PlayFetch also provides deployment and monitoring capabilities, allowing prompts to be exposed as RESTful JSON endpoints. Users can update the prompt from PlayFetch as needed and monitor request performance and costs when the prompt is live. The PlayFetch API is consistent across different model providers, with each prompt or chain exposed as its own endpoint.
The data also includes examples of how to call a single prompt that returns immediately and how to implement chat by passing a continuation key. It also mentions the ability to use functions in OpenAI and provides a simple chat UI example that can be linked to a PlayFetch endpoint.
Key takeaways:
- PlayFetch allows for collaborative prompt creation with features like version control, commenting, labels, and response histories.
- It supports testing and iteration, allowing you to populate test data for your prompts, test different models, and feed production requests back into your tests.
- PlayFetch enables deployment and monitoring of prompts as RESTful JSON endpoints, allowing you to monitor request performance and spending.
- The PlayFetch API is consistent and secure, exposing every prompt or chain as its own endpoint, and all calls are self-contained.