Honeyhive
HoneyHive is a modern AI observability and evaluation platform that enables developers and domain experts to collaboratively build reliable AI applications faster.
In development
Cataloged and scoped, not yet available to run in production.
- 42
- actions
Integrations
View provider documentationActions
Operations this integration can perform.
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.
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.
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 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.
Create Batch Tool Events
Tool to log a batch of external API calls as tool events. Use when you need to record multiple tool events in one request—use after gathering all event data.
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.
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