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Quick Start Guide

Get up and running with HelpingAI in minutes. This guide will walk you through making your first API call using different methods and programming languages.

Authentication

First, you'll need an API key. Sign up at helpingai.co and get your API key from the dashboard.

Keep your API key secure! Never expose it in client-side code or public repositories.

Base URL

All API requests should be made to:

https://api.helpingai.co/v1

Your First API Call

Let's make a simple chat completion request. HelpingAI uses the same format as OpenAI's API, making it easy to integrate.

Python (using requests)

Python
import requests

url = "https://api.helpingai.co/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "model": "Dhanishtha-2.0-preview",
    "messages": [
        {"role": "user", "content": "Hello! I'm excited to try HelpingAI's reasoning capabilities."}
    ],
    "temperature": 0.7,
    "max_tokens": 150
}

response = requests.post(url, headers=headers, json=data)
result = response.json()
print(result["choices"][0]["message"]["content"])

Python (using OpenAI SDK)

Python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.helpingai.co/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "Hello! I'm excited to try HelpingAI's reasoning capabilities."}
    ],
    temperature=0.7,
    max_tokens=150
)

print(response.choices[0].message.content)

Python (using HelpingAI SDK)

Python
from helpingai import HelpingAI

client = HelpingAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "Hello! I'm excited to try HelpingAI's reasoning capabilities."}
    ],
    temperature=0.7,
    max_tokens=150
)

print(response.choices[0].message.content)

JavaScript (using axios)

JavaScript
const axios = require("axios");

(async () => {
  const response = await axios.post(
    "https://api.helpingai.co/v1/chat/completions",
    {
      model: "Dhanishtha-2.0-preview",
      messages: [
        {
          role: "user",
          content:
            "Hello! I'm excited to try HelpingAI's reasoning capabilities.",
        },
      ],
      temperature: 0.7,
      max_tokens: 150,
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
      },
    }
  );

  console.log(response.data.choices[0].message.content);
})();

JavaScript (using OpenAI package)

JavaScript
import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.helpingai.co/v1",
  apiKey: "YOUR_API_KEY",
});

async function main() {
  const completion = await openai.chat.completions.create({
    model: "Dhanishtha-2.0-preview",
    messages: [
      {
        role: "user",
        content:
          "Hello! I'm excited to try HelpingAI's reasoning capabilities.",
      },
    ],
    temperature: 0.7,
    max_tokens: 150,
  });

  console.log(completion.choices[0].message.content);
}

main();

JavaScript (using HelpingAI SDK)

JavaScript
import { HelpingAI } from "helpingai";

const client = new HelpingAI({
  apiKey: "YOUR_API_KEY",
});

async function main() {
  const completion = await client.chat.completions.create({
    model: "Dhanishtha-2.0-preview",
    messages: [
      {
        role: "user",
        content:
          "Hello! I'm excited to try HelpingAI's reasoning capabilities.",
      },
    ],
    temperature: 0.7,
    max_tokens: 150,
  });

  console.log(completion.choices[0].message.content);
}

main();

Understanding the Response

A typical response looks like this:

JSON
{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "Dhanishtha-2.0-preview",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! I'm excited to help you explore what HelpingAI can do with its advanced reasoning capabilities. I'm here to make sure you have a great experience. What would you like to try first?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 20,
    "completion_tokens": 45,
    "total_tokens": 65
  }
}

Notice how HelpingAI responds with information about its reasoning capabilities - ready to demonstrate its advanced mid-response reasoning!

Key Parameters

Required Parameters

  • model: The model to use (currently "Dhanishtha-2.0-preview")
  • messages: Array of message objects with role and content

Common Optional Parameters

  • temperature (0-2): Controls randomness. Higher = more creative, Lower = more focused
  • max_tokens: Maximum tokens to generate
  • stream: Set to true for streaming responses
  • hideThink: Set to false to see AI's reasoning process

Special Features

Chain of Recursive Thoughts with hideThink

HelpingAI can show you its reasoning process:

Python
response = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "What's 15 * 24?"}
    ],
    hideThink=False  # Shows reasoning in <think> tags
)

Streaming Responses

Get responses as they're generated:

Python
stream = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "Tell me a short story"}
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")

Next Steps

Now that you've made your first API call, explore more advanced features:

Need Help?

Welcome to the future of intelligent reasoning AI! 🚀

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