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Documentation Index

Fetch the complete documentation index at: https://docs.galtea.ai/llms.txt

Use this file to discover all available pages before exploring further.

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What is an Endpoint Connection?

An Endpoint Connection tells Galtea how to call your AI system’s API. You configure the URL, authentication, request format, and response mapping once, and Galtea uses it to run evaluations against your endpoint automatically.

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Use Cases

  • Automate evaluations — Galtea calls your endpoint directly for each test case, no manual inference needed
  • Standardize API calls — Define reusable configurations with consistent auth and request formatting
  • Manage multiple environments — Create separate connections for development, staging, and production

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Creating an Endpoint Connection

To create an Endpoint Connection:
  1. Navigate to your product in the Galtea Dashboard
  2. Go to the “Endpoint Connections” section
  3. Click “New Endpoint Connection”
  4. Configure the connection properties as described below

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Quick Start: Single Conversation Endpoint

Most integrations only need one Conversation endpoint. At its simplest, you just need to configure:
  • Input Template — How to format the request body (using {{ input.user_message }} for the simulated user message)
  • Output Mapping — How to extract your product’s AI response (using a JSONPath expression for the output key)
{
  "message": "{{ input.user_message }}"
}
This is all you need to start running evaluations against your endpoint. For advanced template syntax, conversation history loops, state management, and output mapping options, see Templates & Mapping.

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Multi-Step Session Lifecycle (Advanced)

Some AI products expose separate endpoints for session setup and cleanup. In those cases, you can configure up to three endpoint connections:
  • Initialization (optional): runs before conversation
  • Conversation (required): runs for each turn
  • Finalization (optional): runs after conversation

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Session Lifecycle Flow

When a version has initialization and/or finalization endpoints configured, the evaluation follows this lifecycle:

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Example Use Case: Multi-Step Chatbot

Some chatbot APIs require multiple steps:
  • Initialization: create a session and return a session_id
  • Conversation: send messages using that session_id
  • Finalization: clean up the session
In this setup:
  • Your Initialization connection extracts session_id via outputMapping.
  • Your Conversation connection can reuse it in the URL/body using {{ session_id }}.
  • Any additional fields extracted via outputMapping are stored in session metadata and can also be reused in later turns.

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Endpoint Connection Properties

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Name
Text
required
A unique name for the endpoint connection within the product. Example: “Production Chat API” or “Staging Summarizer”
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Type
Enum
required
The purpose of the endpoint connection:
  • INITIALIZATION - Runs before the conversation
  • CONVERSATION - Runs for each turn
  • FINALIZATION - Runs after the conversation
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URL
Text
required
The full URL of the endpoint. Must be a valid HTTP or HTTPS URL. Example: “https://api.company.com/v1/chat”
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HTTP Method
Enum
required
The HTTP method: GET, POST, PUT, PATCH, or DELETE.
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Auth Type
Enum
required
Authentication method: NONE, BEARER, API_KEY, or BASIC.
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Auth Token
Text
The authentication token or credentials. This value is securely stored.
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Headers
JSON
Optional custom headers to include with each request.
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Input Schema
JSON Schema
Optional JSON Schema defining the structure of test case inputs (field types, constraints, enums). When set, Galtea generates structured multi-field test data matching this schema. See Input Schema for details and examples.
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Input Template
String (Jinja2)
required
A Jinja2 template defining the request body. See Templates & Mapping for the full placeholder reference and examples.
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Output Mapping
JSON
required
A JSON object defining how to extract values from the response using JSONPath. See Templates & Mapping for special keys and examples.
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Timeout
Number
Request timeout in seconds (1–300). Default: 30 seconds.
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Rate Limit
Number
Optional rate limit for requests per minute.

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Best Practices

Choose names that clearly identify the endpoint’s purpose and environment, such as “Production Chat API” or “Staging Document Analyzer”.
Set timeouts based on your endpoint’s expected response time. For complex AI operations, you may need longer timeouts (60-120 seconds).
Configure retries for endpoints that may experience transient failures. Start with 2-3 retries with exponential backoff. See Retry Configuration.
Never share your auth tokens. Galtea securely stores and encrypts all authentication credentials.

Concepts overview

How Galtea’s concepts connect — diagram + per-entity quick reference.

Input Schema

Define structured, multi-field inputs for test case generation.

Templates & Mapping

Full reference for Input Templates, Output Mapping, state management, and retry configuration.

Structured Input Template Syntax

Deep dive into {{ input.field_name }} and {{ context.field_name }} placeholder syntax, JSON escaping, and missing field behavior.

Endpoint Connection Service SDK

Manage endpoint connections programmatically using the Python SDK.

Version

Attach endpoint connections to a version for evaluation.

Direct Inferences Tutorial

Run evaluations from the dashboard using your endpoint connection.