Upload dataset via CSV

Once your project is created, you can upload datasets to it. Here's how you can upload a dataset via a CSV file:

Create New Dataset in a Project
  1. Select your newly created project from the project list.

  2. Navigate to the Dataset tab within the project.

  3. Click on the Create New Dataset button.

  4. In the upload window, select the Upload CSV tab.

  5. Click on the upload area and browse/drag and drop your local CSV file. Ensure the file size does not exceed 1GB.

  6. Enter a suitable name for your dataset.

  7. Click Next to proceed.

Next, you will be directed to map your dataset schema with Catalyst's inbuilt schema, so that your column headings don't require editing:

Set Dataset Schema

Here is a list of Catalyst's inbuilt schema elements (definitions are for reference purposes and may vary slightly based on your use case):

Schema ElementDefinition

traceId

Unique ID associated with a trace

metadata

Any additional data not falling into a defined bucket

cost

Expense associated with generating a particular inference

expected_context

Context documents expected to be retrieved for a query

latency

Time taken for an inference to be returned

system_prompt

Predefined instruction provided to an LLM to shape its behaviour during interactions

traceUri

Unique identifier used to trace and log the sequence of operations during an LLM inference process

pipeline

Sequence of processes or stages that an input passes through before producing an output in LLM systems

response

Output generated by an LLM after processing a given prompt or query

context

Surrounding information or history provided to an LLM to inform and influence its responses

sanitized_response

A version of the LLM's output that has been modified to remove sensitive, inappropriate, or undesirable content

prompt

Input or query provided to an LLM that triggers the generation of a response

expected_response

Anticipated or ideal output that an LLM should produce in response to a given prompt

timestamp

Specific date and time at which an LLM action, such as an inference or a response, occurs

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