LSTM Quote Generator 📜

Generate inspiring quotes using a trained LSTM model, built on a dataset of 1000 quotes from various authors and backgrounds.

Overview

This project utilizes a Long Short-Term Memory (LSTM) neural network to generate quotes based on patterns learned from a curated dataset. The model was trained using quotes scraped from a website, ensuring diversity in language and style.

Features ✨

• Quote Generation: Input a starting phrase, word or choose random prompts to generate unique quotes.
• Web Interface: Access the model via a user-friendly Gradio interface for easy interaction.
• API Access: Integrate quote generation into other applications using the provided API endpoints.

Usage 🚀

Web Interface

1. Run the jupyter file then from last cell click on url to redirect to the deployed Gradio interface.

2. Enter a prompt to generate a quote.

3. Explore the generated quotes and their diversity.

   Example

For more example refer this video

API Usage

1. Send a POST request to the API endpoint with a JSON payload containing the prompt.
2. Receive a JSON response with the generated quote.

Example

• Python

from gradio_client import Client

client = Client("https://8a60bc40aabf89f175.gradio.live/")
result = client.predict(
		Prompt="Hello!!",
		nwords=13,
		api_name="/predict"
)
print(result)

• JavaScript

import { Client } from "@gradio/client";

const client = await Client.connect("https://8a60bc40aabf89f175.gradio.live/");
const result = await client.predict("/predict", { 		
		Prompt: "Hello!!", 		
		nwords: 10, 
});

console.log(result.data);

• Bash

curl -X POST https://8a60bc40aabf89f175.gradio.live/call/predict -s -H "Content-Type: application/json" -d '{
  "data": [
    "Hello!!",
    10
]}' \
  | awk -F'"' '{ print $4}'  \
  | read EVENT_ID; curl -N https://8a60bc40aabf89f175.gradio.live/call/predict/$EVENT_ID

Note : Load and run main.ipynb and replace links with current active links. Directly goining to links will not work.

Contributing 🤝

Contributions are welcome! Please fork the repository and create a pull request with your improvements.

License 📝

This project is licensed under the MIT License. See the LICENSE file for details.

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