Fixes#22646
Adds pricing for DashScope models that were missing from the cost map,
causing $0 spend tracking in the proxy dashboard:
- dashscope/qwen3-max-2026-01-23 (tiered, same as qwen3-max)
- dashscope/qwen3-next-80b-a3b-instruct ($0.15/$1.20 per 1M)
- dashscope/qwen3-next-80b-a3b-thinking ($0.15/$1.20 per 1M)
- dashscope/qwen3-vl-235b-a22b-instruct ($0.40/$1.60 per 1M)
- dashscope/qwen3-vl-235b-a22b-thinking ($0.40/$4.00 per 1M)
- dashscope/qwen3-vl-32b-instruct ($0.16/$0.64 per 1M)
- dashscope/qwen3-vl-32b-thinking ($0.16/$2.87 per 1M)
Fixes#22609
Adds pricing for OpenRouter models that were routing correctly but
returning $0 for spend tracking due to missing cost map entries:
- openrouter/anthropic/claude-sonnet-4.6 ($3.00/$15.00 per 1M tokens)
- openrouter/google/gemini-3.1-pro-preview ($2.00/$12.00 per 1M tokens)
- openrouter/openai/gpt-5.1-codex-max ($1.25/$10.00 per 1M tokens)
- openrouter/qwen/qwen3-coder-plus ($1.00/$5.00 per 1M tokens)
- openrouter/z-ai/glm-5 ($0.80/$2.56 per 1M tokens)
* feat(guardrails): team-based guardrail registration and approval workflow
Add team-based guardrail submission system where teams can register
Generic Guardrail API guardrails for admin review. Includes:
- POST /guardrails/register endpoint for team-scoped submissions
- Admin review endpoints (list/get/approve/reject submissions)
- Team Guardrails tab in the UI dashboard
- extra_headers support for forwarding client headers to guardrail APIs
- Prisma schema migration for status, submitted_at, reviewed_at fields
- Documentation for team-based guardrails and static/dynamic headers
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): address review feedback - SSRF, silent failure, redundant query
- Validate api_base URL scheme (http/https only) and hostname in
register_guardrail to prevent SSRF via team submissions
- Return warning field in approve response when in-memory initialization
fails so admins know the guardrail won't work until next sync cycle
- Eliminate redundant DB query in list_guardrail_submissions by fetching
all team guardrails once and deriving both filtered list and summary
counts from the single result set
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): add pending_review status guard to reject endpoint
Prevent rejecting already-active or already-rejected guardrails, which
would create a DB/memory inconsistency (active in memory but rejected
in DB). Now mirrors the approve endpoint's status check.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
OpenRouter supports the Responses API at /api/v1/responses with
encrypted_content for multi-turn stateless reasoning workflows.
Without native registration, requests fall through to the chat
completion bridge, which uses a different format (reasoning_details)
and drops encrypted_content entirely.
This adds OpenRouterResponsesAPIConfig to route requests directly to
OpenRouter's Responses API endpoint, preserving encrypted_content.
Fixes https://github.com/BerriAI/litellm/issues/22189
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
The _resolve_jwks_url method checks response.status_code != 200, but
MagicMock returns a MagicMock object for status_code which is always
truthy (!= 200). Explicitly set mock_response.status_code = 200 so the
tests exercise the intended code path.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
mapped passthrough routes (vertex_ai, bedrock, etc) were compared
against the raw request path without prepending SERVER_ROOT_PATH.
db-registered routes already used _build_full_path_with_root for this
but the mapped routes branch was missed.
fixes#22272
DualCache.async_set_cache and async_set_cache_pipeline were missing the
default_in_memory_ttl injection that the sync set_cache method has. This
caused InMemoryCache to fall back to its own default_ttl (600s) instead
of using DualCache's configured default_in_memory_ttl (typically 60s).
This is particularly impactful for end-user budget enforcement in the
proxy, where cached spend values could remain stale for 10 minutes
instead of 1 minute, allowing users to exceed their budgets.
The response.completed handler in the completion→responses streaming
bridge was discarding the usage object, causing prompt_tokens_details
(and cached_tokens) to always be None when streaming with models that
use the Responses API (e.g. gpt-5.2-codex, gpt-5.3-codex).
Extract usage from the response.completed event and translate it via
the existing _transform_response_api_usage_to_chat_usage helper.
Fixes#22192
All 55 deepinfra models that had `supports_tool_choice: true` were
missing the `supports_function_calling` flag, causing
`litellm.supports_function_calling()` to incorrectly return False.
Fixes#22619
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Add CrowdStrike AIDR guardrail hook
* fixup! use apply_guardrail event hook
* fixup! update imports
* fix(guardrails): include AI response in CrowdStrike AIDR output events
Issue:
_build_guard_input_for_response() was:
- Sending only the original user input (messages).
- Not sending the AI provider response.
This fix will:
- Extract response.choices from the ModelResponse object and include them in guard_input payload.
- Thus, ensure AIDR output rules receive the AI-generated content for analysis.
- Fix and update tests.
* fix(guardrails): prevent duplicate input events in CrowdStrike AIDR guardrail
Issue:
The CrowdStrike AIDR guardrail was running on during_call hooks wihtout event_hook configured.
This fix will:
- Set event_hook to ["pre_call", "post_call"] (AIDR admins will control what policy is applied)
This change will:
- Require default_on parameter
- Prevent duplicate API calls to AIDR for the same input
- Avoid unchecked AI provider API calls on during_call hook
* docs: add CrowdStrike AIDR to the list of Guardrails under Integrations
* docs: update CrowdStrike AIDR documentation page
---------
Co-authored-by: Konstantin Lapine <konstantin.lapine@crowdstrike.com>
Reorder elif branches so is_vertex_ai is checked before "gemini" in model.
Previously, Vertex AI Gemini models (e.g. vertex_ai/gemini-2.5-flash) matched
the "gemini" substring check first and were logged with the Google AI Studio
URL instead of the Vertex AI URL.
mistral-small-latest now points to Small 3.2 (since June 2025).
Updated pricing from $0.10/$0.30 to $0.06/$0.18 per 1M tokens,
context from 32k to 131k, and added vision support to match
mistral-small-3-2-2506.
Add 9 new Mistral models (mistral-large-2512, mistral-medium-3-1-2508,
mistral-small-3-2-2506, ministral-3-3b/8b/14b-2512, saba-2502,
magistral-medium/small-1-2-2509) and update mistral-large-latest,
mistral-large-3, and mistral-medium-latest with correct pricing and
context windows.
Fixes#22585
Fixes#22591 - These models were missing from the pricing JSON, causing
$0 cost tracking when routed via the dashscope/* wildcard.
Pricing sourced from official Alibaba Cloud Model Studio docs (international tier).
Fixes NameError at runtime when ChatGPTToolCallNormalizer is
instantiated. The imports were missed when type hints were changed
from Python 3.10+ syntax (dict[], str | None) to typing module
syntax (Dict[], Optional[str]).
