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Delete Projects and Models from Tables

• Action column in tables - access delete functionality without navigating to individual project pages
• Type-to-confirm deletion - must enter the exact project or model name to prevent accidental deletions
• Streamlined workflow - manage your workspace organization more efficiently

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Create and Manage Prompts via API

• Create prompts - POST /v2/prompts to save prompts with model parameters, tools, and response formats
• List prompts - GET /v2/prompts with filtering by space, cursor-based pagination, and sort by last updated
• Get prompt details - GET /v2/prompts/{prompt_id} to retrieve specific prompt configurations
• Delete prompts - DELETE /v2/prompts/{prompt_id} to remove prompts programmatically
• Version control - systematically manage prompt variations across environments and track changes over time

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Query Spans with Powerful Filters

• Complex filtering - query spans by status code, time range, and custom attributes
• Pagination support - efficiently retrieve large result sets with cursor-based navigation
• Project-scoped access - filter spans within specific projects with proper RBAC enforcement
• Programmatic debugging - quickly identify errors, performance bottlenecks, and behavioral patterns without manual searching

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Escaped Curly Braces in Eval Templates

• Backslash escape syntax - use \{...\} to include curly braces as literal text
• JSON examples support - safely include code snippets like \{"component":"chat-response"\} in prompts
• Cross-stack compatibility - works consistently across frontend, backend TypeScript, Python, and Go services
• Template flexibility - combine template variables {variable} with escaped literals \{literal\} in the same prompt

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Trace Links in Playground Experiments

• Clickable trace links - view complete execution details for each playground run
• Available in multiple views - access traces from dataset pages, experiment comparison views, and the playground
• Bridge experimentation and observability - understand both output quality and execution behavior (latency, costs, tool calls) for every experimental run

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Internal Playground Tracing

• Automatic capture - playground experiments generate traces without manual instrumentation
• Full observability - view latency, token counts, and execution details for every playground run
• Debugging capabilities - troubleshoot issues by examining complete execution paths
• Performance metrics - track and optimize playground interactions with detailed span data

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Enhanced Experiment Metadata

• Run and evaluator tracking - runId and evaluatorId link traces to specific experiment executions
• Parent task relationships - parentTaskId and parentTaskRunId connect chained evaluations
• Row identifiers - spanId for tracing data and exampleId for dataset evaluations
• Prompt templates - capture template strings and variables for reproducibility

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Select All Spans Moved to Floating Panel

• Floating action panel - “Select All Spans” button relocated to the floating panel for easier access
• Cleaner table view - removed dedicated row for select-all, reducing visual clutter
• Streamlined selection - manage span selections more efficiently with grouped controls

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Annotation Queue Progress Tracking

• Total assigned records - see how many records are assigned to annotators in each data cluster
• Progress calculation - track completion rates based on assigned vs. completed annotations
• Workload balancing - monitor task distribution across annotation teams to ensure balanced allocation

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ax-client SDK Published

• Datasets API - create, list, update, and delete datasets programmatically
• Experiments API - manage experiment runs and retrieve results
• Examples API - append and update examples in datasets
• Type-safe imports - full TypeScript support with generated types
• Environment variable configuration - simple setup with API keys

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Clickable Span Table Rows

• Full row clickable - entire table row is now interactive for easier navigation
• Faster debugging - quickly jump to span details without precise clicking on specific cells
• Improved UX - more intuitive interaction pattern consistent with modern data tables

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Dataset Examples Sorting

• Sort by creation date - see newest or oldest examples first
• Sort by update date - identify recently modified examples
• Sort by ID - consistent ordering for reproducible views
• Druid integration - sorting optimized at the database level for performance

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Pivot Table Dashboard Widgets

• Group by dimensions - organize data by categorical fields
• Configurable metrics - select numeric columns with aggregation functions (sum, average, count)
• Ad-hoc analysis - explore data patterns without predefined reports
• Dashboard integration - save pivot configurations as reusable dashboard widgets

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Authentication Type for LLM Integrations

• Auth type column - stores authentication method for each LLM integration
• Multiple auth strategies - prepares platform for API keys, OAuth, and service accounts
• Provider flexibility - manage credentials differently for various LLM providers

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Phoenix Import Dedicated Tab

• Dedicated import tab - separate “Import From Phoenix” tab in project creation
• Traces-only focus - streamlined UI showing only trace connection form
• Cleaner onboarding - removed Phoenix card from LLM tracing setup to reduce confusion
• Feature flag control - controlled rollout with enablePhoenixMigration flag

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Claude Opus 4.6 on Vertex AI

• Vertex AI integration - Claude Opus 4.6 now available in playground and online tasks
• 1M token context window - handle extensive documents and conversations
• Enhanced reasoning - state-of-the-art performance on coding and complex workflows
• Enterprise deployment - leverage Google Cloud infrastructure for Claude models

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External HTTPS Access to Clusters

• Port 443 ingress - external HTTPS traffic now allowed to cluster endpoints
• Secure external access - properly configured TLS/SSL for organization-wide availability
• Integration support - enables webhooks, API callbacks, and external monitoring tools

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Deployment Activity Heatmap

• 52-week view - see deployment activity for the past year at a glance
• Color-coded frequency - darker cells indicate more deployments on that day
• Interactive tooltips - hover to see date, deployment count, and services deployed
• Summary statistics - total deployments and max-per-day metrics
• Filter compatibility - heatmap updates based on service filters

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AI Features Timeline Improvements

• Recent activity focus - main tab shows only features from the last 7 days
• Full history tab - new “History” tab provides access to all past features
• View full history link - easily navigate between recent and historical views
• Direct URL support - ?tab=history parameter for bookmarking and sharing

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Improved Feature Generation Reliability

• Exponential backoff - automatic retries for rate limits and transient errors
• Branch diff context - includes current changes in prompts for better iteration
• Operation tracking - operationUuid field tracks async generation jobs
• Collapsible logs UI - view generation logs with auto-scroll and syntax highlighting

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GKE Infrastructure Upgrades

• GKE 1.33.5 - updated cluster and node pool versions
• Spot node pools - 60-91% cost savings for fault-tolerant workloads
• Extended IAM permissions - SecuritySMTP role updated with required access tokens
• DevOps logging access - roles/logging.viewer granted for improved debugging

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Enhanced Usage Monitoring

• Datasource-level breakdowns for granular usage visibility
• Account-based tracking with improved join keys for accurate reporting
• 10-minute update intervals for near real-time usage insights
• Automated cleanup of expired data for accurate retention calculations

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Enhanced Platform Stability

• Configuration drift resolution in GCP Terraform
• Enhanced error handling across services
• Improved logging and monitoring for faster troubleshooting
• Database migration optimizations for schema updates
• Better resource management for high-volume workloads

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Improved Onboarding Experience

• Redesigned onboarding cards with clearer visual hierarchy
• “My First Playground” experience for hands-on experimentation
• Role collection during signup for personalized setup
• Custom hover states matching each card’s accent color

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Real-Time Evaluations

• Instant evaluation of production traces without delays
• Latent evaluation support for updating earlier spans
• Seamless cutover between batch and real-time processing
• Available across all Arize AX tiers by default

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AWS Bedrock Custom Endpoints

• Custom base URL support for private endpoints
• Inference profile ARNs for multi-region routing
• Custom model configurations for specialized deployments
• Simplified regional management with unified tracking

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Wildcard Array Path Variables

• Wildcard (*) patterns to reference all array elements
• Last-index (-1) access for the most recent item
• Automatic generation of wildcard variants for convenience
• Support in task variables and experiment columns

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Improved Queue Management

• Duplicate detection with clear error messages
• Added and skipped record counts after bulk operations
• Actionable feedback when attempting to add existing records

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Enhanced RBAC System

• Custom roles with specific permissions
• Space-level role bindings for granular access management
• Coexistence with legacy roles during migration
• UI support for role assignment across all user management pages
• Automatic fallback to legacy roles when custom roles are deleted

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Custom Metrics with LIKE Operator

• LIKE and ILIKE operators for pattern matching
• Wildcard support with % syntax
• Case-insensitive matching with ILIKE
• Direct Druid mapping for performance

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Dashboard Template Filtering

• LLM-only space filtering shows only relevant templates
• Context-aware templates based on project types
• Reduced clutter in template selection
• Consistent experience across spaces and projects

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Pivot Table Widget Schema

• Grouped categorical dimensions for organized views
• Configurable numeric columns with aggregations
• Flexible filtering and time range support
• Dashboard integration ready

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Evaluator Hub: Reusable Evaluators

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Why Reusable Evaluators?

• Consistency: The same evaluator definition is used across tasks, eliminating drift in evaluation criteria
• Reliability: LLM configuration (model, provider, parameters) is set at the evaluator level, ensuring the evaluator is tested and validated with a specific model before being deployed to production tasks
• Version Control: Track changes to evaluators over time with commit messages, making it easy to audit and roll back if needed
• Flexibility: Column mappings let you reuse the same evaluator across datasets with different schemas by mapping template variables to your data columns

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What’s New

• Evaluator Hub tab: Browse, search, and manage all your evaluators in one place
• Running Tasks tab: View and manage your active evaluation tasks
• “Use Evaluator” action: Quickly create a task with any evaluator pre-selected
• Column Mappings: Map evaluator template variables to your datasource columns when adding an evaluator to a task
• Evaluator Versioning: Create new versions of evaluators with commit messages to track changes

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Getting Started

1. Navigate to Evaluators in the left sidebar
2. Click New Evaluator to create your first reusable evaluator
3. Choose from pre-built templates or create a custom evaluation from scratch
4. Use your evaluator in tasks by clicking Use Evaluator or selecting it when creating a new task

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Session Evaluations with Conversation Context

• {conversation} template variable for session-level evaluations
• Chronologically ordered input/output pairs
• Automatic aggregation of multi-turn dialogues
• Root span filtering for accurate session context

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Tracing Configuration for Evaluation Tasks

• Toggle tracing on/off in Advanced Options
• Automatic trace generation for monitoring and debugging
• Persistent settings saved with your tasks
• Production-ready visibility into evaluation execution

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Improved Error Handling for Exceptions

• Filter by exception.type and exception.message in the UI
• OpenInference semantic convention support for exceptions
• Consistent data structure across datasources
• Faster troubleshooting of error patterns

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SAML Role Mapping Search

• Client-side search across attributes, spaces, roles, and organizations
• Visual highlighting of search matches
• Keyboard navigation through results
• Improved usability for enterprise customers

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Enhanced Dashboard Time Persistence

• Auto-save time range, time zone, and granularity selections
• Instant restoration when returning to dashboards
• Per-dashboard settings for customized views
• Seamless experience across sessions

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Resizable Trace Slideover

• Draggable slideover width for optimal layout
• Persistent sizing preferences across sessions
• Better content visibility for long traces

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Trace Table Performance Improvements

• 30-50% faster initial load times
• String truncation for large content
• Lazy loading of full values in tooltips
• Minimal impact on user experience

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Scatter Plot Widgets

• Correlation analysis for two numeric dimensions
• Interactive data points for detailed investigation
• Dashboard integration for visual analytics
• Customizable axes and filtering

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Enhanced Session Slideover

• Trace labels with links to detailed views
• Visual separators between traces
• Hover highlighting synchronized between list and conversation
• Improved readability for multi-turn interactions

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Experiment Task Timeout Configuration

• Configurable timeout parameter beyond 120 seconds
• Function-level control in run_experiment and evaluate_experiment
• Backward compatibility with default values
• Support for complex evaluators requiring extended processing

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Configurable Experiment Timeout

• Custom timeout values for long-running tasks
• Per-experiment configuration for flexibility
• Backward compatible defaults for existing code

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Expandable Trace Hierarchy

• Expand traces to see child spans inline
• Hierarchical visualization without opening slideouts
• Faster navigation through complex traces
• Contextual understanding of request flow

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Custom Prompt Release Labels

• Tag prompt versions with meaningful identifiers
• Environment markers like “staging” or “production”
• Dynamic label suggestions from existing prompts
• Easy retrieval of specific prompt releases

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Eval Hub Enhancements

• Model information in evaluator listings with provider icons
• Evaluator counts in running tasks with hover details
• Automatic save when creating or editing evaluators
• Streamlined task flow for faster evaluation setup

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Todo List Management Improvements

• Visual status indicators for all todo states
• Dynamic reminders with exact update calls needed
• Plan preservation across human-in-the-loop pauses
• Clearer instructions positioned near the plan

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Span-to-Queue Workflow

• Multiple entry points from spans table, trace slideover, and queue records
• New or existing queue selection
• Batch operations for efficient queue population
• Dataclusters integration for reliable processing

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Atlantis Terraform Automation

• Pull request integration for Terraform plans
• Automated plan posting as PR comments
• DevOps team permissions for webhook debugging
• Structured review process before applying changes

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Java SDK Space ID Support

• Space ID authentication (space keys deprecated)
• Backward compatibility maintained with existing constructors
• Updated documentation and examples
• Test coverage for new authentication method

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Enhanced Space Model Schema

• Space-level schema lookback overrides for custom retention
• Model-specific configurations for unique requirements
• Flexible data management across different use cases

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Exact Match Code Evaluator

• String equality checks for exact matches
• Expected vs actual comparisons for testing
• Multi-field access with dataset row support
• Alphabetically sorted evaluator list in UI

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Enhanced Annotation Configs

• Color-coded categories based on optimization direction
• Read-only view for reviewing existing configs
• Optimization direction control (maximize, minimize, or none)
• Clear label guidance for consistent evaluations

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Batch Annotation Updates

• Optimization direction support in annotation configs
• Category-based labeling for issue detection
• Best practice guidance for naming and structure
• Streamlined categorization workflows

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Stacked Bar Chart Widgets

• Stacked bar charts for comparing categories over time
• Druid-powered queries for fast rendering
• Customizable groupings and dimensions
• Dashboard integration for comprehensive monitoring

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Enhanced Eval Hub Empty States

• Improved empty state design with clear next steps
• Documentation links for learning resources
• Actionable cards for common workflows

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Google Analytics 4 BigQuery Sync

• Daily GA4 to BigQuery transfers via Terraform
• Raw event data access for advanced analysis
• Overcome GA4 limitations like sampling and retention
• Custom reporting capabilities with full data access

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Vertex AI Migration

• Seamless Vertex AI connectivity for LLM applications
• Enhanced observability for Google Cloud deployments
• Modernized instrumentation for better tracing

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Generative Service Monitoring

• Uptime and health alerts with paging
• CPU and memory monitoring with warnings
• Dedicated Grafana dashboard for visibility
• Runbook documentation for incident response

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Custom Model Migrations

• Custom model endpoint support in evaluations
• Higher traffic model optimization for performance
• Flexible integration options for enterprise deployments

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Prompt Optimization on Experiments

• Experiment selector in optimization task creation
• Dynamic column resolution for experiment data
• Enhanced iteration on proven prompts
• Seamless workflow from experiments to optimization

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Labeling Queue Annotations

• Clear annotations (reset to null) anywhere
• Support across spans, queues, and experiments for consistent workflows
• Improved annotation lifecycle management

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Multi-Span Filters

• AND, OR, NOT operators for combining conditions
• Indirectly Calls (->) and Directly Calls (=>) relationship filters
• Up to 5 filters to find complex patterns like “spans where A calls B, but not C” or “traces containing both X and Y”
• Parentheses to build complex queries and pinpoint the traces that matter

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Support for Opus & Haiku 4.5

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Support for GPT-5.2 and GPT-5.2 Pro

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Improved Playground Views

• LLM Config (provider, model selection, model params, custom endpoint settings)
• Prompt Setup (messages, roles, message content, tool and function calls)
• Generated Results (when setup with datasets)
• Connected Datasource (dataset or span)

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Realtime Ingestion for all new Arize AX Spaces

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Structured Outputs Support for Playground

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Session Annotations

• Input/Output Level: Attach insights to specific output messages, automatically linked to the root span of the trace.
• Span Level: Dive deeper into a trace and annotate individual spans for precise, context-rich feedback.

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Integrations Revamp

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OpenInference TypeScript 2.0

• Added easy manual instrumentation with the same decorators, wrappers, and attribute helpers found in the Python openinference-instrumentation package.
• Introduced function tracing utilities that automatically create spans for sync/async function execution, including specialized wrappers for chains, agents, and tools.
• Added decorator-based method tracing, enabling automatic span creation on class methods via the @observe decorator.
• Expanded attribute helper utilities for standardized OpenTelemetry metadata creation, including helpers for inputs/outputs, LLM operations, embeddings, retrievers, and tool definitions.
• Overall, tracing workflows, agent behavior, and external tool calls is now significantly simpler and more consistent across languages.

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API-Driven Monitors

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Automatic Threshold Ranges for Monitors

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Data Fabric

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New Timeline Tab for Traces

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Tags

• Describe source (from-prod, EHR-record)
• Encode purpose (ab-test, regression-test)
• Indicate readiness (golden, deprecated)
• Group by config (threshold-0.85, cohort_5)

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Sort Datasets and Experiment Listing Table

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Support for Tool Call IDs in OpenInference Messages

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Add Data Region to Login Page

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Add Auth Failures to Tracing

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Total Traces on Stats Bar

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Support for GPT OSS Models on Bedrock

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Expanded LLM Support

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Dashboard Widget Time Setting

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Autocomplete for Annotations on Datasets

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Dataset Management Upgrades