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11 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Mateo Wang
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0cf2bb7296
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fix(openai): warn when the GPT-5 reasoning effort gate drops a level under drop_params (#47761)
* fix(openai): warn when the GPT-5 reasoning effort gate drops a level under drop_params A GPT-5 request whose reasoning_effort the model map does not enable for that model lost the effort with no log line under drop_params. An Azure deployment name missing from the cost map lost reasoning_effort none this way and ran at the model's default effort. The gate now logs a warning naming the model, the level, the map entry it checked, and the model_info.base_model and model_info.reasoning_effort_levels fixes. * fix(openai): warn when the Responses route or a deployment's declared levels drop a reasoning effort The /v1/responses gate dropped a row-disabled GPT-5 effort, and reasoning for an OpenAI model without supports_reasoning, with no log line, and the router logged a declared-level drop only at INFO. Both Responses drops now log a WARNING and the router logs its drop at WARNING. The warning now leads with model_info.reasoning_effort_levels, since base_model only helps a deployment named differently from its underlying model. * fix: warn only when a reasoning level is actually dropped, and on generic reasoning_effort drops * fix: warn when thinking or a Bedrock Converse reasoning level is dropped, and name the router drop a reasoning level * fix: skip the drop warning when a non-reasoning model is asked for no reasoning, and honor declared levels on Bedrock Responses * fix: stay silent when reasoning is turned off on /v1/responses and warn on the Bedrock Responses fallback drop * fix(reasoning): warn when any reasoning-off request is dropped and give each route only the advice it honors A request to turn reasoning off on a model name the catalog lacks now warns on every route, since it may be a reasoning model. Chat suggests model_info.reasoning_effort_levels and, for a name with no catalog entry, model_info.base_model. OpenAI Responses suggests declared levels only where the config honors them, and Bedrock suggests neither. The Bedrock and Mantle Responses forwarding of declared levels is reverted until it can be proven live. * fix(reasoning): suggest reasoning_effort_levels and base_model only where the route reads them The chat gate suggested model_info.reasoning_effort_levels on routes that never pass declared levels (github_copilot, chatgpt and other OpenAIConfig delegates) and model_info.base_model on OpenAI and Azure AI chat, whose gate looks up the deployment name rather than base_model. /v1/responses/compact suggested levels it never reads either. Declared levels are now None when a caller passes none, so the advice appears only when a caller fed them, and the base_model advice is limited to the Azure chat gate, the one that looks up base_model. The openai row of the chat warning test now expects no base_model advice, the Responses warning test goes through get_optional_params_responses_api the way /v1/responses and compact call it, and the Azure direct-config test passes declared levels the way get_optional_params does. Long test lines are wrapped. * fix: read only the built-in catalog when choosing the reasoning drop warning |
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mika-lt
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71babd931b
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fix(llms): move later developer messages for models declared system-first (#48897)
* fix(transformation): merge consecutive system and developer messages for non-OpenAI providers and Responses API
* fix(base_utils): keep later cache_control and billing metadata boundaries when merging system messages
* perf(base_utils): fold consecutive system messages in a single linear pass
The tuple accumulator passed to reduce copied the whole prefix on every step,
making map_developer_role_to_system_role O(n^2) in the number of messages.
Message count is not bounded by default, so a caller could tie up a proxy
worker with thousands of small messages before any provider call. Use a list
and merge into its last element in place instead.
* fix(base_utils): hoist later developer messages into the leading system message for non-OpenAI providers
A developer message that arrives after the first user turn (Codex CLI's
per-turn permissions item, a re-injected instruction after compaction, a
mid-conversation policy update) was translated to a system message in
place, and system-first chat templates such as Fireworks' qwen3.8 reject
any system message that is not at the beginning with 400. The fold that
merges consecutive system messages never saw it because a user turn sat
in between.
Move every developer message that follows the leading system block to
the end of that block before the fold, so it merges into the single
leading system message; client-authored mid-conversation system messages
stay where the client put them.
* fix(openai): hoist later developer messages into one leading system message on OpenAI-compatible backends
Developer role translation moves onto the provider config. OpenAI's own endpoint,
Azure OpenAI, and the o-series keep their current behavior. Every other config
inheriting OpenAIGPTConfig (Fireworks, DeepSeek, Together, vLLM, Groq, openai/
with a custom api_base) hoists developer messages that arrive after the leading
system block into that block and folds the block into a single system message,
which is what system-first chat templates require. Providers with their own
message format are untouched.
Messages carrying cache_control or Anthropic billing metadata fold as their own
text blocks, so breakpoints and provider-side stripping survive the merge. The
Responses bridge goes back to prepending instructions as a separate system
message and lets the hoist fold it.
* refactor(base_utils): fold each run of system messages in one pass
The pairwise fold recopied the accumulated system text or block list on every
merge, so a request carrying many consecutive system or developer messages cost
quadratic time in preprocessing. Group consecutive system messages once and
build the merged message from the whole run: plain strings join with a blank
line, and any cached, billing, or block content keeps one text block per
message. The name of the last named message in the run survives, as before.
* fix(base_utils): keep a closing developer message in place and hoist for OpenAIConfig backends
A developer message that closes the conversation stays where the client put it, translated
to system in place, so the request never ends on the assistant's turn. OpenAIConfig and its
subclasses (Azure AI Foundry, GitHub Copilot, ChatGPT, RAGFlow) now share the OpenAI-compatible
hoist, litellm_proxy passes developer messages through to the downstream proxy, and the Anthropic
billing header literals use the shared constant
* fix(base_utils): keep a closing developer message in place only after an assistant turn
A developer message that closes the conversation after a user or tool message hoists like
any other, so the request shape the ticket reports keeps working on system-first templates;
only a closing run that follows an assistant turn stays in place
* refactor(openai): reuse is_openai_backed_api_base for the hosted endpoint check
* test(base_utils): cover an empty system message inside a block-content run
Codecov flagged the empty-string branch of _text_blocks as the one line the
PR left uncovered. The existing empty-string test only hits the plain-text
join; this one forces the block path by merging an empty system message with
a developer message that carries list content.
* fix(openai): hoist developer messages for litellm_proxy and harden the system fold
- drop the LiteLLMProxyChatConfig passthrough so litellm_proxy/ hoists later developer messages like every other OpenAI-compatible endpoint, whichever backend or LiteLLM version sits downstream
- a system message with null or missing content inside a folded run is dropped instead of raising KeyError('content')
- a message-level cache_control on a list-content member lands on its last block so the breakpoint survives the fold
* fix(litellm_proxy): keep the AllMessageValues import the transform signatures still name
* fix(fireworks_ai): hoist developer items after the first turn on the native Responses path
The native Fireworks Responses path landed on staging mapping developer input items to
system in place, so a developer item after the first input item still hit the same
"System message must be at the beginning" 400 on system-first chat templates. The
ordering rules now live in one shared helper over item roles, and the native path
reorders through it before mapping, keeping a closing developer item after an assistant
turn in place exactly like the chat path does
* fix(transformation): carry the developer-message hoist onto main
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Mateo Wang
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7e14638001
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refactor(llms): rename model-version transformation files to family names (#48509)
gpt_5_transformation.py becomes gpt_reasoning_transformation.py (OpenAI and Azure), the Bedrock anthropic_claude3_transformation.py files become anthropic_claude_transformation.py, anthropic_claude2_transformation.py becomes anthropic_legacy_text_completions_transformation.py, and vertex_ai_partner_models/llama3 becomes vertex_ai_partner_models/llama. Class and symbol names are unchanged. Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Paul El Khoury
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d7620c77a1
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fix(openai): drop unsupported reasoning effort for gpt-6.1-sol (#43935)
* fix(openai): drop unsupported reasoning effort for gpt-6.1-sol gpt-6.1-sol accepts low, medium, high, xhigh, and max. none and minimal were still forwarded, because chat completions ignored an explicit supports_none_reasoning_effort=false and the Responses mapper never applied that contract. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(openai): mark the stripped reasoning object as outgoing JSON Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Azure responses reading the OpenAI effort map gpt-6-astra on Azure accepts reasoning.effort none. The responses gate was checking the OpenAI entry, which rejects it. Signed-off-by: Paul El Khoury <82139421+pOpO1-9@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com> * fix(openai): gate every reasoning_effort level from the cost map on chat and Responses One gate reads the model's cost-map row for whatever effort level a request asks for, on Chat Completions and the Responses API, for OpenAI and Azure. xhigh stays opt-in on chat (Azure also keeps none opt-in); every other level is refused only when its supports_<level>_reasoning_effort flag is false. A refused level is dropped under drop_params or answered with a local 400, and Responses keeps the rest of the reasoning object when it drops effort. The guards that follow judge temperature by the level the provider will see. Tests move into the mapped test files and derive the expected outcome for each level from the map row, so a new GPT-6 model needs only its row. * test(openai): pin gpt-6.1-sol's refused effort levels and prove the row flags alone drive the gate * fix(cost-map): azure gpt-6-astra refuses none and honors max on Responses, as live calls show * test(reasoning_effort): pin the astra max and none flips through the adapter and Foundry paths * fix(reasoning_effort): keep max out of the route gates and correct the gpt-5.3-codex rows The same model honors max on Responses and refuses it on Chat Completions, so one row flag cannot gate it on either route. The gates now skip max, the Azure gpt-6-astra rows keep max off so the /v1/messages adapter degrades to xhigh and /model_group/info stops short of it as on main, and chat still forwards max for the Responses bridge. The gpt-5.3-codex rows said none and xhigh off and minimal on; the live model answers the other way round (2026-10-01), and an opt-out gate would have dropped the levels Codex CLI sends. * fix(reasoning_effort): bridge function tools to Responses when the chat gate drops none * docs(reasoning_effort): correct the max advertisement note * fix(azure_ai): read the Foundry row on the Responses effort gate and turn none off for Azure gpt-6.1-sol * fix(azure): gate a prefixed Foundry deployment's Responses effort off its row litellm.responses(model="azure_ai/<deployment>", api_base=<Foundry host>) is re-routed to the azure provider with the azure_ai/ prefix intact, so the Azure Responses config saw a prefixed name, skipped it as another provider's pass-through, and forwarded none and minimal to Azure even under drop_params. The Azure gpt-5 resolver also read no row at all for a prefixed name. The Azure Responses gate now detects the family the way the Azure chat gate does, and an azure_ai/ name on the Azure OpenAI configs reads its azure_ai/ row when the map has one, else the azure/ twin, the rule the Foundry chat config already applies to the same deployment. * fix(cost-map): turn none off on azure/eu/gpt-6-astra like its sibling rows * docs(reasoning_effort): say how each gate reads none and shorten the module docstring * fix(azure_ai): call the public effort-level check from the Foundry Responses gate * test(reasoning_effort): fold the Foundry Responses tests into the mapped file and type the row helpers --------- Signed-off-by: Paul El Khoury <82139421+pOpO1-9@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> |
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Mateo Wang
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16645cc963
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fix(router)!: bound fake-streamed calls by the request timeout, not stream_timeout (#47162)
* fix(router): bound fake-streamed calls by the request timeout, not stream_timeout A stream=True call that the provider serves as one non-streaming request (Bedrock Converse for json_schema on models without native structured output, tools on some Llama models, ai21) gets no byte until generation ends, so stream_timeout acted as a total-duration cap. The Router now passes timeout and stream_timeout separately to chat completion calls, and completion() applies stream_timeout only when it reads a live stream. * test(timeout): cover stream_timeout on live streams only and the router's timeout split * fix(router): cover every fake-stream site and keep the target group's stream_timeout under prompt management * fix(router): never shorten a fake stream below stream_timeout, and split timeouts on every surface A faked stream now takes the longer of timeout and stream_timeout, so a caller who raised stream_timeout to cover a slow fake stream keeps that headroom. Azure o-series dispatch is mirrored when deciding whether a stream is faked. text_completion, /v1/messages and /v1/responses through the Router now get timeout and stream_timeout separately, like chat calls. * fix(router): report the effective stream timeout, split adapter streams, and cover M365 and Rust messages * fix(router): report and log the timeout each stream was bounded by Native /v1/messages and /v1/responses now record the timeout they applied, so x-litellm-timeout and the cooldown guard read the real limit instead of the raw request value. A prompt-managed model also passes on only the caller's or its own timeout, so the target deployment's timeout still wins. * fix(router): keep the caller's request_timeout on a prompt-managed handoff and report the applied stream limit * fix(router): give streams answered in one piece the longer limit and accept text timeouts on responses * fix(router): give /v1/messages and /v1/responses streams answered in one piece the longer limit * test(integration): cover faked, live and converted stream timeout limits per endpoint * test(router): regression tests for faked-stream timeouts |
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Kerry Lu
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e8550c1454
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fix(openai): send chat completions through client.post so the SDK's per-message param transform stops holding the event loop (#46967)
* fix(openai): send chat completions through client.post so the SDK's per-message param transform stops holding the event loop create() walks every message, content part and tool of the request through openai._utils._transform before posting, 91 ms at 300k tokens and ~300 ms at 1M tokens on the event loop, and returns the same dict for the plain dicts litellm builds. client.post is what create() calls after that walk, same request, headers, retries, raw response and stream objects, so the chat helpers now call it directly through the helper embeddings already used * fix(openai): type the chat client.post result as LegacyAPIResponse so the type gate sees .headers and .parse * fix(openai): assert the chat client.post result is a LegacyAPIResponse instead of casting it * test(openai): stub client.post with a LegacyAPIResponse spec in the empty-response and no-leak tests * test(core-utils): stub client.post with a LegacyAPIResponse spec in the agentic loop leak test * test: every client.post stub on the OpenAI chat path returns a LegacyAPIResponse-spec'd mock --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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ryan-crabbe-berri
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9cf09c18fe
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fix(providers): route Azure Responses past dated api versions, count Grok reasoning tokens on azure_ai, refresh provider sets after register_model, fix gpt-6.1-sol Azure rows (#46377)
* fix(azure): add responses_api_version so the Responses route stops using the deployment chat api_version * fix(azure_ai): fold Grok reasoning tokens into completion_tokens like the xai provider * fix(utils): refresh provider model sets after register_model * fix(cost-map): align azure gpt-6.1-sol reasoning effort flags with the openai row * test(e2e): cover Azure Responses on a deployment pinned to a dated chat api_version * fix(utils): keep router deployment ids out of provider model sets register_model now refreshes the provider sets, so the per-request and router registrations keyed by a deployment id put those opaque ids into wildcard model listings. Those callers now pass add_to_provider_model_sets=False. * fix(azure): carry responses_api_version through the chat to Responses bridge completion() dropped responses_api_version from the litellm_params it hands the Responses bridge, so azure/responses/<model> on a dated chat api_version still built the 404ing /openai/responses URL. Also cover the auto-router marker never forwarding the new param. * fix(azure): stop listing a wrong set of reasoning efforts when none is rejected The message said only low, medium and high are supported, which is wrong for models that also take xhigh such as gpt-6.1-sol. * test(azure): use the latest grok and gpt-5.4 rows in the new azure tests * fix(proxy): list each wildcard-expanded model once A provider set can hold a model both bare and provider-prefixed, which now happens after any priced request registers its openai/<model> key, so the openai/* listing showed that model twice. * fix(azure): route Responses past dated GA api_versions by default A deployment pinned to a dated GA api_version such as 2024-10-21 for chat now sends Responses calls (create, get, delete, cancel, input_items and the azure/responses/ bridge) to the default Responses version, because those dated versions have no Responses route on Azure and 404. responses_api_version still overrides it, -preview, v1, latest and preview versions are kept, an api-version in the api_base query still wins, and chat keeps api_version as before * chore(azure_ai): mark the grok chunk_parser dict as an override contract * fix(azure): rewrite only the route's /openai segment when moving a call to v1 The v1 rewrite in the Azure URL builder replaced every "/openai" substring in the path, so a gateway api_base like https://apim.example.com/openai-gw/team turned into /openai/v1-gw/team/openai/v1/responses. Dated GA Responses calls now land on the v1 route by default, which made this reachable for them too, so the rewrite now only touches the last /openai path segment. The Responses version resolver no longer duplicates the builder's default for an unset api_version. Tests cover the gateway api_base case, the env AZURE_API_BASE query-string precedence, and the e2e suite now has one test for the dated GA default and one where only responses_api_version can make the call work * test(integration): cover Azure Responses api_version, Grok reasoning spend, wildcard listing and reasoning_effort none Wire tests pin the Azure route and query for chat, Responses and the azure/responses bridge on a dated GA api_version, and check responses_api_version never reaches the request body. Cost cases check azure_ai Grok folds reasoning tokens into completion_tokens and spend, streaming and not. A config-driven proxy checks /v1/models next to an openai/* wildcard lists each id once and never a deployment id. Azure gpt-6.1-sol rejects reasoning_effort none before reaching upstream and drops it with drop_params * fix(utils): list ai21 chat and vertex code models under their provider wildcard register_model now files ai21 chat models into ai21_chat_models, which models_by_provider never read, so a registered ai21 chat model dropped out of ai21/* listings. models_by_provider now reads ai21_chat_models and the vertex code chat and code text sets too. * fix(main): keep caller-chosen model names out of provider wildcard listings --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> |
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devin-ai-integration[bot]
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e0398455d0
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test: migrate tests/llm_translation into unit, integration and e2e tiers (#45759)
* test: migrate selected llm translation contracts * test: migrate anthropic completion translation tests * test: migrate bedrock and cohere translation tests * test: tighten bedrock translation migration * test: migrate azure and openai model translation tests * test: migrate openai and small-provider translation tests * test: migrate gemini and vertex translation tests * test: migrate optional params and rerank translation tests * test: migrate huggingface, json and openrouter translation tests * test: fix openrouter integration expectations * test: migrate databricks, xai, cometapi and fireworks translation tests * test: migrate ovhcloud, prompt and small provider translation tests * test: split reasoning effort grid into unit and e2e * test: migrate router and realtime guardrail translation tests * test: migrate google interactions translation tests * test: migrate a2a, evals, skills and hosted vllm translation tests * test: remove remaining llm translation suite * test: tighten migrated llm translation unit tests and land missing rows Restores rows the first pass dropped or weakened (bedrock agentcore and openwebui thinking stream, anthropic prefix, citations and tool_choice, azure agents handler, huggingface bare api_base, optional params num_retries, alternating roles, rerank response type), replaces truthiness and call-count checks with whole-value assertions, and moves tests to the mirror file of the code they cover * test: move cohere, databricks, fireworks and gemini rows to mirror files over mocked HTTP Restores three TestCohereV2Transform methods the first pass nested out of collection, replaces direct transform calls with respx-backed completion calls, and drops the databricks and fireworks files that sat outside their mirror paths * test: close lost-intent gaps found in review of the llm translation migration Points the hosted-mock guard at the triton test's new integration path, restores exact rerank result assertions for infinity, drops the reasoning e2e fallback that passed for any multi-line answer, and adds the mixtral invoke system prompt variants, eval deletion, and async pdf url download that the legacy suite exercised * test: assert provider acceptance in the reasoning effort e2e The live half of the split grid proves each route accepts reasoning_effort. claude-fable-5-1 on the direct route answers without surfacing reasoning content, so a reasoning-presence check either fails on head or needs a fallback that passes for any answer. Wire shape stays covered by the unit grid * test: cover async and stream-end paths the legacy translation suite exercised Adds async variants for bedrock converse file and thinking content, bedrock embedding timeout and region resolution, interaction stream termination and success logging, xai reasoning token folding, and bytes chunks with a prefix before data:. Also scopes the vertex safety settings global in test_vertex_safety_settings with monkeypatch so it stops leaking into gemini request bodies on the same worker * test: type the new llm translation e2e calls and mark moved fixture dirs as packages * test: name the reasoning effort e2e models as module constants * test: assert reasoning content, register the new gemini coverage ids and give the guardrail config e2e a unique name * test: block the prompt the shared guardrail denies and drop the reasoning presence check * test: drop the duplicate litellm import left by the main sync --------- Co-authored-by: yuneng <yuneng@berri.ai> |
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devin-ai-integration[bot]
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fa2c8984ba
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test: move the unit half of 126 mixed legacy files into tests/unit (#45090)
* test: move the unit half of 126 mixed legacy files into tests/unit * test: restore litellm globals that moved tests set * test: finalize migration test cleanup * test: restore original bodies of moved legacy tests The move into tests/unit had rewritten 612 test bodies, and some of the rewrites dropped assertions. Each moved test now carries its original body from the legacy file, with only the imports, helpers, fake provider credentials and monkeypatched env it needs to run under tests/unit test_timeout_streaming goes back to tests/local_testing because it needs the fake OpenAI endpoint server. The image payload fixture moves with its only user, and two tests that leaked global state (a registered model cost entry and queued logging tasks) are now isolated * test: drop module imports shadowed by restored local imports * test: assert on LiteLLM output in no-assertion moved tests and isolate leaks Twenty no-assertion candidates get one assertion on the value LiteLLM returns, with the original lines unchanged. Four tests go back to their legacy files because they only check types or imports, write into the working directory, or cannot assert without a body change Two moved tests leaked globals into later tests in the same worker, so monkeypatch fixtures now restore the retry-after header parser and the end user cost tracking flags * test: drain queued logging tasks before the Phoenix span test The moved Phoenix test counted spans from logging tasks that earlier tests had queued, so the drain fixture moves to tests/unit/conftest.py and both it and the Datadog batch test use it. test_factory_function goes back to its legacy file because its returned wrapper calls the real Assistants API and cannot be asserted on without a body change --------- Co-authored-by: yuneng <yuneng@berri.ai> |
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devin-ai-integration[bot]
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dfe4df8c8a
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test: move whole-unit legacy test files into tests/unit and delete dead skips (#44807)
* test: delete unconditionally skipped legacy tests * test: move whole-unit legacy test files into tests/unit * test: keep moved legacy tests free of import-time global state * test: keep the module-level invocation scan pointed at tests/local_testing * ci: drop the agent_testing CircleCI job emptied by the move * test: fix moved-test isolation and router coverage * test: add Tinyfish search package marker * test: isolate moved tests from logger state leaks * test: isolate Helicone logging fixture state * test: isolate Vertex pass-through credentials between moved tests * test: cancel S3 periodic flush tasks started by moved tests * ci: restore CircleCI assistant test selection after move * test: prevent Datadog datetime import shadowing * ci: drop the litellm_assistants_api_testing CircleCI job emptied by the move * test: deduplicate imports in rebased unit tests * test: remove duplicate passthrough router patch import * test: remove moved legacy source files after rebase * test: align moved tests with rebased main * test: carry main's legacy-file edits into moved destinations * test: make the moved cost map fallback tests assert the fetch and the backup The four fallback cases only checked the result was non-empty, so they still passed with integrity validation disabled. They now inject a mock client, assert one fetch happened, and assert the result is exactly the local backup with the fallback reason recorded. --------- Co-authored-by: yuneng <yuneng@berri.ai> |
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yuneng-jiang
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5e6dc89ba1
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test: move tests/test_litellm/llms into tests/unit/llms (#43191)
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci: rename fork-flag to unit-flag now that it applies on every event * test: move tests/test_litellm root and small trees into tests/unit Pure renames, no content changes. Follow-up commits in this PR fix references, merge the three files that already existed in tests/unit, keep live-provider tests in tests/test_litellm and wire CI. * test: carry tests/test_litellm conftest isolation into tests/unit Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS, proxy-URL and keychain env, and session-end client cleanup now reset for unit tests too. The environment isolation owns its MonkeyPatch so a test's own monkeypatch is undone before the model-cost teardown runs. * test: merge, split and prune the moved root and small-tree tests Merge batches/test_batch_utils.py and the chat_completions and messages dispatch tests into the files that already existed in tests/unit. Keep the live Gemini interactions tests, the async image-fetch format test and the OpenAI embedding scorer test in tests/test_litellm since they need real network or keys. Put test_router.py under tests/unit/test_router so the existing package no longer shadows it. Delete eight tests the audit found superseded by stronger ones kept in this move. * ci: run the moved root and small-tree tests under their legacy flags Add the misc and responses-caching-types flags to unit_selection.sh and CircleCI, extend enterprise-routing and mcp-integration, and point the legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest and change classifier at the new paths. * test: make the new tests/unit directories packages tests/unit/test_package_layout.py requires every directory to carry an __init__.py, and without one the moved and retained test_litellm_responses_bridge.py modules collide on import. * test: scope the unit socket block to tests/unit in shared sessions The GHA shards collect the legacy test-path and the unit selection in one pytest session. The unit conftest's loopback-only block leaked into legacy modules that reach the network at import. The legacy conftest now lifts the restriction at collect and setup time, and the unit conftest re-applies it when collecting its own modules. * test: move tests/test_litellm/llms into tests/unit/llms Rename-only. Moves the provider tests and the fine-tuning fixtures they load, mirroring the old paths. Follow-up commits merge, split and wire them. * test: merge, split and prune the moved llms tests Merges the Databricks chat transformation tests into the existing unit file, keeps the tests that need real keys or the network in tests/test_litellm, deletes the audited tests a stronger unit test already covers, and points imports at tests.unit.llms. * ci: run the moved llms tests under their legacy flags The Vertex AI and All Other Providers shards keep their legacy test-path for the retained files and add the llm-vertex-ai and llm-other-providers unit selections. CircleCI gets matching unit jobs. * test: make the tests/unit/llms directories packages Adds __init__.py to the moved dirs and drops the legacy ones whose directories no longer hold tests. * test: drop script runners and path hacks the llms split left dangling The __main__ runners in the split openai_like files and the Databricks e2e runner called tests that now live in the other half of the split or were deleted. The retained legacy halves also no longer need sys.path edits. * test: give the shard-script tests their own GITHUB_OUTPUT They only passed where the runner set it. The CircleCI unit job's env allowlist drops it, so the script's redirect failed there. * test: point the router and module-deletion checks at tests/unit router_code_coverage and code_qa_check_tests only searched tests/test_litellm, so the moved router tests no longer counted. The two silent-experiment tests the audit deleted were the only direct callers of those methods; they are replaced with tests that assert the forwarded shadow request and the recursion guard. * test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path The Databricks e2e file is a manual script whose main() calls the tests that were pruned, so pruning them broke the documented run. It is back to its main version. The SageMaker Nova docstring now points at the file's real location in tests/local_testing. * test: keep the job's UNIT_FLAG out of the shard-script tests --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |