fix(misc): remove duplicate docs page, update clopus 4.7 (#4200)

* fix(misc): remove duplicate docs page, update clopus 4.7

* fix(docs): consolidate duplicate docs and fix SDK API signatures

- Remove duplicate custom-tools page (custom-tools/index.mdx → tools/custom-tools.mdx is canonical)
- Remove comparison table from custom-tools per product preference
- Fix permissions inconsistency: delete now requires Admin across all docs
- Consolidate sdks/ into api-reference/ (sdks/ directory deleted)
- Fix Python SDK docs: correct param is `input`, not `input_data`
- Fix TypeScript SDK docs: correct signature is executeWorkflow(id, input, options) not options-object form
- Add FAQ sections to both SDK reference pages

* fix(docs): update SDKs card links from /sdks to /api-reference

* fix(docs): update /sdks references to /api-reference in llms.txt files

Author: waleedlatif1

apps/docs/app/llms.txt/route.ts

@@ -62,7 +62,7 @@ ${Object.entries(sections)
 
 - Full documentation content: ${baseUrl}/llms-full.txt
 - Individual page content: ${baseUrl}/llms.mdx/[page-path]
-- API documentation: ${baseUrl}/sdks/
+- API documentation: ${baseUrl}/api-reference/
 - Tool integrations: ${baseUrl}/tools/
 
 ## Statistics

apps/docs/content/docs/de/index.mdx

@@ -51,7 +51,7 @@ Willkommen bei Sim, einem visuellen Workflow-Builder für KI-Anwendungen. Erstel
   <Card title="MCP-Integration" href="/mcp">
     Externe Dienste mit dem Model Context Protocol verbinden
   </Card>
-  <Card title="SDKs" href="/sdks">
+  <Card title="SDKs" href="/api-reference">
     Sim in Ihre Anwendungen integrieren
   </Card>
 </Cards>

apps/docs/content/docs/en/api-reference/python.mdx

@@ -65,14 +65,14 @@ Execute a workflow with optional input data.
 ```python
 result = client.execute_workflow(
     "workflow-id",
-    input_data={"message": "Hello, world!"},
+    input={"message": "Hello, world!"},
     timeout=30.0  # 30 seconds
 )
 ```
 
 **Parameters:**
 - `workflow_id` (str): The ID of the workflow to execute
-- `input_data` (dict, optional): Input data to pass to the workflow
+- `input` (dict, optional): Input data to pass to the workflow
 - `timeout` (float, optional): Timeout in seconds (default: 30.0)
 - `stream` (bool, optional): Enable streaming responses (default: False)
 - `selected_outputs` (list[str], optional): Block outputs to stream in `blockName.attribute` format (e.g., `["agent1.content"]`)
@@ -144,7 +144,7 @@ Execute a workflow with automatic retry on rate limit errors using exponential b
 ```python
 result = client.execute_with_retry(
     "workflow-id",
-    input_data={"message": "Hello"},
+    input={"message": "Hello"},
     timeout=30.0,
     max_retries=3,           # Maximum number of retries
     initial_delay=1.0,       # Initial delay in seconds
@@ -155,7 +155,7 @@ result = client.execute_with_retry(
 
 **Parameters:**
 - `workflow_id` (str): The ID of the workflow to execute
-- `input_data` (dict, optional): Input data to pass to the workflow
+- `input` (dict, optional): Input data to pass to the workflow
 - `timeout` (float, optional): Timeout in seconds
 - `stream` (bool, optional): Enable streaming responses
 - `selected_outputs` (list, optional): Block outputs to stream
@@ -359,7 +359,7 @@ def run_workflow():
         # Execute the workflow
         result = client.execute_workflow(
             "my-workflow-id",
-            input_data={
+            input={
                 "message": "Process this data",
                 "user_id": "12345"
             }
@@ -488,7 +488,7 @@ def execute_async():
         # Start async execution
         result = client.execute_workflow(
             "workflow-id",
-            input_data={"data": "large dataset"},
+            input={"data": "large dataset"},
             async_execution=True  # Execute asynchronously
         )
 
@@ -533,7 +533,7 @@ def execute_with_retry_handling():
         # Automatically retries on rate limit
         result = client.execute_with_retry(
             "workflow-id",
-            input_data={"message": "Process this"},
+            input={"message": "Process this"},
             max_retries=5,
             initial_delay=1.0,
             max_delay=60.0,
@@ -615,7 +615,7 @@ def execute_with_streaming():
         # Enable streaming for specific block outputs
         result = client.execute_workflow(
             "workflow-id",
-            input_data={"message": "Count to five"},
+            input={"message": "Count to five"},
             stream=True,
             selected_outputs=["agent1.content"]  # Use blockName.attribute format
         )
@@ -758,4 +758,15 @@ Configure the client using environment variables:
 
 ## License
 
-Apache-2.0 
+Apache-2.0
+
+import { FAQ } from '@/components/ui/faq'
+
+<FAQ items={[
+  { question: "Do I need to deploy a workflow before I can execute it via the SDK?", answer: "Yes. Workflows must be deployed before they can be executed through the SDK. You can use the validate_workflow() method to check whether a workflow is deployed and ready. If it returns False, deploy the workflow from the Sim UI first and create or select an API key during deployment." },
+  { question: "What is the difference between sync and async execution?", answer: "Sync execution (the default) blocks until the workflow completes and returns the full result. Async execution (async_execution=True) returns immediately with a task ID that you can poll using get_job_status(). Use async mode for long-running workflows to avoid request timeouts. Async job statuses include queued, processing, completed, failed, and cancelled." },
+  { question: "How does the SDK handle rate limiting?", answer: "The SDK provides built-in rate limiting support through the execute_with_retry() method. It uses exponential backoff (1s, 2s, 4s, 8s...) with 25% jitter to avoid thundering herd problems. If the API returns a retry-after header, that value is used instead. You can configure max_retries, initial_delay, max_delay, and backoff_multiplier. Use get_rate_limit_info() to check your current rate limit status." },
+  { question: "Can I use the Python SDK as a context manager?", answer: "Yes. The SimStudioClient supports Python's context manager protocol. Use it with the 'with' statement to automatically close the underlying HTTP session when you are done, which is especially useful for scripts that create and discard client instances." },
+  { question: "How do I handle different types of errors from the SDK?", answer: "The SDK raises SimStudioError with a code property for API-specific errors. Common error codes are UNAUTHORIZED (invalid API key), TIMEOUT (request timed out), RATE_LIMIT_EXCEEDED (too many requests), USAGE_LIMIT_EXCEEDED (billing limit reached), and EXECUTION_ERROR (workflow failed). Use the error code to implement targeted error handling and recovery logic." },
+  { question: "How do I monitor my API usage and remaining quota?", answer: "Use the get_usage_limits() method to check your current usage. It returns sync and async rate limit details (limit, remaining, reset time, whether you are currently limited), plus your current period cost, usage limit, and plan tier. This lets you monitor consumption and alert before hitting limits." },
+]} />

apps/docs/content/docs/en/api-reference/typescript.mdx

@@ -78,16 +78,15 @@ new SimStudioClient(config: SimStudioConfig)
 Execute a workflow with optional input data.
 
 ```typescript
-const result = await client.executeWorkflow('workflow-id', {
-  input: { message: 'Hello, world!' },
+const result = await client.executeWorkflow('workflow-id', { message: 'Hello, world!' }, {
   timeout: 30000 // 30 seconds
 });
 ```
 
 **Parameters:**
 - `workflowId` (string): The ID of the workflow to execute
+- `input` (any, optional): Input data to pass to the workflow
 - `options` (ExecutionOptions, optional):
-  - `input` (any): Input data to pass to the workflow
   - `timeout` (number): Timeout in milliseconds (default: 30000)
   - `stream` (boolean): Enable streaming responses (default: false)
   - `selectedOutputs` (string[]): Block outputs to stream in `blockName.attribute` format (e.g., `["agent1.content"]`)
@@ -158,8 +157,7 @@ if (status.status === 'completed') {
 Execute a workflow with automatic retry on rate limit errors using exponential backoff.
 
 ```typescript
-const result = await client.executeWithRetry('workflow-id', {
-  input: { message: 'Hello' },
+const result = await client.executeWithRetry('workflow-id', { message: 'Hello' }, {
   timeout: 30000
 }, {
   maxRetries: 3,           // Maximum number of retries
@@ -171,6 +169,7 @@ const result = await client.executeWithRetry('workflow-id', {
 
 **Parameters:**
 - `workflowId` (string): The ID of the workflow to execute
+- `input` (any, optional): Input data to pass to the workflow
 - `options` (ExecutionOptions, optional): Same as `executeWorkflow()`
 - `retryOptions` (RetryOptions, optional):
   - `maxRetries` (number): Maximum number of retries (default: 3)
@@ -389,10 +388,8 @@ async function runWorkflow() {
 
     // Execute the workflow
     const result = await client.executeWorkflow('my-workflow-id', {
-      input: {
         message: 'Process this data',
         userId: '12345'
-      }
     });
 
     if (result.success) {
@@ -508,8 +505,7 @@ app.post('/execute-workflow', async (req, res) => {
   try {
     const { workflowId, input } = req.body;
 
-    const result = await client.executeWorkflow(workflowId, {
-      input,
+    const result = await client.executeWorkflow(workflowId, input, {
       timeout: 60000
     });
 
@@ -555,8 +551,7 @@ export default async function handler(
   try {
     const { workflowId, input } = req.body;
 
-    const result = await client.executeWorkflow(workflowId, {
-      input,
+    const result = await client.executeWorkflow(workflowId, input, {
       timeout: 30000
     });
 
@@ -586,9 +581,7 @@ const client = new SimStudioClient({
 async function executeClientSideWorkflow() {
   try {
     const result = await client.executeWorkflow('workflow-id', {
-      input: {
         userInput: 'Hello from browser'
-      }
     });
 
     console.log('Workflow result:', result);
@@ -642,10 +635,8 @@ Alternatively, you can manually provide files using the URL format:
 
       // Include files under the field name from your API trigger's input format
       const result = await client.executeWorkflow('workflow-id', {
-        input: {
           documents: files,  // Must match your workflow's "files" field name
           instructions: 'Analyze these documents'
-        }
       });
 
       console.log('Result:', result);
@@ -669,10 +660,8 @@ Alternatively, you can manually provide files using the URL format:
 
     // Include files under the field name from your API trigger's input format
     const result = await client.executeWorkflow('workflow-id', {
-      input: {
         documents: [file],  // Must match your workflow's "files" field name
         query: 'Summarize this document'
-      }
     });
     ```
   </Tab>
@@ -712,8 +701,7 @@ export function useWorkflow(): UseWorkflowResult {
     setResult(null);
 
     try {
-      const workflowResult = await client.executeWorkflow(workflowId, {
-        input,
+      const workflowResult = await client.executeWorkflow(workflowId, input, {
         timeout: 30000
       });
       setResult(workflowResult);
@@ -774,8 +762,7 @@ const client = new SimStudioClient({
 async function executeAsync() {
   try {
     // Start async execution
-    const result = await client.executeWorkflow('workflow-id', {
-      input: { data: 'large dataset' },
+    const result = await client.executeWorkflow('workflow-id', { data: 'large dataset' }, {
       async: true  // Execute asynchronously
     });
 
@@ -823,9 +810,7 @@ const client = new SimStudioClient({
 async function executeWithRetryHandling() {
   try {
     // Automatically retries on rate limit
-    const result = await client.executeWithRetry('workflow-id', {
-      input: { message: 'Process this' }
-    }, {
+    const result = await client.executeWithRetry('workflow-id', { message: 'Process this' }, {}, {
       maxRetries: 5,
       initialDelay: 1000,
       maxDelay: 60000,
@@ -908,8 +893,7 @@ const client = new SimStudioClient({
 async function executeWithStreaming() {
   try {
     // Enable streaming for specific block outputs
-    const result = await client.executeWorkflow('workflow-id', {
-      input: { message: 'Count to five' },
+    const result = await client.executeWorkflow('workflow-id', { message: 'Count to five' }, {
       stream: true,
       selectedOutputs: ['agent1.content'] // Use blockName.attribute format
     });
@@ -1033,3 +1017,14 @@ function StreamingWorkflow() {
 ## License
 
 Apache-2.0
+
+import { FAQ } from '@/components/ui/faq'
+
+<FAQ items={[
+  { question: "Do I need to deploy a workflow before I can execute it via the SDK?", answer: "Yes. Workflows must be deployed before they can be executed through the SDK. You can use the validateWorkflow() method to check whether a workflow is deployed and ready. If it returns false, deploy the workflow from the Sim UI first and create or select an API key during deployment." },
+  { question: "What is the difference between sync and async execution?", answer: "Sync execution (the default) blocks until the workflow completes and returns the full result. Async execution returns immediately with a task ID that you can poll using getJobStatus(). Use async mode for long-running workflows to avoid request timeouts. Async job statuses include queued, processing, completed, failed, and cancelled." },
+  { question: "How does streaming work with the SDK?", answer: "Enable streaming by setting stream: true and specifying selectedOutputs with block names and attributes in blockName.attribute format (e.g., ['agent1.content']). The response uses Server-Sent Events (SSE) format, sending incremental chunks as the workflow executes. Each chunk includes the blockId and the text content. A final done event includes the execution metadata." },
+  { question: "How does the SDK handle rate limiting?", answer: "The SDK provides built-in rate limiting support through the executeWithRetry() method. It uses exponential backoff (1s, 2s, 4s, 8s...) with 25% jitter to avoid thundering herd problems. If the API returns a retry-after header, that value is used instead. You can configure maxRetries, initialDelay, maxDelay, and backoffMultiplier. Use getRateLimitInfo() to check your current rate limit status." },
+  { question: "Is it safe to use the SDK in browser-side code?", answer: "You can use the SDK in the browser, but you should not expose your API key in client-side code. In production, use a backend proxy server to handle SDK calls, or use a public API key with limited permissions. The SDK works with both Node.js and browser environments, but sensitive keys should stay server-side." },
+  { question: "How do I send files to a workflow through the SDK?", answer: "File objects are automatically detected and converted to base64 format. Include them in the input object under the field name that matches your workflow's API trigger input format. In the browser, pass File objects directly from file inputs. In Node.js, create File objects from buffers. You can also provide files as URL references with type, data, name, and mime fields." },
+]} />

apps/docs/content/docs/en/custom-tools/index.mdx

@@ -51,7 +51,7 @@ Welcome to Sim, the open-source AI workspace where teams build, deploy, and mana
   <Card title="MCP Integration" href="/mcp">
     Connect external services with Model Context Protocol
   </Card>
-  <Card title="SDKs" href="/sdks">
+  <Card title="SDKs" href="/api-reference">
     Integrate Sim into your applications
   </Card>
 </Cards>

apps/docs/content/docs/en/index.mdx

@@ -21,7 +21,6 @@
     "variables",
     "integrations",
     "credentials",
-    "custom-tools",
     "---Platform---",
     "execution",
     "permissions",