File size: 1,538 Bytes
6902bea 9c75197 81d899d a603f6f dd41aff e1979ec dd41aff c91a90a 6902bea dd41aff a603f6f dd41aff 6be12e9 dd41aff a603f6f c91a90a 6be12e9 dd41aff c91a90a dd41aff c91a90a dd41aff a603f6f 5b109c0 c91a90a 6be12e9 5b109c0 c91a90a 9c75197 dd41aff c91a90a 5b109c0 c91a90a 6902bea 73861ff a603f6f c91a90a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
import gradio as gr
from datasets import load_dataset
from itertools import chain
from difflib import get_close_matches
import random
# Load and clean dataset
dataset = load_dataset("asuender/motivational-quotes", "quotes_extended", split="train")
quotes = [item["quote"] for item in dataset if "quote" in item]
authors = [item["author"] if item.get("author") else "Unknown" for item in dataset]
tags_list = [item["tags"].split(", ") if item.get("tags") else [] for item in dataset]
all_tags = sorted(set(chain.from_iterable(tags_list)))
# Quote search logic
def recommend_quote(user_input):
if not user_input:
return "Please enter a category."
matched = get_close_matches(user_input.lower(), all_tags, n=1, cutoff=0.4)
if not matched:
return f"😕 No quotes found for a category like '{user_input}'. Try something else."
selected_tag = matched[0]
matches = [
(q, a) for q, a, t in zip(quotes, authors, tags_list)
if selected_tag in [tag.lower() for tag in t]
]
if not matches:
return f"😕 No quotes found for the tag '{selected_tag}'."
quote, author = random.choice(matches)
return f"“{quote}”\n\n– {author}"
# UI
gr.Interface(
fn=recommend_quote,
inputs=gr.Textbox(
label="Type a category like 'hope', 'courage', 'resilience'...",
placeholder="e.g. hope"
),
outputs="text",
title="MoodMatch",
description="Get inspiring quotes by typing any theme or category — even partial matches work."
).launch()
|