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What is a Version?

A version in Galtea represents a specific iteration of a product. Versions allow you to track changes to your product over time and compare different implementations against the same tests. You can create, view and manage your versions on the Galtea dashboard or programmatically using the Galtea SDK.

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Comparing Versions

One of the key benefits of tracking versions in Galtea is the ability to compare different implementations of your product. This allows you to:
  • Measure improvements between versions
  • Identify regressions in newer versions
  • Compare different model providers or approaches
  • Make data-driven decisions about which version to deploy

Run Evaluations

Learn how to run evaluations for your versions

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Endpoint Connections

An Endpoint Connection tells Galtea how to call your AI system’s API — the URL, authentication, request format, and how to extract the response. Three roles are available:
  • Conversation (required): Handles each interaction turn
  • Initialization (optional): Runs before the conversation to set up a session
  • Finalization (optional): Runs after the conversation to release resources
Most products only need a Conversation endpoint.

Configure Endpoint Connections

Full reference for URLs, auth types, Jinja2 input templates, JSONPath output mapping, session state management, and retry configuration.

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SDK Integration

The Galtea SDK allows you to create, view, and manage versions programmatically. This is particularly useful for organizations that want to automate their versioning process or integrate it into their CI/CD pipeline.

Version Service SDK

Manage product versions using the Python SDK

GitHub Actions

Learn how to set up GitHub Actions to automatically create new versions and evaluate them

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Version Properties

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Version Name
Text
required
The name of the version. Example: “v1.2.0” or “GPT-4 Implementation”
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Version Description
Text
A description of the version, typically highlighting what makes it different from other versions. Example: “Improved summarization algorithm with better fact retention”
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Model
Model
required
The AI Model used by this version. Galtea uses this to track costs, calculate per-evaluation inference spend, and associate the version with the model’s pricing and tokenization characteristics.
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System Prompt
Text
The system prompt used for this version. Example: “You are an expert legal document summarizer. Provide concise summaries that capture all key legal points.”
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Dataset URI
Text
The URI of the dataset used to train or fine-tune this version. Example: “s3://company-datasets/legal-documents-v2/”
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Dataset Description
Text
A description of the dataset used in the version. Example: “Collection of 10,000 legal contracts and agreements with expert-created summaries”
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Guardrails
Text
The guardrails applied to the version, separated by commas. Example: “content filtering, citation checking, legal compliance”
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Conversation Endpoint Connection
EndpointConnection
The primary Endpoint Connection used for the main conversational interactions with your AI product. This is the only required endpoint connection.Used for:
  • Sending user messages
  • Receiving AI responses
  • (Often) creating and maintaining the external session state
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Initialization Endpoint Connection
EndpointConnection
An optional Endpoint Connection executed before the conversation begins. Used to initialize a session with your AI product.Used for:
  • Creating a session on the external API
  • Obtaining a session ID that will be used in subsequent conversation calls
  • Setting up initial context or configuration
The initialization endpoint must return a session_id in its response. Configure the outputMapping with a session_id key pointing to the session identifier in the response. This value is stored in Galtea and made available in subsequent calls via {{ session_id }}.
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Finalization Endpoint Connection
EndpointConnection
An optional Endpoint Connection executed after the conversation ends (including after errors). Used to clean up resources on your AI product.Used for:
  • Closing sessions on the external API
  • Releasing resources
  • Triggering post-conversation processing
The finalization step runs in a finally block, meaning it executes even if the conversation encounters an error. Errors in the finalization step are logged but do not fail the overall evaluation.

Session

A group of inference results that make up a full conversation.

Endpoint Connection

Configure how Galtea calls your AI system’s API.

Evaluation

Run evaluations to assess the performance of your versions.