ad
ad

AI Hashtag Generator For Instagram in Python

Science & Technology


Introduction

In this article, we will walk through the process of building a hashtag generator for Instagram posts using Python. We will implement this functionality with OpenAI’s GPT-4 Mini model, which will generate relevant hashtags based on an uploaded image. The project will be structured into two main sections: the core functionality using a Python script and a web application created with Flask.

Getting Started

Before diving into the code, it is important to mention that this tutorial is made possible thanks to the support of Mammoth AI, a platform offering access to leading generative AI models for a nominal monthly fee.

Final Result

Upon completion, the application will allow users to upload an image and generate a list of hashtags. The application will feature a clean design where users can select and toggle hashtags to curate their final list for Instagram.

Setting Up the Environment

Prerequisites

  1. OpenAI API Key

    • You will need to create an account on OpenAI’s platform (platform.openai.com) to obtain your API key.
  2. Create an Environment File

    • Save your API key in an .env file. The file should be structured as follows:
      OPENAI_API_KEY="your_api_key_here"
      
  3. Install Required Packages

    • We will need the following Python packages:
      pip install requests python-dotenv flask
      

Building the Core Functionality

Create a Python script named main.py. We will import necessary libraries such as requests, os, and base64. We’ll define a function to convert images to a base64 string, which is required for the API request.

import os
import requests
import base64
from dotenv import load_dotenv

## Introduction
load_dotenv()
api_key = os.getenv("OPENAI_API_KEY")

## Introduction
def encode_image(image_path):
    with open(image_path, "rb") as img_file:
        return base64.b64encode(img_file.read()).decode('utf-8')

image_base64 = encode_image("your_image_path_here")

## Introduction
headers = (
    'Content-Type': 'application/json',
    'Authorization': f'Bearer {api_key)'
}

payload = (
    "model": "gpt-4-mini",
    "messages": [
        {
            "role": "system",
            "content": "You are a hashtag generation model for Instagram."
        ),
        (
            "role": "user",
            "content": f"Provide hashtags for this image: {image_base64)"
        }
    ],
    "max_tokens": 500
}

## Introduction
response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
hashtags = response.json()['choices'][0]['message']['content'].split(',')

Creating the Flask Application

Next, we will set up a Flask web application. Create a directory named flask_app and a file named app.py. Import necessary components from Flask and replicate the existing logic from main.py inside the Flask app framework.

from flask import Flask, render_template, request
from dotenv import load_dotenv
import os
import base64
import requests

load_dotenv()
app = Flask(__name__)
api_key = os.getenv("OPENAI_API_KEY")

def encode_image(image_path):
    with open(image_path, "rb") as img_file:
        return base64.b64encode(img_file.read()).decode('utf-8')

@app.route("/", methods=["GET", "POST"])
def index():
    if request.method == "POST":
        image = request.files["image"]
        image.save("temp_image.png")
        image_base64 = encode_image("temp_image.png")
        
        # Prepare headers and payload...
        
        response = requests.post(...)
        hashtags = response.json()['choices'][0]['message']['content'].split(',')
        
        return render_template("index.html", hashtags=hashtags, image_base64=image_base64)
    return render_template("index.html")

HTML Template

Create a folder named templates and an HTML file named index.html. Design the form to allow image uploads and display the results, making use of Bootstrap for styling.

JavaScript Functionality

Include JavaScript to handle toggling hashtags and displaying a preview of the uploaded image.

<script>
function toggleHashtag(hashtag, index) (
    // Toggle the hashtag selection
)

document.getElementById("image-input").addEventListener("change", function(event) (
    // Update image preview
));
</script>

Conclusion

You should now have a fully functional Instagram hashtag generator using Python and Flask. This application allows users to generate relevant hashtags for their posts based on uploaded images.


Keywords

FAQ

  1. What do I need to run the Instagram hashtag generator?

  2. Can I use any type of image?

    • Yes, the application can accept various image formats, thanks to the base64 encoding process.
  3. How are the hashtags generated?

    • The GPT-4 Mini model from OpenAI generates hashtags based on the content of the uploaded image.
  4. What frameworks are used in this project?

    • The project uses Python for backend processing and Flask as the web framework.
  5. Is there a limit to the number of hashtags generated?

    • The system is configured to generate exactly 30 hashtags as specified in the prompt to the OpenAI model.

This concludes our guide on building an AI Hashtag Generator for Instagram in Python. Enjoy generating hashtags for your posts and enhancing your social media engagement!