[Workflows] Fix docs using code review

src/content/docs/workflows/get-started/durable-agents.mdx

@@ -261,7 +261,7 @@
 				{ retries: { limit: 3, delay: "10 seconds", backoff: "exponential" } },
 				async () => {
 					const msg = await client.messages.create({
 						model: "claude-sonnet-4-5-20250929",
 						max_tokens: 4096,
 						tools: toolDefinitions,
 						messages,
@@ -342,7 +342,7 @@
 This is especially important for:
 
 - **LLM calls**: Expensive and slow, should not repeat unnecessarily
 - **External APIs**: May have rate limits or side effects
 - **Idempotency**: Some tools (like sending emails) should not run twice
 
 </Details>
@@ -611,6 +611,7 @@
 ```
 
 ```tsx
+import { useState } from "react";
 import { useAgent } from "agents/react";
 
 function ResearchUI({ agentId = "default" }) {

src/content/docs/workflows/python/bindings.mdx

@@ -26,20 +26,17 @@ From the configuration perspective, enabling Python Workflows requires adding th
 {
 	"$schema": "./node_modules/wrangler/config-schema.json",
 	"name": "workflows-starter",
-	"main": "src/index.ts",
+	"main": "src/index.py",
 	"compatibility_date": "$today",
-	"compatibility_flags": [
-		"python_workflows",
-		"python_workers"
-	],
+	"compatibility_flags": ["python_workflows", "python_workers"],
 	"workflows": [
 		{
 			// name of your workflow
 			"name": "workflows-starter",
 			// binding name env.MY_WORKFLOW
 			"binding": "MY_WORKFLOW",
-			// this is class that extends the Workflow class in src/index.ts
-			"class_name": "MyWorkflow"
+			// this is class that extends the Workflow class in src/index.py
+			"class_name": "MyWorkflow",
 		}
 	]
 }
@@ -50,7 +47,7 @@ From the configuration perspective, enabling Python Workflows requires adding th
 And this is how you use the payload in your workflow:
 
 ```python
-from pyodide.ffi import to_js
+from workers import WorkflowEntrypoint
 
 class DemoWorkflowClass(WorkflowEntrypoint):
     async def run(self, event, step):
@@ -110,15 +107,18 @@ Each element of the `batch` list is expected to include both `id` and `params` p
 ```python
 from pyodide.ffi import to_js
 from js import Object
+from workers import WorkerEntrypoint, Response
 
-# Create a new batch of 3 Workflow instances, each with its own ID and pass params to the Workflow instances
-listOfInstances = [
-  to_js({ "id": "id-abc123", "params": { "hello": "world-0" } }, dict_converter=Object.fromEntries),
-  to_js({ "id": "id-def456", "params": { "hello": "world-1" } }, dict_converter=Object.fromEntries),
-  to_js({ "id": "id-ghi789", "params": { "hello": "world-2" } }, dict_converter=Object.fromEntries)
-];
-
-await env.MY_WORKFLOW.create_batch(listOfInstances);
+class Default(WorkerEntrypoint):
+    async def fetch(self, request):
+        # Create a new batch of 3 Workflow instances, each with its own ID and pass params to the Workflow instances
+        listOfInstances = [
+            to_js({ "id": "id-abc123", "params": { "hello": "world-0" } }, dict_converter=Object.fromEntries),
+            to_js({ "id": "id-def456", "params": { "hello": "world-1" } }, dict_converter=Object.fromEntries),
+            to_js({ "id": "id-ghi789", "params": { "hello": "world-2" } }, dict_converter=Object.fromEntries)
+        ]
+        await self.env.MY_WORKFLOW.create_batch(listOfInstances)
+        return Response.json({"status": "success"})
 ```
 
 ### `get`
@@ -130,14 +130,19 @@ Get a workflow instance by ID.
 Returns a [`WorkflowInstance`](/workflows/build/workers-api/#workflowinstance) object, which can be used to query the status of the workflow instance.
 
 ```python
-instance = await env.MY_WORKFLOW.get("abc-123")
-
-# FFI methods available for WorkflowInstance
-await instance.status()
-await instance.pause()
-await instance.resume()
-await instance.restart()
-await instance.terminate()
+from workers import WorkerEntrypoint, Response
+
+class Default(WorkerEntrypoint):
+    async def fetch(self, request):
+        instance = await self.env.MY_WORKFLOW.get("abc-123")
+
+        # FFI methods available for WorkflowInstance
+        await instance.status()
+        await instance.pause()
+        await instance.resume()
+        await instance.restart()
+        await instance.terminate()
+        return Response.json({"status": "success"})
 ```
 
 ### `send_event`
@@ -150,8 +155,12 @@ Send an event to a workflow instance.
 ```python
 from pyodide.ffi import to_js
 from js import Object
+from workers import WorkerEntrypoint, Response
 
-await env.MY_WORKFLOW.send_event(to_js({ "type": "my-event-type", "payload": { "foo": "bar" } }, dict_converter=Object.fromEntries))
+class Default(WorkerEntrypoint):
+    async def fetch(self, request):
+        await self.env.MY_WORKFLOW.send_event(to_js({ "type": "my-event-type", "payload": { "foo": "bar" } }, dict_converter=Object.fromEntries))
+        return Response.json({"status": "success"})
 ```
 
 :::note

src/content/docs/workflows/python/dag.mdx

@@ -3,7 +3,6 @@ title: DAG Workflows
 pcx_content_type: concept
 sidebar:
   order: 4
-
 ---
 
 The Python Workflows SDK supports DAG workflows in a declarative way, using the `step.do` decorator with the `depends` parameter to define dependencies (other steps that must complete before this step can run).
@@ -19,7 +18,7 @@ class PythonWorkflowStarter(WorkflowEntrypoint):
             except TypeError as e:
                 print(f"Successfully caught {type(e).__name__}: {e}")
 
-        step.sleep('demo sleep', '10 seconds')
+        await step.sleep('demo sleep', '10 seconds')
 
         @step.do('dependency1')
         async def dep_1():
@@ -47,4 +46,4 @@ On this example, `dep_1` and `dep_2` are run concurrently before execution of `f
 
 Having `concurrent=True` allows the dependencies to be resolved concurrently. If one of the callables passed to `depends` has already completed, it will be skipped and its return value will be reused.
 
-This pattern is useful for diamond shaped workflows, where a step depends on two or more other steps that can run concurrently.
+This pattern is useful for diamond shaped workflows, where a step depends on two or more other steps that can run concurrently.

src/content/docs/workflows/python/index.mdx

@@ -46,7 +46,8 @@ class PythonWorkflowStarter(WorkflowEntrypoint):
             # does stuff
             print('executing step2')
 
-        await await_step(step_1,step_2)
+        await step_1()
+        await step_2()
 
 async def on_fetch(request, env):
     await env.MY_WORKFLOW.create()

src/content/docs/workflows/python/python-workers-api.mdx

@@ -3,7 +3,6 @@ title: Python Workers API
 pcx_content_type: concept
 sidebar:
   order: 2
-
 ---
 
 This guide covers the Python Workflows SDK, with instructions on how to build and create workflows using Python.
@@ -16,7 +15,7 @@ The `WorkflowEntrypoint` is the main entrypoint for a Python workflow. It extend
 from workers import WorkflowEntrypoint
 
 class MyWorkflow(WorkflowEntrypoint):
-    def run(self, event, step):
+    async def run(self, event, step):
         # steps here
 ```
 
@@ -62,6 +61,8 @@ async def run(self, event, step):
   * `timestamp` - a `datetime.datetime` object or seconds from the Unix epoch to sleep the workflow instance until.
 
 ```python
+import datetime
+
 async def run(self, event, step):
     await step.sleep_until("my-sleep-step", datetime.datetime.now() + datetime.timedelta(seconds=10))
 ```
@@ -77,7 +78,6 @@ async def run(self, event, step):
     await step.wait_for_event("my-wait-for-event-step", "my-event-type")
 ```
 
-
 ### `event` parameter
 
 The `event` parameter is a dictionary that contains the payload passed to the workflow instance, along with other metadata:
@@ -131,6 +131,8 @@ You can bind a step to a specific retry policy by passing a `WorkflowStepConfig`
 With Python Workflows, you need to make sure that your `dict` respects the [`WorkflowStepConfig`](/workflows/build/workers-api/#workflowstepconfig) type.
 
 ```python
+from workers import WorkflowEntrypoint
+
 class DemoWorkflowClass(WorkflowEntrypoint):
     async def run(self, event, step):
         @step.do('step-name', config={"retries": {"limit": 1, "delay": "10 seconds"}})
@@ -146,6 +148,8 @@ Note that `env` is a JavaScript object exposed to the Python script via [JsProxy
 Let's consider the previous binding called `MY_WORKFLOW`. Here's how you would create a new instance:
 
 ```python
+from workers import Response, WorkerEntrypoint
+
 class Default(WorkerEntrypoint):
     async def fetch(self, request):
         instance = await self.env.MY_WORKFLOW.create()

src/content/docs/workflows/reference/limits.mdx

@@ -74,7 +74,7 @@ type Env = {
 
 export class MyWorkflow extends WorkflowEntrypoint<Env> {
 	async run(event: WorkflowEvent<unknown>, step: WorkflowStep) {
-		const apiResponse = await step.do("initial work", async () => {
+		await step.do("initial work", async () => {
 			let resp = await fetch("https://api.cloudflare.com/client/v4/ips");
 			return await resp.json<any>();
 		});
@@ -86,7 +86,7 @@ export class MyWorkflow extends WorkflowEntrypoint<Env> {
 			{
 				retries: {
 					limit: 5,
-					delay: "5 second",
+					delay: "5 seconds",
 					backoff: "exponential",
 				},
 				timeout: "15 minutes",