Results for “arize-phoenix”

Creates and runs LLM-as-judge evaluators on Arize, including managing tasks, column mappings, and continuous monitoring.

Creates and manages annotation configs and annotation queues on Arize, and applies human annotations to project spans via the Python SDK.

Adds Arize AX tracing to LLM applications using a two-phase agent-assisted flow that analyzes the codebase before implementing instrumentation.

Manage Arize AI integrations that store LLM provider credentials for evaluators and other features. Supports creating, reading, updating, and deleting integrations with providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, and NVIDIA NIM.

Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance using the ax CLI.

Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.

Fuzz Python code and C extensions with coverage guidance and AddressSanitizer support using a libFuzzer-based fuzzer.

Manage Arize datasets and examples using the ax CLI: create, list, get, export, and append datasets for evaluation and experimentation.

Manage Arize AI Observability and Evaluation resources on Azure using the .NET SDK. Create, read, update, and delete Arize organizations via Azure Marketplace.

Run pre-deployment validation checks for Azure readiness, including configuration, infrastructure (Bicep or Terraform), RBAC role assignments, and managed identity permissions.

Manage Azure App Configuration settings, feature flags, and snapshots using the Python SDK with Entra ID authentication.

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK, with support for function tools, hosted tools, MCP servers, conversation threads, and streaming responses.

Send, receive, and manage messages in Azure Queue Storage using Python with sync and async clients.

Centralized configuration management with feature flags, dynamic refresh, and Key Vault references using the Azure App Configuration SDK for TypeScript.

Assess and improve the reliability posture of Azure Functions and App Service applications by scanning for zone redundancy, ZRS storage, health probes, and multi-region failover, then driving staged remediation with user confirmation.

Authenticate to Azure services using the Azure Identity library for JavaScript, supporting DefaultAzureCredential, managed identity, service principals, and interactive browser login.

Build real-time voice AI applications with bidirectional WebSocket communication using the Azure AI Voice Live SDK for .NET.

Deploys Python web apps (Flask, Django, FastAPI) to Azure App Service Linux with automatic resource creation and framework detection.

Architect and provision enterprise Azure infrastructure from workload descriptions, generating Bicep or Terraform for networking, identity, security, and multi-resource topologies aligned with the Well-Architected Framework.

Perform CRUD operations, run queries, and manage containers on Azure Cosmos DB NoSQL API using the Python SDK.

Manage Azure Data Lake Storage Gen2 with Python SDK for hierarchical file systems, big data analytics, and file/directory operations.

Run Playwright tests at scale using Azure Playwright Workspaces with cloud-hosted browsers and integrated Azure portal reporting.

Send and receive messages using Azure Service Bus queues, topics, and subscriptions with Python SDK.

Manage Azure Cache for Redis instances via the Azure Resource Manager .NET SDK, including creation, firewall rules, access keys, patch schedules, geo-replication, and private endpoints.

Configure Azure API Management as an AI Gateway to govern AI models, MCP tools, and agents with policies for caching, rate limiting, content safety, and cost control.

Debug and troubleshoot Azure production issues using AppLens, Azure Monitor, resource health, and systematic diagnosis flows for services like App Service, Functions, AKS, Container Apps, and Messaging.

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing relationships between resources.

Debug LLM applications using the Phoenix CLI: fetch traces, analyze errors, structure trace review with open and axial coding, inspect datasets, review experiments, and query the GraphQL API.