EvalsOne - Streamline AI Prompt Evaluations

What are LLM prompts and why should you use them? LLM prompts are the text inputs or instructions that humans provide to large language models like GPT-3 in order to generate desired text outputs based on the specified context or task. For example: "Write a short fairy tale story" is a simple prompt. "Analyze the pros and cons of implementing a four-day work week policy" is a more complex prompt. Prompts frame and guide what the LLM will generate, so well-crafted prompts are key to getting high-quality, relevant outputs. People need to evaluate language model prompts before deploying generative AI applications for several important reasons: ✔️ Prompt Quality and Effectiveness: Different prompts can lead to vastly different outputs from language models. Evaluating prompts allows you to identify which ones are effective at eliciting the desired type of output consistently and with high quality. ✔️ Mitigating Biases and Harmful Outputs: Large language models can inadvertently generate biased, offensive, or harmful content due to biases in their training data. Testing prompts extensively helps surface these potential issues so they can be mitigated. ✔️ Aligning with Intended Use Case: The same prompt may work well for one use case but poorly for another. Evaluating across your intended scenarios ensures the prompts will perform as expected when deployed. ✔️ Handling Edge Cases: Prompts need to be robust to different phrasings, contexts, and edge cases that may arise from user input. Evaluation surfaces breakdowns to improve prompt reliability. ✔️ Regulatory and Legal Compliance: For applications in regulated industries like healthcare and finance, prompt evaluation provides assurance that outputs will comply with relevant guidelines and laws. ✔️ User Experience: Poor quality prompts can lead to confusing, inconsistent or nonsensical outputs that negatively impact the user experience of your application. Essentially, prompt evaluation acts as a critical quality control and risk mitigation step before putting generative AI models into production environments where they interact with real users and data. It helps maximize performance and safety.

congratulations to the evalsone team on launching such a vital tool. I'm curious about how your platform handles the subtleties of different languages and dialects in prompt evaluations. could you share how you've approached this challenge?

Congrats on the launch. This is exactly what I was missing to speed up my workflow. I do have a question though, can use my own model instead of using default ones?

My god, couldn't have you released this sooner? Congrats on the launch and building such a useful tool

Very good feature . I am really interested in it . I am seeing many people around me start taking interest in it and vote. This is really generic product

Great to know about these features