Update app.py

app.py

@@ -1,20 +1,24 @@
 import streamlit as st
 from transformers import pipeline
-from diffusers import DiffusionPipeline, FluxPipeline
 import torch
 import time
+import requests
+import io
+import os
+from PIL import Image
 
-device = "cpu"
 # 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(device)
-# image_pipe = fluxPipeline("image-generation", model=DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to(device))
 
-# image_pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(device)
-# image_pipe.enable_model_cpu_offload()
-image_pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev")
-image_pipe.to(device)
+# for summarizer api
+SUMMARIZER_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+summarizer_headers = {"Authorization": f"Bearer {os.getenv('GROQ_API_TOKEN')}",
+                     "Content-Type": "application/json"}
+
+
+# for image api
+IMAGE_API_URL = "https://api-inference.huggingface.co/models/ZB-Tech/Text-to-Image"
+img_headers = {"Authorization": f"Bearer {os.getenv('HF_API_TOKEN')}"}
 
 
 # Functions for each task
@@ -25,11 +29,36 @@ def translate_tamil_to_english(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']
+    # Request payload
+    payload = {
+        "model": "mixtral-8x7b-32768",
+        "messages": [
+            {"role": "system", "content": "Create a summary of below paragraph in 30 words max"},
+            {"role": "user", "content": paragraph}
+        ],
+        "max_tokens": 100  # number of words in the output.
+    }
+
+    # Send POST request to Groq API
+    response = requests.post(SUMMARIZER_API_URL, json=payload, headers=summarizer_headers)
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the JSON response
+        result = response.json()
+        # Extract and print the generated text
+        generated_text = result['choices'][0]['message']['content']
+        return generated_text
+    else:
+        return f"Error: {response.status_code}, {response.text}"
 
 def english_text_to_image(text):
-    image = image_pipe(text).images[0]
+    payload = {
+        "inputs": prompt,
+    }
+    response = requests.post(IMAGE_API_URL, headers=img_headers, json=payload)
+    image_bytes = response.content
+    image = Image.open(io.BytesIO(image_bytes))
     return image
 
 # Custom CSS
@@ -93,27 +122,79 @@ st.markdown("""
     </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")
+
+#sidebar styling 
+st.markdown("""
+<style>
+    [data-testid=stSidebar] {
+        background-color: #FFFFFF;
+        margin-right: 20px;
+        border-right: 2px solid #FFFFFF
+    }
+</style>
+""", unsafe_allow_html=True)
+
+#options styling in sidebar and added image in sidebar
+with st.sidebar:
+    selected = option_menu(
+        menu_title="",
+        options=['Home','Tool'],
+        icons=['house-door-fill','setting'],
+        menu_icon='truck-front-fill',
+        default_index=0,
+        styles={
+            "container": {'padding':'5!important','background-color':'#FAF9F6'},
+            "icon": {'color':"#000000", "font-size":"23px"},
+            "nav-link": {'font-size':'16px','text-align':'left','margin':'0px','--hover-color':'#EDEADE','font-weight':'bold'},
+            "nav-link-selector":{'background-color':'#E6E6FA','font-weight':'bold'}
+        }
+    )
+
+
+if selected == "Home":
+    # Page title and header
+    st.title(":blue[Multi-Purpose Tool] - Empowering Educators 🎓")
+
+    # Subheader for the app description
+    st.subheader("A versatile tool designed to assist teachers in translating, summarizing, and visualizing concepts.")
+
+    # Main description with detailed information about the app
+    st.markdown("""
+    The **Multi-Purpose Tool** is a user-friendly platform developed for educators, 
+    enabling them to enhance their teaching experience. Whether it's translating content 
+    into different languages, summarizing lengthy materials, or visualizing concepts 
+    through images, this tool provides a one-stop solution for modern teaching needs.
+    
+    ### Key Features:
+    - **Translation**: Translate text seamlessly between languages (e.g., Tamil to English).
+    - **Summarization**: Quickly generate summaries of long passages for easy understanding.
+    - **Text to Image**: Visualize difficult concepts by generating images from text descriptions.
+    
+    ### Available Worldwide:
+    The Multi-Purpose Tool is deployed on Hugging Face and accessible globally to teachers 
+    and educators at the click of a button. Visit the [app here](https://huggingface.co/spaces/Jesivn/Multi_Purpose_Tool).
+    
+    Empower your classroom with advanced AI tools today!
+    """)
+elif selected=="Tool":    
+    # 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")