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👌 IMPROVE: pipe run for stream and non-stream (#21)
* 📦 NEW: Update pipe run for streaming * 📦 NEW: Update pipe.run for non-stream * 👌 IMPROVE: pipe run
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‎apps/baseai.dev/content/docs/add/quickstart.mdx

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@@ -128,17 +128,17 @@ Add the following code to `index.ts` file:
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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, streamText, getRunner} from '@baseai/core';
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import {Pipe, getRunner} from '@baseai/core';
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import aiTitleGeneratorPipe from './baseai/pipes/ai-title-generator';
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const pipe = new Pipe(aiTitleGeneratorPipe());
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const userMsg = `Generate 5 blog title ideas for an article about Large Language Models`;
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: true
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});
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const runner = getRunner(stream);

‎apps/baseai.dev/content/docs/api-reference/get-runner.mdx

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A stream is a continuous flow of data that can be consumed piece by piece. The `getRunner()` function is a utility function that converts a readable stream in a runner. This runner can be used to run the stream and consume the data.
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The `getRunner()` function can be used together with `pipe.run()` [function](/docs/api-reference/pipe-run) when the stream is `true` or with the `streamText()` [function](/docs/api-reference/stream-text) to consume the stream.
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The `getRunner()` function can be used together with `pipe.run()` [function](/docs/api-reference/pipe-run) when the stream is `true` to consume the stream.
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The BaseAI core package provides a `getRunner()` function that you can use in your app.
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@@ -123,6 +123,7 @@ The BaseAI core package provides a `getRunner()` function that you can use in yo
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```bash {{ title: 'Create a new Pipe' }}
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npx baseai@latest pipe
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# OR
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pnpm dlx baseai@latest pipe
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```
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OPENAI_API_KEY="<REPLACE-WITH-YOUR-OPENAI-KEY>"
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```
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### `getRunner()` example with `streamText()`
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### `getRunner()` example with `pipe.run()`
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<CodeGroup exampleTitle="streamText()" title="streamText()">
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<CodeGroup exampleTitle="pipe.run()" title="pipe.run()">
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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, streamText, getRunner} from '@baseai/core';
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import {Pipe, getRunner} from '@baseai/core';
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import pipeName from './baseai/pipes/agent';
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const pipe = new Pipe(pipeName());
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: 'Hello'}],
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stream: true
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});
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// NOTE: This is a Node.js only example.

‎apps/baseai.dev/content/docs/api-reference/pipe-run.mdx

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OPENAI_API_KEY="<REPLACE-WITH-YOUR-OPENAI-KEY>"
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```
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### `pipe.run()` generate example
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### `pipe.run()` non-stream example
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<CodeGroup exampleTitle="pipe.run()" title="pipe.run()">
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<Property name="choices" type="ChoiceGenerate[]">
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A list of chat completion choices. Can contain more than one elements if n is greater than 1.
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```ts {{title: 'Choice Object for generateText()'}}
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```ts {{title: 'Choice Object for pipe.run() with stream off'}}
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interface ChoiceGenerate {
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index: number;
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message: Message;
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### RunResponseStream Object
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Response of `streamText()` is a `Promise<RunResponseStream>`.
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Response of `pipe.run()` with `stream: true` is a `Promise<RunResponseStream>`.
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```ts {{title: 'RunResponseStream Object'}}
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interface RunResponseStream {
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The different headers of the response.
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</Property>
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<Property name="stream" type="ReadableStream">
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Stream is a StreamText object with a streamed sequence of StreamChunk objects.
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Stream is an object with a streamed sequence of StreamChunk objects.
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```ts {{title: 'StreamResponse Object'}}
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type StreamText = ReadableStream<StreamChunk>;
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type StreamResponse = ReadableStream<StreamChunk>;
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```
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### StreamChunk
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<Property name="choices" type="ChoiceStream[]">
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A list of chat completion choices. Can contain more than one elements if n is greater than 1.
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```js {{title: 'Choice Object for streamText()'}}
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```js {{title: 'Choice Object for pipe.run() with stream true'}}
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interface ChoiceStream {
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index: number;
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delta: Delta;
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```
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```js {{ title: 'RunResponseStream of pipe.run() with stream true' }}
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// Response of a streamText() call is a Promise<StreamResponse>.
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{
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"threadId": "string-uuid-123",
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"stream": StreamText // example of streamed chunks below.
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"stream": StreamResponse // example of streamed chunks below.
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}
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```
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```json {{ title: 'StreamText has stream chunks' }}
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```json {{ title: 'StreamResponse has stream chunks' }}
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// A stream chunk looks like this …
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{
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"id": "chatcmpl-123",

‎apps/baseai.dev/content/docs/guides/using-ollama-embeddings.mdx

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@@ -127,16 +127,16 @@ It will create a pipe in your current directory under `baseai/pipes/chat-with-do
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In your `index.ts` file, add the following code:
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```ts
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import { Pipe, streamText, getRunner } from '@baseai/core';
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import { Pipe, getRunner } from '@baseai/core';
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import chatWithDocsPipeConfig from './baseai/pipes/chat-with-docs-rag';
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// Instantiate the pipe
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const pipe = new Pipe(chatWithDocsPipeConfig());
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: 'How to create a pipe?'}],
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stream: true
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});
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// Convert the stream to a stream runner.

‎apps/baseai.dev/content/docs/memory/quickstart.mdx

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```ts
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import { Pipe, streamText, getRunner } from '@baseai/core';
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import { Pipe, getRunner } from '@baseai/core';
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import chatWithDocsPipeConfig from './baseai/pipes/chat-with-docs-rag';
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// Instantiate the pipe
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const pipe = new Pipe(chatWithDocsPipeConfig());
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: 'How to create a pipe?'}],
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stream: true
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});
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// Convert the stream to a stream runner.

‎apps/baseai.dev/content/docs/tools/quickstart.mdx

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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, generateText} from '@baseai/core';
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import {Pipe} from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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const userMsg = `What's the weather in San Francisco?`;
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async function main() {
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const response = await generateText({
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pipe,
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const response = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: false,
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});
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console.log(response.completion);

‎apps/baseai.dev/content/learn/learn/configure-tool.mdx

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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, streamText, getRunner} from '@baseai/core';
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import {Pipe, getRunner} from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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`;
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: true
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});
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const runner = getRunner(stream);
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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, streamText, getRunner} from '@baseai/core';
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import {Pipe, getRunner} from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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`;
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: true
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});
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const runner = getRunner(stream);

‎apps/baseai.dev/content/learn/learn/integrate-memory-in-pipe.mdx

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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, generateText} from '@baseai/core';
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import {Pipe} from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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const userMsg = `What's the weather in San Francisco?`;
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async function main() {
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const response = await generateText({
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pipe,
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const response = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: false,
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});
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console.log(response.completion);

‎apps/baseai.dev/content/learn/learn/integrate-pipe.mdx

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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import { Pipe, streamText, getRunner } from '@baseai/core';
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import { Pipe, getRunner } from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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`;
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async function main() {
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const { stream } = await streamText({
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pipe,
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messages: [{ role: 'user', content: userMsg }]
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const { stream } = await pipe.run({
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messages: [{ role: 'user', content: userMsg }],
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stream: true
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});
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const runner = getRunner(stream);
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</CodeGroup>
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We have added a user message to the pipe. We will use this message to test the pipe. We will also use the `streamText` method to stream the text on the terminal.
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We have added a user message to the pipe. We will use this message to test the pipe. We will also use the `pipe.run` method with `stream: true` to stream the text in the terminal.
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## Step #3: Add OpenAI API key in env
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‎apps/baseai.dev/content/learn/learn/integrate-tool-in-pipe.mdx

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```ts {{ title: 'index.ts' }}
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import 'dotenv/config';
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import {Pipe, streamText, getRunner} from '@baseai/core';
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import {Pipe, getRunner} from '@baseai/core';
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import pipeSummarizer from './baseai/pipes/summarizer';
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const pipe = new Pipe(pipeSummarizer());
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`;
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async function main() {
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const {stream} = await streamText({
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pipe,
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const {stream} = await pipe.run({
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messages: [{role: 'user', content: userMsg}],
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stream: true
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});
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const runner = getRunner(stream);

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