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7 Commits

Author SHA1 Message Date
Vikhyath Mondreti
1a90c04e1c fix 2026-01-25 23:07:45 -08:00
Vikhyath Mondreti
5b3cc2ba0d update type guard: 2026-01-25 23:03:55 -08:00
Vikhyath Mondreti
7ba07bc428 fix output condition logic 2026-01-25 22:56:13 -08:00
Vikhyath Mondreti
0c69f8b061 fix trigger input format version 2026-01-25 22:44:09 -08:00
Vikhyath Mondreti
57e6203625 fix(multi-trigger): resolution paths for triggers 2026-01-25 22:32:51 -08:00
Vikhyath Mondreti
d83c418111 fix(supabase): storage upload + add basic mode version (#2996)
* fix(supabase): storage upload + add basic mode version

* fix subblock update

* remove redundant check in a2a

* add check consistently for baseline diff
2026-01-25 14:19:30 -08:00
Waleed
be2a9ef0f8 fix(storage): support Azure connection string for presigned URLs (#2997)
* fix(docs): update requirements to be more accurate for deploying the app

* updated kb to support 1536 dimension vectors for models other than text embedding 3 small

* fix(storage): support Azure connection string for presigned URLs

* fix(kb): update test for embedding dimensions parameter

* fix(storage): align credential source ordering for consistency
2026-01-25 13:06:12 -08:00
20 changed files with 276 additions and 124 deletions

View File

@@ -44,7 +44,7 @@ services:
deploy:
resources:
limits:
memory: 4G
memory: 1G
environment:
- NODE_ENV=development
- DATABASE_URL=postgresql://postgres:postgres@db:5432/simstudio

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@@ -10,12 +10,20 @@ Stellen Sie Sim auf Ihrer eigenen Infrastruktur mit Docker oder Kubernetes berei
## Anforderungen
| Ressource | Minimum | Empfohlen |
|----------|---------|-------------|
| CPU | 2 Kerne | 4+ Kerne |
| RAM | 12 GB | 16+ GB |
| Speicher | 20 GB SSD | 50+ GB SSD |
| Docker | 20.10+ | Neueste Version |
| Ressource | Klein | Standard | Produktion |
|----------|-------|----------|------------|
| CPU | 2 Kerne | 4 Kerne | 8+ Kerne |
| RAM | 12 GB | 16 GB | 32+ GB |
| Speicher | 20 GB SSD | 50 GB SSD | 100+ GB SSD |
| Docker | 20.10+ | 20.10+ | Neueste Version |
**Klein**: Entwicklung, Tests, Einzelnutzer (1-5 Nutzer)
**Standard**: Teams (5-50 Nutzer), moderate Arbeitslasten
**Produktion**: Große Teams (50+ Nutzer), Hochverfügbarkeit, intensive Workflow-Ausführung
<Callout type="info">
Die Ressourcenanforderungen werden durch Workflow-Ausführung (isolated-vm Sandboxing), Dateiverarbeitung (In-Memory-Dokumentenparsing) und Vektoroperationen (pgvector) bestimmt. Arbeitsspeicher ist typischerweise der limitierende Faktor, nicht CPU. Produktionsdaten zeigen, dass die Hauptanwendung durchschnittlich 4-8 GB und bei hoher Last bis zu 12 GB benötigt.
</Callout>
## Schnellstart

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@@ -16,12 +16,20 @@ Deploy Sim on your own infrastructure with Docker or Kubernetes.
## Requirements
| Resource | Minimum | Recommended |
|----------|---------|-------------|
| CPU | 2 cores | 4+ cores |
| RAM | 12 GB | 16+ GB |
| Storage | 20 GB SSD | 50+ GB SSD |
| Docker | 20.10+ | Latest |
| Resource | Small | Standard | Production |
|----------|-------|----------|------------|
| CPU | 2 cores | 4 cores | 8+ cores |
| RAM | 12 GB | 16 GB | 32+ GB |
| Storage | 20 GB SSD | 50 GB SSD | 100+ GB SSD |
| Docker | 20.10+ | 20.10+ | Latest |
**Small**: Development, testing, single user (1-5 users)
**Standard**: Teams (5-50 users), moderate workloads
**Production**: Large teams (50+ users), high availability, heavy workflow execution
<Callout type="info">
Resource requirements are driven by workflow execution (isolated-vm sandboxing), file processing (in-memory document parsing), and vector operations (pgvector). Memory is typically the constraining factor rather than CPU. Production telemetry shows the main app uses 4-8 GB average with peaks up to 12 GB under heavy load.
</Callout>
## Quick Start

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@@ -10,12 +10,20 @@ Despliega Sim en tu propia infraestructura con Docker o Kubernetes.
## Requisitos
| Recurso | Mínimo | Recomendado |
|----------|---------|-------------|
| CPU | 2 núcleos | 4+ núcleos |
| RAM | 12 GB | 16+ GB |
| Almacenamiento | 20 GB SSD | 50+ GB SSD |
| Docker | 20.10+ | Última versión |
| Recurso | Pequeño | Estándar | Producción |
|----------|---------|----------|------------|
| CPU | 2 núcleos | 4 núcleos | 8+ núcleos |
| RAM | 12 GB | 16 GB | 32+ GB |
| Almacenamiento | 20 GB SSD | 50 GB SSD | 100+ GB SSD |
| Docker | 20.10+ | 20.10+ | Última versión |
**Pequeño**: Desarrollo, pruebas, usuario único (1-5 usuarios)
**Estándar**: Equipos (5-50 usuarios), cargas de trabajo moderadas
**Producción**: Equipos grandes (50+ usuarios), alta disponibilidad, ejecución intensiva de workflows
<Callout type="info">
Los requisitos de recursos están determinados por la ejecución de workflows (sandboxing isolated-vm), procesamiento de archivos (análisis de documentos en memoria) y operaciones vectoriales (pgvector). La memoria suele ser el factor limitante, no la CPU. La telemetría de producción muestra que la aplicación principal usa 4-8 GB en promedio con picos de hasta 12 GB bajo carga pesada.
</Callout>
## Inicio rápido

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@@ -10,12 +10,20 @@ Déployez Sim sur votre propre infrastructure avec Docker ou Kubernetes.
## Prérequis
| Ressource | Minimum | Recommandé |
|----------|---------|-------------|
| CPU | 2 cœurs | 4+ cœurs |
| RAM | 12 Go | 16+ Go |
| Stockage | 20 Go SSD | 50+ Go SSD |
| Docker | 20.10+ | Dernière version |
| Ressource | Petit | Standard | Production |
|----------|-------|----------|------------|
| CPU | 2 cœurs | 4 cœurs | 8+ cœurs |
| RAM | 12 Go | 16 Go | 32+ Go |
| Stockage | 20 Go SSD | 50 Go SSD | 100+ Go SSD |
| Docker | 20.10+ | 20.10+ | Dernière version |
**Petit** : Développement, tests, utilisateur unique (1-5 utilisateurs)
**Standard** : Équipes (5-50 utilisateurs), charges de travail modérées
**Production** : Grandes équipes (50+ utilisateurs), haute disponibilité, exécution intensive de workflows
<Callout type="info">
Les besoins en ressources sont déterminés par l'exécution des workflows (sandboxing isolated-vm), le traitement des fichiers (analyse de documents en mémoire) et les opérations vectorielles (pgvector). La mémoire est généralement le facteur limitant, pas le CPU. La télémétrie de production montre que l'application principale utilise 4-8 Go en moyenne avec des pics jusqu'à 12 Go sous forte charge.
</Callout>
## Démarrage rapide

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@@ -10,12 +10,20 @@ DockerまたはKubernetesを使用して、自社のインフラストラクチ
## 要件
| リソース | 最小 | 推奨 |
|----------|---------|-------------|
| CPU | 2コア | 4+コア |
| RAM | 12 GB | 16+ GB |
| ストレージ | 20 GB SSD | 50+ GB SSD |
| Docker | 20.10+ | 最新版 |
| リソース | スモール | スタンダード | プロダクション |
|----------|---------|-------------|----------------|
| CPU | 2コア | 4コア | 8+コア |
| RAM | 12 GB | 16 GB | 32+ GB |
| ストレージ | 20 GB SSD | 50 GB SSD | 100+ GB SSD |
| Docker | 20.10+ | 20.10+ | 最新版 |
**スモール**: 開発、テスト、シングルユーザー1-5ユーザー
**スタンダード**: チーム5-50ユーザー、中程度のワークロード
**プロダクション**: 大規模チーム50+ユーザー)、高可用性、高負荷ワークフロー実行
<Callout type="info">
リソース要件は、ワークフロー実行isolated-vmサンドボックス、ファイル処理メモリ内ドキュメント解析、ベクトル演算pgvectorによって決まります。CPUよりもメモリが制約要因となることが多いです。本番環境のテレメトリによると、メインアプリは平均4-8 GB、高負荷時は最大12 GBを使用します。
</Callout>
## クイックスタート

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@@ -10,12 +10,20 @@ import { Callout } from 'fumadocs-ui/components/callout'
## 要求
| 资源 | 最低要求 | 推荐配置 |
|----------|---------|-------------|
| CPU | 2 核 | 4 核及以上 |
| 内存 | 12 GB | 16 GB 及以上 |
| 存储 | 20 GB SSD | 50 GB 及以上 SSD |
| Docker | 20.10+ | 最新版本 |
| 资源 | 小型 | 标准 | 生产环境 |
|----------|------|------|----------|
| CPU | 2 核 | 4 核 | 8+ 核 |
| 内存 | 12 GB | 16 GB | 32+ GB |
| 存储 | 20 GB SSD | 50 GB SSD | 100+ GB SSD |
| Docker | 20.10+ | 20.10+ | 最新版本 |
**小型**: 开发、测试、单用户1-5 用户)
**标准**: 团队5-50 用户)、中等工作负载
**生产环境**: 大型团队50+ 用户)、高可用性、密集工作流执行
<Callout type="info">
资源需求由工作流执行isolated-vm 沙箱、文件处理内存中文档解析和向量运算pgvector决定。内存通常是限制因素而不是 CPU。生产遥测数据显示主应用平均使用 4-8 GB高负载时峰值可达 12 GB。
</Callout>
## 快速开始

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@@ -408,6 +408,7 @@ describe('Knowledge Search Utils', () => {
input: ['test query'],
model: 'text-embedding-3-small',
encoding_format: 'float',
dimensions: 1536,
}),
})
)

View File

@@ -581,6 +581,18 @@ export const GmailV2Block: BlockConfig<GmailToolResponse> = {
results: { type: 'json', description: 'Search/read summary results' },
attachments: { type: 'json', description: 'Downloaded attachments (if enabled)' },
// Draft-specific outputs
draftId: {
type: 'string',
description: 'Draft ID',
condition: { field: 'operation', value: 'draft_gmail' },
},
messageId: {
type: 'string',
description: 'Gmail message ID for the draft',
condition: { field: 'operation', value: 'draft_gmail' },
},
// Trigger outputs (unchanged)
email_id: { type: 'string', description: 'Gmail message ID' },
thread_id: { type: 'string', description: 'Gmail thread ID' },

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@@ -1,7 +1,9 @@
import { getBlockOutputs } from '@/lib/workflows/blocks/block-outputs'
import { normalizeName } from '@/executor/constants'
import type { ExecutionContext } from '@/executor/types'
import type { OutputSchema } from '@/executor/utils/block-reference'
import type { SerializedBlock } from '@/serializer/types'
import type { ToolConfig } from '@/tools/types'
import { getTool } from '@/tools/utils'
export interface BlockDataCollection {
blockData: Record<string, unknown>
@@ -9,6 +11,32 @@ export interface BlockDataCollection {
blockOutputSchemas: Record<string, OutputSchema>
}
export function getBlockSchema(
block: SerializedBlock,
toolConfig?: ToolConfig
): OutputSchema | undefined {
const isTrigger =
block.metadata?.category === 'triggers' ||
(block.config?.params as Record<string, unknown> | undefined)?.triggerMode === true
// Triggers use saved outputs (defines the trigger payload schema)
if (isTrigger && block.outputs && Object.keys(block.outputs).length > 0) {
return block.outputs as OutputSchema
}
// When a tool is selected, tool outputs are the source of truth
if (toolConfig?.outputs && Object.keys(toolConfig.outputs).length > 0) {
return toolConfig.outputs as OutputSchema
}
// Fallback to saved outputs for blocks without tools
if (block.outputs && Object.keys(block.outputs).length > 0) {
return block.outputs as OutputSchema
}
return undefined
}
export function collectBlockData(ctx: ExecutionContext): BlockDataCollection {
const blockData: Record<string, unknown> = {}
const blockNameMapping: Record<string, string> = {}
@@ -18,24 +46,21 @@ export function collectBlockData(ctx: ExecutionContext): BlockDataCollection {
if (state.output !== undefined) {
blockData[id] = state.output
}
}
const workflowBlock = ctx.workflow?.blocks?.find((b) => b.id === id)
if (!workflowBlock) continue
const workflowBlocks = ctx.workflow?.blocks ?? []
for (const block of workflowBlocks) {
const id = block.id
if (workflowBlock.metadata?.name) {
blockNameMapping[normalizeName(workflowBlock.metadata.name)] = id
if (block.metadata?.name) {
blockNameMapping[normalizeName(block.metadata.name)] = id
}
const blockType = workflowBlock.metadata?.id
if (blockType) {
const params = workflowBlock.config?.params as Record<string, unknown> | undefined
const subBlocks = params
? Object.fromEntries(Object.entries(params).map(([k, v]) => [k, { value: v }]))
: undefined
const schema = getBlockOutputs(blockType, subBlocks)
if (schema && Object.keys(schema).length > 0) {
blockOutputSchemas[id] = schema
}
const toolId = block.config?.tool
const toolConfig = toolId ? getTool(toolId) : undefined
const schema = getBlockSchema(block, toolConfig)
if (schema && Object.keys(schema).length > 0) {
blockOutputSchemas[id] = schema
}
}

View File

@@ -378,8 +378,30 @@ function buildManualTriggerOutput(
return mergeFilesIntoOutput(output, workflowInput)
}
function buildIntegrationTriggerOutput(workflowInput: unknown): NormalizedBlockOutput {
return isPlainObject(workflowInput) ? (workflowInput as NormalizedBlockOutput) : {}
function buildIntegrationTriggerOutput(
workflowInput: unknown,
structuredInput: Record<string, unknown>,
hasStructured: boolean
): NormalizedBlockOutput {
const output: NormalizedBlockOutput = {}
if (hasStructured) {
for (const [key, value] of Object.entries(structuredInput)) {
output[key] = value
}
}
if (isPlainObject(workflowInput)) {
for (const [key, value] of Object.entries(workflowInput)) {
if (value !== undefined && value !== null) {
output[key] = value
} else if (!Object.hasOwn(output, key)) {
output[key] = value
}
}
}
return mergeFilesIntoOutput(output, workflowInput)
}
function extractSubBlocks(block: SerializedBlock): Record<string, unknown> | undefined {
@@ -428,7 +450,7 @@ export function buildStartBlockOutput(options: StartBlockOutputOptions): Normali
return buildManualTriggerOutput(finalInput, workflowInput)
case StartBlockPath.EXTERNAL_TRIGGER:
return buildIntegrationTriggerOutput(workflowInput)
return buildIntegrationTriggerOutput(workflowInput, structuredInput, hasStructured)
case StartBlockPath.LEGACY_STARTER:
return buildLegacyStarterOutput(

View File

@@ -1,10 +1,10 @@
import { getBlockOutputs } from '@/lib/workflows/blocks/block-outputs'
import {
isReference,
normalizeName,
parseReferencePath,
SPECIAL_REFERENCE_PREFIXES,
} from '@/executor/constants'
import { getBlockSchema } from '@/executor/utils/block-data'
import {
InvalidFieldError,
type OutputSchema,
@@ -67,15 +67,9 @@ export class BlockResolver implements Resolver {
blockData[blockId] = output
}
const blockType = block.metadata?.id
const params = block.config?.params as Record<string, unknown> | undefined
const subBlocks = params
? Object.fromEntries(Object.entries(params).map(([k, v]) => [k, { value: v }]))
: undefined
const toolId = block.config?.tool
const toolConfig = toolId ? getTool(toolId) : undefined
const outputSchema =
toolConfig?.outputs ?? (blockType ? getBlockOutputs(blockType, subBlocks) : block.outputs)
const outputSchema = getBlockSchema(block, toolConfig)
if (outputSchema && Object.keys(outputSchema).length > 0) {
blockOutputSchemas[blockId] = outputSchema

View File

@@ -8,6 +8,17 @@ const logger = createLogger('EmbeddingUtils')
const MAX_TOKENS_PER_REQUEST = 8000
const MAX_CONCURRENT_BATCHES = env.KB_CONFIG_CONCURRENCY_LIMIT || 50
const EMBEDDING_DIMENSIONS = 1536
/**
* Check if the model supports custom dimensions.
* text-embedding-3-* models support the dimensions parameter.
* Checks for 'embedding-3' to handle Azure deployments with custom naming conventions.
*/
function supportsCustomDimensions(modelName: string): boolean {
const name = modelName.toLowerCase()
return name.includes('embedding-3') && !name.includes('ada')
}
export class EmbeddingAPIError extends Error {
public status: number
@@ -93,15 +104,19 @@ async function getEmbeddingConfig(
async function callEmbeddingAPI(inputs: string[], config: EmbeddingConfig): Promise<number[][]> {
return retryWithExponentialBackoff(
async () => {
const useDimensions = supportsCustomDimensions(config.modelName)
const requestBody = config.useAzure
? {
input: inputs,
encoding_format: 'float',
...(useDimensions && { dimensions: EMBEDDING_DIMENSIONS }),
}
: {
input: inputs,
model: config.modelName,
encoding_format: 'float',
...(useDimensions && { dimensions: EMBEDDING_DIMENSIONS }),
}
const response = await fetch(config.apiUrl, {

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@@ -18,6 +18,52 @@ const logger = createLogger('BlobClient')
let _blobServiceClient: BlobServiceClientInstance | null = null
interface ParsedCredentials {
accountName: string
accountKey: string
}
/**
* Extract account name and key from an Azure connection string.
* Connection strings have the format: DefaultEndpointsProtocol=https;AccountName=...;AccountKey=...;EndpointSuffix=...
*/
function parseConnectionString(connectionString: string): ParsedCredentials {
const accountNameMatch = connectionString.match(/AccountName=([^;]+)/)
if (!accountNameMatch) {
throw new Error('Cannot extract account name from connection string')
}
const accountKeyMatch = connectionString.match(/AccountKey=([^;]+)/)
if (!accountKeyMatch) {
throw new Error('Cannot extract account key from connection string')
}
return {
accountName: accountNameMatch[1],
accountKey: accountKeyMatch[1],
}
}
/**
* Get account credentials from BLOB_CONFIG, extracting from connection string if necessary.
*/
function getAccountCredentials(): ParsedCredentials {
if (BLOB_CONFIG.connectionString) {
return parseConnectionString(BLOB_CONFIG.connectionString)
}
if (BLOB_CONFIG.accountName && BLOB_CONFIG.accountKey) {
return {
accountName: BLOB_CONFIG.accountName,
accountKey: BLOB_CONFIG.accountKey,
}
}
throw new Error(
'Azure Blob Storage credentials are missing set AZURE_CONNECTION_STRING or both AZURE_ACCOUNT_NAME and AZURE_ACCOUNT_KEY'
)
}
export async function getBlobServiceClient(): Promise<BlobServiceClientInstance> {
if (_blobServiceClient) return _blobServiceClient
@@ -127,6 +173,8 @@ export async function getPresignedUrl(key: string, expiresIn = 3600) {
const containerClient = blobServiceClient.getContainerClient(BLOB_CONFIG.containerName)
const blockBlobClient = containerClient.getBlockBlobClient(key)
const { accountName, accountKey } = getAccountCredentials()
const sasOptions = {
containerName: BLOB_CONFIG.containerName,
blobName: key,
@@ -137,13 +185,7 @@ export async function getPresignedUrl(key: string, expiresIn = 3600) {
const sasToken = generateBlobSASQueryParameters(
sasOptions,
new StorageSharedKeyCredential(
BLOB_CONFIG.accountName,
BLOB_CONFIG.accountKey ??
(() => {
throw new Error('AZURE_ACCOUNT_KEY is required when using account name authentication')
})()
)
new StorageSharedKeyCredential(accountName, accountKey)
).toString()
return `${blockBlobClient.url}?${sasToken}`
@@ -168,9 +210,14 @@ export async function getPresignedUrlWithConfig(
StorageSharedKeyCredential,
} = await import('@azure/storage-blob')
let tempBlobServiceClient: BlobServiceClientInstance
let accountName: string
let accountKey: string
if (customConfig.connectionString) {
tempBlobServiceClient = BlobServiceClient.fromConnectionString(customConfig.connectionString)
const credentials = parseConnectionString(customConfig.connectionString)
accountName = credentials.accountName
accountKey = credentials.accountKey
} else if (customConfig.accountName && customConfig.accountKey) {
const sharedKeyCredential = new StorageSharedKeyCredential(
customConfig.accountName,
@@ -180,6 +227,8 @@ export async function getPresignedUrlWithConfig(
`https://${customConfig.accountName}.blob.core.windows.net`,
sharedKeyCredential
)
accountName = customConfig.accountName
accountKey = customConfig.accountKey
} else {
throw new Error(
'Custom blob config must include either connectionString or accountName + accountKey'
@@ -199,13 +248,7 @@ export async function getPresignedUrlWithConfig(
const sasToken = generateBlobSASQueryParameters(
sasOptions,
new StorageSharedKeyCredential(
customConfig.accountName,
customConfig.accountKey ??
(() => {
throw new Error('Account key is required when using account name authentication')
})()
)
new StorageSharedKeyCredential(accountName, accountKey)
).toString()
return `${blockBlobClient.url}?${sasToken}`
@@ -403,13 +446,9 @@ export async function getMultipartPartUrls(
if (customConfig) {
if (customConfig.connectionString) {
blobServiceClient = BlobServiceClient.fromConnectionString(customConfig.connectionString)
const match = customConfig.connectionString.match(/AccountName=([^;]+)/)
if (!match) throw new Error('Cannot extract account name from connection string')
accountName = match[1]
const keyMatch = customConfig.connectionString.match(/AccountKey=([^;]+)/)
if (!keyMatch) throw new Error('Cannot extract account key from connection string')
accountKey = keyMatch[1]
const credentials = parseConnectionString(customConfig.connectionString)
accountName = credentials.accountName
accountKey = credentials.accountKey
} else if (customConfig.accountName && customConfig.accountKey) {
const credential = new StorageSharedKeyCredential(
customConfig.accountName,
@@ -428,12 +467,9 @@ export async function getMultipartPartUrls(
} else {
blobServiceClient = await getBlobServiceClient()
containerName = BLOB_CONFIG.containerName
accountName = BLOB_CONFIG.accountName
accountKey =
BLOB_CONFIG.accountKey ||
(() => {
throw new Error('AZURE_ACCOUNT_KEY is required')
})()
const credentials = getAccountCredentials()
accountName = credentials.accountName
accountKey = credentials.accountKey
}
const containerClient = blobServiceClient.getContainerClient(containerName)
@@ -501,12 +537,10 @@ export async function completeMultipartUpload(
const containerClient = blobServiceClient.getContainerClient(containerName)
const blockBlobClient = containerClient.getBlockBlobClient(key)
// Sort parts by part number and extract block IDs
const sortedBlockIds = parts
.sort((a, b) => a.partNumber - b.partNumber)
.map((part) => part.blockId)
// Commit the block list to create the final blob
await blockBlobClient.commitBlockList(sortedBlockIds, {
metadata: {
multipartUpload: 'completed',
@@ -557,10 +591,8 @@ export async function abortMultipartUpload(key: string, customConfig?: BlobConfi
const blockBlobClient = containerClient.getBlockBlobClient(key)
try {
// Delete the blob if it exists (this also cleans up any uncommitted blocks)
await blockBlobClient.deleteIfExists()
} catch (error) {
// Ignore errors since we're just cleaning up
logger.warn('Error cleaning up multipart upload:', error)
}
}

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@@ -618,13 +618,6 @@ export function getToolOutputs(
}
}
/**
* Generates output paths for a tool-based block.
*
* @param blockConfig - The block configuration containing tools config
* @param subBlocks - SubBlock values for tool selection and condition evaluation
* @returns Array of output paths for the tool, or empty array on error
*/
export function getToolOutputPaths(
blockConfig: BlockConfig,
subBlocks?: Record<string, SubBlockWithValue>
@@ -634,12 +627,22 @@ export function getToolOutputPaths(
if (!outputs || Object.keys(outputs).length === 0) return []
if (subBlocks && blockConfig.outputs) {
const filteredBlockOutputs = filterOutputsByCondition(blockConfig.outputs, subBlocks)
const allowedKeys = new Set(Object.keys(filteredBlockOutputs))
const filteredOutputs: Record<string, any> = {}
for (const [key, value] of Object.entries(outputs)) {
if (allowedKeys.has(key)) {
const blockOutput = blockConfig.outputs[key]
if (!blockOutput || typeof blockOutput !== 'object') {
filteredOutputs[key] = value
continue
}
const condition = 'condition' in blockOutput ? blockOutput.condition : undefined
if (condition) {
if (evaluateOutputCondition(condition, subBlocks)) {
filteredOutputs[key] = value
}
} else {
filteredOutputs[key] = value
}
}

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@@ -52,7 +52,7 @@ services:
deploy:
resources:
limits:
memory: 8G
memory: 1G
healthcheck:
test: ['CMD', 'wget', '--spider', '--quiet', 'http://127.0.0.1:3002/health']
interval: 90s

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@@ -56,7 +56,7 @@ services:
deploy:
resources:
limits:
memory: 8G
memory: 1G
healthcheck:
test: ['CMD', 'wget', '--spider', '--quiet', 'http://127.0.0.1:3002/health']
interval: 90s

View File

@@ -42,7 +42,7 @@ services:
deploy:
resources:
limits:
memory: 4G
memory: 1G
environment:
- DATABASE_URL=postgresql://${POSTGRES_USER:-postgres}:${POSTGRES_PASSWORD:-postgres}@db:5432/${POSTGRES_DB:-simstudio}
- NEXT_PUBLIC_APP_URL=${NEXT_PUBLIC_APP_URL:-http://localhost:3000}

View File

@@ -10,13 +10,13 @@ global:
app:
enabled: true
replicaCount: 2
resources:
limits:
memory: "6Gi"
memory: "8Gi"
cpu: "2000m"
requests:
memory: "4Gi"
memory: "6Gi"
cpu: "1000m"
# Production URLs (REQUIRED - update with your actual domain names)
@@ -49,14 +49,14 @@ app:
realtime:
enabled: true
replicaCount: 2
resources:
limits:
memory: "4Gi"
cpu: "1000m"
requests:
memory: "2Gi"
memory: "1Gi"
cpu: "500m"
requests:
memory: "512Mi"
cpu: "250m"
env:
NEXT_PUBLIC_APP_URL: "https://sim.acme.ai"

View File

@@ -29,10 +29,10 @@ app:
# Resource limits and requests
resources:
limits:
memory: "4Gi"
memory: "8Gi"
cpu: "2000m"
requests:
memory: "2Gi"
memory: "4Gi"
cpu: "1000m"
# Node selector for pod scheduling (leave empty to allow scheduling on any node)
@@ -232,24 +232,24 @@ app:
realtime:
# Enable/disable the realtime service
enabled: true
# Image configuration
image:
repository: simstudioai/realtime
tag: latest
pullPolicy: Always
# Number of replicas
replicaCount: 1
# Resource limits and requests
resources:
limits:
memory: "2Gi"
cpu: "1000m"
requests:
memory: "1Gi"
cpu: "500m"
requests:
memory: "512Mi"
cpu: "250m"
# Node selector for pod scheduling (leave empty to allow scheduling on any node)
nodeSelector: {}