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import streamlit as st
from transformers import pipeline
from diffusers import DiffusionPipeline
import torch
import time
# Load models
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-dra-en")
summarizer = pipeline("summarization", model="Falconsai/text_summarization")
image_pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to("cuda")
# Functions for each task
def translate_tamil_to_english(text):
time.sleep(2)
result = translator(text)
return result[0]['translation_text']
def summarize_english_text(paragraph):
time.sleep(2)
summary = summarizer(paragraph, max_length=100, min_length=25, do_sample=False)
return summary[0]['summary_text']
def english_text_to_image(text):
image = image_pipe(text).images[0]
return image
# Custom CSS
st.markdown("""
<style>
/* Background color */
body {
background-color: #f0f0f5;
}
/* Text color and font */
.stApp {
font-family: 'Arial', sans-serif;
color: #333;
}
/* Titles and subtitles styling */
h1 {
color: #2E8B57;
text-align: center;
text-shadow: 2px 2px 5px #aaaaaa;
}
h2, h3 {
color: #4682B4;
text-shadow: 1px 1px 3px #aaaaaa;
}
/* Background texture */
.stApp {
background: linear-gradient(to bottom right, #fff7e6, #e6f7ff);
}
/* Button styling */
button[kind="primary"] {
background-color: #4682B4;
color: white;
border-radius: 8px;
padding: 0.5rem 1rem;
}
button[kind="primary"]:hover {
background-color: #5b9bd5;
}
/* Text area and input field styling */
textarea, input {
border-radius: 10px;
padding: 1rem;
border: 2px solid #ccc;
background-color: #f9f9f9;
}
/* Styling the output boxes */
.stMarkdown {
background-color: #e6f9ff;
padding: 1rem;
border-radius: 10px;
box-shadow: 2px 2px 10px #ccc;
}
</style>
""", unsafe_allow_html=True)
# Streamlit app layout
st.title("🌟 Multifunctional AI Application 🌟")
# Row 1: Tamil to English translation
st.subheader("🌐 Translate Tamil to English")
tamil_input = st.text_area("Enter Tamil text", "")
if st.button("Translate"):
english_output = translate_tamil_to_english(tamil_input)
st.markdown(f"**Translated English Text**: {english_output}")
# Row 2: English paragraph summarization
st.subheader("📝 Summarize English Paragraph")
english_paragraph = st.text_area("Enter English paragraph", "")
if st.button("Summarize"):
summary_output = summarize_english_text(english_paragraph)
st.markdown(f"**Summary**: {summary_output}")
# Row 3: English text to image generation
st.subheader("🎨 Generate Image from English Text")
image_text = st.text_input("Enter description for image generation", "")
if st.button("Generate Image"):
generated_image = english_text_to_image(image_text)
st.image(generated_image, caption="Generated Image")
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