@arizeai/phoenix-mcp

--- description: Datasets are critical assets for building robust prompts, evals, fine-tuning, --- # How-to: Datasets ## How to create datasets Datasets are critical assets for building robust prompts, evals, fine-tuning, and much more. Phoenix allows you to build datasets manually, programmatically, or from files. * [Create datasets from CSV](creating-datasets.md#from-csv) * [Create datasets from Pandas](creating-datasets.md#create-datasets-from-pandas) * [Create datasets from spans](creating-datasets.md#from-spans) * [Create datasets using synthetic data](creating-datasets.md#syntetic-data) ## Exporting datasets Export datasets for offline analysis, evals, and fine-tuning. * [#exporting-to-csv](exporting-datasets.md#exporting-to-csv "mention") - how to quickly download a dataset to use elsewhere * [Exporting to OpenAI Ft](exporting-datasets.md#exporting-for-fine-tuning) - want to fine tune an LLM for better accuracy and cost? Export llm examples for fine-tuning. * [Exporting to OpenAI Evals](exporting-datasets.md#exporting-openai-evals) - have some good examples to use for benchmarking of llms using OpenAI evals? export to OpenAI evals format.