Analysis Help Guide . This example is the default analysis script to categorize Copilot conversations and to determine whether user's questions we successfully answered.

This recipe takes in a Copilot's Description and Instruction Prompt and then creates a shorter description and 4 sample questions.

Yes, this is a silly (but useful!) AI recipe. Notice the differing emoji styles of Claude3.5 vs GPT-4o. :-)

When released, PaLM 2 not only surpassed other LLMs in translation abilities between multiple languages but also demonstrated significant improvements over Google Translate (see the Technical Report by Google). This example allows you to easily change out the languages and translation text via variables to explore this and compare with other LLMs. You can also add your own TSV or CSV glossary in the format spec'ed by Google Translate. This example run (or runs like it) can be imported into the Translation Recipe to compare with traditional translation tools!

Which language model works best for your prompt? What are the biases inherent in each? Compare LLaMA2, Gemini, Mistral, OpenAI GPT-4 engines with more LLMs being added each month.

Takes in a quarterly report, BUY rating and transcript to output a financial report

Google Palm vs GPT4 vs LLaMA2: Which can easily create code to call the Stripe API using natural language.

This workflow creates a JSON quiz based on a character.

A prompt to compare a golden answer vs an AI generated answer.

This workflow takes a parameters the Gooey.AI workflow title and prompt to then create an image generation prompt that we use in our image generator workflow: https://gooey.ai/compare-ai-image-generators/?run_id=rpuzpn5m&uid=kKZgp2h1H2YxZYxZ2DbiRfUfeDM2

This workflow compares human vs AI generated analyst reports and grades how close the AI generated report is to the human one.

This workflow creates summarized reports for investors about various companies, it takes input as transcripts from calls with the company and financial reports and generates a summary report as per the formats of the particular investment bank.

Analyse Zephyr help bot for topic and question found

LLMs have biases built into them that are subtly reflected in every reference they produce about a subject. These biases will shortly be embedded to every Word Doc, Powerpoint, text and gmail message they help us create. Below we explore what 4 different versions of GPT feel about a collection of car brands.