|
feat(agents): support Databricks Agent Platform agents in the agent gateway (#45681)
* feat(agents): support Databricks Agent Platform agents in the agent gateway Add a databricks_agent provider that speaks the MLflow ResponsesAgent wire (Responses-shaped input, output_text items, output_text.delta SSE) to Model Serving endpoints (/invocations or the unified /serving-endpoints/responses) and Databricks Apps (/responses), with a PAT or OAuth M2M client credentials Register it through the agents config block or the Admin UI agent catalog and call it through /a2a/<agent> (message/send, message/stream) or model: a2a/<agent> chat completions. The chat route now runs every completion-bridge agent through its own provider, and attaches the minted Databricks OAuth token for both bridge and URL agents. Consumed OAuth settings never reach the provider call * fix(agents): harden databricks_agent input, output, and OAuth handling Non-text content parts answer 400 unless drop_params is set, a reply without an output list answers 502, flat OAuth fields resolve an os.environ api_base, the bridge debug log no longer echoes the request model, routing tests stub only the HTTP boundary, and the catalog description fits the dropdown * fix(agents): merge agent and client extra_headers on the a2a chat route, and reject an empty databricks_oauth block * fix(agents): bridge only databricks_agent agents on the a2a chat route, keep the card url over a client api_base, and require workspace_url for a Databricks App * refactor(agents): read the a2a chat bridge providers from a constants set instead of branching on a provider name * fix(databricks_agent): let the configured credential win, reject malformed client extra_headers, and keep a missing endpoint name empty * test(agents): drive the flat OAuth a2a send through the real bridge * fix(agents): keep an empty databricks_oauth block ignored on url agents, as before this change * fix(agents): accept bare App hosts, env service principals, and os.environ refs on Databricks agents * fix(databricks_agent): address review caveats on chat bridging, params, and auth Map max_tokens and max_completion_tokens to max_output_tokens and pass temperature, top_p, and user, so /v1/messages works without drop_params. Send A2A message metadata only with string values, answering 400 or dropping the rest under drop_params. Join message items with a blank line in both stream and non-stream replies. Cache the env service principal token until shortly before it expires. Keep databricks_agent replies out of the response cache. On the chat bridge, let request fields win over the agent's stored params while pinning the agent's api_base and api_key, and apply the agent's static_headers between client and agent extra_headers, as /a2a does. Resolve os.environ/ only for databricks_agent api_base and api_key instead of every bridge provider. Ignore an unusable databricks_oauth block on URL agents on chat, as at the merge base, instead of answering 400. * test(internal_context): list the databricks agent token cache as process-local * fix(databricks_agent): keep the agent's endpoint, input, and target out of client control extra_body model and input answer 400, or are dropped under drop_params. A client api_base or base_url never replaces the agent's card URL on the bridge. Chat to a URL agent keeps its merge-base call, and an incomplete databricks_oauth block on a URL agent keeps its merge-base ValueError. * test(databricks): expect the merge-base 400 for a client api_base on agent chat * fix(databricks): keep agent-owned inputs and identity headers out of a chat caller's reach * fix(databricks): bound the agent-over-caller merge to two levels so it needs no recursion --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
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3cc9e7ef8e
|
perf(proxy): cache the public provider and agent field endpoints (#46617)
/public/providers/fields re-read and re-parsed the bundled 85K provider_create_fields.json on every request, and /public/agents/fields did the same for that file plus agent_create_fields.json. Both are unauthenticated public endpoints, and both did the work inside an `async def`, so the read and the parse ran on the event loop and serialized against every other in-flight request. Measured against the bundled files, that is roughly 0.40 ms of blocking work per request for the provider endpoint and 0.45 ms for the agent endpoint Both now memoize with `lru_cache`, which is what `/public/endpoints` in the same module already does through its `_cached_endpoints` global, so each file is read once per process rather than once per request The agent endpoint mutated the dicts it had just loaded, appending inherited provider credential fields and popping `inherit_credentials_from_provider`. That is only safe while the data is re-read every time, so caching it meant making the merge pure: `_agent_with_inherited_credentials` builds a new mapping per agent, and the cached value is the merged result rather than the raw file contents. Responses are byte identical before and after, checked on both endpoints against a live proxy The bundled records are typed as Mapping[str, object] and narrowed with isinstance at the point of use, rather than typing.Any, which ruff-strict bans Side effects: 3 of the repo's ASYNC230 violations go away, and basedpyright errors in the file drop from 63 to 52 Rebased onto main after /public/providers/fields started validating the bundled JSON through a pydantic adapter on every request. That validation now runs once and the validated records are cached; the agent endpoint keeps merging the raw provider records, so both responses stay byte identical to main. Co-authored-by: Alok Sharma <alok44170@gmail.com> |
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devin-ai-integration[bot]
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a93fee9f6c
|
feat(decisions): add Laya and Bespoke providers to the Add Model form (#45260)
* feat(ui): add decisions and classifier providers to the Add Model form Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost): use literal upstream decisions paths Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: drop duplicate TYPESAFE provider fields entry superseded by main's TypeSafe Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(ui): drop stray blank line in provider_info_helpers test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): type the OSS decisions provider fields test * fix(decisions): keep Laya and Bespoke env keys on their configured server Route laya and bespoke Decisions deployments through the same oss_connection and validate_oss_model rules the pass-through and the classifier router use, so LAYA_API_KEY and BESPOKE_API_KEY only go to LAYA_API_BASE and BESPOKE_API_BASE, an api_base with credentials, a query, or a non-HTTP scheme answers 400, and an unknown checkpoint name answers 400 before any upstream call * fix(decisions): send the Laya and Bespoke env key to a form-added model on the env server A deployment added through Add Model always carries an API base, so the env key only reached deployments with no base. The env key now goes to a deployment whose base matches LAYA_API_BASE or BESPOKE_API_BASE, an empty deployment key counts as no key, and the Bespoke placeholder is the name Ollama serves. * test(decisions): cover the env-base classifier case in the complexity router test * fix(decisions): match the env server with or without /v1 and point Ollama users at bespoke/nimble * fix(decisions): call /v1/systemone once from classifiers and pass-through on a /v1 base * fix(decisions): strip /v1 from the API base path only, so a host named v1 still works --------- Co-authored-by: kerry <kerry@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> |
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devin-ai-integration[bot]
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46a389c60b
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feat(claude-code): emit installationPreference in marketplace.json entries (#41430)
* feat(claude-code): emit installationPreference in marketplace.json entries Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(claude-code): satisfy marketplace CI checks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(claude-code): qualify marketplace entry as read only Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(claude-code): suppress typed marketplace assembly warning Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(claude-code): restrict installation_preference to the documented values Accept only available, auto_install, or required so a typo returns 422 instead of being silently dropped, and cover the PUT full-replace clearing behavior with a test * fix(claude-code): echo installation_preference on the public skill hub * refactor(claude-code): read installation_preference with one membership check and cover hand-edited rows * test(integration): audit installation_preference on the Claude Code marketplace * test(integration): kill a serving worker in the marketplace chaos cell * test(integration): give the marketplace worker-kill cell the two-boot timeout * fix(proxy): keep installationPreference on the MarketplacePluginEntry model * fix(proxy): refuse self-installing preferences off sha256 archives, accept the camelCase key, and echo the preference on POST and PUT * fix(claude-code): serve installation_preference only on archive plugins and refuse both key spellings Claude Code 2.1.75 and older reject a marketplace.json once any plugin carries installationPreference, and every Claude Code release before archive support rejects a catalog with an archive plugin. Requiring an archive source for every value, available included, keeps the field off catalogs those clients can read. A request that sends installation_preference and installationPreference together now gets a 422. * fix(claude-code): read the preference spelling that carries a value when the other is null --------- 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> |
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Kerry Lu
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d7b58126a7
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feat(ui): source Home What's new from day 0 support blog posts (#46260)
* feat(ui): source Home What's new from day 0 support blog posts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(ui): Home cards read card_title and card_summary from blog tags with provider logo Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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2a01fe6e5c
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fix(home): serve the bundled whats_new.json by default so a build shows only its own launches (#45934)
* fix(home): serve the bundled whats_new.json by default so a release shows only its own launches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> (cherry picked from commit |
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devin-ai-integration[bot]
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55c89977d7
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feat(ui): load Home page What's new launches from /public/whats_new at runtime (#45912)
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* feat(ui): load the Home page What's new launches from /public/whats_new at runtime Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(ui): show the three newest What's new launches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * build: ship whats_new.json in the wheel 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> |
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devin-ai-integration[bot]
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9e2aae8490
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feat(ui): add a Home page as the dashboard root with usage summary, recent launches, blog updates and a model leaderboard (#45858)
* feat(ui): add a Home page as the dashboard root with usage summary, recent launches, blog updates and a model leaderboard Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): fall back to spend-log request counts on Home when the gateway has recorded none Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(ui): cover the Home page totals, launches, leaderboard and updates feed Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(ui): render Home Updates as rows and return up to 6 blog posts from /public/litellm_blog_posts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(ui): filter Home Updates by the new-model and api-change blog tags Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(blog): import NotRequired from typing_extensions for py3.10 and test the endpoint passes every fetched post through Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * revert(ui): drop the Updates filter chips, keep Updates as a plain row list Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(ui): restore generated schema.d.ts to main Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(ui): label the Home key button Create New Virtual Key Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(ui): drop the What's new sublabel on Home Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): show an error with retry when Home usage fails to load and move the Home test to the integration tier 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> |
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devin-ai-integration[bot]
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82a5d9842a
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fix(ui): list only catalog models in the Add Model picker (#44877)
The Add Model selector read the merged runtime cost map, so deployment ids and provider-prefixed backend keys registered for proxy deployments showed up as duplicate model choices. The public cost map endpoint now accepts catalog_only=true to return the catalog as loaded, and the Add Model panel requests that view. The default response is unchanged. Resolves LIT-9263 Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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3a3b8cad80
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feat(ui): add TypeSafe and Strands Decider to the Add Model provider list (#45335)
* feat(ui): add TypeSafe and Strands Decider to the Add Model provider list * test(public_endpoints): type the provider fields helper against the route's model --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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Mateo Wang
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58258409c9
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refactor(proxy): expose public names for private proxy helpers (#45170)
* refactor(proxy): expose public names for private proxy helpers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep original class names behind public aliases Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): preserve internal callback filtering Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep _PROXY_ class names for managed files hooks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep old private names in package exports Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): preserve recursive auth helper name Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): align MCP limiter tests with server enforcement Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): match main's MCP limiter tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep old private names bound in importing modules Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): preserve compatibility imports through strict lint Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): use exact pyright suppression in password helper test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(proxy): add reasons to compatibility import noqa comments Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): update IN-list baseline for renamed helpers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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e2971e0af4
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refactor(llms): expose public names for private provider helpers (#45037)
* refactor(litellm): migrate private usage in llms Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): preserve Bedrock batch signature marker Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(litellm): migrate llms private usage symbols Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): preserve UUID Watsonx project IDs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(litellm): retarget llms mocks to public names Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(litellm): limit llms changes to renames and forwarders Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(litellm): keep GCS mock client patching private Vertex auth methods Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(litellm): assert forwarder arguments and type forwarder signatures Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: mateo <mateo@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
|
837c6a7481
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fix(security): remove the publicly known master key from the repo (#44718)
* fix(security): hash the publicly known master key Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * docs: replace weak master key examples and regenerate artifacts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test: replace weak key fixtures with generated test keys Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci: generate master keys for proxy startup Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: preserve lens dev key entropy Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: restore proxy key compatibility in scrub examples Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: scrub merged SSO fixture and refresh dashboard bundle Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ci): stabilize test keys and metadata collection Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore: drop the rebuilt dashboard bundle Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: mateo <mateo@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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8b1990b4bc
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feat(decisions): add unified /v1/decisions endpoint for Jev-compatible providers (#44236)
* feat(decisions): add unified /v1/decisions endpoint for Jev-compatible providers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(decisions): register typesafe as a provider so Jev deployments load Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(decisions): move provider endpoints under llms and validate proxy bodies Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(decisions): add Cloudflare Clef and Strands Decider backends Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(decisions): register decisions routes for managed agents and gateway Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(decisions): use raw regex for cloudflare missing account match Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(decisions): avoid cast in Cloudflare response unwrapping Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(decisions): default model, evaluation health probe, short Cloudflare names The proxy validates only state and questions, so a request without a model falls through to the configured default model like every other route. Health checks probe evaluation-mode deployments through the Decisions API instead of failing with an unsupported mode, and cloudflare/clef and cloudflare/clef-flash get cost-map rows so the short names resolve a mode and a price. The registry no longer claims typed decisions for a provider with no backend. * fix(decisions): let health_check_params override the evaluation probe Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): audit the decisions endpoint across providers, limits, health and chaos Adds the /v1/decisions audit cells: one wire contract per provider (path, key, body and cost-map billing), the gateway-only fields and tags, the sad paths (invalid bodies, unknown model, key checks, api_base in the body, upstream 401/429/500, a 200 without answers, an unreachable upstream), the two evaluation-mode health probes, and three chaos cells (a mixed-failure burst over both routes, a worker SIGKILL mid-burst, an upstream outage and restart on the same port). The PR's cost case read the upstream observations through the gateway, which answers 404 for that path; it now reads them from the upstream URL. The owned proxy harness takes extra CLI arguments, and its graceful stop waits as long as a worker boot may take, since a worker still starting honors SIGTERM only once it is up and the 30 second wait forced a cleanup under load. * fix(decisions): send env API keys to a configured api_base Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(decisions): add zero-cost evaluation cost-map entry for Strands Decider Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(decisions): register the routes through the lazy feature registry The Decisions router was included at import, ahead of the config and DB pass-through endpoints, so a pass-through configured at /v1/decisions was skipped and answered 400 as an unknown Decisions provider. The routes now register through LAZY_FEATURES, which splices them in after every eager route, so a pass-through at /v1/decisions keeps its route while /decisions still serves natively. The lazy OpenAPI snapshot carries the two paths so the schema shows them before the first call. The audit cells add the env-key egress to a configured api_base, the client api_base opt-in shared with chat, the pass-through precedence on an owned proxy, and the Strands evaluation health check resolved from the cost map. The integration config exports the Perplexity env key the first cell needs. * fix(decisions): keep the Cloudflare api_base message in its transformation and read the audit upstream once per cell * fix(proxy): let a config pass-through beat a lazily registered route in eager mode With LITELLM_DISABLE_LAZY_ROUTES set the decisions routes are registered at startup, so SafeRouteAdder treated a config pass-through at exactly /v1/decisions as already registered and dropped it. In lazy mode a pass-through created through the API after the first native call was skipped the same way. Routes a lazy feature owns no longer count as registered, and a route added at one of their paths is placed ahead of them, the precedence lazy mode gives a config pass-through when the feature has not loaded yet. --------- 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> |
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Jim Aldon D'Souza
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19da81579b
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fix(ui): register tencent in the Add Model provider dropdown (#40924)
* fix(ui): register tencent in the Add Model provider dropdown The Add Model provider dropdown is driven by the proxy's /public/providers/fields endpoint, which serves provider_create_fields.json. Tencent was frozen in the test's ADD_MODEL_UNLISTED_PROVIDERS set, so it never appeared in the dropdown. Add a Tencent entry (optional api_base + required api_key, matching TENCENT_API_BASE/TENCENT_API_KEY) and unfreeze it in the backend test. Register Tencent in the UI Providers enum, provider_map, and placeholder map so the dropdown resolves the display name and model placeholder. * fix(tencent): drop test docstring to satisfy comment policy * fix(ui): bundle the Tencent Cloud logo for the provider dropdown |
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devin-ai-integration[bot]
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25109a523b
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test(proxy): move utils, agent_endpoints and endpoint tests into tests/unit/proxy (#44006)
* test(proxy): move utils, agent_endpoints and endpoint tests into tests/unit/proxy Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): package moved unit test directories Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): exclude proxy-db-owned files from the misc target Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): drop the redundant fixture docstrings in the proxy conftest Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yuneng <yuneng@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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devin-ai-integration[bot]
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248f0eb159
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ci: move tests/proxy_unit_tests to tests/unit/proxy and run the proxy-db shards from litellm-tests (#42903)
* ci: fix the litellm-tests unit job with sysmon coverage, an env allowlist and coverage upload on failure * test: replace key-dependent proxy, enterprise and mcp unit tests with synthetic values and integration and e2e coverage * test: drop key reads at the legacy proxy, enterprise and mcp paths and wire the gemini pass-through split * ci: move caching, proxy-extras, gateway and enterprise tests into tests/unit and run them from litellm-tests under their legacy flags * ci: move caching, proxy-extras, gateway and enterprise tests into tests/unit and run them from litellm-tests under their legacy flags * ci: move tests/proxy_unit_tests to tests/unit/proxy and run the proxy-db shards from litellm-tests * ci: fail the unit shard when circleci tests split errors * test: drop restating comments from the gemini pass-through split * build: point the local proxy unit targets at the nested tests/unit/proxy tree * ci: exit the unit shard cleanly when circleci tests split assigns it no files --------- Co-authored-by: yuneng <yuneng@berri.ai> |