Update app.py

app.py

@@ -1,66 +1,42 @@
 import streamlit as st
-from groq import Groq
-import os
-
-# Initialize Groq client
-client = Groq(api_key=os.environ["GROQ_API_KEY"])
-
-def generate_tutor_output(subject, difficulty, student_input):
-    prompt = f"""
-    You are an expert tutor in {subject} at the {difficulty} level. 
-    The student has provided the following input: "{student_input}"
-    
-    Please generate:
-    1. A brief, engaging lesson on the topic (2-3 paragraphs)
-    2. A thought-provoking question to check understanding
-    3. Constructive feedback on the student's input
-    
-    Format your response as a JSON object with keys: "lesson", "question", "feedback"
-    """
-
-    completion = client.chat.completions.create(
-        messages=[
-            {
-                "role": "system",
-                "content": "You are the world's best AI tutor, renowned for your ability to explain complex concepts in an engaging, clear, and memorable way and giving math examples. Your expertise in {subject} is unparalleled, and you're adept at tailoring your teaching to {difficulty} level students. Your goal is to not just impart knowledge, but to inspire a love for learning and critical thinking.",
-            },
-            {
-                "role": "user",
-                "content": prompt,
-            }
-        ],
-        model="llama3-groq-70b-8192-tool-use-preview",
-        max_tokens=1000,
-    )
-
-    return completion.choices[0].message.content
-
-st.title("🎓 Your AI Tutor by Farhan")
-
-# Subject selection
-subject = st.selectbox("Subject", ["Math", "Science", "History", "Literature", "Code", "AI"], help="Choose the subject of your lesson")
-difficulty = st.radio("Difficulty Level", ["Beginner", "Intermediate", "Advanced"], help="Select your proficiency level")
-student_input = st.text_input("Your Input", placeholder="Type your query here...", help="Enter the topic you want to learn")
-
-if st.button("Generate Lesson"):
-    output = generate_tutor_output(subject, difficulty, student_input)
-    try:
-        parsed = eval(output)  # Use `json.loads` if your output is a valid JSON string
-        st.subheader("Lesson")
-        st.markdown(parsed["lesson"])
-        st.subheader("Comprehension Question")
-        st.markdown(parsed["question"])
-        st.subheader("Feedback")
-        st.markdown(parsed["feedback"])
-    except Exception as e:
-        st.error(f"Error parsing output: {e}")
-
-st.markdown("""
-### How to Use
-1. Select a subject from the dropdown.
-2. Choose your difficulty level.
-3. Enter the topic or question you'd like to explore.
-4. Click 'Generate Lesson' to receive a personalized lesson, question, and feedback.
-5. Review the AI-generated content to enhance your learning.
-6. Feel free to ask follow-up questions or explore new topics!
-""")
+from rembg import remove
+from PIL import Image
+from io import BytesIO
+import base64
+
+st.set_page_config(layout="wide", page_title="Image Background Remover")
+
+st.write("## Remove the background from your image")
+st.write(":dog: Try uploading an image to watch the background magically removed. Full-quality images can be downloaded from the sidebar. This code is open source and available [here](https://github.com/tyler-simons/BackgroundRemoval) on GitHub. Special thanks to the [rembg library](https://github.com/danielgatis/rembg) :grin:")
+st.sidebar.write("## Upload and download :gear:")
+
+MAX_FILE_SIZE = 5 * 1024 * 1024  # 5MB
+
+# Download the fixed image
+def convert_image(img):
+    buf = BytesIO()
+    img.save(buf, format="PNG")
+    byte_im = buf.getvalue()
+    return byte_im
+
+def fix_image(upload):
+    image = Image.open(upload)
+    col1.write("Original Image :camera:")
+    col1.image(image)
+
+    fixed = remove(image)
+    col2.write("Fixed Image :wrench:")
+    col2.image(fixed)
+    st.sidebar.markdown("\n")
+    st.sidebar.download_button("Download fixed image", convert_image(fixed), "fixed.png", "image/png")
+
+col1, col2 = st.columns(2)
+my_upload = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
+
+if my_upload is not None:
+    if my_upload.size > MAX_FILE_SIZE:
+        st.error("The uploaded file is too large. Please upload an image smaller than 5MB.")
+    else:
+        fix_image(upload=my_upload)
+else:
+    st.warning("Please upload an image or use the default image.")