# HoneyHive AI Docs

> AI observability and evaluation platform. Trace, evaluate, monitor, and improve AI agents and LLM applications.

## Documentation

- [Introducing HoneyHive](https://docs.honeyhive.ai/v2/introduction/what-is-hhai.md): HoneyHive is the agent observability platform for tracing, evaluating, monitoring, and improving agents from development through production.

## Getting Started

- [How to Trace Your First Agent](https://docs.honeyhive.ai/v2/introduction/tracing-quickstart.md): In about 5 minutes, instrument an OpenAI call with HoneyHive, send your first trace, and inspect the full request and response in the dashboard.
- [How to Run Your First Experiment](https://docs.honeyhive.ai/v2/introduction/experiments-quickstart.md): Run your first HoneyHive experiment in 5 minutes: define a function, score outputs with an evaluator, and compare results in the Experiments dashboard.
- [Use with Coding Agents](https://docs.honeyhive.ai/v2/introduction/ai-coding-agents.md): Equip Cursor, Claude, and other AI coding agents with HoneyHive skills, CLI access, MCP docs search, and live SDK context for faster integrations.
- [Troubleshooting & FAQs](https://docs.honeyhive.ai/v2/introduction/troubleshooting.md): Fix common HoneyHive tracing and evaluation issues: missing traces, export errors, session conflicts, SDK configuration problems, and dashboard FAQs.

## Observability

- [AI Application Tracing with HoneyHive](https://docs.honeyhive.ai/v2/tracing/introduction.md): Start tracing AI applications with HoneyHive: capture LLM calls, tool invocations, and agent steps in a hierarchical execution view using OpenTelemetry.
- [HoneyHive Tracing Concepts](https://docs.honeyhive.ai/v2/tracing/concepts.md): Learn HoneyHive's tracing data model: sessions, events, wide-event schema, and OpenTelemetry architecture for AI application observability.
- [How to Create Custom Spans in HoneyHive](https://docs.honeyhive.ai/v2/tracing/custom-spans.md): Use the @trace decorator and context managers to trace business logic, workflows, and async functions beyond automatic LLM instrumentation.
- [How to Initialize the HoneyHive Tracer](https://docs.honeyhive.ai/v2/tracing/tracer-initialization.md): Learn where to initialize HoneyHiveTracer for scripts, evaluate(), Lambda, and web servers, and how to create per-request session context.
- [How to Enrich Traces with Metadata and Metrics](https://docs.honeyhive.ai/v2/tracing/enrich-traces.md): Add metadata, metrics, feedback, config, and user context to HoneyHive traces with enrich_span() and enrich_session() for filtering and evaluation.
- [Schema Reference](https://docs.honeyhive.ai/v2/tracing/enrichment-schema.md): Reference HoneyHive enrichment namespaces, supported data types, and backend attribute names for metadata, metrics, feedback, config, and user properties.
- [User Feedback](https://docs.honeyhive.ai/v2/tracing/setting-user-feedback.md): Capture thumbs-up/down ratings, comments, and implicit signals on HoneyHive traces to connect user sentiment with LLM outputs and agent behavior.
- [Custom Metrics](https://docs.honeyhive.ai/v2/tracing/client-side-evals.md): Log evaluation scores, guardrail results, and custom numeric metrics from your application code onto HoneyHive traces for monitoring and analysis.
- [Configuration](https://docs.honeyhive.ai/v2/tracing/configuration-details.md): Log prompt templates, model parameters, git context, and deployment config on HoneyHive traces to correlate outputs with the settings that produced them.
- [User Properties](https://docs.honeyhive.ai/v2/tracing/setting-user-properties.md): Attach user IDs, account tiers, and tenant context to HoneyHive traces with user properties for per-user filtering, segmentation, and analysis.
- [Online Experiments](https://docs.honeyhive.ai/v2/tracing/online-experimentation.md): Tag HoneyHive traces with experiment IDs and variant names to analyze A/B tests, compare prompt or model changes, and measure impact in production.
- [How to Set Up Distributed Tracing](https://docs.honeyhive.ai/v2/tracing/distributed-tracing.md): Link traces across microservices and Lambda functions so LLM calls from every service appear in one HoneyHive session for end-to-end debugging.
- [How to Trace MCP Servers and Clients](https://docs.honeyhive.ai/v2/tracing/mcp-tracing.md): Instrument Model Context Protocol servers and clients with HoneyHive using OpenInference auto-tracing or @trace decorators for production MCP apps.
- [Multi-Instance Tracing](https://docs.honeyhive.ai/v2/tracing/multi-instance.md): Run multiple HoneyHiveTracer instances for multi-tenant apps, A/B tests, or per-agent routing so each instance exports to the right project and session.
- [Multi-Provider Tracing](https://docs.honeyhive.ai/v2/tracing/multi-provider.md): Trace workflows that call OpenAI, Anthropic, Bedrock, or other providers in the same HoneyHive session with multi-provider instrumentation patterns.
- [Multi-Modal Tracing](https://docs.honeyhive.ai/v2/tracing/multi-modal.md): Trace multi-modal AI pipelines in HoneyHive that process images, audio, video, and text so media handling steps appear alongside LLM spans.
- [Multi-Threading (Python)](https://docs.honeyhive.ai/v2/tracing/multithreading.md): Propagate HoneyHive trace context across Python threads so multi-threaded agent and RAG workloads keep correct parent-child span relationships intact.
- [Sampling](https://docs.honeyhive.ai/v2/tracing/sampling.md): Control trace volume in high-throughput AI apps with HoneyHive sampling strategies so you capture errors, priority users, and representative traffic.
- [Span Filtering](https://docs.honeyhive.ai/v2/tracing/filtering.md): Drop noisy framework spans from HoneyHive traces with prefix-based span filtering rules so LLM, tool, and custom events stay readable at scale.
- [Tracing via API](https://docs.honeyhive.ai/v2/tracing/manual-instrumentation.md): Log AI application events to HoneyHive via the REST API when you cannot use the Python SDK, for custom runtimes or language-specific integrations.
- [Explore in UI](https://docs.honeyhive.ai/v2/tracing/ui-flows.md): Navigate the HoneyHive Traces page to debug sessions, inspect span trees, filter events, and curate production data for datasets and experiments.
- [Tree View](https://docs.honeyhive.ai/v2/tracing/tree-view.md): Use HoneyHive Tree View to inspect parent-child span relationships, drill into LLM and tool events, and debug hierarchical AI agent execution.
- [Timeline View](https://docs.honeyhive.ai/v2/tracing/timeline-view.md): Use HoneyHive Timeline View as a Gantt chart to find latency bottlenecks, compare span durations, and pinpoint slow LLM or tool calls in a session.
- [Graph View](https://docs.honeyhive.ai/v2/tracing/graph-view.md): Explore HoneyHive Graph View to visualize agent execution as a directed graph, surface latency bottlenecks, and follow branching tool and model paths.
- [Trajectory View](https://docs.honeyhive.ai/v2/tracing/trajectory-view.md): Visualize agent behavior in HoneyHive Trajectory View as a bubble chart to spot loops, stuck steps, outliers, and costly execution paths across steps.
- [Thread View](https://docs.honeyhive.ai/v2/tracing/thread-view.md): Follow multi-turn conversations in HoneyHive Thread View as a chronological message thread across sub-agents, tools, and internal context handoffs.
- [Session Aggregations](https://docs.honeyhive.ai/v2/tracing/aggregation-logic.md): Understand reserved HoneyHive session metadata fields that the platform automatically aggregates from child spans, including cost, tokens, and duration totals.
- [Export Data](https://docs.honeyhive.ai/v2/tracing/query-data.md): Query and export HoneyHive trace data programmatically via the REST API or SDK to build custom reports, dashboards, and downstream analytics pipelines.
- [Monitor AI Application Performance in HoneyHive](https://docs.honeyhive.ai/v2/monitoring/overview.md): Track cost, latency, token usage, and evaluator scores in HoneyHive's monitoring dashboard to detect failures and quality drift in production.
- [Custom Charts](https://docs.honeyhive.ai/v2/monitoring/charts.md): Build custom HoneyHive charts with the Discover interface to query traces, plot cost and latency trends, and save views to your project dashboard.
- [Online Evaluations](https://docs.honeyhive.ai/v2/monitoring/onlineevals.md): Configure HoneyHive online evaluations to score production traces automatically with code or LLM judges and surface quality drift on your dashboard.
- [Overview](https://docs.honeyhive.ai/v2/monitoring/alerts/alerts_overview.md): Learn how HoneyHive alerts monitor LLM cost, latency, error rates, and evaluator scores, including alert types, states, and notification channels.
- [Creating Alerts](https://docs.honeyhive.ai/v2/monitoring/alerts/alerts.md): Create HoneyHive alerts on AI performance, quality, and cost metrics with step-by-step rules so your team gets notified before users see failures.

## Evaluation

- [AI Experiments and Evaluations in HoneyHive](https://docs.honeyhive.ai/v2/evaluation/introduction.md): Run offline experiments on datasets with evaluate() to compare prompts, models, and pipelines, score outputs, and catch regressions before deploy.
- [Concepts](https://docs.honeyhive.ai/v2/evaluation/concepts.md): Understand how HoneyHive experiments are structured: functions, datasets, evaluators, runs, and trace linking for reproducible AI quality measurement.
- [Comparing Experiments](https://docs.honeyhive.ai/v2/evaluation/comparing_evals.md): Compare HoneyHive experiment runs side by side to spot prompt regressions, model improvements, and metric deltas across versions before you ship changes.
- [Sync Offline Evaluations](https://docs.honeyhive.ai/v2/evaluation/sync-offline-results.md): Push evaluation results you already computed into HoneyHive experiments - no server-side evaluators or SDK required
- [Experiments via API](https://docs.honeyhive.ai/v2/evaluation/via-api.md): Run HoneyHive experiments through the REST API from TypeScript, Go, or CI pipelines when you need custom orchestration outside the Python evaluate() SDK.
- [CI Regression Detection](https://docs.honeyhive.ai/v2/evaluation/ci-regression-detection.md): Gate pull requests on HoneyHive evaluation metrics with GitHub Actions so prompt, model, or pipeline changes fail CI when quality scores drop.
- [Introduction](https://docs.honeyhive.ai/v2/evaluators/introduction.md): Overview of HoneyHive evaluators for measuring AI output quality offline and online. Learn evaluator types, when to use each, and how they fit your workflow.
- [Client-Side Evaluators](https://docs.honeyhive.ai/v2/evaluators/client_side.md): Run client-side evaluators in your application code during experiments and CI. Compute scores locally with the SDK and send results to HoneyHive with traces.
- [Python Evaluators](https://docs.honeyhive.ai/v2/evaluators/python.md): Create custom server-side Python evaluators in HoneyHive to score AI outputs with your own logic. Write deterministic checks and return structured metrics.
- [LLM Evaluators](https://docs.honeyhive.ai/v2/evaluators/llm.md): Create LLM-powered evaluators in HoneyHive using custom prompts and rubrics. Score traces and experiment outputs with model-based judges and event filters.
- [Use Portkey for LLM Evaluators](https://docs.honeyhive.ai/v2/evaluators/portkey.md): Route LLM evaluator calls through Portkey's AI gateway to access any of its 1,600+ supported models.
- [Human Evaluators](https://docs.honeyhive.ai/v2/evaluators/human.md): Create human evaluator fields in HoneyHive for manual review and annotation of AI outputs. Collect reviewer scores, notes, and labels on traces and results.
- [Version Control](https://docs.honeyhive.ai/v2/evaluators/versioning.md): Version and roll back HoneyHive evaluators as prompts and logic change. Track evaluator history, compare versions, and restore prior definitions.
- [Evaluator Template List](https://docs.honeyhive.ai/v2/evaluators/evaluator-templates.md): Browse HoneyHive server-side evaluator templates for common quality checks. Use built-in templates for toxicity, relevance, JSON validity, and more.
- [Introduction](https://docs.honeyhive.ai/v2/datasets/introduction.md): Learn how HoneyHive datasets store test cases and ground truth for experiments, CI/CD evals, and fine-tuning. Centralize curated datapoints for AI development.
- [Curate from Traces](https://docs.honeyhive.ai/v2/datasets/dataset-curation.md): Build HoneyHive datasets from production traces and sessions. Filter logged events in the UI or SDK, add ground truth, and curate regression sets.
- [Upload Datasets](https://docs.honeyhive.ai/v2/datasets/import.md): Upload datasets to HoneyHive through the web UI or Python SDK. Import JSON, JSONL, and CSV files with inputs, ground truth, and metadata for evals.
- [Run Experiments with HoneyHive Datasets](https://docs.honeyhive.ai/v2/datasets/run-experiments.md): Run experiments against HoneyHive datasets with evaluate(dataset_id=...). HoneyHive loads datapoints and aggregates run results server-side while your function and evaluators execute locally.
- [Sync from External Sources](https://docs.honeyhive.ai/v2/datasets/sync.md): Keep HoneyHive datasets synced with S3, databases, and other external sources. Automate updates so experiment and evaluation data stays current.
- [Export Datasets](https://docs.honeyhive.ai/v2/datasets/export.md): Export HoneyHive datasets programmatically with the Python SDK. Download curated datapoints as JSON for fine-tuning, external tools, or backup workflows.
- [Import from Hugging Face](https://docs.honeyhive.ai/v2/datasets/hf-datasets.md): Import datasets from Hugging Face Datasets into HoneyHive for experiments and evaluation. Load HF splits via the SDK and map columns to datapoints.
- [Annotation Queues](https://docs.honeyhive.ai/v2/evaluation/annotation-queues.md): Create HoneyHive annotation queues for human review of agent outputs, collect expert labels, and turn judgments into ground truth for evaluators.

## Prompt Management

- [Managing Prompts](https://docs.honeyhive.ai/v2/prompts/overview.md): Create, test, version, and manage prompts in the HoneyHive Playground. Iterate on templates, compare models, and deploy prompt versions to your projects.
- [Using Prompts in Code](https://docs.honeyhive.ai/v2/prompts/deploy.md): Learn to fetch deployed prompts from HoneyHive by name or version and integrate them in your application code using the Python SDK or TypeScript API SDK.

## Administration

- [Organization Hierarchy](https://docs.honeyhive.ai/v2/workspace/organization-hierarchy.md): Understand how organizations, workspaces, and projects structure your HoneyHive account and control access to traces, datasets, evaluators, and provider keys.
- [Managing Projects](https://docs.honeyhive.ai/v2/workspace/projects.md): Create and manage HoneyHive projects to organize apps, separate environments, and control access to traces, datasets, evaluators, and prompts per app.
- [Inviting Teammates](https://docs.honeyhive.ai/v2/workspace/inviting-teammates.md): Learn how to invite teammates to your HoneyHive organization, workspaces, and projects, then assign roles so they can access traces, datasets, and evaluators.
- [Role Based Access Control](https://docs.honeyhive.ai/v2/workspace/roles.md): Manage role-based access across your HoneyHive organization, workspaces, and projects. Control who can view traces, edit evaluators, and manage datasets.
- [API Keys](https://docs.honeyhive.ai/v2/workspace/api-keys.md): Compare HoneyHive's classic and fine-grained API keys, then create a fine-grained key that lets your own systems manage projects and alerts.
- [Identity Provider](https://docs.honeyhive.ai/v2/workspace/identity-provider.md): Connect your HoneyHive deployment to an OIDC identity provider in a self-hosted or managed environment.
- [Provider Keys](https://docs.honeyhive.ai/v2/workspace/provider-keys.md): Configure AI provider API keys for LLM evaluators and the Playground in HoneyHive. Store credentials securely and scope provider access by workspace.
- [Templates](https://docs.honeyhive.ai/v2/workspace/templates.md): Configure standard evaluators and monitoring charts as org-wide templates so every HoneyHive project inherits baseline evaluators, charts, and dashboards.
- [Usage](https://docs.honeyhive.ai/v2/workspace/usage.md): View event counts, enrichment metrics, and usage trends in Organization Settings, then export reports to track HoneyHive usage across workspaces and projects.
- [Multi-Tenant SaaS](https://docs.honeyhive.ai/v2/setup/managed.md): Get started on HoneyHive multi-tenant SaaS cloud. Create your account, connect projects, and start sending traces to HoneyHive's shared cloud in AWS US-West-2.
- [Dedicated Cloud](https://docs.honeyhive.ai/v2/setup/dedicated.md): Get started on HoneyHive Dedicated Cloud with an isolated Data Plane in your AWS region. Meet data residency, compliance, and private networking requirements.
- [Self-Hosting Overview](https://docs.honeyhive.ai/v2/setup/self-hosted.md): Deploy HoneyHive in your AWS environment. Plan architecture, install Helm charts, and configure a fully self-hosted HoneyHive platform.
- [Security Architecture](https://docs.honeyhive.ai/v2/setup/self-hosted/security.md): Review security controls, encryption, authentication, and compliance requirements for HoneyHive self-hosted deployments in regulated or air-gapped environments.
- [Data Flow & Residency](https://docs.honeyhive.ai/v2/setup/self-hosted/data-flow.md): Understand data classification, flow boundaries, and residency controls in HoneyHive self-hosted deployments. See where trace and evaluation data is stored.
- [Operations Guide](https://docs.honeyhive.ai/v2/setup/self-hosted/operations.md): Use this guide after installing self-hosted HoneyHive to handle upgrades, monitoring, backups, scaling, incident response, and keep clusters reliable.
- [Application Metrics](https://docs.honeyhive.ai/v2/setup/self-hosted/metrics.md): Use this reference to scrape per-service Prometheus metrics for signup, ingestion, trace storage, evaluation jobs, and the LLM proxy in self-hosted HoneyHive.
- [Infrastructure Requirements](https://docs.honeyhive.ai/v2/setup/infrastructure-requirements.md): Review supported dependency versions, required Kubernetes operators, and infrastructure prerequisites before you deploy HoneyHive in a self-hosted environment.
- [HoneyHive Platform Architecture](https://docs.honeyhive.ai/v2/platform-architecture.md): Understand how HoneyHive separates the Control Plane and Data Plane so traces, evaluations, and datasets stay isolated while you scale hosting models.
- [Security](https://docs.honeyhive.ai/v2/setup/security.md): Learn how HoneyHive protects your data, infrastructure, and AI applications with encryption, access controls, network security, and compliance practices.

## Learn More

- [HoneyHive Platform Concepts](https://docs.honeyhive.ai/v2/concepts.md): Learn core HoneyHive concepts: projects, sessions, events, datasets, experiments, evaluators, and prompts. See how they connect observability and evaluation.
- [End-to-End: Multi-Agent Tracing and Evaluation](https://docs.honeyhive.ai/v2/tutorials/multi-agent-cookbook.md): Build a multi-agent customer support bot with Google ADK, add HoneyHive tracing, and run evaluations end to end. Follow a cookbook from agents to quality.
- [Add Tracing to Existing Apps](https://docs.honeyhive.ai/v2/tutorials/add-tracing-5min.md): Add HoneyHive tracing to an existing LLM app in about five minutes. Install the SDK, initialize HoneyHiveTracer, instrument your provider, and see traces.
- [Enrich Your Traces](https://docs.honeyhive.ai/v2/tutorials/enriching-traces.md): Enrich HoneyHive traces with user IDs, session metadata, and custom attributes. Make production spans easier to filter, debug, and evaluate with context.
- [Deploy Tracing to Production](https://docs.honeyhive.ai/v2/tutorials/production-deployment.md): Deploy HoneyHive tracing to production with environment config, sampling, and reliability patterns. Set API keys, batching, and settings for LLM workloads.
- [Trace Distributed Systems](https://docs.honeyhive.ai/v2/tutorials/distributed-tracing.md): Trace requests across services with HoneyHive context propagation. Connect parent and child spans over HTTP, queues, or RPC for multi-service LLM workflows.

## SDK Reference

- [SDK Overview](https://docs.honeyhive.ai/v2/sdk-reference/overview.md): Compare HoneyHive Python and TypeScript SDKs to pick the right client for tracing, evaluation workflows, and REST API access in your stack.

## Python SDK

- [Python SDK](https://docs.honeyhive.ai/v2/sdk-reference/python-sdk-ref.md): Explore the HoneyHive Python SDK reference for OpenTelemetry tracing, decorators, evaluations, and configuration options in your LLM application code.
- [Environment Variables](https://docs.honeyhive.ai/v2/sdk-reference/environment-variables.md): Configure the HoneyHive Python SDK with environment variables for API keys, endpoints, tracer behavior, and sampling without hardcoding secrets in code.
- [Python SDK Changelog](https://docs.honeyhive.ai/v2/sdk-reference/python-sdk-changelog.md): Track HoneyHive Python SDK releases, breaking changes, new features, and bug fixes so you can plan upgrades for your tracing and evaluation code.
- [Migrate to SDK v1](https://docs.honeyhive.ai/v2/sdk-reference/python/migration/v0-to-v1.md): Upgrade HoneyHive Python SDK projects from v0.x to v1 with code rewrites for tracing, evaluations, and v2-ready instrumentation patterns.
- [Migrate from Logger to v1](https://docs.honeyhive.ai/v2/sdk-reference/python/migration/logger-to-v1.md): Replace honeyhive-logger start, log, and update calls with HoneyHive Python SDK v1 tracer APIs so legacy instrumentation keeps sending traces.
- [Migrate from honeyhive-bundled to v1](https://docs.honeyhive.ai/v2/sdk-reference/python/migration/honeyhive-bundled-to-v1.md): Switch from the honeyhive-bundled package to the main HoneyHive Python SDK v1 install with updated imports, config, and tracing setup steps.

## TypeScript API SDK

- [TypeScript API SDK](https://docs.honeyhive.ai/v2/sdk-reference/typescript.md): Install and use the type-safe HoneyHive TypeScript API client to manage datasets, experiments, traces, and metrics with full editor autocompletion.
- [Migrate from @honeyhive/logger](https://docs.honeyhive.ai/v2/sdk-reference/typescript-logger-to-api-sdk-migration.md): Migrate from @honeyhive/logger to @honeyhive/api-client with step-by-step rewrites for sessions, events, and configuration in TypeScript projects.
- [Environment Variables](https://docs.honeyhive.ai/v2/sdk-reference/typescript/environment-variables.md): Configure the HoneyHive TypeScript API client with environment variables for API keys, data plane URLs, and request timeouts in Node or browser apps.
- [Namespaces](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/namespaces.md): The SDK client is organized into namespaces. Explore the namespaces below to learn more about each method.
- [Client](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/Client.md): HoneyHive TypeScript Data Plane SDK client class reference
- [FetchOptions](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/FetchOptions.md): Per-request options for HoneyHive TypeScript SDK methods
- [Charts Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/index.md): HoneyHive TypeScript Data Plane SDK Charts namespace reference
- [CreateChartRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/CreateChartRequest.md): TypeScript request type for the HoneyHive API
- [CreateChartResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/CreateChartResponse.md): TypeScript response type from the HoneyHive API
- [DeleteChartRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/DeleteChartRequest.md): TypeScript request type for the HoneyHive API
- [DeleteChartResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/DeleteChartResponse.md): TypeScript response type from the HoneyHive API
- [GetChartRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/GetChartRequest.md): TypeScript request type for the HoneyHive API
- [GetChartResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/GetChartResponse.md): TypeScript response type from the HoneyHive API
- [GetChartsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/GetChartsResponse.md): TypeScript response type from the HoneyHive API
- [UpdateChartRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/UpdateChartRequest.md): TypeScript request type for the HoneyHive API
- [UpdateChartResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/charts/UpdateChartResponse.md): TypeScript response type from the HoneyHive API
- [Datapoints Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/index.md): HoneyHive TypeScript Data Plane SDK Datapoints namespace reference
- [BatchCreateDatapointsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/BatchCreateDatapointsRequest.md): TypeScript request type for the HoneyHive API
- [BatchCreateDatapointsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/BatchCreateDatapointsResponse.md): TypeScript response type from the HoneyHive API
- [CreateDatapointRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/CreateDatapointRequest.md): TypeScript request type for the HoneyHive API
- [CreateDatapointResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/CreateDatapointResponse.md): TypeScript response type from the HoneyHive API
- [DeleteDatapointRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/DeleteDatapointRequest.md): TypeScript request type for the HoneyHive API
- [DeleteDatapointResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/DeleteDatapointResponse.md): TypeScript response type from the HoneyHive API
- [GetDatapointRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/GetDatapointRequest.md): TypeScript request type for the HoneyHive API
- [GetDatapointResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/GetDatapointResponse.md): TypeScript response type from the HoneyHive API
- [GetDatapointsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/GetDatapointsRequest.md): TypeScript request type for the HoneyHive API
- [GetDatapointsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/GetDatapointsResponse.md): TypeScript response type from the HoneyHive API
- [UpdateDatapointRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/UpdateDatapointRequest.md): TypeScript request type for the HoneyHive API
- [UpdateDatapointResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datapoints/UpdateDatapointResponse.md): TypeScript response type from the HoneyHive API
- [Datasets Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/index.md): HoneyHive TypeScript Data Plane SDK Datasets namespace reference
- [AddDatapointsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/AddDatapointsRequest.md): TypeScript request type for the HoneyHive API
- [AddDatapointsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/AddDatapointsResponse.md): TypeScript response type from the HoneyHive API
- [CreateDatasetRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/CreateDatasetRequest.md): TypeScript request type for the HoneyHive API
- [CreateDatasetResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/CreateDatasetResponse.md): TypeScript response type from the HoneyHive API
- [DeleteDatasetRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/DeleteDatasetRequest.md): TypeScript request type for the HoneyHive API
- [DeleteDatasetResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/DeleteDatasetResponse.md): TypeScript response type from the HoneyHive API
- [GetDatasetsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/GetDatasetsRequest.md): TypeScript request type for the HoneyHive API
- [GetDatasetsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/GetDatasetsResponse.md): TypeScript response type from the HoneyHive API
- [RemoveDatapointRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/RemoveDatapointRequest.md): TypeScript request type for the HoneyHive API
- [RemoveDatapointResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/RemoveDatapointResponse.md): TypeScript response type from the HoneyHive API
- [UpdateDatasetRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/UpdateDatasetRequest.md): TypeScript request type for the HoneyHive API
- [UpdateDatasetResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/datasets/UpdateDatasetResponse.md): TypeScript response type from the HoneyHive API
- [Events Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/index.md): HoneyHive TypeScript Data Plane SDK Events namespace reference
- [CreateEventBatchRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/CreateEventBatchRequest.md): TypeScript request type for the HoneyHive API
- [CreateEventBatchResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/CreateEventBatchResponse.md): TypeScript response type from the HoneyHive API
- [CreateEventRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/CreateEventRequest.md): TypeScript request type for the HoneyHive API
- [CreateEventResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/CreateEventResponse.md): TypeScript response type from the HoneyHive API
- [GetEventRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/GetEventRequest.md): TypeScript request type for the HoneyHive API
- [GetEventResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/GetEventResponse.md): TypeScript response type from the HoneyHive API
- [SearchEventsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/SearchEventsRequest.md): TypeScript request type for the HoneyHive API
- [SearchEventsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/SearchEventsResponse.md): TypeScript response type from the HoneyHive API
- [UpdateEventRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/events/UpdateEventRequest.md): TypeScript request type for the HoneyHive API
- [Experiments Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/index.md): HoneyHive TypeScript Data Plane SDK Experiments namespace reference
- [CreateRunRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/CreateRunRequest.md): TypeScript request type for the HoneyHive API
- [CreateRunResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/CreateRunResponse.md): TypeScript response type from the HoneyHive API
- [DeleteRunRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/DeleteRunRequest.md): TypeScript request type for the HoneyHive API
- [DeleteRunResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/DeleteRunResponse.md): TypeScript response type from the HoneyHive API
- [GetExperimentCompareEventsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentCompareEventsRequest.md): TypeScript request type for the HoneyHive API
- [GetExperimentCompareEventsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentCompareEventsResponse.md): TypeScript response type from the HoneyHive API
- [GetExperimentComparisonRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentComparisonRequest.md): TypeScript request type for the HoneyHive API
- [GetExperimentComparisonResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentComparisonResponse.md): TypeScript response type from the HoneyHive API
- [GetExperimentRunMetricsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentRunMetricsRequest.md): TypeScript request type for the HoneyHive API
- [GetExperimentRunMetricsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentRunMetricsResponse.md): TypeScript response type from the HoneyHive API
- [GetExperimentSummaryRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentSummaryRequest.md): TypeScript request type for the HoneyHive API
- [GetExperimentSummaryResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetExperimentSummaryResponse.md): TypeScript response type from the HoneyHive API
- [GetRunRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunRequest.md): TypeScript request type for the HoneyHive API
- [GetRunResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunResponse.md): TypeScript response type from the HoneyHive API
- [GetRunSchemaRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunSchemaRequest.md): TypeScript request type for the HoneyHive API
- [GetRunSchemaResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunSchemaResponse.md): TypeScript response type from the HoneyHive API
- [GetRunsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunsRequest.md): TypeScript request type for the HoneyHive API
- [GetRunsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunsResponse.md): TypeScript response type from the HoneyHive API
- [GetRunsSchemaRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunsSchemaRequest.md): TypeScript request type for the HoneyHive API
- [GetRunsSchemaResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/GetRunsSchemaResponse.md): TypeScript response type from the HoneyHive API
- [UpdateRunRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/UpdateRunRequest.md): TypeScript request type for the HoneyHive API
- [UpdateRunResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/experiments/UpdateRunResponse.md): TypeScript response type from the HoneyHive API
- [Metric Versions Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/index.md): HoneyHive TypeScript Data Plane SDK Metric Versions namespace reference
- [CreateMetricVersionRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/CreateMetricVersionRequest.md): TypeScript request type for the HoneyHive API
- [CreateMetricVersionResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/CreateMetricVersionResponse.md): TypeScript response type from the HoneyHive API
- [DeployMetricVersionRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/DeployMetricVersionRequest.md): TypeScript request type for the HoneyHive API
- [DeployMetricVersionResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/DeployMetricVersionResponse.md): TypeScript response type from the HoneyHive API
- [GetMetricVersionsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/GetMetricVersionsRequest.md): TypeScript request type for the HoneyHive API
- [GetMetricVersionsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metric-versions/GetMetricVersionsResponse.md): TypeScript response type from the HoneyHive API
- [Metrics Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/index.md): HoneyHive TypeScript Data Plane SDK Metrics namespace reference
- [CreateMetricRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/CreateMetricRequest.md): TypeScript request type for the HoneyHive API
- [CreateMetricResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/CreateMetricResponse.md): TypeScript response type from the HoneyHive API
- [DeleteMetricRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/DeleteMetricRequest.md): TypeScript request type for the HoneyHive API
- [DeleteMetricResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/DeleteMetricResponse.md): TypeScript response type from the HoneyHive API
- [GetMetricsRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/GetMetricsRequest.md): TypeScript request type for the HoneyHive API
- [GetMetricsResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/GetMetricsResponse.md): TypeScript response type from the HoneyHive API
- [RunMetricRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/RunMetricRequest.md): TypeScript request type for the HoneyHive API
- [RunMetricResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/RunMetricResponse.md): TypeScript response type from the HoneyHive API
- [UpdateMetricRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/UpdateMetricRequest.md): TypeScript request type for the HoneyHive API
- [UpdateMetricResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/metrics/UpdateMetricResponse.md): TypeScript response type from the HoneyHive API
- [Sessions Methods](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/sessions/index.md): HoneyHive TypeScript Data Plane SDK Sessions namespace reference
- [CreateSessionEventBatchRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/sessions/CreateSessionEventBatchRequest.md): TypeScript request type for the HoneyHive API
- [CreateSessionEventBatchResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/sessions/CreateSessionEventBatchResponse.md): TypeScript response type from the HoneyHive API
- [CreateSessionRequest](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/sessions/CreateSessionRequest.md): TypeScript request type for the HoneyHive API
- [CreateSessionResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/sessions/CreateSessionResponse.md): TypeScript response type from the HoneyHive API
- [ApiError](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/ApiError.md): Error class thrown by the HoneyHive TypeScript SDK
- [ErrorResponse](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/ErrorResponse.md): TypeScript response type from the HoneyHive API
- [HoneyHiveError](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/HoneyHiveError.md): Error class thrown by the HoneyHive TypeScript SDK
- [NetworkError](https://docs.honeyhive.ai/v2/sdk-reference/typescript/ref/classes/NetworkError.md): Error class thrown by the HoneyHive TypeScript SDK

## TypeScript Control Plane SDK

- [TypeScript Control Plane SDK](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript.md): Install and use the type-safe HoneyHive TypeScript Control Plane client to provision projects and manage alerts programmatically with full editor autocompletion.
- [Environment Variables](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/environment-variables.md): Configure the HoneyHive TypeScript Control Plane client with environment variables for fine-grained API keys, control plane URLs, and verbose logging.
- [Namespaces](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/namespaces.md): The SDK client is organized into namespaces. Explore the namespaces below to learn more about each method.
- [Client](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/Client.md): HoneyHive TypeScript Control Plane SDK client class reference
- [FetchOptions](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/FetchOptions.md): Per-request options for HoneyHive TypeScript SDK methods
- [Alerts Methods](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/index.md): HoneyHive TypeScript Control Plane SDK Alerts namespace reference
- [CreateAlertRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/CreateAlertRequest.md): TypeScript request type for the HoneyHive API
- [CreateAlertResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/CreateAlertResponse.md): TypeScript response type from the HoneyHive API
- [GetAlertRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/GetAlertRequest.md): TypeScript request type for the HoneyHive API
- [GetAlertResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/GetAlertResponse.md): TypeScript response type from the HoneyHive API
- [ListAlertsRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/ListAlertsRequest.md): TypeScript request type for the HoneyHive API
- [ListAlertsResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/alerts/ListAlertsResponse.md): TypeScript response type from the HoneyHive API
- [Projects Methods](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/index.md): HoneyHive TypeScript Control Plane SDK Projects namespace reference
- [CreateProjectRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/CreateProjectRequest.md): TypeScript request type for the HoneyHive API
- [CreateProjectResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/CreateProjectResponse.md): TypeScript response type from the HoneyHive API
- [DeleteProjectRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/DeleteProjectRequest.md): TypeScript request type for the HoneyHive API
- [DeleteProjectResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/DeleteProjectResponse.md): TypeScript response type from the HoneyHive API
- [GetProjectRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/GetProjectRequest.md): TypeScript request type for the HoneyHive API
- [GetProjectResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/GetProjectResponse.md): TypeScript response type from the HoneyHive API
- [UpdateProjectRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/UpdateProjectRequest.md): TypeScript request type for the HoneyHive API
- [UpdateProjectResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/projects/UpdateProjectResponse.md): TypeScript response type from the HoneyHive API
- [Virtual Dataplanes Methods](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/index.md): HoneyHive TypeScript Control Plane SDK Virtual Dataplanes namespace reference
- [CreateVirtualDataplaneRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/CreateVirtualDataplaneRequest.md): TypeScript request type for the HoneyHive API
- [CreateVirtualDataplaneResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/CreateVirtualDataplaneResponse.md): TypeScript response type from the HoneyHive API
- [DeleteVirtualDataplaneRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/DeleteVirtualDataplaneRequest.md): TypeScript request type for the HoneyHive API
- [DeleteVirtualDataplaneResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/DeleteVirtualDataplaneResponse.md): TypeScript response type from the HoneyHive API
- [GetVirtualDataplaneRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/GetVirtualDataplaneRequest.md): TypeScript request type for the HoneyHive API
- [GetVirtualDataplaneResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/GetVirtualDataplaneResponse.md): TypeScript response type from the HoneyHive API
- [UpdateVirtualDataplaneRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/UpdateVirtualDataplaneRequest.md): TypeScript request type for the HoneyHive API
- [UpdateVirtualDataplaneResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/virtual-dataplanes/UpdateVirtualDataplaneResponse.md): TypeScript response type from the HoneyHive API
- [Workspaces Methods](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/index.md): HoneyHive TypeScript Control Plane SDK Workspaces namespace reference
- [CreateWorkspaceRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/CreateWorkspaceRequest.md): TypeScript request type for the HoneyHive API
- [CreateWorkspaceResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/CreateWorkspaceResponse.md): TypeScript response type from the HoneyHive API
- [DeleteWorkspaceRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/DeleteWorkspaceRequest.md): TypeScript request type for the HoneyHive API
- [DeleteWorkspaceResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/DeleteWorkspaceResponse.md): TypeScript response type from the HoneyHive API
- [GetWorkspaceRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/GetWorkspaceRequest.md): TypeScript request type for the HoneyHive API
- [GetWorkspaceResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/GetWorkspaceResponse.md): TypeScript response type from the HoneyHive API
- [UpdateWorkspaceRequest](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/UpdateWorkspaceRequest.md): TypeScript request type for the HoneyHive API
- [UpdateWorkspaceResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/workspaces/UpdateWorkspaceResponse.md): TypeScript response type from the HoneyHive API
- [ApiError](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/ApiError.md): Error class thrown by the HoneyHive TypeScript SDK
- [ErrorResponse](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/ErrorResponse.md): TypeScript response type from the HoneyHive API
- [HoneyHiveError](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/HoneyHiveError.md): Error class thrown by the HoneyHive TypeScript SDK
- [NetworkError](https://docs.honeyhive.ai/v2/control-plane-sdk-reference/typescript/ref/classes/NetworkError.md): Error class thrown by the HoneyHive TypeScript SDK

## Semantic Conventions

- [Semantic Convention Reference](https://docs.honeyhive.ai/v2/sdk-reference/semconv-reference.md): Look up canonical HoneyHive trace attribute names, platform behaviors, and UI sideview mappings to structure spans and events for observability.
- [Framework Attribute Mapping](https://docs.honeyhive.ai/v2/sdk-reference/semconv-alignment.md): Map OpenTelemetry GenAI, OpenInference, and Traceloop attributes to HoneyHive canonical keys so framework instrumentations normalize in your traces.

## OpenAPI Client

- [OpenAPI Client (Any Language)](https://docs.honeyhive.ai/v2/sdk-reference/openapi-sdks.md): Generate HoneyHive REST API clients in any language from the public OpenAPI specs for serverless, polyglot, or regulated environments without vendor SDKs.

## CLI Reference

- [Getting Started](https://docs.honeyhive.ai/v2/cli-reference/getting-started.md): Install and authenticate the HoneyHive CLI, then run your first commands to manage projects, traces, datasets, evaluators, and more from the terminal.
- [Config as Code](https://docs.honeyhive.ai/v2/cli-reference/config-as-code.md): Learn to define HoneyHive evaluators, datasets, and platform resources as version-controlled files, then apply and sync them to your workspace with the CLI.
- [Environment Variables](https://docs.honeyhive.ai/v2/cli-reference/environment-variables.md): Configure the HoneyHive CLI with environment variables. Reference supported variables for authentication, project scope, API endpoints, and runtime behavior.
- [Namespaces](https://docs.honeyhive.ai/v2/cli-reference/namespaces.md): Commands in the CLI are organized into namespaces. Explore the namespaces below to learn more about each command.

## Reference

- [Alerts](https://docs.honeyhive.ai/v2/cli-reference/ref/alerts.md): Define and manage alerts. Alerts evaluate event metrics on a schedule and trigger notifications when configured thresholds are crossed.
- [Charts](https://docs.honeyhive.ai/v2/cli-reference/ref/charts.md): Define and manage saved charts. Charts are visualizations that aggregate metrics over time with bucketing, filters, and groupings.
- [Datapoints](https://docs.honeyhive.ai/v2/cli-reference/ref/datapoints.md): Manage individual records inside datasets, including batch creation and mapping to source events.
- [Datasets](https://docs.honeyhive.ai/v2/cli-reference/ref/datasets.md): Curate collections of datapoints used as test sets for evaluations and experiments.
- [Events](https://docs.honeyhive.ai/v2/cli-reference/ref/events.md): Read and write trace events. Events are the spans that capture every step of an AI application's execution.
- [Experiments](https://docs.honeyhive.ai/v2/cli-reference/ref/experiments.md): Run, retrieve, and compare evaluation runs to measure how prompt or configuration changes affect agent performance.
- [Metric Versions](https://docs.honeyhive.ai/v2/cli-reference/ref/metric-versions.md): Snapshot, list, and deploy versions of a metric's definition so changes can be reviewed and rolled back without losing history.
- [Metrics](https://docs.honeyhive.ai/v2/cli-reference/ref/metrics.md): Define and run evaluators, i.e. automated quality checks that score traces against criteria like accuracy, safety, or correctness.
- [Projects](https://docs.honeyhive.ai/v2/cli-reference/ref/projects.md): Create and manage projects within a workspace. A project is the container for the events, datasets, evaluations, and alerts logged against it.
- [Sessions](https://docs.honeyhive.ai/v2/cli-reference/ref/sessions.md): Group related trace events into sessions, the top-level container for a multi-step or multi-service AI interaction.
- [Virtual Dataplanes](https://docs.honeyhive.ai/v2/cli-reference/ref/virtual-dataplanes.md): Create and manage virtual data planes. A virtual data plane is a logical tenant boundary inside an organization, hosted on a physical cluster; several virtual data planes commonly share one cluster. Workspaces live inside a virtual data plane.
- [Workspaces](https://docs.honeyhive.ai/v2/cli-reference/ref/workspaces.md): Read and manage workspaces. A workspace groups the projects belonging to one team or environment, and owns the API keys and AI provider secrets its projects share.

## API Reference

- [Data Plane API (OpenAPI spec)](https://raw.githubusercontent.com/honeyhiveai/honeyhive-openapi/main/data_plane_openapi.yaml): Machine-readable OpenAPI spec for the HoneyHive Data Plane API.
- [Control Plane API (OpenAPI spec)](https://raw.githubusercontent.com/honeyhiveai/honeyhive-openapi/main/control_plane_openapi.yaml): Machine-readable OpenAPI spec for the HoneyHive Control Plane API.

## Integrations

- [Overview](https://docs.honeyhive.ai/v2/integrations/overview.md): Connect HoneyHive to the agent frameworks, model providers, and tools in your AI stack

## Agent Frameworks & Platforms

- [How to trace AWS Strands Agents with HoneyHive](https://docs.honeyhive.ai/v2/integrations/strands.md): Trace AWS Strands Agents workflows, tool calls, and model requests with HoneyHive. Instrument Strands apps to capture multi-step agent execution in dashboard.
- [How to trace Claude Agent SDK with HoneyHive](https://docs.honeyhive.ai/v2/integrations/claude-agent-sdk.md): Trace Claude Agent SDK sessions, tool use, and model calls with HoneyHive. Instrument agent runs to capture multi-turn workflows and execution details.
- [How to trace CrewAI with HoneyHive](https://docs.honeyhive.ai/v2/integrations/crewai.md): Trace CrewAI crews, tasks, and agent collaboration with HoneyHive. Instrument crew workflows to capture role assignments, tool use, and model calls.
- [How to trace Cursor SDK with HoneyHive](https://docs.honeyhive.ai/v2/integrations/cursor-sdk.md): Trace Cursor SDK agent runs, tool calls, and model requests with HoneyHive. Instrument Cursor SDK sessions to capture agent execution and debugging context.
- [How to integrate HoneyHive with Databricks Agent Bricks](https://docs.honeyhive.ai/v2/integrations/databricks-agent-bricks.md): HoneyHive integration for Databricks Agent Bricks and MLflow Tracing. Export agent spans over OTLP with MLflow's native attributes or GenAI semantic conventions.
- [How to trace DSPy with HoneyHive](https://docs.honeyhive.ai/v2/integrations/dspy.md): Trace DSPy programs, modules, and LM calls with HoneyHive. Instrument DSPy pipelines to capture prompts, completions, and optimization runs in the dashboard.
- [How to integrate HoneyHive with Google ADK](https://docs.honeyhive.ai/v2/integrations/google-adk.md): Integrate HoneyHive with Google ADK to trace agent runs, tool calls, and model requests. Add four lines of setup with the OpenInference Google ADK instrumentor.
- [How to trace LangChain with HoneyHive](https://docs.honeyhive.ai/v2/integrations/langchain.md): Trace LangChain agents, chains, tools, and LLM calls with HoneyHive. Add four lines of setup and use OpenInference to instrument your existing LangChain app.
- [How to trace LangGraph with HoneyHive](https://docs.honeyhive.ai/v2/integrations/langgraph.md): Trace LangGraph state graphs, node transitions, and LLM calls with HoneyHive. Add four lines of setup with the LangChain OpenInference instrumentor.
- [How to trace LlamaIndex with HoneyHive](https://docs.honeyhive.ai/v2/integrations/llamaindex.md): Trace LlamaIndex query engines, retrieval, embeddings, and agents with HoneyHive. Add four lines of setup and use OpenInference to capture RAG workflows.
- [How to trace Microsoft AutoGen with HoneyHive](https://docs.honeyhive.ai/v2/integrations/autogen.md): Trace Microsoft AutoGen conversations, tool calls, and model requests with HoneyHive. Instrument multi-agent chats to capture delegation, tools, and LLM usage.
- [Microsoft Copilot Studio](https://docs.honeyhive.ai/v2/integrations/copilot-studio.md): Forward Microsoft Copilot Studio agent telemetry to HoneyHive with an Azure Function trace forwarder
- [How to trace Semantic Kernel with HoneyHive](https://docs.honeyhive.ai/v2/integrations/semantic-kernel.md): Trace Microsoft Semantic Kernel plugins, planners, and LLM calls with HoneyHive. Instrument your Semantic Kernel app to capture orchestration and model usage.
- [n8n](https://docs.honeyhive.ai/v2/integrations/n8n.md): Export n8n AI Agent workflow observability to HoneyHive with the execution-history shipper
- [How to trace OpenAI Agents SDK with HoneyHive](https://docs.honeyhive.ai/v2/integrations/openai-agents.md): Trace OpenAI Agents SDK runs, handoffs, and tool calls with HoneyHive. Instrument agent workflows to capture multi-step reasoning and model interactions.
- [How to trace Pydantic AI with HoneyHive](https://docs.honeyhive.ai/v2/integrations/pydantic-ai.md): Trace PydanticAI agents, tools, and LLM calls with HoneyHive. Add three lines of setup with HoneyHiveTracer.init() and Agent.instrument_all() for native OTel.
- [How to integrate HoneyHive with Salesforce Agentforce](https://docs.honeyhive.ai/v2/integrations/salesforce-agentforce.md): HoneyHive integration for Salesforce Agentforce. Poll Session Trace OTel API spans and forward OTLP traces for LLM calls, tools, and agent sessions.

## Model Providers

- [How to trace Anthropic with HoneyHive](https://docs.honeyhive.ai/v2/integrations/anthropic.md): Trace Anthropic Claude messages, tool use, and streaming with HoneyHive. Add four lines of setup and use OpenInference to capture every API call automatically.
- [How to trace AWS Bedrock with HoneyHive](https://docs.honeyhive.ai/v2/integrations/aws_bedrock.md): Trace AWS Bedrock model invocations, Converse API calls, and streaming with HoneyHive. Add four lines of setup and use OpenInference for Bedrock automatically.
- [How to trace Azure OpenAI with HoneyHive](https://docs.honeyhive.ai/v2/integrations/azure_openai.md): Trace Azure OpenAI chat completions, embeddings, and deployments with HoneyHive. Add four lines of setup and use OpenInference for Azure-hosted models.
- [How to trace Gemini with HoneyHive](https://docs.honeyhive.ai/v2/integrations/gemini.md): Trace Google Gemini chat, embeddings, and multimodal requests with HoneyHive. Add four lines of setup and use OpenInference to capture Gemini API calls.
- [How to trace OpenAI with HoneyHive](https://docs.honeyhive.ai/v2/integrations/openai.md): Trace OpenAI chat completions, tool calls, and embeddings with HoneyHive. Add four lines of setup and use OpenInference to capture every API call automatically.

## AI Gateways

- [How to trace Cloudflare AI Gateway with HoneyHive](https://docs.honeyhive.ai/v2/integrations/cloudflare-ai-gateway.md): HoneyHive integration for Cloudflare AI Gateway. Trace any HoneyHive-instrumented provider SDK through the gateway with the matching instrumentor.
- [How to trace LiteLLM with HoneyHive](https://docs.honeyhive.ai/v2/integrations/litellm.md): Trace LiteLLM proxy requests across providers with HoneyHive. Instrument LiteLLM to capture unified spans for chat completions, embeddings, and routed calls.
- [How to integrate HoneyHive with Portkey](https://docs.honeyhive.ai/v2/integrations/portkey.md): Integrate HoneyHive with Portkey AI Gateway to trace routed LLM requests. Capture gateway spans, provider calls, and metadata from Portkey-enabled apps.
- [How to integrate HoneyHive with TrueFoundry](https://docs.honeyhive.ai/v2/integrations/truefoundry.md): Integrate HoneyHive with TrueFoundry AI Gateway to export OTLP/HTTP traces. Route gateway spans to HoneyHive for unified observability across model providers.

## Coding Agents

- [How to integrate HoneyHive with Claude Code](https://docs.honeyhive.ai/v2/integrations/claude-code.md): Integrate HoneyHive with Claude Code to export session traces for observability and evaluation. Send Claude Code runs to HoneyHive to debug agent quality.
- [How to integrate HoneyHive with Devin](https://docs.honeyhive.ai/v2/integrations/devin.md): Integrate HoneyHive with Devin to export session traces for observability and evaluation. Send Devin runs to HoneyHive to review agent work and outcomes.

## Evaluation

- [ASSERT](https://docs.honeyhive.ai/v2/integrations/assert.md): Run ASSERT behavior evaluations against HoneyHive-traced agents

## Changelog

- [Product](https://docs.honeyhive.ai/v2/changelog/product.md): See what is new in the HoneyHive platform and UI. Browse product updates, feature launches, and major improvements that affect how you build and monitor AI.
- [Clients](https://docs.honeyhive.ai/v2/changelog/clients.md): Browse release notes for the HoneyHive Python SDK, TypeScript API SDK, TypeScript Control Plane SDK, and CLI. Stay current with new features, bug fixes, and breaking API changes.
- [Self-Hosting](https://docs.honeyhive.ai/v2/changelog/self-hosting.md): Review Helm chart updates and release notes for self-hosted HoneyHive. Find upgrade guidance, configuration changes, and migration steps for your deployment.