Prompt Playground
Iterate on prompts with curated data from development and production
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Iterate on prompts with curated data from development and production
Last updated
Was this helpful?
Prompt Playground helps developers experiment with prompt templates, input variables, LLM models, and parameters. This no-code platform empowers both coding and non-coding experts to refine their prompts for production applications.
Iterate on your prompts with any model using our Playground Integrations
Replay spans from your production data
Build prompts with AI using ourCopilot: prompt builder
Manage your prompts in one place with Prompt Hub
You can iterate on prompts by comparing them side by side with different models, tools, LLM parameters, prompt templates, and variables. The first step is to select the "clone prompt" or "+ prompt" button to create a new prompt.
Another approach to reducing hallucinations is modifying the template. Using Copilot, the user optimizes the prompt, instructing the LLM to respond with 'I don’t know' when the answer is not found in the provided context. After pressing 'Run' with the updated prompt template, the New Output confirms that the LLM now responds with 'I don’t know' instead of generating a fabricated answer.
While we have observed improved performance on a single example, how can we ensure consistent improvement across many examples? To validate that a new prompt effectively reduces hallucinations more broadly, we can load a dataset of hallucinated examples into the Prompt Playground and test the updated prompt against the entire dataset.
If you'd like to share playground runs with your team, you can save them as an experiment to showcase the results in a shareable link.
The most common way to enter the Prompt Playground is through a span on the LLM tracing page. For instance, users can filter spans where an flagged the LLM output as a hallucination and then bring one of these examples into the Prompt Playground to refine the prompt, ensuring the LLM produces factual responses in the future.
The template can also be saved to the , making it especially valuable for production use cases and collaboration.
Use tool calling
Debug your tool calling directly in playground
Use image inputs
Send images and debug your multimodal prompts
Prompt hub
Store and manage prompts in one central repo