Fixes cross-platform Docker build issue where `prisma generate` fails
when building for amd64 platform from macOS. The Prisma CLI requires
Node.js and npm to be available in the runtime environment.
The Python prisma package (v0.11.0) uses nodeenv to bootstrap Node.js
if not found. However, the downloaded npm v10 fails with a
"sizeCalculation" error in minimal Chainguard environments during
cross-platform builds. Providing system nodejs/npm resolves this.
Changes:
- Added nodejs and npm to runtime dependencies (Dockerfile:51)
- This enables prisma generate to run successfully during the build
Error without fix:
npm error cannot set sizeCalculation without setting maxSize or maxEntrySize
subprocess.CalledProcessError: Command '[...nodeenv/bin/npm', 'install',
'prisma@5.4.2']' returned non-zero exit status 1.
Testing:
docker buildx build --platform linux/amd64 -t litellm:test .
Co-authored-by: Claude <noreply@anthropic.com>
* fix: fix getting mcp servers
* fix(litellm_logging.py): handle list objects for final response in standard logging payload
Fixes issue where mcp tool call response wouldn't show up
* fix(litellm_responses_transformation/): remove invalid item error for unmapped objects - breaks stream and there's no real value to this as outside of a few of them, not all can be mapped to chat completions
resolves error for web search calls via chat completions to responses api
* Litellm dev 11 22 2025 p1 (#16975)
* fix(model_armor.py): return response after applying changes
* fix: initial commit adding guardrail span logging to otel on post-call runs
sends it as a separate span right now, need to include in the same llm request/response span
* fix(opentelemetry.py): include guardrail in received request log + set input/ouput fields on parent otel span instead of nesting it
allows request/response to be seen easily on observability tools
* fix(model_armor.py): working model armor logging on post call events
* fix: fix exception message
* fix(opentelemetry.py): add backwards compatibility for litellm_request
allow users building on the spec change to use previous spec
* feat(teams.py): param for disabling guardrails by team
allows use-case where you don't run global guardrails for team - only run team-specific guardrails
* feat(custom_guardrail.py): add support for disabling global guardrails
only run guardrails requested for in the request/key/team
* feat: support adding disable_global_guardrails to metadata if present in key/team metadata
* feat(create_key_button.tsx): new disable global guardrails field
* feat(key_edit_view.tsx): support disabling global guardrails on key edit
* feat(teams.tsx): add disable global guardrails on create team on UI
* feat(team_info.tsx): allow disabling global guardrails on team update
* fix: prevent memory blowout in LoggingWorker
Tasks were being executed sequentially with each task awaited before
processing the next one. When the queue had 10k+ tasks, only one could
execute at a time. Since the request rate exceeded execution speed,
objects accumulated in memory (50k+), holding references to heavy
objects and causing memory blowout.
The new implementation uses a semaphore to allow up to 1000 concurrent
tasks while properly tracking and cleaning up each task, significantly
improving throughput and preventing queue buildup.
* fix: require semaphor before removing task from queue
* fix: make worker concurrency configurable
* fix: clean comments
* fix: clarify new env purpose
* fix: add missing lib
* make constants configurable instead of hardcoded
* add more aggressive cleaning when queue is full
* add helpers function for the aggressive cleaning functionality
* use envs instead of static constants
* import and document constants
* add unit test for new functionality
* fix default value on config_settings
* fix: remove unused variables and imports to resolve linter errors
- Remove unused time_since_last_clear variable in logging_worker.py
The variable was calculated but never used in _handle_queue_full()
method, causing F841 linter error.
- Remove unused TYPE_CHECKING import in mcp_server/server.py
The import was not used anywhere in the file, causing F401 linter error.
These changes improve code cleanliness and ensure the codebase passes
all linter checks without affecting functionality.
* add missing log expected by test_queue_full_handling
* fix: clean config_setting.md file
* fix: handle logging errors gracefully during shutdown in _flush_on_exit
During process shutdown, logging handlers may be closed while _flush_on_exit
tries to flush queued logging coroutines. This causes 'ValueError: I/O
operation on closed file' errors when coroutines attempt to log.
Changes:
- Add _safe_log helper method that wraps logging calls and suppresses
errors when logging handlers are closed (ValueError, OSError, AttributeError)
- Replace all verbose_logger calls in _flush_on_exit with _safe_log
- Remove logging from exception handler in coroutine execution loop
to prevent cascading errors during shutdown
This ensures graceful shutdown even when logging handlers are closed,
which is common during process termination.
* feat(anthropic/chat/transformations): for claude-4-5-sonnet and opus-4-1 support passing structured output to anthropic api
* docs: document new feature
* fix: fix output format
* fix: cleanup
* fix(transformation.py): conditionally pass in json tool call
* fix: support ARIZE_SPACE_ID instead of ARIZE_SPACE_KEY
* docs(arize_integration.md): cleanup arize docs
* feat(callback_info_helpers.tsx): allow setting arize space id via ui
* fix: fix linting error
* fix(opentelemetry.py): working arize phoenix root span tracing
Sameer Kankute