Prompt Chain

Evaluate JSON Output from LLMs

Promptfoo example workflow for evaluating JSON output from language models.


80
Spark score
out of 100
Updated 6 days ago
Version 0.121.20

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Why it matters

Ensure your Large Language Model outputs are consistently valid JSON. This asset helps you programmatically check and validate the structure and content of JSON responses.

Outcomes

What it gets done

01

Validate LLM-generated JSON against a schema.

02

Extract specific data points from JSON output.

03

Classify JSON output based on predefined criteria.

04

Automate the evaluation of LLM responses.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/pfoo-eval-json-output | bash

Steps

Steps in the chain

01
Set OPENAI_API_KEY environment variable
02
Edit promptfooconfig.yaml
03
Run promptfoo eval
04
View results

Overview

Eval Json Output

Eval Json Output is a promptfoo example workflow for evaluating JSON-formatted responses from language models. It demonstrates how to use promptfoo's evaluation framework to test LLM outputs and view results. Use this workflow when you want to learn how promptfoo works with JSON outputs from language models. It's an example for understanding evaluation setup and execution during development.

What it does

Eval Json Output is a promptfoo example workflow that works with JSON-formatted responses from language models. It provides a starting point for testing LLM outputs in your development environment.

When to use - and when NOT to

Use this workflow when you want to explore promptfoo's evaluation capabilities with JSON outputs from language models. It's a learning example to help you understand how to set up and run evaluations.

Do NOT use this if you're looking for a production-ready validation system or need real-time processing. This is an example workflow for development and learning purposes.

Inputs and outputs

You provide a promptfooconfig.yaml file and your OPENAI_API_KEY environment variable. The workflow runs evaluations and produces results that you can view through the promptfoo view command.

Integrations

This workflow requires OpenAI's API (OPENAI_API_KEY) and runs within the promptfoo evaluation framework.

Who it's for

This workflow is designed for AI engineers and developers who want to learn how to use promptfoo for evaluating language model outputs, particularly those working with JSON responses.

Getting started

To run this example:

npx promptfoo@latest init --example eval-json-output
cd eval-json-output

Set your OPENAI_API_KEY environment variable, edit the promptfooconfig.yaml file, then execute:

promptfoo eval

After evaluation completes, view the results by running promptfoo view.

Source README

eval-json-output (Json Output)

You can run this example with:

npx promptfoo@latest init --example eval-json-output
cd eval-json-output

Usage

To get started, set your OPENAI_API_KEY environment variable.

Next, edit promptfooconfig.yaml.

Then run:

promptfoo eval

Afterwards, you can view the results by running promptfoo view

Discussion

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