Update app.py

app.py

@@ -1,41 +1,84 @@
-import streamlit as st
+import streamlit as st  # type: ignore
 from scrape import scrape_website, extract_body_content, clean_body_content, split_dom_content
-from parse import parse_with_ollama
+from parse_utils import parse_with_groq  # Updated to 'parse_utils'
 
-# Streamlit UI
-st.title("AI Web Scraper")
-url = st.text_input("Enter Website URL")
+# Streamlit UI with sidebar configuration
+st.set_page_config(page_title="AI Web Scraping App", page_icon="🌐")
+
+st.sidebar.title("🚀 Model Selection")
+selected_model = st.sidebar.selectbox(
+    "Choose a Model for Parsing:",
+    [
+        "llama3-8b-8192",
+        "llama3-groq-70b-8192-tool-use-preview", 
+        "llama-3.1-8b-instant",
+        "llava-v1.5-7b-4096-preview",
+        "mixtral-8x7b-32768",
+    ]
+)
+
+# Application title and description
+st.title("AI Web Scraper App 🌐")
+st.write("Easily scrape and analyze web content using advanced AI models. 🌟")
+
+# Input for website URL
+url = st.text_input("Enter Website URL 🔗")
 
 # Step 1: Scrape the Website
 if st.button("Scrape Website"):
     if url:
-        st.write("Scraping the website...")
+        st.write("🕵️‍♂️ Scraping the website...")
 
-        # Scrape the website using requests and BeautifulSoup
+        # Scrape the website
         dom_content = scrape_website(url)
-        if dom_content:
-            body_content = extract_body_content(dom_content)
-            cleaned_content = clean_body_content(body_content)
+        body_content = extract_body_content(dom_content)
+        cleaned_content = clean_body_content(body_content)
 
-            # Store the cleaned DOM content in Streamlit session state
-            st.session_state.dom_content = cleaned_content
+        # Store the DOM content in Streamlit session state
+        st.session_state.dom_content = cleaned_content
 
-            # Display the cleaned DOM content in an expandable text box
-            with st.expander("View Cleaned DOM Content"):
-                st.text_area("DOM Content", cleaned_content, height=300)
-        else:
-            st.error("Failed to scrape the website. Please check the URL.")
+        # Display the DOM content in an expandable text box
+        with st.expander("View DOM Content"):
+            st.text_area("DOM Content", cleaned_content, height=300)
 
-
-# Step 2: Ask Questions About the DOM Content
+# Step 2: Parse the Content
 if "dom_content" in st.session_state:
-    parse_description = st.text_area("Describe what you want to parse")
+    parse_description = st.text_area("Describe what you want to parse 📝")
 
     if st.button("Parse Content"):
         if parse_description:
-            st.write("Parsing the content...")
+            st.write(f"🤖 Parsing the content with {selected_model}...")
 
-            # Parse the content with Ollama
+            # Parse content using Groq
             dom_chunks = split_dom_content(st.session_state.dom_content)
-            parsed_result = parse_with_ollama(dom_chunks, parse_description)
+            parsed_result = parse_with_groq(dom_chunks, parse_description, model=selected_model)
             st.write(parsed_result)
+
+# Custom CSS for footer at the bottom of the sidebar
+st.markdown(
+    """
+    <style>
+    .footer {
+        position: fixed;
+        bottom: 0;
+        left: 0;
+        width: 100%;
+        background-color: #272432;  /* Dark background for visibility */
+        color: white;
+        text-align: center;
+        padding: 10px;
+        font-size: 14px;
+    }
+    .sidebar .footer {
+        position: fixed;
+        bottom: 0;
+    }
+    </style>
+
+    <div class="footer">
+    Made with ❤️ by Usman Yousaf 🚀<br>
+    Feel free to improve and expand this app for more powerful insights! 🔥
+    </div>
+    """,
+    unsafe_allow_html=True
+)