bikash119

Configure output 
 Bikash-Patras-MacBook:node bikashpatra$ ./configure --without-ssl
Checking for program g++ or c++          : /usr/bin/g++ 
Checking for program cpp                 : /usr/bin/cpp 
Checking for program ar                  : /usr/bin/ar 
Checking for program ranlib              : /usr/bin/ranlib 
Checking for g++                         : ok  
Checking for program gcc or cc           : /usr/bin/gcc 
Checking for program ar                  : /usr/bin/ar 
Checking for program ranlib              : /usr/bin/ranlib 

bikash119

description
Distilabel is an AI Feedback (AIF) framework for building datasets with and for LLMs.

Installation

You will need to have at least Python 3.9 or higher, up to Python 3.12, since support for the latter is still a work in progress.

bikash119

Define LLMs as local or remote models

Working with LLMs

LLM subclasses are designed to be used within a [Task][distilabel.steps.tasks.Task], but they can also be used standalone.

from distilabel.llms import OpenAILLM

llm = OpenAILLM(model="gpt-4")

bikash119

Generating Synthetic Data with Distilabel

🧑 human (Sep 27, 2024, 05:42 PM)

help me with code to generate synthetic data using distilabel

🤖 assistant (Sep 27, 2024, 05:42 PM)

Certainly, I can help you with code to generate synthetic data using Distilabel. Distilabel is a library for creating labeled datasets using language models. Let's create a simple example to demonstrate how to use it.

<antArtifact identifier="distilabel-synthetic-data" type="application/vnd.ant.code" language="python" title="Synthetic Data Generation with Distilabel">

bikash119

synthetic data

🧑 human (Sep 27, 2024, 05:45 PM)

help me create synthetic data with distilabel

🤖 assistant (Sep 27, 2024, 05:45 PM)

Certainly! I'd be happy to help you create synthetic data using Distilabel. Let's walk through the process of setting up a simple pipeline to generate synthetic data. We'll use the OpenAI API for this example, but you can adjust it based on your preferred LLM provider.

Here's a step-by-step guide to create a basic synthetic data generation pipeline:

1. First, make sure you have Distilabel installed:

bikash119

Tried creating new npm project using cloudflare@latest 
`npm create cloudflare@latest new-prj -- --framework=react-router`


--- 2025-05-28T06:01:29.031Z debug
🪵  Writing logs to "/Users/boredmgr/Library/Preferences/.wrangler/logs/wrangler-2025-05-28_06-01-28_851.log"
---

--- 2025-05-28T06:01:29.031Z debug
Metrics dispatcher: Posting data {"deviceId":"a5847bd1-ae19-4037-847d-da6b141f9944","event":"wrangler command started","timestamp":1748412089031,"properties":{"amplitude_session_id":1748412089025,"amplitude_event_id":0,"wranglerVersion":"4.17.0","osPlatform":"Mac OS","osVersion":"Darwin Kernel Version 21.6.0: Mon Jun 24 00:56:10 PDT 2024; root:xnu-8020.240.18.709.2~1/RELEASE_X86_64","nodeVersion":22,"packageManager":"npm","isFirstUsage":false,"configFileType":"jsonc","isCI":false,"isPagesCI":false,"isWorkersCI":false,"isInteractive":true,"hasAssets":false,"argsUsed":[],"argsCombination":"","command":"wrangler types","args":{"xJsonConfig":true,"j":true,"envInterface":"<REDACTED>","includeRuntime":true,"incl

bikash119

{
  "name": "AI Funamentalist",
  "nodes": [
    {
      "parameters": {
        "method": "POST",
        "url": "https://api.brightdata.com/dca/trigger",
        "sendQuery": true,
        "queryParameters": {
          "parameters": [