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Leveraging GPT-4 to Search Airtable and Auto-Answer Questions

Unlock the power of GPT-4 for efficient Airtable searches, revolutionizing data management with AI- driven natural language query capabilities.

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Streamline your business processes with

custom workflow automation in Airtable.

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Harness the power of APIs to connect and

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insightful reports and dashboards.

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Bring your ideas to life with rapid MVP creation

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Overview Airtable Video Overview Airtable Video

Leveraging GPT-4 to Search Airtable and Auto-Answer Questions

Unlock the power of GPT-4 for efficient Airtable searches, revolutionizing data management with AI-driven natural language query capabilities.

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Are you tired of manually searching for information within your Airtable bases? In this blog, we’ll explore how to use the powerful GPT-4 AI to search Airtable, making it quicker and more efficient to find the data you need. We’ll walk you through the process of setting up GPT-4 and Airtable to work together, using a property management base as an example.

Step 1: Setting up your Airtable base For this demonstration, we’ve created a property management base called General Property Tracker (GPT). This base is designed to track properties, people, rental agreements, and rent payments. To make it easy for GPT-4 to search the base, we’ve created a concatenate field called “searchField”. It concatenates most of the other fields in a table and increases the chances of a search term being correctly found. It is no vector search though.

Step 2: Populating base schema To help GPT-4 understand the base structure, we’ve used a script and a Make scenario to populate the base schema in a metadata base. This metadata base contains information about bases, tables, and fields, including their IDs and descriptions. By concatenating these fields into a formula and rolling them into tables, we create a single string that represents the entire base schema.

Step 3: Creating a search strategy field To guide GPT-4 in searching the base, we’ve created a field called “searchStrategy” in our test base. This field contains base-specific instructions and tips that help GPT-4 devise a search strategy.

Step 4: Sending the question to Make.com When a search is triggered, the question is sent to Make via a webhook. Make receives the initial instructions, base schema, tips, and the original question as payload. This information is then sent to GPT-4 to develop a search strategy.

Step 5: GPT-4 creates a search formula GPT-4 generates a search formula and provides the correct base ID, table ID, and, if needed, field ID. When sent to the Airtable API, this search formula returns a list of records stored in a datastore. All previous replies and messages to ChatGPT are stored in the datastore as well.

Step 6: Iterating through the search process For each new run of the repeater module, the information is sent back to GPT-4 for analysis. After multiple searches and iterations, GPT-4 determines if it has enough information to answer the original question. If it does, it produces the answer along with a “complete” flag, which is used to terminate the execution.

Using GPT-4 to search Airtable can potentially revolutionize the way you manage your data, making it faster and more efficient. However, it’s important to note that this powerful tool comes at a cost. In our example, the search for names and contact details of people with overdue rent payments cost 53 cents over 5x GPT-4 API calls to Make (GPT 3.5 and older can’t handle the large amount of text and logic). Despite the expense, the increased efficiency and convenience may well be worth the investment for many users. And as vector databases become easy to deploy, or Airtable adds it on, it’ll become much more cost competitive. Give this innovative approach a try and see how it can transform your Airtable experience!

Further Use Cases:

Customer Relationship Management (CRM): Use GPT-4 to search for specific customer information, such as contact details, purchase history, or customer feedback. Salesforce already seems to have implemented this. Inventory Management: Quickly find products based on criteria like stock levels, suppliers, or categories. Platform agnostic search: Answer questions directly from within Slack, or wherever. Human Resources: Use GPT-4 to locate employee data like performance reviews, hire dates, or job titles. Content Management: Search for articles, images, or multimedia files based on keywords or categories.