// Fetch deployed prompt snapshots from Adaline at runtime. Use when integrating prompt deployments, environment-based latest lookups, prompt caching, or pinned deployment IDs.
| name | adaline-deployments |
| description | Fetch deployed prompt snapshots from Adaline at runtime. Use when integrating prompt deployments, environment-based latest lookups, prompt caching, or pinned deployment IDs. |
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:
deploymentId=latestSet these environment variables when credentials are available:
ADALINE_API_KEY — workspace API key from Admin > API KeysADALINE_PROMPT_ID — prompt to fetchADALINE_DEPLOYMENT_ENVIRONMENT_ID — environment for latest lookupBase URL: https://api.adaline.ai/v2
GET /deployments?promptId=...&deploymentId=latest&deploymentEnvironmentId=....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.
| 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 |
# 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"
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.
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.
deployment.prompt.config.settings through to the provider after adapting provider-specific casing where needed.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.
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