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9 commits
| Author | SHA1 | Message | Date | |
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yuneng-jiang
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6a0d03914c
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test: drop the cwd-relative sys.path.insert calls from the test suite (#37802)
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
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mateo-berri
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791b478d77 |
fix(router): only resolve structured input when messages is absent
Keeps an explicit empty messages list on the pre-existing path (default model, provider validation error) instead of dropping the routing decision and surfacing a misleading tags 401. |
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mateo-berri
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dd18389365 |
fix(router): route Responses API input through the auto-router
Auto-router strategy hook returned None whenever the request carried input instead of messages, so tagged /v1/responses requests (Codex CLI) never picked a tier and tag filtering left nothing to route to. Resolve input through the shared prompt-template helper before matching routes. |
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Abhimanyu Kapur
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c76882b51b
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fix(auto-router): stop the embedding model's context window from failing long requests (#35956)
* fix(auto-router): stop the embedding model's context window from failing long requests The auto-router embeds the last user message to pick a model and sent it to the embedding model unbounded. Embedding models carry 512 to 8k token windows while the chat models they route to carry 200k+, so any prompt over the encoder's window failed at the routing step with a 400 the destination model would never have raised. Cut every doc to a character cap inside LiteLLMRouterEncoder, which is the one choke point the auto-router, complexity-router, semantic guard and MCP tool filter all share. Default 2000 chars, roughly 500 tokens, which fits even a 512-token self-hosted encoder, overridable per deployment with auto_router_max_input_chars and globally with DEFAULT_MAX_EMBEDDING_INPUT_CHARS. Truncation alone cannot cover provider-side batch and byte limits, so any failure of the route call now falls back to the auto-router's default model instead of propagating. That path also fixes two latent bugs: a no-match left the auto-router alias in place as the model name, which fails downstream with "Unmapped LLM provider" rather than reaching default_model, and an empty route list raised IndexError. Fixes #17869 Fixes #20277 * fix(auto-router): make the embedding input cap opt-in so guards still see whole prompts Defaulting the cap inside the shared encoder truncated every consumer, not just the auto-router. The semantic guard builds the same encoder, so its pre-call check would have classified only the first 2000 characters while the full message still reached the model, which a benign opener in front of an injection payload walks straight past. The MCP tool filter and complexity router were silently narrowed the same way. The encoder now defaults to sending docs whole and cuts only when a caller passes max_input_chars. The auto-router is the only caller that does, so guard, MCP filter and complexity-router behaviour is unchanged from before this branch. DEFAULT_MAX_EMBEDDING_INPUT_CHARS becomes DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS, since it is now specific to the auto-router, and drops its env override: the per-deployment auto_router_max_input_chars already covers it, and every env var in constants.py has to be documented, which is what broke the documentation and code-quality checks. Also drops the added comments and the redundant type: ignore that review flagged. * test(auto-router): cover the max_input_chars wiring from litellm_params Nothing asserted that auto_router_max_input_chars on the deployment reaches the AutoRouter that embeds prompts. Dropping the wiring left every test green while the cap silently reverted to the default, so an operator with a 512-token embedding model could not lower it and every long prompt would fall back to the default model instead of being routed. * test(auto-router): cover the populated route-choice list branch The route layer can hand back a list, and picking its first element is where the IndexError lived: the empty case was covered but the populated one was not, so the branch that reads route_choice[0].name could be deleted with every test still green. |
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Krrish Dholakia
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e7bc316db0
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Litellm krrish staging 04 20 2026 (#26138)
* feat(router): add auto_router/quality_router for quality-tier routing (#25987) * feat(router): add auto_router/quality_router for quality-tier routing Adds a new auto-router type that routes a request to a model at a target quality tier. The quality tier is inferred by re-using the existing ComplexityRouter's classification, then mapped through an admin-configured complexity_to_quality table. Each candidate model declares its own quality_tier in model_info.litellm_routing_preferences. Resolution strategy: exact tier match, else round up to the next higher tier, else fall back to default_model. Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * feat(quality_router): add capability-based filtering Each deployment can declare a `capabilities: List[str]` field in `model_info.litellm_routing_preferences` (e.g. ["vision", "function_calling"]). Requests can pass `litellm_capabilities` in `request_kwargs` to require specific capabilities — the router will only route to deployments whose declared capabilities are a superset. Resolution still walks tier (exact → round up), but at each tier filters by capability before picking. Falls back to default_model only when it also satisfies the required capabilities; otherwise raises rather than silently routing to a model that lacks a required capability. Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * feat(quality_router): expose routing decision in response headers For transparency, expose the QualityRouter's routing decision in the proxy response headers: x-litellm-quality-router-model → picked model_name (e.g. "haiku-vision") x-litellm-quality-router-tier → resolved quality tier (e.g. "1") x-litellm-quality-router-complexity → ComplexityTier name (e.g. "SIMPLE") Mechanism: the pre-routing hook stashes the decision in request_kwargs["metadata"]["quality_router_decision"]. After the call returns, Router.set_response_headers lifts the decision into response._hidden_params["additional_headers"] alongside the existing x-litellm-model-group / x-litellm-model-id headers. Existing metadata keys (trace_id, user_id, etc.) are preserved. Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * feat(quality_router): replace capabilities with keyword override Drops the capability-based filtering in favor of a keyword-based override for v0: - RoutingPreferences.keywords: List[str] (replaces capabilities) — each deployment can declare substring keywords. - If any declared keyword (case-insensitive) appears in the user message, the router short-circuits the complexity-classification flow and routes to the matching deployment. - Tiebreaker for overlapping keyword matches: quality_tier DESC, then cheapest model_info.input_cost_per_token ASC. Unpriced models lose ties to priced ones. Decision metadata + headers now expose the override: x-litellm-quality-router-via → "keyword" | "quality_tier" x-litellm-quality-router-keyword → matched keyword (only on keyword route) x-litellm-quality-router-complexity → complexity tier (only on tier route) Removes: - request_kwargs["litellm_capabilities"] reading - _model_capabilities, _model_supports_capabilities, _first_capable_model_at_tier, capability filter in _resolve_model_for_quality_tier Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * feat(quality_router): add explicit `order` to RoutingPreferences Adds an explicit priority field to RoutingPreferences for resolving collisions deterministically: RoutingPreferences.order: Optional[int] # lower wins; unset = +inf Used as the PRIMARY tiebreaker in two places: 1. Keyword overlap: when multiple deployments declare the same matching keyword, sort by (order ASC, quality_tier DESC, input_cost_per_token ASC, model_name ASC). Explicit always beats implicit. 2. Tier resolution: when multiple deployments share a quality tier, `_resolve_model_for_quality_tier` picks the one with the lowest order. The tier list is now sorted at index-build time. This lets admins make routing decisions explicit when the natural quality-and-price ordering would pick the wrong model. Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * feat(quality_router): reorder tiebreak to (quality, order, price) Changes the tiebreak ordering so quality_tier always wins first, then explicit `order` is used to break ties within the same tier, then price breaks the rest: 1. quality_tier DESC ← best model wins first 2. order ASC ← explicit priority within a tier 3. input_cost_per_token ASC 4. model_name ASC Previously `order` was the primary key — that meant a tier-2 model with `order=1` would beat a tier-3 model with no `order`, which is the wrong default. Now `order` only resolves collisions among same-tier candidates. Tier resolution (within a single tier) keeps the same key minus quality: (order ASC, cost ASC, name). Test renames + flips: - test_explicit_order_overrides_quality_tier → test_quality_wins_over_explicit_order - new: test_order_breaks_tie_within_same_quality_tier Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * fix(quality_router): resolve Greptile review feedback Addresses four P1 findings from PR review plus test coverage: 1. set_model_list missing quality_routers reset - Hot-reloading the Router would leave stale QualityRouter instances pointing at the old model_list. `set_model_list` now clears `self.quality_routers` alongside the other indices. 2. Round-down fallback before default_model - `_resolve_model_for_quality_tier` now rounds DOWN to the closest lower tier after round-up fails, before falling back to `default_model`. Degrades gracefully rather than jumping straight off-tier. 3. RoutingPreferences validation bypass - `_build_tier_index` now instantiates `RoutingPreferences(**prefs)` so invalid shapes (e.g. non-int quality_tier) raise a clear ValueError instead of silently succeeding. 4. Config-ordering dependency - `_tier_to_models` is now built lazily on first access. Previously, eager construction in `__init__` meant a QualityRouter deployment had to appear AFTER all its referenced models in config.yaml, because `Router._create_deployment` populates `model_list` incrementally. Any `available_models` defined after the router entry would silently be reported as missing. Also adds 6 new tests covering each fix: - test_invalid_quality_tier_type_raises_clear_error - test_router_can_be_instantiated_before_its_targets_exist - test_set_model_list_clears_quality_routers_registry - test_rounds_down_when_no_higher_tier_exists - test_rounds_down_prefers_closest_lower_tier - test_prefers_round_up_over_round_down Co-Authored-By: Claude Opus 4 (1M context) <noreply@anthropic.com> * style: apply black 24.10.0 formatting to pre-existing offenders Unblocks the LiteLLM Linting check for this PR — these 12 files are already failing `black --check` on main (the lint workflow only runs on PRs, so main drifts). No behavior changes; formatting-only. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Update litellm/router.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --------- Co-authored-by: Claude Opus 4 (1M context) <noreply@anthropic.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * Support /v1/responses in complexity router (#26137) * feat(proxy): add --reload flag for uvicorn hot reload (dev only) Opt-in CLI flag, off by default, no env var. Only affects the uvicorn run path; gunicorn/hypercorn paths and prod (which doesn't pass the flag) are unaffected. * Feature/add audio support for scaleway (#26110) * feat(scaleway): add SCALEWAY to LlmProviders enum * feat(scaleway): add audio transcription config and dispatch wiring Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * test(scaleway): add behavior tests for audio transcription config Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * chore(scaleway): advertise audio_transcriptions in endpoint-support JSON * docs(scaleway): document audio transcription support * fix(scaleway): address PR review — plain-text response_format + missing-key fail-fast Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * test(scaleway): cover new response paths, drop gettysburg.wav coupling Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * Prompt Compression - add it to the proxy (#25729) * refactor: new agentic loop event hook simplifies how to create logic for tool based multi llm calls * fix: compress - make it work on anthropic input as well * fix(compress.py): working prompt compression for claude code ensures claude code messages can run through proxy easily * docs: add agentic loop hook guide * docs: add agentic_loop_hook to sidebar * fix: fix multiple arguments error * fix: fix tool call loop for compression on streaming /v1/messages * fix: fix linting errors * fix: fix ci/cd errors * feat(litellm_pre_call_utils.py): use claude code session for litellm session id allows claude code logs to be stitched together, making it easy to know they were all part of the same conversation * fix: suppress incorrect mypy warning rE: module * revert: drop PR's changes to litellm/proxy/_experimental/out/ Restores the 34 HTML files under _experimental/out/ to their pre-PR paths (X/index.html -> X.html). All renames are R100 (content unchanged); no other files are touched. * fix: address greptile review comments on PR #25729 - Skip ``kwargs["tools"] = []`` injection when compression is a no-op — Anthropic Messages rejects empty tool arrays on requests that did not originally declare tools. - Move agentic-loop safety guards (fingerprint cycle / max depth) out of the per-callback try/except so they propagate instead of being swallowed by the generic exception handler. Extracted _check_agentic_loop_safety. - Gate generic ``x-<vendor>-session-id`` capture behind the LITELLM_CAPTURE_VENDOR_SESSION_HEADERS env var (off by default) to preserve backwards compatibility; explicit x-litellm-* headers are unaffected. - Fix monkeypatch target in pre-call-hook test to patch the actual module-level binding (litellm.integrations.compression_interception.handler.compress). - Add regression tests for empty-tools skip and opt-in session capture. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * revert: drop LITELLM_CAPTURE_VENDOR_SESSION_HEADERS flag Generic x-<vendor>-session-id header capture is a new feature and only runs *after* the explicit x-litellm-trace-id / x-litellm-session-id checks, so it does not change behavior for any existing caller that was already using the LiteLLM headers — no backwards-incompatibility to gate. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor(compress): replace input_type with CallTypes call_type Drop the bespoke ``CompressionInputType`` literal and use the existing ``litellm.types.utils.CallTypes`` enum instead. ``litellm.compress()`` now takes ``call_type: Union[CallTypes, str]`` (default ``CallTypes.completion``) — no new concept to learn, and the enum is already the way the rest of the codebase talks about request shapes. Supported values: ``completion`` / ``acompletion`` (OpenAI chat-completions shape) and ``anthropic_messages`` (Anthropic structured content blocks). Updated: compress(), the compression_interception handler, tests, docs, and the two eval scripts. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * Support /v1/responses in complexity router Adds cross-format support to the complexity router via the guardrail translation handler dispatch. Adds get_structured_messages to base translation plus OpenAI chat, Responses, and Anthropic handlers. Auto-router helper _extract_text_from_messages handles tool-call and multimodal messages. Widens async_pre_routing_hook messages type to Dict[str, Any]. Fixes https://github.com/BerriAI/litellm/issues/25134 * chore: apply black formatting * fix: fallback to trying each handler when route inference fails --------- Co-authored-by: Ryan Crabbe <ryan@berri.ai> Co-authored-by: nhyy244 <106547304+nhyy244@users.noreply.github.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * test: cover _is_quality_router_deployment and init_quality_router_deployment * fix: reset auto_routers on set_model_list to prevent hot-reload ValueError * style: apply black formatting to websearch_interception and agentic_streaming_iterator --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Opus 4 (1M context) <noreply@anthropic.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Ryan Crabbe <ryan@berri.ai> Co-authored-by: nhyy244 <106547304+nhyy244@users.noreply.github.com> |
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Ishaan Jaffer
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e8461b5b97
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style: run black formatter on files from main merge | ||
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Ishaan Jaff
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20450bfe94 | fix mapped test | ||
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Ishaan Jaff
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106a298f0a
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[Feat] UI - Allow Adding LiteLLM Auto Router on UI (#12960)
* add router.json
* test_router_auto_router
* async_pre_routing_hook
* fixes for auto router
* add async_pre_routing_hook
* add LiteLLMRouterEncoder
* update test auto_router_embedding_model
* add auto_router_embedding_model
* add AutoRouter
* fix async_pre_routing_hook
* update async_pre_routing_hook
* fix auto router
* fix router.json
* working router init
* working embedding encoder
* working auto router
* test_router_auto_router
* test auto router
* add semantic-router as optional for litellm
* add extras
* semantic_router==0.1.10
* ruff fix
* use aiohttp==3.10.11
* python-dotenv==1.0.1
* test auto router
* test_router_auto_router
* semantic_router
* test_is_auto_router_deployment
* fix check
* fix docker build step
* add semantic_router
* UI - Add auto router on litellm
* working utterances config
* fix route config builder
* kind of working add automodel router
* move loc of add deployment
* fixes for AutoRouter
* add auto_router_config in types.py
* fixes for init_auto_router_deployment
* fix adding auto router models
* working auto-router with dB
* Revert "add semantic_router"
This reverts commit
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Ishaan Jaff
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b8e404dd95
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[Feat] Backend Router - Add Auto-Router powered by semantic-router (#12955)
* add router.json
* test_router_auto_router
* async_pre_routing_hook
* fixes for auto router
* add async_pre_routing_hook
* add LiteLLMRouterEncoder
* update test auto_router_embedding_model
* add auto_router_embedding_model
* add AutoRouter
* fix async_pre_routing_hook
* update async_pre_routing_hook
* fix auto router
* fix router.json
* working router init
* working embedding encoder
* working auto router
* test_router_auto_router
* test auto router
* add semantic-router as optional for litellm
* add extras
* semantic_router==0.1.10
* ruff fix
* use aiohttp==3.10.11
* python-dotenv==1.0.1
* test auto router
* test_router_auto_router
* semantic_router
* test_is_auto_router_deployment
* fix check
* fix docker build step
* add semantic_router
* Revert "add semantic_router"
This reverts commit
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