// Fetch deployed prompt snapshots from Adaline at runtime. Use when integrating prompt deployments, environment-based latest lookups, prompt caching, or pinned deployment IDs.
Create and manage evaluation datasets in Adaline. Use when building test cases, adding dataset columns/rows, importing data, or triggering dynamic columns.
Run and manage evaluations in Adaline to test prompt quality at scale. Use when creating evaluation runs, polling status, analyzing results, or cancelling runs.
Create and manage evaluators in Adaline to score prompt outputs. Use when setting up LLM-as-a-judge, JavaScript, text-matcher, cost, latency, or response-length evaluators.
High-level guide for integrating your AI application with Adaline. Use when starting a new Adaline integration, choosing between API/SDK approaches, or planning which Adaline features to adopt.
Send traces and spans to Adaline for AI agent observability. Use when instrumenting LLM calls, tools, retrieval, embeddings, guardrails, or custom operations.
Create and manage prompts in Adaline via the v2 API or SDK clients. Use when programmatically creating prompts, updating prompt drafts, listing prompts, or reading prompt/playground data.
| 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.