Honeyhive
AI observability with traces, evaluations, datasets, experiments, and prompt versions.
Reads a trace from a failing run, compares evaluation scores between versions, and finds which prompt caused a regression.
Use Honeyhive with Snow
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What Snow can do with Honeyhive
These are the Honeyhive operations Snow and the apps you build with it can run. Sign in to choose which ones Snow may run without asking.
Reads19
Look at your data without changing it.
- Compare Experiment Runs
Tool to retrieve experiment comparison between two evaluation runs. Use when you need to analyze the differences in metrics, datapoints, and events between two runs.
- Compare Runs Events
Tool to compare events between two experiment runs side-by-side. Use when analyzing differences in model behavior, performance metrics, or outputs between evaluation runs. Returns matched event pairs with their respective data from both runs for comparison.
- Get Configurations
Tool to retrieve a list of configurations. Use when you need to fetch all configurations for a specific project before making changes.
- Get Datasets
Retrieve datasets from HoneyHive for a specified project. Use this tool when you need to: - List all datasets within a project - Find datasets by type (evaluation or fine-tuning) - Retrieve a specific dataset by its ID Returns dataset details including name, description, datapoints count, type, and timestamps.
- Get Evaluation Run Details
Tool to get details of an evaluation run by its UUID. Use when you need to check the status, configuration, results, or metadata of a specific evaluation run.
- Get Evaluation Runs
Tool to retrieve a list of evaluation runs from HoneyHive. Use when you need to: - List all evaluation runs for analysis - Find runs by status, name, or dataset - Get specific runs by their IDs - Paginate through large sets of evaluation runs Returns evaluation details including status, results, configuration, and timestamps.
- Get Events By Session ID
Tool to retrieve the complete tree of nested events for a specific session. Use when you need to analyze all events (model calls, tool calls, chains) that occurred within a session, including their hierarchical relationships, inputs, outputs, metrics, and costs. Returns a tree structure with recursive children.
- Get Metrics
Retrieves all metrics associated with a HoneyHive project. Returns a list of metrics including their configuration (name, type, description, thresholds, evaluator details) and metadata (creation/update timestamps, sampling settings). Use this tool when you need to: - List all metrics configured for a project - Get metric IDs for updating metrics via HONEYHIVE_UPDATE_METRIC - Understand what evaluations are set up for a project Prerequisites: Obtain a valid project_name using HONEYHIVE_GET_PROJECTS first.
- Get Projects
Tool to retrieve all projects in the HoneyHive account. Use when you need to list available projects, get project IDs for use in other API calls, or search for a specific project by name.
- Get Run Metrics
Tool to get event metrics for an experiment run. Use when you need to retrieve metrics computed on events within a specific experiment run. Returns an array of event objects with their associated metrics, which can be filtered by date range or custom filters.
Creates12
Add something new to your account.
- Batch Create Datapoints
Tool to create multiple datapoints in a single batch operation. Use when you need to bulk-import events into a dataset or create many datapoints at once. Supports filtering by date range, event IDs, or custom criteria. Efficient for migrating large numbers of events to evaluation datasets.
- Create Configuration
Creates a new configuration in HoneyHive for managing LLM or pipeline settings. Use this to define reusable configurations with specific models, prompts, and parameters that can be deployed across different environments (dev, staging, prod). Configurations enable version control and environment-specific management of your AI application settings.
- Create Datapoint
Tool to create a new datapoint with input-output pairs. Use when you need to add a single datapoint with inputs, ground truth, conversation history, and metadata.
- Create Dataset
Tool to create a dataset. Use when you need to initialize a new dataset within a project.
- Create Event
Tool to create a new event in HoneyHive to track execution of different parts of your application. Use when you need to log a model call, tool execution, or chain step. Events can be grouped into sessions and nested hierarchically using parent_id and children_ids.
- Create Metric
Tool to create a new metric in HoneyHive. Use when you need to define how to evaluate model outputs, whether through code (PYTHON), AI evaluation (LLM), human review (HUMAN), or combining multiple metrics (COMPOSITE). Important: LLM metrics require both model_provider and model_name to be specified.
- Create Tool
Creates a new tool definition in a HoneyHive project. Use this to register functions or plugins that can be invoked and tracked within HoneyHive. Tools are defined with a JSON Schema for their parameters, allowing HoneyHive to validate inputs and track tool usage in your AI workflows. Tool names must be unique within a project.
- Start Evaluation Run
Creates a new evaluation run to group and track multiple session events for analysis. Use this action when you want to: - Compare model performance across multiple sessions - Create evaluation batches for quality assurance - Link existing events to datasets for structured evaluation Prerequisites: - Get project ID using Get Projects action - Get event IDs from Start Session or Retrieve Events actions - (Optional) Get dataset ID from Get Datasets action
- Start Session
Start a new HoneyHive session for tracing and observability. Use this tool to initiate a tracking session that groups together related model, tool, and chain events. Returns a session_id that should be used to link subsequent events to this session. Common use cases: - Start tracing a user conversation - Begin logging an LLM pipeline execution - Initialize observability for a batch processing job
- Create Batch Model Events
Tool to create multiple model events in a single request. Use when you need to log a batch of event interactions to HoneyHive.
Updates9
Change something that is already there.
- Add datapoints to dataset
Tool to add datapoints to a dataset. Use when you need to append multiple entries with specified input, ground truth, and history mappings.
- End Evaluation Run
Tool to update an evaluation run's status and metadata. Use to mark a run as completed after finishing evaluations, or update run properties like name, metadata, configuration, and associated event/datapoint IDs.
- Update Configuration
Tool to update an existing HoneyHive configuration. Use when you need to modify a configuration's name, provider, model parameters, environments, or other settings. You must provide the configuration ID (obtainable via Get Configurations action) and the name field. All other fields are optional and will only update if provided.
- Update Datapoint
Update an existing datapoint by ID. Use this to modify any combination of inputs, ground_truth, history, metadata, linked_datasets, or linked_evals for a datapoint. Requires a valid datapoint ID obtained from retrieve_datapoints or add_datapoints_to_dataset.
- Update Dataset
Tool to update an existing dataset. Use when you need to modify a dataset's details (name, description, datapoints, linked evaluations, or metadata) after confirming its ID.
- Update Event
Update an existing HoneyHive event by ID. Use to attach feedback, metrics, metadata, outputs, config, user properties, or update duration on events created via start_session or batch event creation. At least one optional field must be provided alongside the event_id.
- Update Metric
Tool to update an existing metric. Use when you need to modify a metric’s properties after creation. Ensure you retrieve the metric first to verify its current state.
- Update Project
Updates an existing HoneyHive project's name or description. Use this action to modify project metadata after creation. You must provide the project_id and at least one field to update (name or description). To find project IDs, use the Get Projects action first.
- Update Tool
Tool to update an existing tool in HoneyHive. Use when you need to modify a tool's name, description, parameters, or type after confirming its ID. At least one optional field must be provided alongside the required tool ID.
Deletes2
Remove something. This often cannot be undone.
- Delete Datapoint
Tool to delete a specific datapoint by its ID. Use when you need to remove a datapoint from HoneyHive after confirming its identifier.
- Delete Dataset
Tool to delete a dataset by ID. Use when you need to remove a dataset after confirming its ID.
Related integrations
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