Update app.py

app.py

@@ -23,9 +23,7 @@ list_llm = [
 list_llm_simple = [os.path.basename(llm) for llm in list_llm]
 
 def load_doc(list_file_path):
-    """
-    Load and split PDF documents into chunks
-    """
+    """Load and split PDF documents into chunks"""
     loaders = [PyPDFLoader(x) for x in list_file_path]
     pages = []
     for loader in loaders:
@@ -38,17 +36,13 @@ def load_doc(list_file_path):
     return doc_splits
 
 def create_db(splits):
-    """
-    Create vector database from document splits
-    """
+    """Create vector database from document splits"""
     embeddings = HuggingFaceEmbeddings()
     vectordb = FAISS.from_documents(splits, embeddings)
     return vectordb
 
 def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, progress=gr.Progress()):
-    """
-    Initialize the language model chain
-    """
+    """Initialize the language model chain"""
     llm = HuggingFaceEndpoint(
         repo_id=llm_model,
         huggingfacehub_api_token=api_token,
@@ -76,27 +70,21 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, pr
     return qa_chain
 
 def initialize_database(list_file_obj, progress=gr.Progress()):
-    """
-    Initialize the document database
-    """
+    """Initialize the document database"""
     list_file_path = [x.name for x in list_file_obj if x is not None]
     doc_splits = load_doc(list_file_path)
     vector_db = create_db(doc_splits)
     return vector_db, "Database created successfully!"
 
 def initialize_LLM(llm_option, llm_temperature, max_tokens, top_k, vector_db, progress=gr.Progress()):
-    """
-    Initialize the Language Model
-    """
+    """Initialize the Language Model"""
     llm_name = list_llm[llm_option]
     print("Selected LLM model:", llm_name)
     qa_chain = initialize_llmchain(llm_name, llm_temperature, max_tokens, top_k, vector_db, progress)
     return qa_chain, "Analysis Assistant initialized and ready!"
 
 def format_chat_history(message, chat_history):
-    """
-    Format chat history for the model
-    """
+    """Format chat history for the model"""
     formatted_chat_history = []
     for user_message, bot_message in chat_history:
         formatted_chat_history.append(f"User: {user_message}")
@@ -104,9 +92,7 @@ def format_chat_history(message, chat_history):
     return formatted_chat_history
 
 def conversation(qa_chain, message, history):
-    """
-    Handle conversation and document analysis
-    """
+    """Handle conversation and document analysis"""
     formatted_chat_history = format_chat_history(message, history)
     response = qa_chain.invoke({"question": message, "chat_history": formatted_chat_history})
     response_answer = response["answer"]
@@ -123,30 +109,18 @@ def conversation(qa_chain, message, history):
     return qa_chain, gr.update(value=""), new_history, response_source1, response_source1_page, response_source2, response_source2_page, response_source3, response_source3_page
 
 def demo():
-    """
-    Main demo application
-    """
-    # Enhanced theme with professional colors
+    """Main demo application"""
     theme = gr.themes.Default(
         primary_hue="indigo",
         secondary_hue="blue",
         neutral_hue="slate",
-        font=[gr.themes.GoogleFont("Roboto"), "system-ui", "sans-serif"]
     )
     
-    css = """
-        .container { max-width: 1200px; margin: auto; }
-        .metadata { font-size: 0.9em; color: #666; }
-        .highlight { background-color: #f0f7ff; padding: 1em; border-radius: 8px; }
-        .warning { color: #e53e3e; }
-        .success { color: #38a169; }
-    """
-    
-    with gr.Blocks(theme=theme, css=css) as demo:
+    with gr.Blocks(theme=theme) as demo:
         vector_db = gr.State()
         qa_chain = gr.State()
         
-        # Enhanced header
+        # Header
         gr.HTML(
             """
             <div style='text-align: center; padding: 20px;'>
@@ -156,7 +130,7 @@ def demo():
             """
         )
         
-        # Marketing and feature description
+        # Marketing description
         gr.Markdown(
             """
             ### 🔍 Specialized Metrology Analysis
@@ -175,47 +149,33 @@ def demo():
 
         with gr.Row():
             with gr.Column(scale=86):
-                gr.Markdown(
-                    """
-                    ### 📥 Step 1: Document Loading and Preparation
-                    Upload your metrology reports for expert analysis.
-                    """
-                )
+                gr.Markdown("### 📥 Step 1: Document Loading and Preparation")
+                gr.Markdown("Upload your metrology reports for expert analysis.")
+                
                 with gr.Row():
                     document = gr.Files(
-                        height=300,
+                        label="Upload Metrology Reports (PDF)",
                         file_count="multiple",
                         file_types=["pdf"],
                         interactive=True,
-                        label="Upload Metrology Reports (PDF)",
-                        info="Accepts multiple PDF files"
                     )
                 with gr.Row():
-                    db_btn = gr.Button(
-                        "Process Documents",
-                        variant="primary",
-                        size="lg"
-                    )
+                    db_btn = gr.Button("Process Documents")
                 with gr.Row():
                     db_progress = gr.Textbox(
                         value="Waiting for documents...",
-                        show_label=False,
-                        container=False
+                        label="Status"
                     )
                 
-                gr.Markdown(
-                    """
-                    ### 🤖 Analysis Engine Configuration
-                    Select and configure the AI model to best meet your needs.
-                    """
-                )
+                gr.Markdown("### 🤖 Analysis Engine Configuration")
+                gr.Markdown("Select and configure the AI model to best meet your needs.")
+                
                 with gr.Row():
                     llm_btn = gr.Radio(
-                        list_llm_simple,
+                        choices=list_llm_simple,
                         label="Available AI Models",
                         value=list_llm_simple[0],
-                        type="index",
-                        info="Choose the most suitable model for your analysis"
+                        type="index"
                     )
                 
                 with gr.Row():
@@ -226,9 +186,7 @@ def demo():
                                 maximum=1.0,
                                 value=0.5,
                                 step=0.1,
-                                label="Analysis Precision",
-                                info="Controls the balance between precision and creativity in analysis",
-                                interactive=True
+                                label="Analysis Precision"
                             )
                         with gr.Row():
                             slider_maxtokens = gr.Slider(
@@ -236,9 +194,7 @@ def demo():
                                 maximum=9192,
                                 value=4096,
                                 step=128,
-                                label="Response Length",
-                                info="Defines the level of detail in analyses",
-                                interactive=True
+                                label="Response Length"
                             )
                         with gr.Row():
                             slider_topk = gr.Slider(
@@ -246,21 +202,15 @@ def demo():
                                 maximum=10,
                                 value=3,
                                 step=1,
-                                label="Analysis Diversity",
-                                info="Controls the variety of perspectives in analysis",
-                                interactive=True
+                                label="Analysis Diversity"
                             )
                 
                 with gr.Row():
-                    qachain_btn = gr.Button(
-                        "Initialize Analysis Assistant",
-                        variant="primary",
-                        size="lg"
-                    )
+                    qachain_btn = gr.Button("Initialize Analysis Assistant")
                 with gr.Row():
                     llm_progress = gr.Textbox(
                         value="Waiting for initialization...",
-                        show_label=False
+                        label="Assistant Status"
                     )
 
             with gr.Column(scale=200):
@@ -280,8 +230,6 @@ def demo():
                 )
                 chatbot = gr.Chatbot(
                     height=505,
-                    show_label=True,
-                    container=True,
                     label="Metrology Analysis"
                 )
                 
@@ -289,43 +237,32 @@ def demo():
                     with gr.Row():
                         doc_source1 = gr.Textbox(
                             label="Technical Reference 1",
-                            lines=2,
-                            container=True,
-                            scale=20
+                            lines=2
                         )
-                        source1_page = gr.Number(label="Page", scale=1)
+                        source1_page = gr.Number(label="Page")
                     with gr.Row():
                         doc_source2 = gr.Textbox(
                             label="Technical Reference 2",
-                            lines=2,
-                            container=True,
-                            scale=20
+                            lines=2
                         )
-                        source2_page = gr.Number(label="Page", scale=1)
+                        source2_page = gr.Number(label="Page")
                     with gr.Row():
                         doc_source3 = gr.Textbox(
                             label="Technical Reference 3",
-                            lines=2,
-                            container=True,
-                            scale=20
+                            lines=2
                         )
-                        source3_page = gr.Number(label="Page", scale=1)
+                        source3_page = gr.Number(label="Page")
                 
                 with gr.Row():
                     msg = gr.Textbox(
                         placeholder="Enter your question about the metrology report...",
-                        container=True,
                         label="Your Query"
                     )
                 with gr.Row():
-                    submit_btn = gr.Button(
-                        "Submit Query",
-                        variant="primary"
-                    )
+                    submit_btn = gr.Button("Submit Query")
                     clear_btn = gr.ClearButton(
                         [msg, chatbot],
-                        value="Clear Conversation",
-                        variant="secondary"
+                        value="Clear Conversation"
                     )
 
         # Footer