Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from transformers import pipeline
|
2 |
+
import streamlit as st
|
3 |
+
|
4 |
+
def create_product_description_app():
|
5 |
+
st.title("KI-gestützter Produktbeschreibungsgenerator")
|
6 |
+
|
7 |
+
# Interface erstellen
|
8 |
+
product_name = st.text_input("Produktname:")
|
9 |
+
key_features = st.text_area("Hauptmerkmale (durch Kommas getrennt):")
|
10 |
+
target_audience = st.text_input("Zielgruppe:")
|
11 |
+
|
12 |
+
if st.button("Beschreibung generieren"):
|
13 |
+
# Prompt zusammenbauen
|
14 |
+
prompt = f"""
|
15 |
+
Produkt: {product_name}
|
16 |
+
Merkmale: {key_features}
|
17 |
+
Zielgruppe: {target_audience}
|
18 |
+
Erstelle eine verkaufsfördernde Produktbeschreibung.
|
19 |
+
"""
|
20 |
+
|
21 |
+
# Generator initialisieren
|
22 |
+
generator = pipeline('text-generation',
|
23 |
+
model='gpt2')
|
24 |
+
|
25 |
+
# Beschreibung generieren
|
26 |
+
description = generator(prompt,
|
27 |
+
max_length=200,
|
28 |
+
num_return_sequences=1)[0]['generated_text']
|
29 |
+
|
30 |
+
st.write("Generierte Beschreibung:")
|
31 |
+
st.write(description)
|
32 |
+
|
33 |
+
if __name__ == "__main__":
|
34 |
+
create_product_description_app()
|