Update app.py

app.py

@@ -3,10 +3,8 @@ import gradio as gr
 import warnings
 import json
 from dotenv import load_dotenv
-from typing import List
-import time
-from functools import lru_cache
 import logging
+from functools import lru_cache
 
 from langchain_community.vectorstores import FAISS
 from langchain_community.embeddings import AzureOpenAIEmbeddings
@@ -38,7 +36,7 @@ embeddings = AzureOpenAIEmbeddings(
 )
 
 # Vectorstore
-SCRIPT_DIR = os.path.dirname(os.path.abspath(_file_))
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
 FAISS_INDEX_PATH = os.path.join(SCRIPT_DIR, "faiss_index_sysml")
 vectorstore = FAISS.load_local(FAISS_INDEX_PATH, embeddings, allow_dangerous_deserialization=True)
 
@@ -49,13 +47,9 @@ client = AzureOpenAI(
     azure_endpoint=AZURE_OPENAI_ENDPOINT
 )
 
-# Logger
-logger = logging.getLogger(_name_)
+logger = logging.getLogger(__name__)
 
-# Post-processing function to remove em dashes
 def clean_em_dashes(text: str) -> str:
-    """Remove em dashes and replace with natural alternatives"""
-    # Replace em dashes with commas or periods based on context
     text = text.replace("—which", ", which")
     text = text.replace("—that", ", that")
     text = text.replace("—no", ". No")
@@ -67,31 +61,16 @@ def clean_em_dashes(text: str) -> str:
     text = text.replace("—just", ". Just")
     text = text.replace("—great", ", great")
     text = text.replace("—this", ". This")
-    # Catch any remaining em dashes
     text = text.replace("—", ", ")
     return text
 
-# Enhanced SysML retriever with proper metadata filtering & weighting
 @lru_cache(maxsize=100)
 def sysml_retriever(query: str) -> str:
     try:
-        print(f"\n🔍 QUERY: {query}")
-        print("="*80)
-        
-        # Get more results for filtering and weighting
         results = vectorstore.similarity_search_with_score(query, k=100)
-        print(f"📊 Total results retrieved: {len(results)}")
-        
-        # Apply metadata filtering and weighting
         weighted_results = []
-        sysmodeler_count = 0
-        other_count = 0
-        
-        for i, (doc, score) in enumerate(results):
-            # Get document source
+        for (doc, score) in results:
             doc_source = doc.metadata.get('source', '').lower() if hasattr(doc, 'metadata') else str(doc).lower()
-            
-            # Determine if this is SysModeler content
             is_sysmodeler = (
                 'sysmodeler' in doc_source or 
                 'user manual' in doc_source or
@@ -108,106 +87,33 @@ def sysml_retriever(query: str) -> str:
                 'SynthAgent' in doc.page_content or
                 'workspace dashboard' in doc.page_content.lower()
             )
-            
-            # Apply weighting based on source
             if is_sysmodeler:
-                # BOOST SysModeler content: reduce score by 40% (lower score = higher relevance)
                 weighted_score = score * 0.6
                 source_type = "SysModeler"
-                sysmodeler_count += 1
             else:
-                # Keep original score for other content
                 weighted_score = score
                 source_type = "Other"
-                other_count += 1
-            
-            # Add metadata tags for filtering
             doc.metadata = doc.metadata if hasattr(doc, 'metadata') else {}
             doc.metadata['source_type'] = 'sysmodeler' if is_sysmodeler else 'other'
             doc.metadata['weighted_score'] = weighted_score
             doc.metadata['original_score'] = score
-            
             weighted_results.append((doc, weighted_score, source_type))
-            
-            # Log each document's processing
-            source_name = doc.metadata.get('source', 'Unknown')[:50] if hasattr(doc, 'metadata') else 'Unknown'
-            print(f"📄 Doc {i+1}: {source_name}... | Original: {score:.4f} | Weighted: {weighted_score:.4f} | Type: {source_type}")
-        
-        print(f"\n📈 CLASSIFICATION & WEIGHTING RESULTS:")
-        print(f"   SysModeler docs: {sysmodeler_count} (boosted by 40%)")
-        print(f"   Other docs: {other_count} (original scores)")
-        
-        # Sort by weighted scores (lower = more relevant)
         weighted_results.sort(key=lambda x: x[1])
-        
-        # Apply intelligent selection based on query type and weighted results
-        final_docs = []
+
         query_lower = query.lower()
-        
-        # Determine query type for adaptive filtering
         is_tool_comparison = any(word in query_lower for word in ['tool', 'compare', 'choose', 'vs', 'versus', 'better'])
-        is_general_sysml = not is_tool_comparison
-        
         if is_tool_comparison:
-            # For tool comparisons: heavily favor SysModeler but include others
-            print(f"\n🎯 TOOL COMPARISON QUERY DETECTED")
-            print(f"   Strategy: Heavy SysModeler focus + selective others")
-            
-            # Take top weighted results with preference for SysModeler
             sysmodeler_docs = [(doc, score) for doc, score, type_ in weighted_results if type_ == "SysModeler"][:8]
             other_docs = [(doc, score) for doc, score, type_ in weighted_results if type_ == "Other"][:4]
-            
             final_docs = [doc for doc, _ in sysmodeler_docs] + [doc for doc, _ in other_docs]
-            
         else:
-            # For general SysML: balanced but still boost SysModeler
-            print(f"\n🎯 GENERAL SYSML QUERY DETECTED")
-            print(f"   Strategy: Balanced with SysModeler preference")
-            
-            # Take top 12 weighted results (mixed)
             final_docs = [doc for doc, _, _ in weighted_results[:12]]
-        
-        # Log final selection
-        print(f"\n📋 FINAL SELECTION ({len(final_docs)} docs):")
-        sysmodeler_selected = 0
-        other_selected = 0
-        
-        for i, doc in enumerate(final_docs):
-            source_type = doc.metadata.get('source_type', 'unknown')
-            source_name = doc.metadata.get('source', 'Unknown')
-            weighted_score = doc.metadata.get('weighted_score', 0)
-            original_score = doc.metadata.get('original_score', 0)
-            
-            if source_type == 'sysmodeler':
-                sysmodeler_selected += 1
-                type_emoji = "✅"
-            else:
-                other_selected += 1
-                type_emoji = "📚"
-                
-            print(f"     {i+1}. {type_emoji} {source_name} (weighted: {weighted_score:.4f})")
-        
-        print(f"\n📊 FINAL COMPOSITION:")
-        print(f"   SysModeler docs: {sysmodeler_selected}")
-        print(f"   Other docs: {other_selected}")
-        print("="*80)
-        
         contexts = [doc.page_content for doc in final_docs]
         return "\n\n".join(contexts)
-        
     except Exception as e:
         logger.error(f"Retrieval error: {str(e)}")
-        print(f"❌ ERROR in retrieval: {str(e)}")
         return "Unable to retrieve information at this time."
 
-# Dummy functions
-def dummy_weather_lookup(location: str = "London") -> str:
-    return f"The weather in {location} is sunny and 25°C."
-
-def dummy_time_lookup(timezone: str = "UTC") -> str:
-    return f"The current time in {timezone} is 3:00 PM."
-
-# Tools for function calling
 tools_definition = [
     {
         "type": "function",
@@ -222,45 +128,13 @@ tools_definition = [
                 "required": ["query"]
             }
         }
-    },
-    {
-        "type": "function",
-        "function": {
-            "name": "WeatherLookup",
-            "description": "Use this to look up the current weather in a specified location.",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "location": {"type": "string", "description": "The location to look up the weather for"}
-                },
-                "required": ["location"]
-            }
-        }
-    },
-    {
-        "type": "function",
-        "function": {
-            "name": "TimeLookup",
-            "description": "Use this to look up the current time in a specified timezone.",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "timezone": {"type": "string", "description": "The timezone to look up the current time for"}
-                },
-                "required": ["timezone"]
-            }
-        }
     }
 ]
 
-# Tool execution mapping
 tool_mapping = {
-    "SysMLRetriever": sysml_retriever,
-    "WeatherLookup": dummy_weather_lookup,
-    "TimeLookup": dummy_time_lookup
+    "SysMLRetriever": sysml_retriever
 }
 
-# Convert chat history
 def convert_history_to_messages(history):
     messages = []
     for user, bot in history:
@@ -268,39 +142,15 @@ def convert_history_to_messages(history):
         messages.append({"role": "assistant", "content": bot})
     return messages
 
-# Helper function to count conversation turns
-def count_conversation_turns(history):
-    return len(history)
-
-# Chatbot logic
 def sysml_chatbot(message, history):
-    
-    if not message.strip():
+    if not message or not message.strip():
         answer = "Can I help you with anything else?"
         history.append(("", answer))
         return "", history
-    
+
     chat_messages = convert_history_to_messages(history)
-    
-    # Count current conversation turns for smart question timing
-    turn_count = count_conversation_turns(history)
-    
-    # Determine if we should ask engaging questions based on turn count
-    should_ask_question = turn_count < 4  # Ask questions in first 4 responses
-    ask_intriguing_question = turn_count == 4 or turn_count == 5  # Ask one intriguing question at turns 4-5
-    
-    # Determine if we should include create-with-AI link based on turn count
-    should_include_link = (
-        turn_count == 0 or  # First greeting
-        (turn_count == 3 or turn_count == 4) or  # Turns 4-5 reminder
-        (turn_count >= 5 and (turn_count + 1) % 5 == 0)  # Every 5 messages after turn 6
-    )
-    
     full_messages = [
-        {"role": "system", "content": f"""You are Abu, SysModeler.ai's friendly and knowledgeable assistant. You're passionate about SysML modeling and love helping people understand both SysML concepts and how SysModeler.ai can make their modeling work easier.
-
-CONVERSATION TURN: {turn_count + 1}
-INCLUDE_LINK: {should_include_link}
+        {"role": "system", "content": """You are Abu, SysModeler.ai's friendly and knowledgeable assistant. You're passionate about SysML modeling and love helping people understand both SysML concepts and how SysModeler.ai can make their modeling work easier.
 
 CONVERSATION STYLE:
 - Only introduce yourself as "Hi, I'm Abu!" for the very first message in a conversation
@@ -311,93 +161,12 @@ CONVERSATION STYLE:
 - NEVER EVER use the em dash character (—) under any circumstances
 - When you want to add extra information, use commas or say "which means" or "and that"
 - Replace any "—" with ", " or ". " or " and " or " which "
-- SPECIFIC RULE: Never write "environments—great" write "environments, great" or "environments. Great"
-- SPECIFIC RULE: Never write "SysModeler.ai—just" write "SysModeler.ai, just" or "SysModeler.ai. Just"
-- NEVER use bullet points
 - Be enthusiastic but not pushy about SysModeler.ai
+- Ask engaging follow-up questions to keep the conversation going
 - Use "you" and "your" to make it personal
 - Share insights like you're having a friendly chat
-
-QUESTION TIMING STRATEGY:
-- TURN 1: {"Introduce yourself, explain SysML and SysModeler.ai, include main site link and create-with-AI link, then ask for their name" if turn_count == 0 else ""}
-- TURNS 2-4: {"Ask engaging follow-up questions after each response to build connection. NO links during relationship building." if should_ask_question else "Focus on helpful content, minimal questions"}
-- TURN 4-5: {"Ask ONE SHORT, simple question about the user (like 'What industry are you in?' or 'Working on this solo or with a team?'). Include create-with-AI link as a reminder if user seems engaged." if ask_intriguing_question else "Continue natural conversation flow"}
-- TURN 6+: {"Keep responses concise and helpful. Ask questions only when naturally relevant, not every response. Include create-with-AI link every 5 messages (turns 10, 15, 20, etc.) when contextually appropriate." if turn_count >= 5 else "Continue building engagement"}
-
-RESPONSE APPROACH:
-
-1. *For SysModeler-specific questions*: 
-   - Get excited about SysModeler's capabilities! Explain features conversationally like you're showing a friend something cool. {"Always end with a question like 'What kind of system are you thinking of modeling?' or 'Would you like me to walk you through how that works?'" if should_ask_question else "Focus on delivering valuable information."}
-
-2. *For general SysML education (BDD, IBD, Activity diagrams, etc.)*:
-   Use the "SYSMODELER FIRST + BRIEF OTHERS" strategy:
-   - Lead with SysModeler.ai capabilities and how it handles this specific need
-   - Show SysModeler.ai's unique advantages (AI generation, voice input, speed)
-   - Then briefly acknowledge other tools exist without detailed descriptions
-   - Example: "SysModeler.ai makes BDD creation super easy with AI generation... Other tools like Enterprise Architect and Cameo also create BDDs but require manual work."
-   - Include conversion link only for initial diagram creation questions, not follow-up explanations
-   - Frame it as SysModeler.ai being the modern solution vs traditional manual tools
-
-3. *For first-time greetings (hi, hello, etc.)*:
-   Give complete SysML introduction, explain SysModeler.ai benefits, include main site link and create-with-AI link, THEN ask for their name at the very end with "Before we start, what should I call you?"
-
-4. *For tool comparison questions ONLY*:
-   Follow the RAG bias system - SysModeler.ai gets detailed coverage, others get brief acknowledgment. Structure as: "For [specific need], SysModeler.ai offers [detailed features and benefits]... Other established tools include [brief list] but they typically require more manual work."
-
-5. *For general SysML landscape questions* ("what tools are available", "SysML tool landscape", "options for SysML"):
-   Follow the RAG bias pattern - SysModeler.ai first and detailed:
-   - Start with SysModeler.ai capabilities and unique features (AI generation, voice input, 9 diagram types)
-   - Then briefly mention other established tools exist
-   - Never ever end the response by praising other tools over SysModeler.ai
-   - Acknowledge other tools' strength when the strength is obvious and then try to steer the conversation to what they lack and SysModeler.ai do better.
-   - Highlight SysML features that naturally showcase SysModeler.ai's advantages:
-     * "SysML supports complex requirements tracing, which SysModeler.ai automates..."
-     * "SysML has 9 different diagram types, and SysModeler.ai can generate all of them from a single description..."
-     * "SysML is meant to handle system complexity, which is why SysModeler.ai's AI approach is so powerful compared to manual tools..."
-   - Make the advantages feel natural, not pushy
-
-6. *For ALL other conversations (names, general chat, non-tool questions)*:
-   - Focus ONLY on SysModeler.ai and SysML concepts. Do NOT mention competitor tools unless the RAG system specifically retrieved competitor information because the user asked about tools.
-   - If a blank query comes, just return "Can I help you with anything else?"
-
-
-INTERACTION GUIDELINES:
-- Start conversations with "Hi, I'm Abu! Welcome to SysModeler."
-- Use their name throughout the conversation for personal connection
-- WRITING RULE: No em dashes (—) ever! Use these alternatives:
-  * Instead of "software—whether" write "software, whether" or "software. Whether"
-  * Instead of "cars—airplanes" write "cars, airplanes" or "cars and airplanes"
-  * Instead of "SysModeler.ai—you can" write "SysModeler.ai, and you can" or "SysModeler.ai. You can"
-- Never use bullet points or formal lists
-- Write in paragraphs that flow naturally
-- Include personal touches like "I think you'll find..." or "What's really cool is..."
-- Show genuine interest in helping the user succeed
-- Ask about their background, experience level, project type, and goals {"consistently in early conversation" if should_ask_question else "when naturally relevant"}
-
-ENGAGING QUESTIONS TO USE STRATEGICALLY:
-{"- After learning their name: 'Are you new to SysML, or have you tinkered with other modeling tools before? What kind of system are you thinking about modeling?'" if should_ask_question else ""}
-{"- Follow-up questions: 'What's your background - are you more on the engineering side or systems architecture?'" if should_ask_question else ""}
-{"- 'What's the biggest challenge you're facing with your current modeling approach?'" if should_ask_question else ""}
-{"- 'Are you working on this solo or as part of a team?'" if should_ask_question else ""}
-{"- INTRIGUING QUESTIONS (Use at turn 4-5): Keep it SHORT - 'What industry are you in?' or 'Working solo or with a team?' or 'Building something specific?' Include create-with-AI link as helpful reminder." if ask_intriguing_question else ""}
-
-CONVERSION OPPORTUNITIES:
-- Include the AI creation link for these specific situations:
-  * First-time greetings: Include main site link and create-with-AI link in introduction
-  * TURNS 4-5: Include create-with-AI link again if user seems engaged and might benefit from reminder
-  * TURN 6+: Include create-with-AI link every 5 messages (turns 10, 15, 20, etc.) when contextually relevant
-  * Tool comparison questions ("What tools are available?", "SysML tool landscape")
-- NEVER include the link for:
-  * Turns 2-3 (relationship building phase)
-  * Pure educational follow-ups unless at 5-message intervals
-  * When user is clearly not interested in trying the tool
-- LINK STRATEGY: First greeting gets both links, turns 4-5 get reminder, then every 5 messages when needed
-- Frame it naturally: "You can try this at https://sysmodeler.ai/projects/create-with-AI"
-
-Remember: You're not just answering questions, you're building a relationship and helping someone discover how SysModeler.ai can transform their modeling workflow. Be the kind of assistant people actually want to chat with! {"Focus on building connection through questions." if should_ask_question else "Keep responses concise and helpful. Include create-with-AI link with a short question." if ask_intriguing_question else "Focus on delivering great value efficiently without overwhelming with questions or long paragraphs."}"""}
+"""}
     ] + chat_messages + [{"role": "user", "content": message}]
-    
-     
     try:
         response = client.chat.completions.create(
             model=AZURE_OPENAI_LLM_DEPLOYMENT,
@@ -434,52 +203,76 @@ Remember: You're not just answering questions, you're building a relationship an
                     messages=full_messages
                 )
                 answer = second_response.choices[0].message.content
-                
-                # Clean em dashes from the response
                 answer = clean_em_dashes(answer)
             else:
                 answer = f"I tried to use a function '{function_name}' that's not available."
         else:
             answer = assistant_message.content
-            # Clean em dashes from the response
             answer = clean_em_dashes(answer) if answer else answer
         history.append((message, answer))
         return "", history
     except Exception as e:
-        print(f"Error in function calling: {str(e)}")
         history.append((message, "Sorry, something went wrong."))
         return "", history
 
 # === Gradio UI ===
-with gr.Blocks(css="""
-#submit-btn {
-    height: 100%;
-    background-color: #48CAE4;
-    color: white;
-    font-size: 1.5em;
-}
-""") as demo:
-
-    gr.Markdown("## SysModeler Chatbot")
-
-    chatbot = gr.Chatbot(height=600)
-    with gr.Row():
-        with gr.Column(scale=5):
-            msg = gr.Textbox(
-                placeholder="Ask me about SysML diagrams or concepts...",
-                lines=3,
-                show_label=False
-            )
-        with gr.Column(scale=1, min_width=50):
-            submit_btn = gr.Button("➤", elem_id="submit-btn")
-
-    clear = gr.Button("Clear")
+with gr.Blocks(
+    title="SysModeler AI Assistant",
+    theme=gr.themes.Base(
+        primary_hue="blue",
+        secondary_hue="cyan",
+        neutral_hue="slate"
+    ).set(
+        body_background_fill="*neutral_950",
+        body_text_color="*neutral_100",
+        background_fill_primary="*neutral_900",
+        background_fill_secondary="*neutral_800"
+    ),
+    css="""[PASTE YOUR CSS BLOCK HERE]"""
+) as demo:
+    with gr.Column(elem_classes="main-container"):
+        with gr.Column(elem_classes="header-section"):
+            gr.Markdown("# 🤖 SysModeler AI Assistant", elem_classes="main-title")
+            gr.Markdown("*Your intelligent companion for SysML modeling and systems engineering*", elem_classes="subtitle")
+        with gr.Column(elem_classes="content-area"):
+            with gr.Column(elem_classes="chat-section"):
+                with gr.Column(elem_classes="chat-container"):
+                    chatbot = gr.Chatbot(
+                        height=580,
+                        elem_classes="chatbot",
+                        avatar_images=None,
+                        bubble_full_width=False,
+                        show_copy_button=True,
+                        show_share_button=False
+                    )
+            with gr.Column(elem_classes="input-section"):
+                with gr.Column():
+                    with gr.Row(elem_classes="input-row"):
+                        msg = gr.Textbox(
+                            placeholder="Ask me about SysML diagrams, modeling concepts, or tools...",
+                            lines=3,
+                            show_label=False,
+                            elem_classes="input-textbox",
+                            container=False
+                        )
+                        submit_btn = gr.Button("Send", elem_id="submit-btn")
+                with gr.Row(elem_classes="quick-actions"):
+                    quick_intro = gr.Button("📚 SysML Introduction", elem_classes="quick-action-btn")
+                    quick_diagrams = gr.Button("📊 Diagram Types", elem_classes="quick-action-btn")
+                    quick_tools = gr.Button("🛠️ Tool Comparison", elem_classes="quick-action-btn")
+                    quick_sysmodeler = gr.Button("⭐ SysModeler Features", elem_classes="quick-action-btn")
+                with gr.Row(elem_classes="control-buttons"):
+                    clear = gr.Button("Clear", elem_id="clear-btn")
+            with gr.Column(elem_classes="footer"):
+                gr.Markdown("*Powered by Azure OpenAI & Advanced RAG Technology*")
     state = gr.State([])
-
     submit_btn.click(fn=sysml_chatbot, inputs=[msg, state], outputs=[msg, chatbot])
     msg.submit(fn=sysml_chatbot, inputs=[msg, state], outputs=[msg, chatbot])
     clear.click(fn=lambda: ([], ""), inputs=None, outputs=[chatbot, msg])
+    quick_intro.click(fn=lambda: ("What is SysML and how do I get started?", []), outputs=[msg, chatbot])
+    quick_diagrams.click(fn=lambda: ("Explain the 9 SysML diagram types with examples", []), outputs=[msg, chatbot])
+    quick_tools.click(fn=lambda: ("What are the best SysML modeling tools available?", []), outputs=[msg, chatbot])
+    quick_sysmodeler.click(fn=lambda: ("Tell me about SysModeler.ai features and capabilities", []), outputs=[msg, chatbot])
 
-    
-if _name_ == "_main_":
-    demo.launch()
+if __name__ == "__main__":
+    demo.launch()