Documentation Index
Fetch the complete documentation index at: https://www.adaline.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Deployment types represent deployed prompts with their complete configuration, messages, tools, and variables.
Deployment
A specific instance of a prompt that has been deployed to an environment.
interface Deployment {
id: string;
createdAt: UnixTimestamp;
updatedAt: UnixTimestamp;
createdByUserId: string;
updatedByUserId: string;
projectId: string;
promptId: string;
deploymentEnvironmentId: string;
prompt: PromptSnapshot;
}
Properties:
id - Deployment identifier
createdAt - Creation timestamp
updatedAt - Last update timestamp
createdByUserId - Creator user ID
updatedByUserId - Last updater user ID
projectId - Associated project ID
promptId - Associated prompt ID
deploymentEnvironmentId - Target environment ID
prompt - Complete deployed prompt snapshot
Example:
import { Adaline } from '@adaline/client';
import type { Deployment } from '@adaline/api';
const adaline = new Adaline();
const deployment: Deployment = await adaline.getLatestDeployment({
promptId: 'prompt_abc123',
deploymentEnvironmentId: 'environment_abc123'
});
console.log(`ID: ${deployment.id}`);
console.log(`Model: ${deployment.prompt.config.model}`);
console.log(`Provider: ${deployment.prompt.config.providerName}`);
console.log(`Messages: ${deployment.prompt.messages.length}`);
console.log(`Tools: ${deployment.prompt.tools.length}`);
console.log(`Created: ${new Date(deployment.createdAt).toISOString()}`);
JSON:
{
"id": "deploy_abc123",
"createdAt": 1704067200000,
"updatedAt": 1704153600000,
"createdByUserId": "user_456",
"updatedByUserId": "user_456",
"projectId": "proj_789",
"promptId": "prompt_abc123",
"deploymentEnvironmentId": "production",
"prompt": {
"config": {...},
"messages": [...],
"tools": [],
"variables": []
}
}
PromptSnapshot
See the dedicated PromptSnapshot page for full documentation.
Prompt snapshot with messages, tools, config, and variables.
interface PromptSnapshot {
config: PromptSnapshotConfig;
messages: PromptMessage[];
tools: ToolFunction[];
variables: PromptVariable[];
}
Properties:
config - Model provider and settings
messages - Array of prompt messages
tools - Array of tool function definitions
variables - Array of prompt variable definitions
JSON:
{
"config": {
"providerName": "openai",
"providerId": "provider_123",
"model": "gpt-4o",
"settings": { "temperature": 0.7 }
},
"messages": [
{
"role": "system",
"content": [{ "modality": "text", "value": "You are helpful." }]
}
],
"tools": [],
"variables": []
}
PromptSnapshotConfig
See the dedicated PromptSnapshotConfig page for full documentation.
Model provider and settings configuration. All fields are optional because a deployment snapshot may have an incomplete configuration.
interface PromptSnapshotConfig {
providerName?: string;
providerId?: string;
model?: string;
settings?: any;
}
Properties:
providerName - Provider name (e.g., ‘openai’, ‘anthropic’, ‘google’)
providerId - Adaline internal provider UUID
model - Model identifier (e.g., ‘gpt-4o’, ‘claude-3-opus’)
settings - Provider-specific runtime configuration
JSON:
{
"providerName": "openai",
"providerId": "provider_abc123",
"model": "gpt-4o",
"settings": {
"temperature": 0.7,
"maxTokens": 1000
}
}
Complete Example
import { Adaline } from '@adaline/client';
import type {
Deployment,
PromptSnapshot,
PromptSnapshotConfig,
PromptVariable
} from '@adaline/api';
import { Gateway } from '@adaline/gateway';
import { OpenAI } from '@adaline/openai';
const adaline = new Adaline();
const gateway = new Gateway();
const openaiProvider = new OpenAI();
async function useDeployment() {
// Get deployment from Adaline
const deployment: Deployment = await adaline.getLatestDeployment({
promptId: 'prompt_abc123',
deploymentEnvironmentId: 'environment_abc123'
});
// Access deployed prompt configuration
const prompt: PromptSnapshot = deployment.prompt;
const config: PromptSnapshotConfig = prompt.config;
const variables: PromptVariable[] = prompt.variables;
// Log configuration
console.log('Deployed Prompt Configuration:');
console.log(` Provider: ${config.providerName}`);
console.log(` Model: ${config.model}`);
console.log(` Settings:`, config.settings);
console.log(` Messages: ${prompt.messages.length}`);
console.log(` Tools: ${prompt.tools.length}`);
console.log(` Variables: ${variables.map(v => v.name).join(', ')}`);
// Call LLM using Adaline Gateway
const model = openaiProvider.chatModel({
modelName: config.model,
apiKey: process.env.OPENAI_API_KEY!
});
const gatewayResponse = await gateway.completeChat({
model,
config: config.settings,
messages: prompt.messages,
tools: prompt.tools
});
// Log response details
console.log('Gateway Response:');
console.log(JSON.stringify(gatewayResponse.response, null, 2));
// Return the first message content
return gatewayResponse.response.messages[0].content[0].value;
}