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jancbeck/omnivore-ai-annotations: This serverless function can be used to automatically add annotations to Omnivore articles when a specific label (say, "summarize") is added to them.

Mar 21, 20247 min read

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jancbeck/omnivore-ai-annotations: This serverless function can be used to automatically add annotations to Omnivore articles when a specific label (say, “summarize”) is added to them.

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date_saved: 2024-03-16 04:42:59

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Let ChatGPT annotate Omnivore articles for you

Overview

This serverless function can be used to automatically add annotations to Omnivore articles when a specific label (say, “summarize”) is added to them. It uses Omnivore’s API and webhooks as well as OpenAI’s chat completions API.

How to Use

For most convenience, deployment using Vercel is recommended. Theoretically it could work on other serverless functions providers but I have only tested it with Vercel. Vercel offers a free hobby plan that should cover basic usage of this function.

Deploy the example using Vercel:

Deploy with Vercel

Vercel Setup

When adding the repo to Vercel, set the environment variables to make the APIs work and allow customization.

  • OMNIVORE_API_KEY (required): omnivore.app ⇒ API Key
  • OPENAI_API_KEY (required): platform.openai.com ⇒ API Keys
  • OMNIVORE_ANNOTATE_LABEL (optional): set this to the name of label you want to use to trigger processing. Example: “Summarize” (without quotes). Not required if you use the PAGE_CREATED Omnivore webhook event type which process every article added to Omnivore.
  • OPENAI_PROMPT (required): the instruction that’s send to OpenAI’s GPT model in addition to the article content.
  • OPENAI_MODEL (optional): the model name to use. Defaults to “gpt-3.5-turbo-16k” (without quotes).
  • OPENAI_SETTINGS (optional, advanced): additional request parameters send when generating the chat completion. Use JSON. Example: {"temperature": 0, "seed": 1234}.

Deploy and copy the URL of your deployment.

Omnivore Webhook Setup

In Omnivore add a new webhook and set the URL to the deployed Vercel function URL from the step above and add the path /api/annotate to it. Example: https://projectname.vercel.app/api/annotate

If you have defined a label name to listen for in the step above, then select LABEL_ADDED as event type. If you want the function to process every article you add to Omnivore, then instead select PAGE_CREATED.

Now either add a new article to Omnivore or your label to an existing article. Within less than a minute, the response of the model’s completion should appear in the notebook of the article.

Check the runtime logs if you encounter issues. Check your API keys and never share them publicly.

Development

Clone and Deploy

git clone https://github.com/jancbeck/omnivore-ai-annotations

Install the Vercel CLI and dependencies:

Then run the app at the root of the repository:

API Endpoints

  • POST /api/annotate: Annotates an article with an AI generated response.

Local testing with Postman

  1. Local Testing: Vercel offers a local development environment using the vercel dev command. Run this command in your project directory.
  2. Postman Setup: Open Postman and create a new request. Set the request type to whatever your function expects (likely POST or GET).
  3. Request URL: Use http://localhost:3000/api/annotate as the URL, replacing 3000 with whatever port vercel dev is using.
  4. Send Request: Click “Send” in Postman to trigger the function.

Observe the response and terminal output for logging information.

License

MIT License.

Ideas

  • use individual article highlights to allow “chatting” within Omnivore (e.g. highlight text, add note “explain” and GPT will generate the highlight with a reply based on the prompt and context.
  • instruct the model to highlight the article for you via function calls. Perhaps using the article notebook as an instruction input.

Highlights

jancbeck/omnivore-ai-annotations: ⤴️

jancbeck/omnivore-ai-annotations: This serverless function can be used to automatically add annotations to Omnivore articles when a specific label (say, “summarize”) is added to them. ⤴️

标题：Let ChatGPT annotate Omnivore articles for you 作者：Unknown 标签：API, webhooks, serverless function, Omnivore, OpenAI

一句话总结：该文介绍了如何使用ChatGPT自动为Omnivore文章添加注释。

摘要：本文介绍了一个使用ChatGPT自动为Omnivore文章添加注释的serverless函数。它利用了Omnivore的API和webhooks以及OpenAI的chat completions API。文章详细介绍了如何使用该函数，推荐使用Vercel进行部署，并提供了Vercel的设置步骤。同时，文章还提供了开发和本地测试的指导，并列举了API的端点。最后，作者给出了一些建议，如使用文章中的高亮部分进行对话或让模型为文章添加高亮等。

大纲：

  • 概述
  • 如何使用
  • Vercel设置
  • Omnivore Webhook设置
  • 开发
  • API端点
  • 本地测试
  • 许可证
  • 点子

第一步，请详细叙述大纲中每一部分的内容：

  • 概述：介绍了该文的目的和内容，以及使用ChatGPT自动为Omnivore文章添加注释的方法。
  • 如何使用：介绍了使用Vercel进行部署和设置步骤，并说明了需要的环境变量。
  • Vercel设置：具体说明了如何在Vercel中添加repo以及设置环境变量。
  • Omnivore Webhook设置：介绍了在Omnivore中设置webhook的步骤，包括设置URL和事件类型。
  • 开发：说明了如何克隆和部署应用，并提供了运行应用的命令。
  • API端点：列出了可用的API端点，包括\“/api/annotate\“。
  • 本地测试：提供了使用Postman进行本地测试的方法。
  • 许可证：说明文中所使用的许可证类型。
  • 点子：给出了一些扩展的点子，如利用文章中的高亮部分进行对话等。

第二步，总结文章的结论：本文介绍了如何使用ChatGPT自动为Omnivore文章添加注释的方法，通过使用Omnivore的API和webhooks以及OpenAI的chat completions API，使得自动添加注释变得更加便利。

第三步，列举读这篇文章，我可以学到哪些知识？

  • 学习如何使用ChatGPT自动为Omnivore文章添加注释
  • 了解如何使用Omnivore的API和webhooks以及OpenAI的chat completions API
  • 掌握使用Vercel进行部署和设置的方法
  • 学习如何在Omnivore中设置webhook
  • 掌握开发和本地测试的方法
  • 了解API的端点和如何进行本地测试
  • 了解文中所使用的许可证类型
  • 获得一些扩展的点子，如利用文章中的高亮部分进行对话等。

第四步，针对文章的内容，提出三个用户在阅读的过程中可能会有的疑问：

  1. 使用Vercel进行部署是否有其他替代方案？
  2. 如何正确设置环境变量以确保API能够正常工作？
  3. 在Omnivore中设置webhook时，如何选择正确的事件类型？

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