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Use Case

Automated product reviews and comparisons

Generative AI models like Language Learning Models (LLMs) and image generators can be harnessed for automated product reviews and comparisons. For instance, an LLM like GPT-3 by OpenAI can be trained and deployed to create detailed, accurate, and unbiased reviews using simple prompts. For example, given product specifications and user feedback, the model can generate a comprehensive review highlighting key features, user experience, and comparison with similar products. Image generators can be employed to create visual comparisons of products. Using machine learning algorithms to identify key elements in images, they can generate visual comparisons highlighting differences in size, color, or design. For instance, using an image of a product, the AI can produce a visual comparing it with other similar products, visually pointing out distinctions, and offering a user-friendly review.Likewise, these technologies can be combined to give a holistic view, creating a unified text-visual product comparison that's automated, accurate, and user-focused.

How to build with Clevis

Text Input

Prompt the user to enter the names of two products

Prompt ChatGPT

Use ChatGPT to generate a review for the first product based on user feedback and specifications

HTTP Request

Fetch product details and specifications for the second product from an online API

Prompt ChatGPT

Use ChatGPT to generate a review for the second product based on fetched specifications and comparisons with the first product

Display Output

Display the generated reviews and comparisons in a user-friendly format

This is an example app that you can build using Clevis, a tool known for its versatility in creating AI applications. Named 'Automated Product Reviews and Comparisons,' the application simplifies generating reviews and comparisons of products. Let's delve into how the application works.

The process begins with Text Input step, prompting the user to enter the names of two products they wish to compare. Next, the app uses ChatGPT, a language model, in step 2 to produce an automated review for the first product based on user-provided feedback and specifications.

Following this, the app executes an Http Request step to fetch details and specifications for the second product from an online API. With sufficient information now for both products, the app uses ChatGPT again, this time to generate a review for the second product, which includes contrast with the first product, thus facilitating comparison.

The final step, Display Output, involves showcasing the resulting reviews and comparisons in a comprehensible, user-friendly format.

Just like this, you can design and build applications within the same area, all thanks to the flexibility of Clevis.


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