AI-310: address streaming sample review comments

Move streaming config onto the client plugin, where its modelParams
propagate into the Workflow via the config header; drop the inert
worker-plugin modelParams. Remove the client's OPENAI_API_KEY
requirement since the client never calls the model, and correct the
README accordingly. Make the fake model emit incremental per-word
deltas so the sample and test genuinely demonstrate streaming.

Author: xumaple

openai-agents/src/streaming/README.md

@@ -8,15 +8,19 @@ topic, and an external client subscribes to that topic to print the deltas live.
 
 The Workflow (`src/streaming/workflows.ts`) constructs `new WorkflowStream()` at the top, then
 iterates the `StreamedRunResult` to drive the run to completion and returns the final text. The
-Worker configures `modelParams.streamingTopic` (and a `streamingBatchInterval`) on the
-`OpenAIAgentsPlugin` so the streaming Activity knows which topic to publish to. The client
-(`src/streaming/client.ts`) subscribes from outside the Workflow with
+client (`src/streaming/client.ts`) configures `modelParams.streamingTopic` and `streamingBatchInterval`
+on its `OpenAIAgentsPlugin`, and the client interceptor injects them into the Workflow via the config
+header so the streaming Activity knows which topic to publish to. The client also subscribes from
+outside the Workflow with
 `WorkflowStreamClient.create(client, workflowId).topic(streamingTopic).subscribe()`.
 
 ## Run
 
 Run these from the `openai-agents/` root (run `npm install` there once first).
 
+Only the Worker needs `OPENAI_API_KEY`, because the model runs in the Worker's Activity. The client
+never calls the model, so it starts without a key.
+
 ```bash
 # In one terminal, start the Worker (requires a local Temporal server and OPENAI_API_KEY):
 OPENAI_API_KEY=sk-... npx ts-node src/streaming/worker.ts

openai-agents/src/streaming/client.ts

@@ -11,18 +11,14 @@ interface ModelStreamEvent {
 }
 
 async function run() {
-  const apiKey = process.env.OPENAI_API_KEY;
-  if (!apiKey) {
-    throw new Error('OPENAI_API_KEY environment variable is required');
-  }
-
   const connection = await Connection.connect();
   const client = new Client({
     connection,
     plugins: [
       new OpenAIAgentsPlugin({
-        modelProvider: new OpenAIProvider({ apiKey }),
-        modelParams: { streamingTopic },
+        // The client never calls the model (it runs in the Worker's Activity); this only satisfies the plugin's required modelProvider field.
+        modelProvider: new OpenAIProvider({}),
+        modelParams: { streamingTopic, streamingBatchInterval: '200 milliseconds' },
       }),
     ],
   });

openai-agents/src/streaming/mocha/fake-model.ts

@@ -17,8 +17,9 @@ export function streamingTextEvents(text: string): StreamEvent[] {
       status: 'completed',
     },
   ];
+  const chunks = text.match(/\s*\S+\s*/g) ?? [text];
   return [
-    { type: 'output_text_delta', delta: text },
+    ...chunks.map((delta) => ({ type: 'output_text_delta', delta })),
     {
       type: 'response_done',
       response: {

openai-agents/src/streaming/mocha/workflows.test.ts

@@ -37,7 +37,6 @@ describe('openai-agents/streaming workflow scenarios', function () {
       plugins: [
         new OpenAIAgentsPlugin({
           modelProvider: new StreamingFakeModelProvider(events),
-          modelParams: { streamingTopic, streamingBatchInterval: '50 milliseconds' },
         }),
       ],
       bundlerOptions: {
@@ -57,7 +56,7 @@ describe('openai-agents/streaming workflow scenarios', function () {
       plugins: [
         new OpenAIAgentsPlugin({
           modelProvider: new StreamingFakeModelProvider(events),
-          modelParams: { streamingTopic },
+          modelParams: { streamingTopic, streamingBatchInterval: '50 milliseconds' },
         }),
       ],
     });
@@ -91,7 +90,11 @@ describe('openai-agents/streaming workflow scenarios', function () {
         received.map((e) => e.type),
         events.map((e) => e.type),
       );
-      assert.strictEqual(received[0]!.delta, 'Hello streamed world');
+      const streamedText = received
+        .filter((e) => e.type === 'output_text_delta')
+        .map((e) => e.delta)
+        .join('');
+      assert.strictEqual(streamedText, 'Hello streamed world');
       return finalOutput;
     });
 

openai-agents/src/streaming/worker.ts

@@ -1,7 +1,6 @@
 import { NativeConnection, Worker } from '@temporalio/worker';
 import { OpenAIAgentsPlugin } from '@temporalio/openai-agents';
 import { OpenAIProvider } from '@openai/agents-openai';
-import { streamingTopic } from './workflows';
 
 async function run() {
   const apiKey = process.env.OPENAI_API_KEY;
@@ -18,7 +17,6 @@ async function run() {
       plugins: [
         new OpenAIAgentsPlugin({
           modelProvider: new OpenAIProvider({ apiKey }),
-          modelParams: { streamingTopic, streamingBatchInterval: '200 milliseconds' },
         }),
       ],
       bundlerOptions: {