Testing AI bots and copilots (https://gooey.ai/copilot) in practice is complex because the answer a bot will give is affected not just by the user's last question but also by the conversation history that preceded that question. Hence, this bulk example shows you how to format your CSV to include a bot/user conversation history before each question is asked. The output columns also show which knowledge documents were returned as results that the bot used in trying to formulate its answer.

Testing AI bots and copilots (https://gooey.ai/copilot) in practice is complex because the answer a bot will give is affected not just by the user's last question but also by the conversation history that preceded that question. Hence, this bulk example shows you how to format your CSV to include a bot/user conversation history before each question is asked. The output columns also show which knowledge documents were returned as results that the bot used in trying to formulate its answer.

This run is useful if you are only interested in Regression testing, Monitoring and Evaluation, Observability and Bugs.

In this bulk run example, we compare 6 different Gooey.AI speech recognition + translations workflows (https://gooey.ai/speech), each of which uses a different AI speech model:
Whisper Telugu Bhashini
Whisper v2
Google Chirp
Azure
Meta Seemless 4MT
AI4Bharat.org Conformer Hindi

We then evaluate them at https://gooey.ai/eval/ (where you can see what works best....)