adaline-deployments

Adaline Deployments

Concepts

Adaline deployments are immutable prompt snapshots that your application fetches at runtime. The public v2 API currently exposes deployment read operations: create and promote deployments in the Adaline Platform UI, then fetch the approved snapshot from code.

Key terms:

• Deployment — a prompt snapshot deployed to an environment
• Deployment environment — an isolation boundary such as development, staging, or production
• Latest deployment — the current snapshot for a prompt/environment pair, fetched with deploymentId=latest
• Pinned deployment — a concrete deployment ID fetched directly for reproducibility

Configuration

Set these environment variables when credentials are available:

• ADALINE_API_KEY — workspace API key from Admin > API Keys
• ADALINE_PROMPT_ID — prompt to fetch
• ADALINE_DEPLOYMENT_ENVIRONMENT_ID — environment for latest lookup

Base URL: https://api.adaline.ai/v2

How It Works

1. Build and test a prompt in the Prompt area of Adaline.
2. Deploy the prompt snapshot to an environment in the Platform UI.
3. Fetch the current snapshot with GET /deployments?promptId=...&deploymentId=latest&deploymentEnvironmentId=....
4. Cache the returned Deployment in your app and refresh it on a timer, restart, or product-specific webhook signal.

Each deployment includes prompt.config, prompt.messages, prompt.tools, and prompt.variables. Config values use providerName, providerId, model, and flexible settings.

Quick Triage

Symptom	First Fix
Fetch returns 404	Verify promptId, deploymentId, and deploymentEnvironmentId
Latest lookup fails	Include deploymentEnvironmentId when deploymentId=latest or current
Wrong model settings	Read deployment.prompt.config.settings; temperature/max token fields are not top-level
Variables not substituted	Replace {{name}} placeholders in text message content before calling the provider
Python example returns coroutine	Await SDK methods inside an asyncio event loop

Approach 1: REST API

# Latest deployment for an environment
curl "https://api.adaline.ai/v2/deployments?promptId=$ADALINE_PROMPT_ID&deploymentId=latest&deploymentEnvironmentId=$ADALINE_DEPLOYMENT_ENVIRONMENT_ID" \
  -H "Authorization: Bearer $ADALINE_API_KEY"

# Specific deployment by ID
curl "https://api.adaline.ai/v2/deployments?promptId=$ADALINE_PROMPT_ID&deploymentId=deploy_abc123" \
  -H "Authorization: Bearer $ADALINE_API_KEY"

Approach 2: TypeScript SDK

import { Adaline } from '@adaline/client';

const adaline = new Adaline(); // reads ADALINE_API_KEY

const deployment = await adaline.getLatestDeployment({
  promptId: process.env.ADALINE_PROMPT_ID!,
  deploymentEnvironmentId: process.env.ADALINE_DEPLOYMENT_ENVIRONMENT_ID!,
});

const pinned = await adaline.getDeployment({
  promptId: process.env.ADALINE_PROMPT_ID!,
  deploymentId: 'deploy_abc123',
});

Install: npm install @adaline/client @adaline/api

See references/typescript-sdk.md for a complete inference example.

Approach 3: Python SDK

import asyncio
from adaline import Adaline

async def main():
    adaline = Adaline()  # reads ADALINE_API_KEY

    deployment = await adaline.get_latest_deployment(
        prompt_id="prompt_abc123",
        deployment_environment_id="environment_abc123",
    )

    pinned = await adaline.get_deployment(
        prompt_id="prompt_abc123",
        deployment_id="deploy_abc123",
    )

asyncio.run(main())

Install: pip install adaline-client adaline-api

See references/python-sdk.md for a complete inference example.

Best Practices

1. Use latest lookup for normal runtime traffic and pinned deployment IDs for reproducible tests.
2. Cache deployments in memory; do not fetch on every user request.
3. Store IDs in environment variables or configuration, not source code.
4. Substitute variables only in text content. Preserve image, PDF, tool-call, tool-response, and reasoning content as structured objects.
5. Pass deployment.prompt.config.settings through to the provider after adapting provider-specific casing where needed.

References

See references/api.md for the REST contract. See references/typescript-sdk.md for TypeScript SDK usage. See references/python-sdk.md for Python SDK usage.