Now that you understand how websites, URLs, and APIs work, let's go a level deeper and see what makes up an HTTP request. As I mentioned in the last lesson, every HTTP request consists of six parts: 1. The API endpoint– Where the request is sent 2. The
Make.com HTTP Modiule
Understanding URLs and Websites We use websites every day and access them using unique URLs, right? For example, we type in the URL https://www.google.com to access Google's website. Similarly, we type in the URL https://www.instagram.com to access Instagram's website. Just
Make.com HTTP Modiule
As you already know, the official apps on Make.com makes it really easy to work with popular services like Google Sheets, Convertio, Airtable, and a ton of other services. But sometimes, you need to work with APIs that don’t have an official app on Make.com. For example,
Make.com AI Automation
Sometimes, it's best to delay the next step of an automation rather than executing it immediately. For example, if ChatGPT's analysis determines that an applicant is “Not Recommended,” we should send them a rejection email. But instead of sending the rejection email immediately, we can send
So far, we’ve built a solid automation: It works well, but we can make it even better! Right now, ChatGPT evaluates resumes and gives a Final Recommendation with one of these four options: 1. Strong Hire 2. Potential Hire 3. Need More Information 4. Not Recommended Now, let’s
The solution to our problem is two-folds: 1. First, Instead of receiving a long text response from ChatGPT, we need ChatGPT to output its analysis in JSON format. 2. Next, we need to force Make.com to parse the structured JSON data produced by ChatGPT and convert that data into
In order to understand the problem, we should try to map the key details from ChatGPT’s verdict to the corresponding columns in the Airtable base. But before that, we need to implement the following steps: 1. Add the “Create a Record” module from Airtable at the end of the
The Agenda Here is the automation we have built so far: 1. Using Tally’s module, we’ve set up a webhook to detect resume submissions. 2. When a resume is submitted, the automation instantly gets triggered and sends the resume file to the Convertio API. 3. Finally, Convertio converts
In the last lesson: 1. With the help of Tally's “Watch New Responses” module, we set up a webhook that listens for form submission events. 2. Once the form is submitted, we receive its details in a bundle, including the file URL of the uploaded resume. If you
If you remember, Tally has shared a link for accessing the form: Your form link will look different. Use it to submit a resume. You can either use your resume or my resume as the file upload: naresh-devineni-resume-2024Download “Okay! I have submitted the form, but the automation didn't
Webhooks Recap Unlike the automations we have built so far, the resume screener automation only needs to run when someone submits a CV. In other words, instead of running all the time or manually running at the click of a button, the automation should wait for the event (a CV
For the automation to kick in, an applicant must fill in the job submission form. That's the input data for our automation. From there, the automation will take control. So... First, we should build a form on the Tally.so website. The need for a form builder service