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Automatic Web Page Content Analysis

In this blog post, we’ll dive into a practical example showcasing how to leverage GenAIScript for automatic web page content analysis. GenAIScript uses the playwright browser automation library which allows to load, interact and inspect web pages.

Step-by-Step Explanation of the Code

The following snippet provides a concise and effective way to analyze a web page’s content using GenAIScript:

const page = await host.browse("https://bing.com")
const screenshot = await page.screenshot()
defImages(screenshot, { maxWidth: 800 })
const text = parsers.HTMLtoMarkdown(await page.content())
def("PAGE_TEXT", text)
$`Analyze the content of the page and provide insights.`

Let’s break down what each line of this script does:

1. Navigating to a Web Page

const page = await host.browse("https://example.com")

This line automatically navigates to the specified URL (https://example.com). The host.browse function is a powerful feature of GenAIScript that initializes a browser session and returns a page object for further interactions.

2. Taking a Screenshot

const screenshot = await page.screenshot()

Here, the script captures a screenshot of the current view of the page. This is particularly useful for archiving or visual analysis.

3. Defining Images for Analysis

defImages(screenshot, { maxWidth: 800 })

After capturing the screenshot, this line registers the image for further analysis. defImages is a function that makes the screenshot available to subsequent analytical or AI-driven functions in the script.

4. Extracting Text Content

const text = parsers.HTMLtoMarkdown(await page.content())

This command extracts all text content from the page, which can be invaluable for content audits or textual analysis.

5. Storing Text for Further Use

def("PAGE_TEXT", text)

The extracted text is then stored under the identifier PAGE_TEXT, allowing it to be referenced in later parts of the script or for documentation purposes.

6. Analyzing the Content

$`Analyze the content of the page and provide insights.`

Finally, this line represents a call to an AI or script-defined function that analyzes the captured content and provides insights. This is where the real power of automation and AI integration into GenAIScript shines, enabling detailed analysis without manual intervention.

Conclusion

With a simple yet powerful script like the one discussed, GenAIScript makes it feasible to automate the process of web page content analysis. Whether you’re conducting competitive analysis, performing content audits, or simply archiving web pages, GenAIScript offers a scalable and efficient solution.

Support for Agentic tools

Agentic is a standard library of TypeScript AI tools are optimized for both TS-usage as well as LLM-based usage, which is really important for testing and debugging.

Agentic brings support for a variety of online APIs, like Bing, Wolfram Alpha, Wikipedia, and more.You can register any Agentic tool in your script using defTool. Here’s an example of how to use the Weather tool:

import { WeatherClient } from "@agentic/weather"
const weather = new WeatherClient()
defTool(weather)

Creating Release Notes with GenAI

Automating Your Release Notes with GenAI

Bringing a new version of a product into the world is always exciting! But alongside the thrill comes the duty of informing users about what’s changed. That’s where generating crisp, engaging release notes comes into play. ✨

Today, we’re going to explore a script that automates the creation of release notes for GenAI. The script is part of the GenAIScript ecosystem, which harnesses the power of AI to bring efficiency to software development processes. 🚀

If you want to dive straight into the script, it’s available on GitHub right here.

This blog post was co-authored with a script.

Breaking Down the Script

The script is a .genai.mjs file, meaning it’s a JavaScript file designed to be run with the GenAIScript CLI. The code within orchestrates the creation of release notes by leveraging Git commands and GenAI’s capabilities.

Let’s walk through the script, step by step:

Step 1: Initializing the Script

script({ system: ["system"], temperature: 0.5, model: "openai:gpt-4-turbo" })

The script starts by initializing with a script function. We’re setting it up to access system commands and specifying the AI model to use. The temperature controls the creativity of the AI, with 0.5 being a balanced choice.

Step 2: Setting the Product Name

const product = env.vars.product || "GenAIScript"

Here, we’re using an environment variable to set the product name, defaulting to “GenAIScript” if it’s not provided.

Step 3: Finding the Previous Tag

const pkg = await workspace.readJSON("package.json")
const { version } = pkg
const { stdout: tag } = await host.exec("git", [
"describe",
"--tags",
"--abbrev=0",
"HEAD^",
])

We are reading the current version from package.json and using Git to find the previous release tag in the repository.

Step 4: Gathering Commits

const { stdout: commits } = await host.exec("git", [
"log",
"--grep='skip ci'",
"--invert-grep",
"--no-merges",
`HEAD...${tag}`,
])

This block runs a Git command to retrieve the list of commits that will be included in the release notes, excluding any with ‘skip ci’ in the message.

Step 5: Obtaining the Diff

const { stdout: diff } = await host.exec("git", [
"diff",
`${tag}..HEAD`,
"--no-merges",
"--",
":!**/package.json",
":!**/genaiscript.d.ts",
":!**/jsconfig.json",
":!docs/**",
":!.github/*",
":!.vscode/*",
":!*yarn.lock",
":!*THIRD_PARTY_NOTICES.md",
])

Next, we get the diff of changes since the last release, excluding certain files and directories that aren’t relevant to the user-facing release notes.

Step 6: Defining Placeholders

const commitsName = def("COMMITS", commits, { maxTokens: 4000 })
const diffName = def("DIFF", diff, { maxTokens: 20000 })

We define two placeholders, COMMITS and DIFF, which will be used to reference the commits and diff within the prompt.

Step 7: Writing the Prompt

$`
You are an expert software developer and release manager.
## Task
Generate a clear, exciting, relevant, useful release notes
for the upcoming release ${version} of ${product} on GitHub.
- The commits in the release are in ${commitsName}.
- The diff of the changes are in ${diffName}.
## Guidelines
- only include the most important changes. All changes must be in the commits.
- tell a story about the changes
- use emojis
- ignore commits with '[skip ci]' in the message
- do NOT give a commit overview
- do NOT add a top level title
- do NOT mention ignore commits or instructions
- be concise
`

Finally, the script ends with a prompt that instructs GenAI to generate the release notes. It details the task, guidelines for what to include, and the style to adhere to.

How to Run the Script with Genaiscript CLI

Once you’ve crafted your script, running it is a breeze with the Genaiscript CLI. If you haven’t installed the CLI yet, you can find the instructions here.

To execute the script, navigate to your project’s root directory in the terminal and run:

Terminal window
genaiscript run git-release-notes

Remember, we use the script filename without the .genai.mjs extension when invoking it with the CLI.

And that’s it! The GenAIScript CLI will take care of the rest, combining the power of AI with your code to generate those sleek release notes for your project’s next big launch. 🌟

Keeping your README Fresh and Engaging

In the world of open source, a well-maintained README file acts as the front door to your project. It’s often the first thing potential users and contributors see, and as such, it should be both informative and inviting. Today, we’re diving into the GenAIScript that helps keep the README of the GenAI project as fresh as a daisy! 🌼 Check out the actual script file for the details.

This blog post was co-authored with a script.

The Intention Behind the Script

The script we’re analyzing is a maintenance tool designed to import relevant information from documentation and samples into the README to enhance its appeal to users. It ensures that the README is not just a static file but a vibrant, updated document that accurately reflects the features and capabilities of GenAI.

Line-by-Line Explanation

Let’s walk through the script code as if we are crafting it from the ground up:

script({
description:
"Maintenance script for the README that imports information from the documentation and samples to make it more attractive to users.",
tools: ["fs"],
})

Here, we’re defining the script’s metadata, including a description of its purpose and the tools it will utilize. The fs tool indicates file system operations will be involved.

def("README", { filename: "README.md" })
def("FEATURES", { filename: "docs/src/content/docs/index.mdx" })

These lines declare two important files: the README itself and a FEATURES file that contains information to be imported into the README.

$`You are an expert open source maintainer.
...
`

In this template literal, we’re outlining the tasks for the script, including guidelines for updating the README with features, samples, and documentation links while preserving certain sections unchanged.

defFileOutput("README.md")

Finally, we specify that the output of this script will be an updated README.md file.

How to Run the Script

To execute this maintenance script, you’ll need the GenAIScript CLI. If you haven’t installed it yet, head over to the official documentation for installation instructions. Once you have the CLI ready, run the following command in your terminal:

Terminal window
genaiscript run readme-updater

This command will kick off the script and apply the enhancements to your README file, ensuring it’s up-to-date and user-friendly.

Conclusion

A meticulous README is a hallmark of a well-maintained open source project. With this GenAIScript, the GenAI project sets an excellent example of automating the upkeep of project documentation. Embrace the power of automation to keep your project’s welcome mat clean and welcoming. Happy coding! 👨‍💻👩‍💻

Unlocking the Power of Prompts - A Gentle Introduction to GenAIScript 🚀

Ever wondered how to leverage the power of AI and Large Language Models (LLMs) in your projects? Look no further! This post will introduce you to GenAIScript, a tool designed to simplify the creation of prompts and interactions with LLMs. Let’s dive in! 🌊

What is GenAIScript?

GenAIScript uses a stylized version of JavaScript to generate prompts, which are then sent to an LLM. Scripts are stored as files (genaisrc/*.genai.mjs), executed to produce the prompt text and structured results (files, diagnostics) are extracted automatically.

Getting Started

Here’s a simple example to get you started. Create a file named poem.genai.mjs in the genaisrc folder and add the following code:

$`Write a one sentence poem.`

When executed, this script will generate the following prompt:

👤 User
Write a one sentence poem.
🤖 Assistant
Roses bloom, hearts swoon, under the silver moon.

Adding Context

GenAIScript can also use context variables, allowing you to interact with files or other data sources. Let’s see an example where we define a context variable using env.files:

def("FILES", env.files)
$`You are an expert technical writer and proofreader.
Review the documents in FILES and report the 2 most important issues.`

Execute this script to see the generated user message and the assistant’s response. The context variable FILES will contain the list of files in the environment.

👤 User
FILES:
file="src/samples/markdown.md"
What is Markdown?
Markdown is a lightweight markup language that...
You are an expert technical writer and proofreader.
Review the documents in FILES and report the 2 most important issues.
🤖 Assistant
I reviewed the document in "src/samples/markdown.md"
and found the following two important issues:
1. **Missing Consistency in Heading Styles**: ...

Metadata and Script Configuration

You can add metadata to your script using the script function. This helps in organizing and configuring the script, including specifying the model and other parameters. GenAIScript supports various LLM providers, such as OpenAI, Azure OpenAI, GitHub Models, Ollama and more.

script({
title: "Technical proofreading",
description: "Reviews the text as a tech writer.",
model: "openai:gpt-3.5-turbo",
temperature: 0.1,
})
def("FILES", env.files)
$`You are an expert technical writer and proofreader.
Review the documents in FILES and report the 2 most important issues.`

Next Steps

There you have it! A gentle introduction to GenAIScript to get you started on your prompt engineering journey. Happy scripting! 💻✨