For multi-turn conversations, convert thinking_blocks on assistant
messages into content blocks prepended before the rest of the content,
so reasoning context is passed back to the hosted_vllm API.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix aviation safety topic filter: remove overly broad exceptions, add cockpit access block words
* fix airline brand protection filter: add identifier words, competitor/ops block words, tighten exceptions
* update policy templates with competitor pre/post guardrails and streaming enrichment
* sync policy_templates_backup.json with policy_templates.json
* add streaming enrichment endpoint, competitor variations, and model selection
* add streaming enrichPolicyTemplate networking function
* rewrite template parameter modal with streaming tags, AI/manual toggle, model selector
* update policies panel to pass enrichment options and show discovered competitors
* show discovered competitors as tags in guardrail selection modal
* use llm_router instead of litellm.acompletion, extract helpers, move constants
* validate competitors list size, cap variation prompt input
* add refinement instruction support for competitor discovery
* add instruction and existingCompetitors params to streaming enrichment
* add refinement input for iterating on competitor list with AI
* emit status events during variation generation so UI shows progress
* add onStatus callback to streaming enrichment
* show status spinner during variation generation, widen modal to 700px
* add tests for competitor enrichment helper functions
Add a new team member permission `/team/daily/activity` that allows
non-admin team members to see all team usage data, not just their own.
## Changes
- Add `TEAM_DAILY_ACTIVITY` to `KeyManagementRoutes` enum and available
team member permissions
- Add `_team_member_has_permission` helper in `common_utils.py`
- Modify `/team/daily/activity` endpoint to skip API key filtering when
the member has this permission
- Add permission description and method detection in the UI
- Add backend and frontend tests
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Four tests were broken by commit e00c181f0c (Mcp user permissions #21462):
1. test_list_tools_single_server_unprefixed_names: The commit changed
_get_tools_from_mcp_servers to always add server prefixes (add_prefix=True),
removing the conditional that skipped prefixing for single servers.
Updated assertion from "toolA" → "zapier-toolA".
2. test_mcp_get_prompt_success: mcp_get_prompt now extracts the server name
from a prefixed prompt name via split_server_prefix_from_name(). Passing
unprefixed "hello" returns server_name="" which matches no server → 403.
Updated call to use "server_a-hello" so the server lookup succeeds.
3. test_e2e_jwt_team_mcp_permissions_enforced &
4. test_e2e_jwt_team_mcp_key_intersection:
The commit replaced `from typing import List` with
`from litellm.proxy.proxy_server import general_settings` in
MCPRequestHandler.get_allowed_mcp_servers(). Both tests mock
litellm.proxy.proxy_server with a types.ModuleType that lacked
general_settings, causing ImportError. Added general_settings={} to
both mock modules.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
test_complete_reload_flow and test_distributed_reload_check_function both
trigger code paths that assign a minimal stub dict to litellm.model_cost
(via the /reload/model_cost_map endpoint and _check_and_reload_model_cost_map).
Without restoring, subsequent tests in the same worker can't find gpt-4o
pricing and calculate spend=0.0 instead of the expected value.
Added try/finally save-and-restore of litellm.model_cost in both tests,
matching the pattern used in test_reload_model_cost_map_admin_access.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(schema.prisma): add object permissions for end users
allows controlling if end user can call specific mcp servers
* feat: cleanup for customer_endpoints support of object permission id
* fix: cleanup str
* feat(customers/): enforce end user can only call allowed mcps - if configured
* docs: document customer/end user object permission usage
* feat: enforce end user permissions on MCP tool calls
This commit implements end user permission enforcement for MCP servers:
1. Always add server prefixes to MCP tool names
- Removed conditional logic that only added prefixes when multiple servers existed
- Now always adds server prefix for consistent tool naming across all scenarios
- Updated 5 locations in server.py (list_tools, get_prompts, get_resources,
get_resource_templates, get_prompt)
2. Created MCP End User Permission Guardrail Hook
- New guardrail hook: litellm/proxy/guardrails/guardrail_hooks/mcp_end_user_permission.py
- Runs on post_call to validate tool calls in LLM responses
- Extracts MCP server name from tool names (splits on first '-')
- Checks if end_user_id has permissions for the MCP server
- Raises GuardrailRaisedException if end user lacks permission
- Supports both streaming and non-streaming responses
3. Added comprehensive tests
- Test file: tests/test_litellm/proxy/guardrails/guardrail_hooks/test_mcp_end_user_permission.py
- Tests cover: authorized/unauthorized tools, non-MCP tools, no end_user scenarios
- Tests permission checking logic and exception raising
The hook integrates with the existing MCPRequestHandler._get_allowed_mcp_servers_for_end_user
to fetch end user permissions and enforce access control at the response level.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
* refactor: remove redundant add_prefix variable assignments
Simplified the code by removing intermediate `add_prefix` variable
assignments and passing `True` directly to function calls since
we now always add server prefixes.
Changes:
- Removed `add_prefix = True` variable assignments in 5 locations
- Changed `add_prefix=add_prefix` to `add_prefix=True` in function calls
- Added inline comments to clarify the behavior
This makes the code more concise and clearer in intent.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
* feat(auth_utils.py): support safety_identifier as a valid way of passing the end user id for responses api
* feat(llms): ensure 'tools' is correctly updated for responses api
* fix: fix greptile feedback
* feat: transformation.py
proper responses api tool handling for guardrail translation layer
---------
Co-authored-by: Claude Sonnet 4.5 <noreply@anthropic.com>
* feat(ui/): initial commit adding a compliance testing playground
allow proxy admins to test policies and guardrails against datasets
* feat(ui/): make score more friendly
* feat(policy_endpoints.py): new helper function for testing policies
* feat(policy_endpoints.py): expose new endpoint for testing policies and guardrails
enables compliance playground to work as expected
* feat(complianceui.tsx): show returned text
* docs: add DATABRICKS_API_KEY to environment settings reference
* fix: streaming test usage check on Pydantic model
* fix: mock litellm.proxy.proxy_server in test_skip_server_startup
Users had to set store_model_in_db in the config YAML and restart the proxy,
causing service downtime. This change allows the value to be written to the
LiteLLM_Config table and read from the database at runtime, with DB values
overriding config file values.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(middleware): replace BaseHTTPMiddleware with pure ASGI middleware
BaseHTTPMiddleware wraps streaming responses with receive_or_disconnect
per chunk, blocking the event loop and causing severe throughput
degradation under concurrent streaming load (53% of CPU in profiling).
Converts PrometheusAuthMiddleware to a pure ASGI middleware using the
__call__(scope, receive, send) protocol.
* fix(streaming): remove expensive debug logging and optimize usage stripping
- Remove print_verbose calls that format chunk/response Pydantic objects,
triggering millions of __repr__ calls (8% of CPU in profiling)
- Guard remaining verbose_logger.debug with isEnabledFor(DEBUG) and use
lazy %s formatting instead of f-strings
- Replace usage stripping round-trip (model_dump + delete + reconstruct)
with a _usage_stripped flag, deferring exclusion to serialization time
* fix(proxy): remove per-chunk debug log and use _usage_stripped flag
- Remove verbose_proxy_logger.debug that formatted every streaming chunk
- Honor _usage_stripped flag from streaming handler to exclude usage
during model_dump_json serialization instead of reconstructing objects
* fix(proxy): remove per-chunk debug log in async_data_generator
Remove verbose_proxy_logger.debug that formatted every streaming chunk,
which triggered expensive Pydantic serialization on the hot path.
* fix indentation and add clarifying comment for usage stripping
* fix: guard calculate_total_usage against None usage in chunks
* fix: store chunk copy to preserve usage for calculate_total_usage
When `default_internal_user_params` was set, `insert_sso_user()` only
preserved SSO-provided roles if `role_mappings` was explicitly configured.
Roles from other valid SSO sources (Microsoft app_roles,
GENERIC_USER_ROLE_ATTRIBUTE, custom SSO handlers) were silently
overwritten with the default "internal_user" role, causing admin users
to be downgraded on first login or after user deletion.
Replace the `role_mappings_configured` gate with `_should_use_role_from_sso_response()`
which validates the role is a recognized LitellmUserRoles value regardless
of origin. Also removes an unnecessary DB round-trip to litellm_ssoconfig
on every new SSO user creation.
Fixes: admin users seeing internal-user UI after SSO login
Fixes: test_get_redirect_url_for_sso flaking due to local env vars
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Save and restore litellm.initialized_langfuse_clients around
test_max_langfuse_clients_limit to prevent ordering-dependent failures
in other tests that rely on the counter's value.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- test_litellm_pre_call_utils.py: wrap test body in try/finally so
litellm.callbacks is always restored even when an assertion fails,
addressing greptile review comment
- test_langfuse_otel.py: resolve trivial merge conflict in comment
("unpatched" vs "unpatch-ed"), keeping correct spelling
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
test_reload_model_cost_map_admin_access calls the /reload/model_cost_map
HTTP endpoint with get_model_cost_map mocked to return a single-entry
dict. The endpoint handler does a direct module-level assignment
(litellm.model_cost = new_model_cost_map) which persists after the
patch context manager exits, stripping all models except gpt-3.5-turbo
from the in-memory cost map and causing subsequent tests that rely on
models like gemini-1.5-flash, multimodalembedding@001, and gpt-4o to
fail with "model not mapped" errors or zero-cost spend payloads.
Fix: save litellm.model_cost before the test and restore it (along with
invalidating the case-insensitive lookup cache) in a finally block.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: guard against None metadata in prometheus metrics
Use get_litellm_metadata_from_kwargs and get_metadata_variable_name_from_kwargs
helpers to properly resolve metadata from both 'metadata' and 'litellm_metadata'
keys, with None safety.
* test: add test for None metadata in prometheus metrics
Update provider matching so github/<model> aliases can resolve capabilities from existing upstream model metadata, including OpenAI and Anthropic entries. Add regression tests for known github aliases and unknown-model fallback behavior.
Three test isolation issues fixed:
1. test_mcp_debug.py: Replace deprecated asyncio.get_event_loop().run_until_complete()
with asyncio.run() in TestWrapSendWithDebugHeaders. In Python 3.10+,
get_event_loop() raises RuntimeError when no event loop is set in the
current thread, causing test_injects_headers and test_body_messages_unchanged
to fail in isolation.
2. test_mcp_server_manager.py: After _reload_mcp_manager_module() creates a new
global_mcp_server_manager instance, server.py still holds a stale reference
to the old instance. Tests in test_mcp_server.py that populate the new
manager's registry and then call server.py functions (e.g. _get_tools_from_mcp_servers)
get empty results because server.py reads from the old manager. Fix: update
server.py's module-level reference after each reload.
3. test_litellm_pre_call_utils.py: test_add_litellm_metadata_from_request_headers
sets litellm.callbacks without restoring it afterward. Add cleanup to restore
original callbacks after the test to prevent state leaking to subsequent tests.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Four finally blocks in test_internal_user_endpoints.py and one in
test_ui_sso.py used the pattern:
if original_default_params is not None:
litellm.default_internal_user_params = original_default_params
else:
delattr(litellm, "default_internal_user_params")
Since the attribute is defined in litellm/__init__.py with a default of
None, `getattr(litellm, "default_internal_user_params", None)` returns
None. The else branch then calls delattr(), permanently removing the
attribute from the module for the rest of the process.
Subsequent tests in the same pytest-xdist worker (e.g.
test_add_new_member_* in test_management_helpers_utils.py) then fail
with: AttributeError: module 'litellm' has no attribute
'default_internal_user_params'
Fix: replace all five flawed finally blocks with a simple assignment:
litellm.default_internal_user_params = original_default_params
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Sameer Kankute