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import gradio as gr
import pandas as pd
import requests
from io import StringIO
# Dataset'inizi Hugging Face Hub'dan indirin
def download_file(url):
response = requests.get(url)
response.raise_for_status()
return StringIO(response.text)
dataset_url = "https://huggingface.co/datasets/ta2cay/caycuma_info/resolve/main/caycuma_info.csv"
data = pd.read_csv(download_file(dataset_url))
# Soruya cevap veren ve ilgili görseli döndüren fonksiyon
def answer_question(question):
response = data[data["Soru"].str.contains(question, case=False, na=False)]
if not response.empty:
answer = response.iloc[0]["Cevap"]
# Belirli sorulara göre görsel eklemek
if "nerede" in question.lower():
image = "caycuma_map.png"
elif "nüfus" in question.lower():
image = "caycuma_population.png"
elif "tarih" in question.lower():
image = "caycuma_history.png"
else:
image = None
else:
answer = "Bu soruya dair bir bilgi bulamadım."
image = None
return answer, image
# Gradio arayüzü
iface = gr.Interface(
fn=answer_question,
inputs=gr.Textbox(lines=2, placeholder="Sorunuzu buraya yazın...", label="Soru"),
outputs=["text", "image"],
title="Çaycuma Bilgi Modeli",
description="Çaycuma ile ilgili sorularınızı sorun ve ilgili görselleri görün.",
theme="default"
)
if __name__ == "__main__":
iface.launch()
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