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