Update app.py

app.py

@@ -2,7 +2,7 @@ import os
 import gdown
 import time
 import gradio as gr
-# REMOVED: from google.colab import userdata (This was the cause of the error)
+from google.colab import userdata
 
 # Modern Imports
 from langchain_community.document_loaders import PyPDFLoader
@@ -17,15 +17,13 @@ from langchain_core.output_parsers import StrOutputParser
 # ==========================================
 # 1. SETUP & KEYS
 # ==========================================
-# Use os.getenv instead of userdata.get
-os.environ["GROQ_API_KEY"] = os.getenv('GROQ_API_KEY') 
-
+os.environ["GROQ_API_KEY"] = userdata.get('ragapikey')
 
 # --- UPDATE THIS LIST WITH ALL YOUR LINKS ---
 links_to_process = [
     "https://drive.google.com/file/d/1rb7AeJZrDNR-bq8Q9V4IvtzYZsDOvDH0/view?usp=sharing",
     "https://drive.google.com/file/d/16PcJo_JaQHh1bx01lCAkc4QwQ6YnLb-K/view?usp=sharing"
-    #"https://drive.google.com/drive/folders/ANOTHER_FOLDER_ID" 
+    #"https://drive.google.com/drive/folders/ANOTHER_FOLDER_ID"
 ]
 
 output_dir = 'knowledge_base'
@@ -37,7 +35,7 @@ if not os.path.exists(output_dir):
 # ==========================================
 def build_vector_db(links):
     print(f"📥 Starting synchronization for {len(links)} sources...")
-    
+
     for link in links:
         try:
             if "/folders/" in link:
@@ -47,7 +45,7 @@ def build_vector_db(links):
                 print(f"📄 Syncing Individual File: {link}")
                 # Use output_dir + "/" to ensure it saves into the folder
                 gdown.download(url=link, output=output_dir + "/", quiet=True)
-            
+
             time.sleep(1) # Small pause to respect Drive rate limits
         except Exception as e:
             print(f"⚠️ Skip Link: Could not download {link}. Error: {e}")
@@ -63,22 +61,22 @@ def build_vector_db(links):
                     all_docs.extend(loader.load())
                 except Exception as e:
                     print(f"❌ Error loading {filename}: {e}")
-    
+
     if not all_docs:
         raise ValueError("No PDF documents found! Ensure links are set to 'Anyone with the link'.")
 
     # Chunking & Embeddings
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)
     chunks = text_splitter.split_documents(all_docs)
-    
+
     print(f"🧠 Creating embeddings for {len(chunks)} text chunks...")
     embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
-    
+
     vector_db = FAISS.from_documents(chunks, embeddings)
     print("✅ Multi-Source Vector Database Created Successfully!")
     return vector_db
 
-# Initialize 
+# Initialize
 vector_store = build_vector_db(links_to_process)
 retriever = vector_store.as_retriever(search_kwargs={"k": 3})
 
@@ -106,68 +104,37 @@ rag_chain = (
 # ==========================================
 # 4. PROFESSIONAL FRONTEND (GRADIO BLOCKS)
 # ==========================================
-
-
-# ==========================================
-# 4. PROFESSIONAL FRONTEND (STYLING FIXED)
-# ==========================================
-
-# Improved CSS for high-contrast visibility
 custom_css = """
 #main-container { max-width: 900px; margin: auto; padding: 20px; }
 .header-text { text-align: center; color: #1e293b; margin-bottom: 2px; }
-
-/* The result box styling */
-.report-box { 
-    background-color: #ffffff !important; 
-    border-radius: 12px !important; 
-    border: 2px solid #4f46e5 !important; 
-    padding: 20px !important; 
-    min-height: 250px !important;
-    box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1) !important;
-}
-
-/* Force text inside the result box to be Bold Black */
-.report-box p, .report-box span, .report-box div { 
-    color: #000000 !important; 
-    font-weight: 500 !important;
-    font-size: 1.1rem !important;
-}
-
-/* Ensure Markdown headers (# Header) are extra bold and dark */
-.report-box h1, .report-box h2, .report-box h3 {
-    color: #1e1b4b !important;
-    font-weight: 800 !important;
-    border-bottom: 1px solid #e2e8f0;
-}
+.report-box { background-color: #ffffff; border-radius: 8px; border: 1px solid #e2e8f0; padding: 15px; min-height: 200px; }
 """
 
+def process_query(query):
+    if not query.strip():
+        return "### ⚠️ System Note\n*Please enter a strategic inquiry to begin analysis.*"
+    try:
+        return rag_chain.invoke(query)
+    except Exception as e:
+        return f"### ❌ Error\nAn error occurred: {str(e)}"
+
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo"), css=custom_css) as demo:
     with gr.Column(elem_id="main-container"):
-        gr.Markdown("# 🏛️ ByteWise: CS Intelligence", elem_classes="header-text")
-        gr.Markdown("<p style='text-align: center;'>Specialized Synthesis for Assembly & Data Structures</p>")
+        gr.Markdown("# 🏛️ Enterprise Knowledge Engine", elem_classes="header-text")
+        gr.Markdown("<p style='text-align: center;'>Multi-Source Document Synthesis via Groq & FAISS</p>")
         gr.HTML("<hr>")
-        
-        user_input = gr.Textbox(
-            label="Strategic Inquiry", 
-            placeholder="Ask a question about Assembly or Data Structures...", 
-            lines=3
-        )
-        
+
+        user_input = gr.Textbox(label="Strategic Inquiry", placeholder="Ask a question about the collected knowledge base...", lines=3)
+
         with gr.Row():
             submit_btn = gr.Button("ANALYZE DATA", variant="primary", scale=2)
-            clear_btn = gr.ClearButton([user_input], value="RESET", scale=1)
+            clear_btn = gr.ClearButton([user_input], value="RESET DASHBOARD", scale=1)
 
         gr.Markdown("### 📋 Intelligence Report")
-        
-        # We apply 'report-box' here to ensure the Markdown inherits the high-contrast CSS
         with gr.Column(elem_classes="report-box"):
-            output_display = gr.Markdown(
-                value="_Awaiting input... Results will appear here in high-contrast black text._"
-            )
+            output_display = gr.Markdown(value="_Awaiting input..._")
 
     submit_btn.click(fn=process_query, inputs=user_input, outputs=output_display)
     user_input.submit(fn=process_query, inputs=user_input, outputs=output_display)
 
-# Launch
 demo.launch(share=True)