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    • Data Processing
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      • Automated Data Processing (DP_ADP)
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      • Data Encoding (DP_3)
      • Data Split (DP_4)
      • Feature Scaling (DP_5)
      • Drop Columns (DP_6)
      • Time Stepper (DP_7)
      • Parse Datetime (DP_PDT)
      • Reorder Columns (DP_ROC)
      • Feature Sampling (DP_FSP)
      • Reshape Array (DP_RSH)
      • Column Astype (DP_ASP)
      • Show Duplicates (DP_SDC)
      • Drop Duplicates (DP_DRD)
      • Scalar to Ndarray (DP_STN)
      • Image to Ndarray (DP_ITN)
      • Dataset Info (DP_INF)
      • Dataset Correlations (DP_CRR)
      • Dataset Description (DP_DSC)
      • Dataset Datatypes (DP_DTY)
      • Dataset Uniques (DP_UNQ)
      • Dataset Stats Counts (DP_STC)
      • Principal Component Analysis (DP_PCA)
      • Text Vectorizer (DP_VEC)
      • Resampler (DP_RES)
    • Data Visualization
      • Scatter Plots (DP_SCP)
      • Ordinary Plots (DP_ORD)
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      • Pie Plots (DP_PIE)
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    • Machine Learning
      • Simple Linear Regression (ML_R_1)
      • Multiple Linear Regression (ML_R_2)
      • Polynomial Linear Regression (ML_R_3)
      • Support Vector Regression (ML_R_4)
      • Decision Tree Regression (ML_R_5)
      • Random Forest Regression (ML_R_6)
      • Logistic Regression (ML_CN_1)
      • K-Nearest Neighbors - KNN (ML_CN_2)
      • Support Vector Machine (ML_CN_3)
      • Kernel SVM (ML_CN_4)
      • Naive Bayes (ML_CN_5)
      • Decision Tree Classification (ML_CN_6)
      • Random Forest Classification (ML_CN_7)
      • Hierarchical Clustering (ML_CG_1)
      • K-Means Clustering (ML_CG_2)
      • XGBoost (MS_XGBOOST)
      • Grid Search (ML_GRID)
      • Shap Explain (ML_SHAP)
      • Isolation Forest (ML_ISF)
      • (ML_DBS)
    • Automated Machine Learning
      • AutoRegression (AUTO_R_1)
      • AutoClassification (AUTO_CN_1)
      • AutoRegression II (AUTO_R_2)
    • Deep Learning
      • Artificial Neural Network (DL_ANN)
      • Self Organizing Maps (DL_SOM)
      • Restricted Boltzmann Machine (DL_RBM)
    • Automated Deep Learning
      • Auto Image Classification (A_DL_IMC)
      • Auto Image Regression (A_DL_IMR)
      • Auto Text Classification (A_DL_TXC)
      • Auto Text Regression (A_DL_TXR)
      • Auto Structured Data Classification (A_DL_SDC)
      • Auto Structured Data Regression (A_DL_SDR)
      • General AutoDL Blocks (A_DL_ALL)
  • LabelCraft
    • Images, Annotations and Augmentation
    • Import and Export
    • Model Training and Prediction
  • Production APIs
    • Production Pipelines
  • Autogon Qore
    • Vision AI
    • Natural Language AI
      • Text Classification (Deprecated)
      • Text Summary (Deprecated)
      • Ask Your Data
      • Generate Synthetic Data
      • Speech To Text
      • Text To Speech
      • Sentiment Analyzer (Deprecated)
      • Conversation with Chatbot Agent
      • Conversational Interaction with GPT-4
      • Essay Marker
      • Resume Ranker
      • Translator
    • Voice Cloning
      • Create a Voice
      • Get Voices
      • Text-To-Speech
  • Other APIs
    • Project
      • List all projects
      • Create a New Project
      • Get Project Details
      • Delete a Project
    • Dataset
      • List all datasets
      • Create a Dataset
      • Get a Dataset
      • Updating a dataset
      • Delete a Dataset
      • Dataset Connection
      • Visualize Dataset
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On this page
  • Our Structure
  • Getting your API Keys
  • Install the library
  • Make your first request
  • Create project.

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Get Started

This page should help you get started on grabbing your API Keys from the dashboard and making your first request to Autogon.

Our Structure

Our API is based on both a single and multi-endpoint architecture. Specific operations are determined by requests sent to the respective endpoints.

Some requests made to Autogon will require an API key. Please refer to the sections below on API key creation.

While most requests require authentication using API keys; any of such requests that doesn't include an API key will return an error. You can generate an API key from your portal at any time.

Getting your API Keys

Before you begin integration with the Autogon API,

  1. Create an Autogon account and complete necessary verification

  2. Fetch your integration credentials from the Integrations tab in Settings.

  3. Proceed to set up your integration.

Refer to the article/video embedded below for a complete guide on how to get API keys and integrate with the Autogon API.

Install the library

The best way to interact with our API is to use any of our supported integration libraries:

# Install via NPM
npm install -g autogonai-node
# Install via pip
pip3 install autogonai-python

Make your first request

To make your first request, send an authenticated request to the project endpoint. This will create a project. A project is the baseline for using our powerful tools.

Create project.

POST https://autogon.ai/api/v1/project

Creates a new project.

Request Body

Name
Type
Description

project_name*

String

name of project

project_description

String

short description for project.

{
    "id": 1,
    "app_id": "a295d247-05c9-424d-aa8c-5a8990ef5f6a",
    "project_name": "My First Project",
    "project_description": "This is a great project. I hope to achieve more with Autogon",
    "project_compiled_models": null,
    "created_at": "2023-01-22T01:47:43.158604Z"
}
{
    "status": "false",
    "message": "This project name already exists"
}

Take a look at how you might call this method using our official libraries, or via curl:

curl -L -X POST "https://autogon.ai/api/v1/api/v1/engine/project" -H "X-AUG-KEY: <API-KEY>" -H "Content-Type: application/json" --data-raw "{
    \"project_name\": \"My First Project\",
    \"project_description\": \"This is a great project. I hope to achieve more with Autogon\"
}"
// require the autogonai module and set it up with your API key
const autogonai = require('autogonai');

// load environment variables
require("dotenv").config();

// initilalize client
const client = new Client(process.env.AUTOGON_API_KEY);

// create project
const newProject = await client.Project.create({
    project_name: 'My First Project',
    project_description: 'This is a great project. I hope to achieve more with Autogon',
})
import os
from dotenv import load_dotenv
from autogonai.core import Client

# Set your API key before making the request
client = Client(api_key=API_KEY)

client.Project.create(
    project_name="My First Project",
    project_description="This is a great project. I hope to achieve" \
    " more with Autogon",
)
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Last updated 1 year ago

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Learn More: Find out more about our supported libraries .

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