3 posts tagged with "admin ui"

New Models / Updated Models​

1. New OpenAI /image/variations endpoint BETA support Docs
2. Topaz API support on OpenAI /image/variations BETA endpoint Docs
3. Deepseek - r1 support w/ reasoning_content (Deepseek API, Vertex AI, Bedrock)
4. Azure - Add azure o1 pricing See Here
5. Anthropic - handle -latest tag in model for cost calculation
6. Gemini-2.0-flash-thinking - add model pricing (it’s 0.0) See Here
7. Bedrock - add stability sd3 model pricing See Here (s/o Marty Sullivan)
8. Bedrock - add us.amazon.nova-lite-v1:0 to model cost map See Here
9. TogetherAI - add new together_ai llama3.3 models See Here

LLM Translation​

1. LM Studio -> fix async embedding call
2. Gpt 4o models - fix response_format translation
3. Bedrock nova - expand supported document types to include .md, .csv, etc. Start Here
4. Bedrock - docs on IAM role based access for bedrock - Start Here
5. Bedrock - cache IAM role credentials when used
6. Google AI Studio (gemini/) - support gemini 'frequency_penalty' and 'presence_penalty'
7. Azure O1 - fix model name check
8. WatsonX - ZenAPIKey support for WatsonX Docs
9. Ollama Chat - support json schema response format Start Here
10. Bedrock - return correct bedrock status code and error message if error during streaming
11. Anthropic - Supported nested json schema on anthropic calls
12. OpenAI - metadata param preview support
    1. SDK - enable via litellm.enable_preview_features = True
    2. PROXY - enable via litellm_settings::enable_preview_features: true
13. Replicate - retry completion response on status=processing

Spend Tracking Improvements​

1. Bedrock - QA asserts all bedrock regional models have same supported_ as base model
2. Bedrock - fix bedrock converse cost tracking w/ region name specified
3. Spend Logs reliability fix - when user passed in request body is int instead of string
4. Ensure ‘base_model’ cost tracking works across all endpoints
5. Fixes for Image generation cost tracking
6. Anthropic - fix anthropic end user cost tracking
7. JWT / OIDC Auth - add end user id tracking from jwt auth

Management Endpoints / UI​

1. allows team member to become admin post-add (ui + endpoints)
2. New edit/delete button for updating team membership on UI
3. If team admin - show all team keys
4. Model Hub - clarify cost of models is per 1m tokens
5. Invitation Links - fix invalid url generated
6. New - SpendLogs Table Viewer - allows proxy admin to view spend logs on UI
   1. New spend logs - allow proxy admin to ‘opt in’ to logging request/response in spend logs table - enables easier abuse detection
   2. Show country of origin in spend logs
   3. Add pagination + filtering by key name/team name
7. /key/delete - allow team admin to delete team keys
8. Internal User ‘view’ - fix spend calculation when team selected
9. Model Analytics is now on Free
10. Usage page - shows days when spend = 0, and round spend on charts to 2 sig figs
11. Public Teams - allow admins to expose teams for new users to ‘join’ on UI - Start Here
12. Guardrails
    1. set/edit guardrails on a virtual key
    2. Allow setting guardrails on a team
    3. Set guardrails on team create + edit page
13. Support temporary budget increases on /key/update - new temp_budget_increase and temp_budget_expiry fields - Start Here
14. Support writing new key alias to AWS Secret Manager - on key rotation Start Here

Helm​

1. add securityContext and pull policy values to migration job (s/o https://github.com/Hexoplon)
2. allow specifying envVars on values.yaml
3. new helm lint test

Logging / Guardrail Integrations​

1. Log the used prompt when prompt management used. Start Here
2. Support s3 logging with team alias prefixes - Start Here
3. Prometheus Start Here
   1. fix litellm_llm_api_time_to_first_token_metric not populating for bedrock models
   2. emit remaining team budget metric on regular basis (even when call isn’t made) - allows for more stable metrics on Grafana/etc.
   3. add key and team level budget metrics
   4. emit litellm_overhead_latency_metric
   5. Emit litellm_team_budget_reset_at_metric and litellm_api_key_budget_remaining_hours_metric
4. Datadog - support logging spend tags to Datadog. Start Here
5. Langfuse - fix logging request tags, read from standard logging payload
6. GCS - don’t truncate payload on logging
7. New GCS Pub/Sub logging support Start Here
8. Add AIM Guardrails support Start Here

Security​

1. New Enterprise SLA for patching security vulnerabilities. See Here
2. Hashicorp - support using vault namespace for TLS auth. Start Here
3. Azure - DefaultAzureCredential support

Health Checks​

1. Cleanup pricing-only model names from wildcard route list - prevent bad health checks
2. Allow specifying a health check model for wildcard routes - https://docs.litellm.ai/docs/proxy/health#wildcard-routes
3. New ‘health_check_timeout ‘ param with default 1min upperbound to prevent bad model from health check to hang and cause pod restarts. Start Here
4. Datadog - add data dog service health check + expose new /health/services endpoint. Start Here

Performance / Reliability improvements​

1. 3x increase in RPS - moving to orjson for reading request body
2. LLM Routing speedup - using cached get model group info
3. SDK speedup - using cached get model info helper - reduces CPU work to get model info
4. Proxy speedup - only read request body 1 time per request
5. Infinite loop detection scripts added to codebase
6. Bedrock - pure async image transformation requests
7. Cooldowns - single deployment model group if 100% calls fail in high traffic - prevents an o1 outage from impacting other calls
8. Response Headers - return
   1. x-litellm-timeout
   2. x-litellm-attempted-retries
   3. x-litellm-overhead-duration-ms
   4. x-litellm-response-duration-ms
9. ensure duplicate callbacks are not added to proxy
10. Requirements.txt - bump certifi version

General Proxy Improvements​

1. JWT / OIDC Auth - new enforce_rbac param,allows proxy admin to prevent any unmapped yet authenticated jwt tokens from calling proxy. Start Here
2. fix custom openapi schema generation for customized swagger’s
3. Request Headers - support reading x-litellm-timeout param from request headers. Enables model timeout control when using Vercel’s AI SDK + LiteLLM Proxy. Start Here
4. JWT / OIDC Auth - new role based permissions for model authentication. See Here

Complete Git Diff​

This is the diff between v1.57.8-stable and v1.59.8-stable.

Use this to see the changes in the codebase.

Git Diff

UI Improvements​

[Opt In] Admin UI - view messages / responses​

You can now view messages and response logs on Admin UI.

How to enable it - add store_prompts_in_spend_logs: true to your proxy_config.yaml

Once this flag is enabled, your messages and responses will be stored in the LiteLLM_Spend_Logs table.

general_settings:
  store_prompts_in_spend_logs: true

DB Schema Change​

Added messages and responses to the LiteLLM_Spend_Logs table.

By default this is not logged. If you want messages and responses to be logged, you need to opt in with this setting

general_settings:
  store_prompts_in_spend_logs: true

deepgram, fireworks ai, vision, admin ui, dependency upgrades

New Models​

Deepgram Speech to Text​

New Speech to Text support for Deepgram models. Start Here

from litellm import transcription
import os 

# set api keys 
os.environ["DEEPGRAM_API_KEY"] = ""
audio_file = open("/path/to/audio.mp3", "rb")

response = transcription(model="deepgram/nova-2", file=audio_file)

print(f"response: {response}")

Fireworks AI - Vision support for all models​

LiteLLM supports document inlining for Fireworks AI models. This is useful for models that are not vision models, but still need to parse documents/images/etc. LiteLLM will add #transform=inline to the url of the image_url, if the model is not a vision model See Code

Proxy Admin UI​

• Test Key Tab displays model used in response

• Test Key Tab renders content in .md, .py (any code/markdown format)

Dependency Upgrades​

• (Security fix) Upgrade to fastapi==0.115.5 https://github.com/BerriAI/litellm/pull/7447

Bug Fixes​

• Add health check support for realtime models Here
• Health check error with audio_transcription model https://github.com/BerriAI/litellm/issues/5999