v0.5.87: workflow block auth fix

v0.5.86: server side copilot, copilot mcp, error notifications, jira outputs destructuring, slack trigger improvements
v0.5.85: deployment improvements
2026-02-14 08:25:03 -05:00 · 2026-02-10 22:33:55 -08:00 · 2026-02-10 21:49:58 -08:00 · 2026-02-09 10:49:33 -08:00 · 2026-02-07 19:06:53 -08:00 · 2026-02-07 12:27:11 -08:00
11 changed files with 7 additions and 700 deletions
--- a/apps/sim/blocks/blocks/agent.ts
+++ b/apps/sim/blocks/blocks/agent.ts
@@ -10,11 +10,9 @@ import {
  getReasoningEffortValuesForModel,
  getThinkingLevelsForModel,
  getVerbosityValuesForModel,
-  MODELS_WITH_DEEP_RESEARCH,
  MODELS_WITH_REASONING_EFFORT,
  MODELS_WITH_THINKING,
  MODELS_WITH_VERBOSITY,
-  MODELS_WITHOUT_MEMORY,
  providers,
  supportsTemperature,
 } from '@/providers/utils'
@@ -414,22 +412,12 @@ Return ONLY the JSON array.`,
      title: 'Tools',
      type: 'tool-input',
      defaultValue: [],
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-        not: true,
-      },
    },
    {
      id: 'skills',
      title: 'Skills',
      type: 'skill-input',
      defaultValue: [],
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-        not: true,
-      },
    },
    {
      id: 'memoryType',
@@ -443,11 +431,6 @@ Return ONLY the JSON array.`,
        { label: 'Sliding window (tokens)', id: 'sliding_window_tokens' },
      ],
      defaultValue: 'none',
-      condition: {
-        field: 'model',
-        value: MODELS_WITHOUT_MEMORY,
-        not: true,
-      },
    },
    {
      id: 'conversationId',
@@ -461,7 +444,6 @@ Return ONLY the JSON array.`,
      condition: {
        field: 'memoryType',
        value: ['conversation', 'sliding_window', 'sliding_window_tokens'],
-        and: { field: 'model', value: MODELS_WITHOUT_MEMORY, not: true },
      },
    },
    {
@@ -472,7 +454,6 @@ Return ONLY the JSON array.`,
      condition: {
        field: 'memoryType',
        value: ['sliding_window'],
-        and: { field: 'model', value: MODELS_WITHOUT_MEMORY, not: true },
      },
    },
    {
@@ -483,7 +464,6 @@ Return ONLY the JSON array.`,
      condition: {
        field: 'memoryType',
        value: ['sliding_window_tokens'],
-        and: { field: 'model', value: MODELS_WITHOUT_MEMORY, not: true },
      },
    },
    {
@@ -497,13 +477,9 @@ Return ONLY the JSON array.`,
      condition: () => ({
        field: 'model',
        value: (() => {
-          const deepResearch = new Set(MODELS_WITH_DEEP_RESEARCH.map((m) => m.toLowerCase()))
          const allModels = Object.keys(getBaseModelProviders())
          return allModels.filter(
-            (model) =>
-              supportsTemperature(model) &&
-              getMaxTemperature(model) === 1 &&
-              !deepResearch.has(model.toLowerCase())
+            (model) => supportsTemperature(model) && getMaxTemperature(model) === 1
          )
        })(),
      }),
@@ -519,13 +495,9 @@ Return ONLY the JSON array.`,
      condition: () => ({
        field: 'model',
        value: (() => {
-          const deepResearch = new Set(MODELS_WITH_DEEP_RESEARCH.map((m) => m.toLowerCase()))
          const allModels = Object.keys(getBaseModelProviders())
          return allModels.filter(
-            (model) =>
-              supportsTemperature(model) &&
-              getMaxTemperature(model) === 2 &&
-              !deepResearch.has(model.toLowerCase())
+            (model) => supportsTemperature(model) && getMaxTemperature(model) === 2
          )
        })(),
      }),
@@ -536,11 +508,6 @@ Return ONLY the JSON array.`,
      type: 'short-input',
      placeholder: 'Enter max tokens (e.g., 4096)...',
      mode: 'advanced',
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-        not: true,
-      },
    },
    {
      id: 'responseFormat',
@@ -548,11 +515,6 @@ Return ONLY the JSON array.`,
      type: 'code',
      placeholder: 'Enter JSON schema...',
      language: 'json',
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-        not: true,
-      },
      wandConfig: {
        enabled: true,
        maintainHistory: true,
@@ -645,16 +607,6 @@ Example 3 (Array Input):
        generationType: 'json-schema',
      },
    },
-    {
-      id: 'previousInteractionId',
-      title: 'Previous Interaction ID',
-      type: 'short-input',
-      placeholder: 'e.g., {{agent_1.interactionId}}',
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-      },
-    },
  ],
  tools: {
    access: [
@@ -818,13 +770,5 @@ Example 3 (Array Input):
      description: 'Provider timing information',
    },
    cost: { type: 'json', description: 'Cost of the API call' },
-    interactionId: {
-      type: 'string',
-      description: 'Interaction ID for multi-turn deep research follow-ups',
-      condition: {
-        field: 'model',
-        value: MODELS_WITH_DEEP_RESEARCH,
-      },
-    },
  },
 }
--- a/apps/sim/content/blog/enterprise/index.mdx
+++ b/apps/sim/content/blog/enterprise/index.mdx
@@ -2,8 +2,8 @@
 slug: enterprise
 title: 'Build with Sim for Enterprise'
 description: 'Access control, BYOK, self-hosted deployments, on-prem Copilot, SSO & SAML, whitelabeling, Admin API, and flexible data retention—enterprise features for teams with strict security and compliance requirements.'
-date: 2026-02-11
-updated: 2026-02-11
+date: 2026-01-23
+updated: 2026-01-23
 authors:
  - vik
 readingTime: 10
@@ -13,8 +13,8 @@ ogAlt: 'Sim Enterprise features overview'
 about: ['Enterprise Software', 'Security', 'Compliance', 'Self-Hosting']
 timeRequired: PT10M
 canonical: https://sim.ai/studio/enterprise
-featured: true
-draft: false
+featured: false
+draft: true
 ---

 We've been working with security teams at larger organizations to bring Sim into environments with strict compliance and data handling requirements. This post covers the enterprise capabilities we've built: granular access control, bring-your-own-keys, self-hosted deployments, on-prem Copilot, SSO & SAML, whitelabeling, compliance, and programmatic management via the Admin API.
--- a/apps/sim/content/blog/workflow-bench/index.mdx
+++ b/apps/sim/content/blog/workflow-bench/index.mdx
@@ -1,90 +0,0 @@
---
-slug: workflow-bench
-title: 'Introducing Workflow Bench - Benchmarking Natural Language Workflow Building'
-description: 'How we built a benchmark to measure how well AI models translate natural language instructions into executable workflows, and what we learned along the way'
-date: 2026-02-11
-updated: 2026-02-11
-authors:
-  - sid
-readingTime: 10
-tags: [Benchmark, Evaluation, Workflows, Natural Language]
-ogImage: /studio/workflow-bench/cover.png
-ogAlt: 'Workflow Bench benchmark overview'
-about: ['Benchmarking', 'Workflow Building', 'Natural Language']
-timeRequired: PT10M
-canonical: https://sim.ai/studio/workflow-bench
-featured: false
-draft: true
---
-
-Building workflows from natural language sounds straightforward until you try to measure it. When a user says "send me a Slack message every morning with a summary of my unread emails," how do you evaluate whether the resulting workflow is correct? Is partial credit fair? What about workflows that are functionally equivalent but structurally different?
-
-We built Workflow Bench to answer these questions. This post covers why we needed a dedicated benchmark, how we designed it, and what the results tell us about the current state of natural language workflow building.
-
-## Why a Workflow Benchmark?
-
-<!-- TODO: Motivation for building Workflow Bench -->
-<!-- - Gap in existing benchmarks (code gen benchmarks don't capture workflow semantics) -->
-<!-- - Need to track progress as we iterate on the copilot / natural language builder -->
-<!-- - Workflows are structured artifacts, not just code — they have topology, block types, connections, configs -->
-
-## What We're Measuring
-
-<!-- TODO: Define the core evaluation dimensions -->
-<!-- - Structural correctness (right blocks, right connections) -->
-<!-- - Configuration accuracy (correct params, API mappings) -->
-<!-- - Functional equivalence (does it do the same thing even if shaped differently?) -->
-<!-- - Edge cases: loops, conditionals, parallel branches, error handling -->
-
-## Benchmark Design
-
-<!-- TODO: How the benchmark dataset is constructed -->
-<!-- - Task categories and complexity tiers -->
-<!-- - How ground truth workflows are defined -->
-<!-- - Natural language prompt variations (terse vs. detailed, ambiguous vs. precise) -->
-
-### Task Categories
-
-<!-- TODO: Break down the types of workflows in the benchmark -->
-<!-- - Simple linear (A → B → C) -->
-<!-- - Branching / conditional -->
-<!-- - Looping / iterative -->
-<!-- - Parallel fan-out / fan-in -->
-<!-- - Multi-trigger -->
-
-### Scoring
-
-<!-- TODO: Explain the scoring methodology -->
-<!-- - How partial credit works -->
-<!-- - Structural similarity metrics -->
-<!-- - Config-level accuracy -->
-<!-- - Overall composite score -->
-
-## Evaluation Pipeline
-
-<!-- TODO: How we run the benchmark end to end -->
-<!-- - Prompt → model → workflow JSON → evaluator → score -->
-<!-- - Automation and reproducibility -->
-<!-- - How we handle non-determinism across runs -->
-
-## Results
-
-<!-- TODO: Present the benchmark results -->
-<!-- - Model comparisons -->
-<!-- - Performance by task category -->
-<!-- - Where models struggle most -->
-<!-- - Trends over time as we iterate -->
-
-## What We Learned
-
-<!-- TODO: Key takeaways from running the benchmark -->
-<!-- - Surprising strengths and weaknesses -->
-<!-- - How benchmark results influenced product decisions -->
-<!-- - Common failure modes -->
-
-## What's Next
-
-<!-- TODO: Future directions -->
-<!-- - Expanding the benchmark (more tasks, more complexity) -->
-<!-- - Community contributions / open-sourcing -->
-<!-- - Using the benchmark to guide copilot improvements -->
--- a/apps/sim/executor/handlers/agent/agent-handler.ts
+++ b/apps/sim/executor/handlers/agent/agent-handler.ts
@@ -999,7 +999,6 @@ export class AgentBlockHandler implements BlockHandler {
      reasoningEffort: inputs.reasoningEffort,
      verbosity: inputs.verbosity,
      thinkingLevel: inputs.thinkingLevel,
-      previousInteractionId: inputs.previousInteractionId,
    }
  }

@@ -1070,7 +1069,6 @@ export class AgentBlockHandler implements BlockHandler {
        reasoningEffort: providerRequest.reasoningEffort,
        verbosity: providerRequest.verbosity,
        thinkingLevel: providerRequest.thinkingLevel,
-        previousInteractionId: providerRequest.previousInteractionId,
      })

      return this.processProviderResponse(response, block, responseFormat)
@@ -1271,7 +1269,6 @@ export class AgentBlockHandler implements BlockHandler {
      content: result.content,
      model: result.model,
      ...this.createResponseMetadata(result),
-      ...(result.interactionId && { interactionId: result.interactionId }),
    }
  }

--- a/apps/sim/executor/handlers/agent/types.ts
+++ b/apps/sim/executor/handlers/agent/types.ts
@@ -20,8 +20,6 @@ export interface AgentInputs {
  conversationId?: string // Required for all non-none memory types
  slidingWindowSize?: string // For message-based sliding window
  slidingWindowTokens?: string // For token-based sliding window
-  // Deep research multi-turn
-  previousInteractionId?: string // Interactions API previous interaction reference
  // LLM parameters
  temperature?: string
  maxTokens?: string
--- a/apps/sim/providers/gemini/core.ts
+++ b/apps/sim/providers/gemini/core.ts
@@ -5,7 +5,6 @@ import {
  type GenerateContentConfig,
  type GenerateContentResponse,
  type GoogleGenAI,
-  type Interactions,
  type Part,
  type Schema,
  type ThinkingConfig,
@@ -28,7 +27,6 @@ import {
 import type { FunctionCallResponse, ProviderRequest, ProviderResponse } from '@/providers/types'
 import {
  calculateCost,
-  isDeepResearchModel,
  prepareToolExecution,
  prepareToolsWithUsageControl,
 } from '@/providers/utils'
@@ -383,468 +381,6 @@ export interface GeminiExecutionConfig {
  providerType: GeminiProviderType
 }

-const DEEP_RESEARCH_POLL_INTERVAL_MS = 10_000
-const DEEP_RESEARCH_MAX_DURATION_MS = 60 * 60 * 1000
-
-/**
- * Sleeps for the specified number of milliseconds
- */
-function sleep(ms: number): Promise<void> {
-  return new Promise((resolve) => setTimeout(resolve, ms))
-}
-
-/**
- * Collapses a ProviderRequest into a single input string and optional system instruction
- * for the Interactions API, which takes a flat input rather than a messages array.
- *
- * Deep research is single-turn only — it takes one research query and returns a report.
- * Memory/conversation history is hidden in the UI for deep research models, so only
- * the last user message is used as input. System messages are passed via system_instruction.
- */
-function collapseMessagesToInput(request: ProviderRequest): {
-  input: string
-  systemInstruction: string | undefined
-} {
-  const systemParts: string[] = []
-  const userParts: string[] = []
-
-  if (request.systemPrompt) {
-    systemParts.push(request.systemPrompt)
-  }
-
-  if (request.messages) {
-    for (const msg of request.messages) {
-      if (msg.role === 'system' && msg.content) {
-        systemParts.push(msg.content)
-      } else if (msg.role === 'user' && msg.content) {
-        userParts.push(msg.content)
-      }
-    }
-  }
-
-  return {
-    input:
-      userParts.length > 0
-        ? userParts[userParts.length - 1]
-        : 'Please conduct research on the provided topic.',
-    systemInstruction: systemParts.length > 0 ? systemParts.join('\n\n') : undefined,
-  }
-}
-
-/**
- * Extracts text content from a completed interaction's outputs array.
- * The outputs array can contain text, thought, google_search_result, and other types.
- * We concatenate all text outputs to get the full research report.
- */
-function extractTextFromInteractionOutputs(outputs: Interactions.Interaction['outputs']): string {
-  if (!outputs || outputs.length === 0) return ''
-
-  const textParts: string[] = []
-  for (const output of outputs) {
-    if (output.type === 'text') {
-      const text = (output as Interactions.TextContent).text
-      if (text) textParts.push(text)
-    }
-  }
-
-  return textParts.join('\n\n')
-}
-
-/**
- * Extracts token usage from an Interaction's Usage object.
- * The Interactions API provides total_input_tokens, total_output_tokens, total_tokens,
- * and total_reasoning_tokens (for thinking models).
- *
- * Also handles the raw API field name total_thought_tokens which the SDK may
- * map to total_reasoning_tokens.
- */
-function extractInteractionUsage(usage: Interactions.Usage | undefined): {
-  inputTokens: number
-  outputTokens: number
-  reasoningTokens: number
-  totalTokens: number
-} {
-  if (!usage) {
-    return { inputTokens: 0, outputTokens: 0, reasoningTokens: 0, totalTokens: 0 }
-  }
-
-  const usageLogger = createLogger('DeepResearchUsage')
-  usageLogger.info('Raw interaction usage', { usage: JSON.stringify(usage) })
-
-  const inputTokens = usage.total_input_tokens ?? 0
-  const outputTokens = usage.total_output_tokens ?? 0
-  const reasoningTokens =
-    usage.total_reasoning_tokens ??
-    ((usage as Record<string, unknown>).total_thought_tokens as number) ??
-    0
-  const totalTokens = usage.total_tokens ?? inputTokens + outputTokens
-
-  return { inputTokens, outputTokens, reasoningTokens, totalTokens }
-}
-
-/**
- * Builds a standard ProviderResponse from a completed deep research interaction.
- */
-function buildDeepResearchResponse(
-  content: string,
-  model: string,
-  usage: {
-    inputTokens: number
-    outputTokens: number
-    reasoningTokens: number
-    totalTokens: number
-  },
-  providerStartTime: number,
-  providerStartTimeISO: string,
-  interactionId?: string
-): ProviderResponse {
-  const providerEndTime = Date.now()
-  const duration = providerEndTime - providerStartTime
-
-  return {
-    content,
-    model,
-    tokens: {
-      input: usage.inputTokens,
-      output: usage.outputTokens,
-      total: usage.totalTokens,
-    },
-    timing: {
-      startTime: providerStartTimeISO,
-      endTime: new Date(providerEndTime).toISOString(),
-      duration,
-      modelTime: duration,
-      toolsTime: 0,
-      firstResponseTime: duration,
-      iterations: 1,
-      timeSegments: [
-        {
-          type: 'model',
-          name: 'Deep research',
-          startTime: providerStartTime,
-          endTime: providerEndTime,
-          duration,
-        },
-      ],
-    },
-    cost: calculateCost(model, usage.inputTokens, usage.outputTokens),
-    interactionId,
-  }
-}
-
-/**
- * Creates a ReadableStream from a deep research streaming interaction.
- *
- * Deep research streaming returns InteractionSSEEvent chunks including:
- * - interaction.start: initial interaction with ID
- * - content.delta: incremental text and thought_summary updates
- * - content.start / content.stop: output boundaries
- * - interaction.complete: final event (outputs is undefined in streaming; must reconstruct)
- * - error: error events
- *
- * We stream text deltas to the client and track usage from the interaction.complete event.
- */
-function createDeepResearchStream(
-  stream: AsyncIterable<Interactions.InteractionSSEEvent>,
-  onComplete?: (
-    content: string,
-    usage: {
-      inputTokens: number
-      outputTokens: number
-      reasoningTokens: number
-      totalTokens: number
-    },
-    interactionId?: string
-  ) => void
-): ReadableStream<Uint8Array> {
-  const streamLogger = createLogger('DeepResearchStream')
-  let fullContent = ''
-  let completionUsage = { inputTokens: 0, outputTokens: 0, reasoningTokens: 0, totalTokens: 0 }
-  let completedInteractionId: string | undefined
-
-  return new ReadableStream({
-    async start(controller) {
-      try {
-        for await (const event of stream) {
-          if (event.event_type === 'content.delta') {
-            const delta = (event as Interactions.ContentDelta).delta
-            if (delta?.type === 'text' && 'text' in delta && delta.text) {
-              fullContent += delta.text
-              controller.enqueue(new TextEncoder().encode(delta.text))
-            }
-          } else if (event.event_type === 'interaction.complete') {
-            const interaction = (event as Interactions.InteractionEvent).interaction
-            if (interaction?.usage) {
-              completionUsage = extractInteractionUsage(interaction.usage)
-            }
-            completedInteractionId = interaction?.id
-          } else if (event.event_type === 'interaction.start') {
-            const interaction = (event as Interactions.InteractionEvent).interaction
-            if (interaction?.id) {
-              completedInteractionId = interaction.id
-            }
-          } else if (event.event_type === 'error') {
-            const errorEvent = event as { error?: { code?: string; message?: string } }
-            const message = errorEvent.error?.message ?? 'Unknown deep research stream error'
-            streamLogger.error('Deep research stream error', {
-              code: errorEvent.error?.code,
-              message,
-            })
-            controller.error(new Error(message))
-            return
-          }
-        }
-
-        onComplete?.(fullContent, completionUsage, completedInteractionId)
-        controller.close()
-      } catch (error) {
-        streamLogger.error('Error reading deep research stream', {
-          error: error instanceof Error ? error.message : String(error),
-        })
-        controller.error(error)
-      }
-    },
-  })
-}
-
-/**
- * Executes a deep research request using the Interactions API.
- *
- * Deep research uses the Interactions API ({@link https://ai.google.dev/api/interactions-api}),
- * a completely different surface from generateContent. It creates a background interaction
- * that performs comprehensive research (up to 60 minutes).
- *
- * Supports both streaming and non-streaming modes:
- * - Streaming: returns a StreamingExecution with a ReadableStream of text deltas
- * - Non-streaming: polls until completion and returns a ProviderResponse
- *
- * Deep research does NOT support custom function calling tools, MCP servers,
- * or structured output (response_format). These are gracefully ignored.
- */
-export async function executeDeepResearchRequest(
-  config: GeminiExecutionConfig
-): Promise<ProviderResponse | StreamingExecution> {
-  const { ai, model, request, providerType } = config
-  const logger = createLogger(providerType === 'google' ? 'GoogleProvider' : 'VertexProvider')
-
-  logger.info('Preparing deep research request', {
-    model,
-    hasSystemPrompt: !!request.systemPrompt,
-    hasMessages: !!request.messages?.length,
-    streaming: !!request.stream,
-    hasPreviousInteractionId: !!request.previousInteractionId,
-  })
-
-  if (request.tools?.length) {
-    logger.warn('Deep research does not support custom tools — ignoring tools parameter')
-  }
-  if (request.responseFormat) {
-    logger.warn(
-      'Deep research does not support structured output — ignoring responseFormat parameter'
-    )
-  }
-
-  const providerStartTime = Date.now()
-  const providerStartTimeISO = new Date(providerStartTime).toISOString()
-
-  try {
-    const { input, systemInstruction } = collapseMessagesToInput(request)
-
-    // Deep research requires background=true and store=true (store defaults to true,
-    // but we set it explicitly per API requirements)
-    const baseParams = {
-      agent: model as Interactions.CreateAgentInteractionParamsNonStreaming['agent'],
-      input,
-      background: true,
-      store: true,
-      ...(systemInstruction && { system_instruction: systemInstruction }),
-      ...(request.previousInteractionId && {
-        previous_interaction_id: request.previousInteractionId,
-      }),
-      agent_config: {
-        type: 'deep-research' as const,
-        thinking_summaries: 'auto' as const,
-      },
-    }
-
-    logger.info('Creating deep research interaction', {
-      inputLength: input.length,
-      hasSystemInstruction: !!systemInstruction,
-      streaming: !!request.stream,
-    })
-
-    // Streaming mode: create a streaming interaction and return a StreamingExecution
-    if (request.stream) {
-      const streamParams: Interactions.CreateAgentInteractionParamsStreaming = {
-        ...baseParams,
-        stream: true,
-      }
-
-      const streamResponse = await ai.interactions.create(streamParams)
-      const firstResponseTime = Date.now() - providerStartTime
-
-      const streamingResult: StreamingExecution = {
-        stream: undefined as unknown as ReadableStream<Uint8Array>,
-        execution: {
-          success: true,
-          output: {
-            content: '',
-            model,
-            tokens: { input: 0, output: 0, total: 0 },
-            providerTiming: {
-              startTime: providerStartTimeISO,
-              endTime: new Date().toISOString(),
-              duration: Date.now() - providerStartTime,
-              modelTime: firstResponseTime,
-              toolsTime: 0,
-              firstResponseTime,
-              iterations: 1,
-              timeSegments: [
-                {
-                  type: 'model',
-                  name: 'Deep research (streaming)',
-                  startTime: providerStartTime,
-                  endTime: providerStartTime + firstResponseTime,
-                  duration: firstResponseTime,
-                },
-              ],
-            },
-            cost: {
-              input: 0,
-              output: 0,
-              total: 0,
-              pricing: { input: 0, output: 0, updatedAt: new Date().toISOString() },
-            },
-          },
-          logs: [],
-          metadata: {
-            startTime: providerStartTimeISO,
-            endTime: new Date().toISOString(),
-            duration: Date.now() - providerStartTime,
-          },
-          isStreaming: true,
-        },
-      }
-
-      streamingResult.stream = createDeepResearchStream(
-        streamResponse,
-        (content, usage, streamInteractionId) => {
-          streamingResult.execution.output.content = content
-          streamingResult.execution.output.tokens = {
-            input: usage.inputTokens,
-            output: usage.outputTokens,
-            total: usage.totalTokens,
-          }
-          streamingResult.execution.output.interactionId = streamInteractionId
-
-          const cost = calculateCost(model, usage.inputTokens, usage.outputTokens)
-          streamingResult.execution.output.cost = cost
-
-          const streamEndTime = Date.now()
-          if (streamingResult.execution.output.providerTiming) {
-            streamingResult.execution.output.providerTiming.endTime = new Date(
-              streamEndTime
-            ).toISOString()
-            streamingResult.execution.output.providerTiming.duration =
-              streamEndTime - providerStartTime
-            const segments = streamingResult.execution.output.providerTiming.timeSegments
-            if (segments?.[0]) {
-              segments[0].endTime = streamEndTime
-              segments[0].duration = streamEndTime - providerStartTime
-            }
-          }
-        }
-      )
-
-      return streamingResult
-    }
-
-    // Non-streaming mode: create and poll
-    const createParams: Interactions.CreateAgentInteractionParamsNonStreaming = {
-      ...baseParams,
-      stream: false,
-    }
-
-    const interaction = await ai.interactions.create(createParams)
-    const interactionId = interaction.id
-
-    logger.info('Deep research interaction created', { interactionId, status: interaction.status })
-
-    // Poll until a terminal status
-    const pollStartTime = Date.now()
-    let result: Interactions.Interaction = interaction
-
-    while (Date.now() - pollStartTime < DEEP_RESEARCH_MAX_DURATION_MS) {
-      if (result.status === 'completed') {
-        break
-      }
-
-      if (result.status === 'failed') {
-        throw new Error(`Deep research interaction failed: ${interactionId}`)
-      }
-
-      if (result.status === 'cancelled') {
-        throw new Error(`Deep research interaction was cancelled: ${interactionId}`)
-      }
-
-      logger.info('Deep research in progress, polling...', {
-        interactionId,
-        status: result.status,
-        elapsedMs: Date.now() - pollStartTime,
-      })
-
-      await sleep(DEEP_RESEARCH_POLL_INTERVAL_MS)
-      result = await ai.interactions.get(interactionId)
-    }
-
-    if (result.status !== 'completed') {
-      throw new Error(
-        `Deep research timed out after ${DEEP_RESEARCH_MAX_DURATION_MS / 1000}s (status: ${result.status})`
-      )
-    }
-
-    const content = extractTextFromInteractionOutputs(result.outputs)
-    const usage = extractInteractionUsage(result.usage)
-
-    logger.info('Deep research completed', {
-      interactionId,
-      contentLength: content.length,
-      inputTokens: usage.inputTokens,
-      outputTokens: usage.outputTokens,
-      reasoningTokens: usage.reasoningTokens,
-      totalTokens: usage.totalTokens,
-      durationMs: Date.now() - providerStartTime,
-    })
-
-    return buildDeepResearchResponse(
-      content,
-      model,
-      usage,
-      providerStartTime,
-      providerStartTimeISO,
-      interactionId
-    )
-  } catch (error) {
-    const providerEndTime = Date.now()
-    const duration = providerEndTime - providerStartTime
-
-    logger.error('Error in deep research request:', {
-      error: error instanceof Error ? error.message : String(error),
-      stack: error instanceof Error ? error.stack : undefined,
-    })
-
-    const enhancedError = error instanceof Error ? error : new Error(String(error))
-    Object.assign(enhancedError, {
-      timing: {
-        startTime: providerStartTimeISO,
-        endTime: new Date(providerEndTime).toISOString(),
-        duration,
-      },
-    })
-    throw enhancedError
-  }
-}
-
 /**
 * Executes a request using the Gemini API
 *
@@ -855,12 +391,6 @@ export async function executeGeminiRequest(
  config: GeminiExecutionConfig
 ): Promise<ProviderResponse | StreamingExecution> {
  const { ai, model, request, providerType } = config
-
-  // Route deep research models to the interactions API
-  if (isDeepResearchModel(model)) {
-    return executeDeepResearchRequest(config)
-  }
-
  const logger = createLogger(providerType === 'google' ? 'GoogleProvider' : 'VertexProvider')

  logger.info(`Preparing ${providerType} Gemini request`, {
--- a/apps/sim/providers/models.ts
+++ b/apps/sim/providers/models.ts
@@ -46,9 +46,6 @@ export interface ModelCapabilities {
    levels: string[]
    default?: string
  }
-  deepResearch?: boolean
-  /** Whether this model supports conversation memory. Defaults to true if omitted. */
-  memory?: boolean
 }

 export interface ModelDefinition {
@@ -828,7 +825,7 @@ export const PROVIDER_DEFINITIONS: Record<string, ProviderDefinition> = {
    name: 'Google',
    description: "Google's Gemini models",
    defaultModel: 'gemini-2.5-pro',
-    modelPatterns: [/^gemini/, /^deep-research/],
+    modelPatterns: [/^gemini/],
    capabilities: {
      toolUsageControl: true,
    },
@@ -931,19 +928,6 @@ export const PROVIDER_DEFINITIONS: Record<string, ProviderDefinition> = {
        },
        contextWindow: 1000000,
      },
-      {
-        id: 'deep-research-pro-preview-12-2025',
-        pricing: {
-          input: 2.0,
-          output: 2.0,
-          updatedAt: '2026-02-10',
-        },
-        capabilities: {
-          deepResearch: true,
-          memory: false,
-        },
-        contextWindow: 1000000,
-      },
    ],
  },
  vertex: {
@@ -1054,19 +1038,6 @@ export const PROVIDER_DEFINITIONS: Record<string, ProviderDefinition> = {
        },
        contextWindow: 1000000,
      },
-      {
-        id: 'vertex/deep-research-pro-preview-12-2025',
-        pricing: {
-          input: 2.0,
-          output: 2.0,
-          updatedAt: '2026-02-10',
-        },
-        capabilities: {
-          deepResearch: true,
-          memory: false,
-        },
-        contextWindow: 1000000,
-      },
    ],
  },
  deepseek: {
@@ -2509,37 +2480,6 @@ export function getThinkingLevelsForModel(modelId: string): string[] | null {
  return capability?.levels ?? null
 }

-/**
- * Get all models that support deep research capability
- */
-export function getModelsWithDeepResearch(): string[] {
-  const models: string[] = []
-  for (const provider of Object.values(PROVIDER_DEFINITIONS)) {
-    for (const model of provider.models) {
-      if (model.capabilities.deepResearch) {
-        models.push(model.id)
-      }
-    }
-  }
-  return models
-}
-
-/**
- * Get all models that explicitly disable memory support (memory: false).
- * Models without this capability default to supporting memory.
- */
-export function getModelsWithoutMemory(): string[] {
-  const models: string[] = []
-  for (const provider of Object.values(PROVIDER_DEFINITIONS)) {
-    for (const model of provider.models) {
-      if (model.capabilities.memory === false) {
-        models.push(model.id)
-      }
-    }
-  }
-  return models
-}
-
 /**
 * Get the max output tokens for a specific model.
 *
--- a/apps/sim/providers/types.ts
+++ b/apps/sim/providers/types.ts
@@ -95,8 +95,6 @@ export interface ProviderResponse {
    total: number
    pricing: ModelPricing
  }
-  /** Interaction ID returned by the Interactions API (used for multi-turn deep research) */
-  interactionId?: string
 }

 export type ToolUsageControl = 'auto' | 'force' | 'none'
@@ -171,8 +169,6 @@ export interface ProviderRequest {
  verbosity?: string
  thinkingLevel?: string
  isDeployedContext?: boolean
-  /** Previous interaction ID for multi-turn Interactions API requests (deep research follow-ups) */
-  previousInteractionId?: string
 }

 export const providers: Record<string, ProviderConfig> = {}
--- a/apps/sim/providers/utils.ts
+++ b/apps/sim/providers/utils.ts
@@ -12,8 +12,6 @@ import {
  getMaxOutputTokensForModel as getMaxOutputTokensForModelFromDefinitions,
  getMaxTemperature as getMaxTempFromDefinitions,
  getModelPricing as getModelPricingFromDefinitions,
-  getModelsWithDeepResearch,
-  getModelsWithoutMemory,
  getModelsWithReasoningEffort,
  getModelsWithTemperatureSupport,
  getModelsWithTempRange01,
@@ -955,8 +953,6 @@ export const MODELS_WITH_TEMPERATURE_SUPPORT = getModelsWithTemperatureSupport()
 export const MODELS_WITH_REASONING_EFFORT = getModelsWithReasoningEffort()
 export const MODELS_WITH_VERBOSITY = getModelsWithVerbosity()
 export const MODELS_WITH_THINKING = getModelsWithThinking()
-export const MODELS_WITH_DEEP_RESEARCH = getModelsWithDeepResearch()
-export const MODELS_WITHOUT_MEMORY = getModelsWithoutMemory()
 export const PROVIDERS_WITH_TOOL_USAGE_CONTROL = getProvidersWithToolUsageControl()

 export function supportsTemperature(model: string): boolean {
@@ -975,10 +971,6 @@ export function supportsThinking(model: string): boolean {
  return MODELS_WITH_THINKING.includes(model.toLowerCase())
 }

-export function isDeepResearchModel(model: string): boolean {
-  return MODELS_WITH_DEEP_RESEARCH.includes(model.toLowerCase())
-}
-
 /**
 * Get the maximum temperature value for a model
 * @returns Maximum temperature value (1 or 2) or undefined if temperature not supported
--- a/apps/sim/public/studio/enterprise/cover.png
+++ b/apps/sim/public/studio/enterprise/cover.png
--- a/apps/sim/public/studio/enterprise/self-hosted.png
+++ b/apps/sim/public/studio/enterprise/self-hosted.png