| import os |
| import gradio as gr |
| from langchain_openai import ChatOpenAI |
| from crewai import Agent, Task, Crew, LLM |
| from crewai_tools import SerperDevTool |
| from typing import List, Tuple |
| import time |
|
|
| OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY") |
| SERPER_API_KEY = os.getenv("SERPER_API_KEY") |
|
|
| if not OPENROUTER_API_KEY: |
| raise ValueError("Missing OPENROUTER_API_KEY environment variable") |
| if not SERPER_API_KEY: |
| raise ValueError("Missing SERPER_API_KEY environment variable") |
|
|
|
|
| crew_llm = LLM( |
| model="openrouter/deepseek/deepseek-r1", |
| base_url="https://openrouter.ai/api/v1", |
| api_key=OPENROUTER_API_KEY, |
| temperature=0.7 |
| ) |
|
|
|
|
| direct_llm = ChatOpenAI( |
| model="deepseek/deepseek-r1", |
| openai_api_key=OPENROUTER_API_KEY, |
| openai_api_base="https://openrouter.ai/api/v1", |
| temperature=0.7, |
| max_tokens=2000 |
| ) |
|
|
| class ConstructionChatbot: |
| def __init__(self): |
| self.memory: List[Tuple[str, str]] = [] |
| self.setup_tools() |
| self.setup_crew() |
| |
| def setup_tools(self): |
| """Set up web search tools""" |
| try: |
| self.search_tool = SerperDevTool() |
| print("✅ Web search tool initialized successfully") |
| except Exception as e: |
| self.search_tool = None |
| print(f"⚠️ Warning: Could not initialize web search tool: {e}") |
| |
| def setup_crew(self): |
| """Set up CrewAI agents and tasks""" |
| |
| tools = [] |
| if self.search_tool: |
| tools.append(self.search_tool) |
| |
|
|
| self.construction_agent = Agent( |
| role='Construction Expert Assistant', |
| goal='Provide accurate construction-related information ONLY. Reject all non-construction queries.', |
| backstory="""You are a specialized construction industry expert with deep knowledge in: |
| - Building safety and regulations |
| - Fire safety codes and compliance |
| - Construction materials and costs |
| - Project management methodologies |
| - Heavy machinery and equipment |
| - Civil engineering principles |
| - Structural design and analysis |
| - Site management and safety protocols |
| |
| IMPORTANT: You MUST ONLY respond to construction-related questions. |
| If a user asks about anything not related to construction, building, |
| engineering, safety, materials, or project management, you must respond |
| with EXACTLY: "I can only assist with construction-related queries. Please ask about building, safety, materials, project management, or engineering topics." |
| |
| When you need current information about construction topics, use the search tool.""", |
| llm=crew_llm, |
| tools=tools, |
| verbose=True, |
| allow_delegation=False, |
| max_iter=3, |
| max_execution_time=45 |
| ) |
| |
|
|
| if self.search_tool: |
| self.research_agent = Agent( |
| role='Construction Research Specialist', |
| goal='Search and gather current construction-related information from the internet ONLY', |
| backstory="""You are a specialized researcher focused exclusively on construction industry topics. |
| You search for the most current information about: |
| - Construction practices and regulations |
| - Building costs and material prices |
| - Safety standards and compliance requirements |
| - Industry trends and new technologies |
| - Engineering standards and best practices |
| |
| You ONLY research construction-related topics. If asked to research non-construction |
| topics, decline politely and redirect to construction subjects.""", |
| llm=crew_llm, |
| tools=[self.search_tool], |
| verbose=True, |
| allow_delegation=False, |
| max_iter=2, |
| max_execution_time=30 |
| ) |
| else: |
| self.research_agent = None |
| |
| def add_to_memory(self, user_query: str, response: str): |
| """Add interaction to rolling memory window""" |
| self.memory.append((user_query, response)) |
| if len(self.memory) > 5: |
| self.memory.pop(0) |
| |
| def get_chat_history(self) -> str: |
| """Format chat history for prompt""" |
| if not self.memory: |
| return "No previous conversation." |
| |
| history = "" |
| for i, (user_msg, bot_msg) in enumerate(self.memory, 1): |
| history += f"Message {i}:\nUser: {user_msg}\nAssistant: {bot_msg}\n\n" |
| return history.strip() |
| |
| def is_construction_related(self, query: str) -> bool: |
| """Simple check if query is construction-related""" |
| construction_keywords = [ |
| 'construction', 'building', 'concrete', 'steel', 'foundation', 'safety', |
| 'project management', 'engineering', 'structure', 'material', 'cost', |
| 'regulation', 'fire safety', 'osha', 'machinery', 'equipment', 'site', |
| 'contractor', 'cement', 'rebar', 'excavation', 'blueprint', 'architect', |
| 'electrical', 'plumbing', 'hvac', 'roofing', 'insulation', 'drywall' |
| ] |
| |
| query_lower = query.lower() |
| return any(keyword in query_lower for keyword in construction_keywords) |
| |
| def generate_response_with_crew(self, user_query: str) -> str: |
| """Generate response using CrewAI with web search capabilities""" |
|
|
| if not self.is_construction_related(user_query): |
| response = "I can only assist with construction-related queries. Please ask about building, safety, materials, project management, or engineering topics." |
| self.add_to_memory(user_query, response) |
| return response |
| |
| chat_history = self.get_chat_history() |
| |
| try: |
|
|
| search_keywords = ['current', 'latest', 'recent', 'today', '2024', '2025', 'price', 'cost', 'regulation', 'new', 'trend'] |
| needs_search = any(keyword in user_query.lower() for keyword in search_keywords) |
| |
| if needs_search and self.research_agent: |
|
|
| research_task = Task( |
| description=f"""Search for current construction-related information about: {user_query} |
| |
| Focus on finding: |
| - Latest construction industry data |
| - Current material prices and costs |
| - Recent regulations and safety updates |
| - New construction technologies and methods |
| - Industry trends and market information |
| |
| Search query should be concise and focused on construction industry information. |
| """, |
| expected_output="Current, accurate construction industry information and data", |
| agent=self.research_agent |
| ) |
| |
|
|
| response_task = Task( |
| description=f"""Based on research findings and chat history, provide a comprehensive response to: {user_query} |
| |
| Chat history: {chat_history} |
| |
| Guidelines: |
| - Use the research data to provide accurate, current information |
| - Focus on construction industry expertise |
| - Provide practical, actionable advice |
| - Include specific details like prices, regulations, or technical specifications when available |
| - Structure the response clearly and professionally |
| """, |
| expected_output="Detailed, informative construction industry response with current data", |
| agent=self.construction_agent, |
| context=[research_task] |
| ) |
| |
|
|
| crew = Crew( |
| agents=[self.research_agent, self.construction_agent], |
| tasks=[research_task, response_task], |
| verbose=False |
| ) |
| |
| else: |
|
|
| response_task = Task( |
| description=f"""Provide expert construction advice for: {user_query} |
| |
| Chat history: {chat_history} |
| |
| Guidelines: |
| - Draw from your construction industry expertise |
| - Provide detailed, accurate information |
| - Include relevant safety considerations |
| - Suggest best practices and standards |
| - Structure the response professionally |
| """, |
| expected_output="Expert construction industry advice and information", |
| agent=self.construction_agent |
| ) |
| |
|
|
| crew = Crew( |
| agents=[self.construction_agent], |
| tasks=[response_task], |
| verbose=False |
| ) |
| |
|
|
| result = crew.kickoff() |
| response = str(result).strip() |
| |
|
|
| if not response or len(response) < 10: |
| response = "I apologize, but I'm having trouble generating a proper response. Could you please rephrase your construction-related question?" |
| |
|
|
| self.add_to_memory(user_query, response) |
| return response |
| |
| except Exception as e: |
| print(f"CrewAI Error: {e}") |
|
|
| return self.generate_response_direct(user_query) |
| |
| def generate_response_direct(self, user_query: str) -> str: |
| """Fallback method using direct LLM with construction filtering""" |
| if not self.is_construction_related(user_query): |
| response = "I can only assist with construction-related queries. Please ask about building, safety, materials, project management, or engineering topics." |
| self.add_to_memory(user_query, response) |
| return response |
| |
| chat_history = self.get_chat_history() |
| |
| prompt = f"""You are a specialized construction industry AI assistant with expertise in building, safety, materials, project management, and engineering. |
| |
| Chat history: {chat_history} |
| |
| User question: {user_query} |
| |
| Provide a detailed, professional response focusing on construction industry knowledge. Include specific information about safety standards, building codes, material specifications, cost estimates, or project management advice as relevant to the question. |
| |
| Response:""" |
|
|
| try: |
| response = direct_llm.invoke(prompt) |
| if hasattr(response, 'content'): |
| response_text = response.content |
| else: |
| response_text = str(response) |
| |
| self.add_to_memory(user_query, response_text) |
| return response_text |
| |
| except Exception as e: |
| fallback_response = f"""I apologize, but I'm experiencing technical difficulties. However, I can still help with construction-related questions about safety, materials, project management, and engineering. Please try rephrasing your question. |
| |
| Technical error: {str(e)[:100]}...""" |
| |
| self.add_to_memory(user_query, fallback_response) |
| return fallback_response |
| |
| def generate_response(self, user_query: str) -> str: |
| """Main response generation method""" |
| try: |
| return self.generate_response_with_crew(user_query) |
| except Exception as e: |
| print(f"Crew method failed, using direct method: {e}") |
| return self.generate_response_direct(user_query) |
|
|
|
|
| chatbot = ConstructionChatbot() |
|
|
| custom_css = """ |
| /* Construction-themed color palette */ |
| :root { |
| --construction-orange: #ff6b1a; |
| --construction-yellow: #ffc107; |
| --construction-blue: #1e88e5; |
| --construction-green: #4caf50; |
| --construction-red: #f44336; |
| --construction-dark: #2d3436; |
| --construction-darker: #1a1a1a; |
| --construction-light-gray: #ecf0f1; |
| --construction-medium-gray: #95a5a6; |
| --construction-steel: #34495e; |
| } |
| |
| /* Main container styling */ |
| .gradio-container { |
| background: linear-gradient(135deg, var(--construction-dark) 0%, var(--construction-darker) 100%); |
| font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; |
| min-height: 100vh; |
| } |
| |
| /* Header styling */ |
| .construction-header { |
| background: linear-gradient(45deg, var(--construction-orange), var(--construction-yellow)); |
| color: #000; |
| text-align: center; |
| padding: 25px; |
| font-weight: bold; |
| font-size: 28px; |
| border-radius: 15px; |
| margin-bottom: 25px; |
| box-shadow: 0 8px 25px rgba(255, 107, 26, 0.4); |
| border: 3px solid var(--construction-yellow); |
| text-shadow: 1px 1px 2px rgba(0,0,0,0.1); |
| } |
| |
| /* Chat container - Custom styling */ |
| .chatbot { |
| border: 3px solid var(--construction-orange) !important; |
| border-radius: 15px !important; |
| background: linear-gradient(135deg, var(--construction-steel), #2c3e50) !important; |
| box-shadow: 0 10px 30px rgba(0, 0, 0, 0.3) !important; |
| } |
| |
| /* Message bubbles styling */ |
| .message-wrap { |
| margin: 15px 0 !important; |
| } |
| |
| .message-wrap.svelte-1lcyrx4.user { |
| justify-content: flex-end !important; |
| } |
| |
| .message-wrap.svelte-1lcyrx4.bot { |
| justify-content: flex-start !important; |
| } |
| |
| /* User message styling */ |
| .message-wrap.user .message { |
| background: linear-gradient(135deg, var(--construction-orange), var(--construction-yellow)) !important; |
| color: #000 !important; |
| border-radius: 20px 20px 5px 20px !important; |
| padding: 15px 20px !important; |
| max-width: 75% !important; |
| font-weight: 500 !important; |
| box-shadow: 0 4px 15px rgba(255, 107, 26, 0.3) !important; |
| border: 2px solid var(--construction-yellow) !important; |
| } |
| |
| /* Bot message styling */ |
| .message-wrap.bot .message { |
| background: linear-gradient(135deg, var(--construction-blue), #1565c0) !important; |
| color: #ffffff !important; |
| border-radius: 20px 20px 20px 5px !important; |
| padding: 15px 20px !important; |
| max-width: 75% !important; |
| box-shadow: 0 4px 15px rgba(30, 136, 229, 0.3) !important; |
| border-left: 5px solid var(--construction-green) !important; |
| } |
| |
| /* Input styling */ |
| .input-container { |
| background: linear-gradient(135deg, var(--construction-steel), #2c3e50); |
| border-radius: 25px; |
| padding: 15px; |
| border: 3px solid var(--construction-orange); |
| margin-top: 20px; |
| box-shadow: 0 5px 20px rgba(0, 0, 0, 0.2); |
| } |
| |
| /* Textbox styling */ |
| .textbox { |
| background: var(--construction-dark) !important; |
| border: 2px solid var(--construction-orange) !important; |
| border-radius: 20px !important; |
| color: var(--construction-light-gray) !important; |
| padding: 15px 20px !important; |
| font-size: 16px !important; |
| } |
| |
| .textbox:focus { |
| border-color: var(--construction-yellow) !important; |
| box-shadow: 0 0 15px rgba(255, 193, 7, 0.3) !important; |
| } |
| |
| /* Button styling */ |
| .btn-primary { |
| background: linear-gradient(135deg, var(--construction-orange), var(--construction-yellow)) !important; |
| color: #000 !important; |
| border: none !important; |
| border-radius: 20px !important; |
| padding: 15px 25px !important; |
| font-weight: bold !important; |
| font-size: 16px !important; |
| cursor: pointer !important; |
| transition: all 0.3s ease !important; |
| box-shadow: 0 4px 15px rgba(255, 107, 26, 0.3) !important; |
| } |
| |
| .btn-primary:hover { |
| background: linear-gradient(135deg, var(--construction-yellow), #ffeb3b) !important; |
| transform: translateY(-2px) !important; |
| box-shadow: 0 6px 20px rgba(255, 193, 7, 0.4) !important; |
| } |
| |
| .btn-secondary { |
| background: linear-gradient(135deg, var(--construction-steel), #34495e) !important; |
| color: var(--construction-light-gray) !important; |
| border: 2px solid var(--construction-medium-gray) !important; |
| border-radius: 15px !important; |
| padding: 12px 20px !important; |
| font-weight: bold !important; |
| transition: all 0.3s ease !important; |
| } |
| |
| .btn-secondary:hover { |
| background: linear-gradient(135deg, var(--construction-blue), #1976d2) !important; |
| border-color: var(--construction-blue) !important; |
| transform: translateY(-2px) !important; |
| } |
| |
| /* Status and info styling */ |
| .status-info { |
| background: linear-gradient(135deg, rgba(76, 175, 80, 0.1), rgba(30, 136, 229, 0.1)); |
| border: 2px solid var(--construction-green); |
| border-radius: 12px; |
| padding: 15px; |
| margin: 15px 0; |
| color: var(--construction-light-gray); |
| font-size: 14px; |
| box-shadow: 0 3px 10px rgba(76, 175, 80, 0.2); |
| } |
| |
| /* Warning/info boxes */ |
| .warning-box { |
| background: linear-gradient(135deg, rgba(244, 67, 54, 0.1), rgba(255, 107, 26, 0.1)); |
| border: 2px solid var(--construction-red); |
| border-radius: 12px; |
| padding: 20px; |
| margin: 20px 0; |
| color: var(--construction-light-gray); |
| box-shadow: 0 4px 15px rgba(244, 67, 54, 0.2); |
| } |
| |
| .info-box { |
| background: linear-gradient(135deg, rgba(30, 136, 229, 0.1), rgba(255, 193, 7, 0.1)); |
| border: 2px solid var(--construction-blue); |
| border-radius: 12px; |
| padding: 20px; |
| margin: 20px 0; |
| color: var(--construction-light-gray); |
| box-shadow: 0 4px 15px rgba(30, 136, 229, 0.2); |
| } |
| |
| .success-box { |
| background: linear-gradient(135deg, rgba(76, 175, 80, 0.1), rgba(255, 193, 7, 0.1)); |
| border: 2px solid var(--construction-green); |
| border-radius: 12px; |
| padding: 20px; |
| margin: 20px 0; |
| color: var(--construction-light-gray); |
| box-shadow: 0 4px 15px rgba(76, 175, 80, 0.2); |
| } |
| |
| /* Headings */ |
| h1, h2, h3, h4 { |
| color: var(--construction-orange) !important; |
| text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3) !important; |
| font-weight: bold !important; |
| } |
| |
| /* Links */ |
| a { |
| color: var(--construction-yellow) !important; |
| text-decoration: none !important; |
| font-weight: bold !important; |
| } |
| |
| a:hover { |
| color: var(--construction-orange) !important; |
| text-decoration: underline !important; |
| } |
| |
| /* Code styling */ |
| code { |
| background: var(--construction-darker) !important; |
| color: var(--construction-yellow) !important; |
| padding: 2px 6px !important; |
| border-radius: 4px !important; |
| font-family: 'Courier New', monospace !important; |
| } |
| |
| /* Lists */ |
| ul, ol { |
| color: var(--construction-light-gray); |
| } |
| |
| li { |
| margin: 8px 0; |
| padding-left: 5px; |
| border-left: 3px solid var(--construction-orange); |
| padding-left: 10px; |
| margin-left: 10px; |
| } |
| |
| /* Status indicators */ |
| .status-indicator { |
| display: inline-block; |
| width: 12px; |
| height: 12px; |
| border-radius: 50%; |
| margin-right: 10px; |
| animation: pulse 2s infinite; |
| } |
| |
| .status-online { |
| background: var(--construction-green); |
| box-shadow: 0 0 15px rgba(76, 175, 80, 0.6); |
| } |
| |
| .status-offline { |
| background: var(--construction-red); |
| box-shadow: 0 0 15px rgba(244, 67, 54, 0.6); |
| } |
| |
| @keyframes pulse { |
| 0% { opacity: 1; } |
| 50% { opacity: 0.5; } |
| 100% { opacity: 1; } |
| } |
| |
| /* Badge styling */ |
| .badge { |
| background: linear-gradient(135deg, var(--construction-blue), #1565c0); |
| color: white; |
| padding: 6px 12px; |
| border-radius: 15px; |
| font-size: 12px; |
| font-weight: bold; |
| display: inline-block; |
| margin: 2px; |
| box-shadow: 0 2px 8px rgba(30, 136, 229, 0.3); |
| } |
| |
| /* Scrollbar styling */ |
| ::-webkit-scrollbar { |
| width: 10px; |
| } |
| |
| ::-webkit-scrollbar-track { |
| background: var(--construction-darker); |
| border-radius: 5px; |
| } |
| |
| ::-webkit-scrollbar-thumb { |
| background: linear-gradient(135deg, var(--construction-orange), var(--construction-yellow)); |
| border-radius: 5px; |
| } |
| |
| ::-webkit-scrollbar-thumb:hover { |
| background: linear-gradient(135deg, var(--construction-yellow), #ffeb3b); |
| } |
| |
| /* Responsive design */ |
| @media (max-width: 768px) { |
| .construction-header { |
| font-size: 20px; |
| padding: 20px 15px; |
| } |
| |
| .message { |
| max-width: 90% !important; |
| padding: 12px 15px !important; |
| } |
| } |
| |
| /* Animation for new messages */ |
| .message-wrap { |
| animation: slideIn 0.3s ease-out; |
| } |
| |
| @keyframes slideIn { |
| from { |
| opacity: 0; |
| transform: translateY(20px); |
| } |
| to { |
| opacity: 1; |
| transform: translateY(0); |
| } |
| } |
| """ |
|
|
| def create_interface(): |
| """Create the Gradio interface with construction theme""" |
| |
| with gr.Blocks(css=custom_css, title="🏗️ Construction AI Assistant - DeepSeek R1 🏗️") as interface: |
| |
|
|
| gr.HTML(""" |
| <div class="construction-header"> |
| 🏗️ CONSTRUCTION COMPANY AI ASSISTANT 🏗️ |
| <br> |
| <small style="font-size: 18px; font-weight: normal; opacity: 0.9;"> |
| Powered by <span class="badge">DeepSeek R1</span> | Expert Construction Guidance with Live Web Search |
| </small> |
| </div> |
| """) |
| |
|
|
| def get_status_info(): |
| search_status = "🌐 Web Search: ONLINE" if chatbot.search_tool else "🌐 Web Search: OFFLINE" |
| search_class = "status-online" if chatbot.search_tool else "status-offline" |
| memory_count = len(chatbot.memory) |
| |
| return f""" |
| <div class="status-info"> |
| <span class="status-indicator {search_class}"></span> |
| <strong>🧠 DeepSeek R1 ACTIVE</strong> | |
| <strong>{search_status}</strong> | |
| <strong>💭 Memory: {memory_count}/5</strong> | |
| <strong>🏗️ Construction Expert Ready</strong> |
| <br> |
| <small>🔍 Real-time construction data | 📊 Current prices & regulations | ⚡ Lightning fast responses</small> |
| </div> |
| """ |
| |
| memory_status = gr.HTML(get_status_info()) |
| |
|
|
| with gr.Row(): |
| with gr.Column(): |
| chatbot_interface = gr.Chatbot( |
| [], |
| height=500, |
| show_label=False, |
| container=True, |
| avatar_images=("👤", "🏗️"), |
| bubble_full_width=False, |
| type="messages", |
| show_copy_button=True, |
| elem_classes=["chatbot"] |
| ) |
| |
|
|
| with gr.Row(): |
| with gr.Column(scale=8): |
| msg_input = gr.Textbox( |
| placeholder="🏗️ Ask me about construction, safety, materials, project management, engineering, costs, regulations... (Non-construction queries will be declined)", |
| show_label=False, |
| container=False, |
| lines=2, |
| max_lines=4, |
| elem_classes=["textbox"] |
| ) |
| with gr.Column(scale=2, min_width=120): |
| send_btn = gr.Button( |
| "🚀 SEND", |
| variant="primary", |
| size="lg", |
| elem_classes=["btn-primary"] |
| ) |
| |
| |
| with gr.Row(): |
| with gr.Column(scale=1): |
| clear_btn = gr.Button("🗑️ Clear Chat", variant="secondary", elem_classes=["btn-secondary"]) |
| with gr.Column(scale=1): |
| examples_btn = gr.Button("💡 Examples", variant="secondary", elem_classes=["btn-secondary"]) |
| |
| |
| examples_html = f""" |
| <div class="success-box"> |
| <h4>✅ CONSTRUCTION QUESTIONS I CAN ANSWER {'(with Live Web Search!)' if chatbot.search_tool else ''}:</h4> |
| <ul> |
| <li><strong>📊 Current Costs:</strong> "What are today's steel and concrete prices for construction?"</li> |
| <li><strong>🔥 Safety Regulations:</strong> "Latest fire safety codes for high-rise buildings in 2024?"</li> |
| <li><strong>🏗️ Engineering:</strong> "How to calculate foundation requirements for a 10-story building?"</li> |
| <li><strong>⚠️ Safety Equipment:</strong> "OSHA requirements for construction site safety equipment?"</li> |
| <li><strong>📋 Project Management:</strong> "Best methodologies for managing large construction projects?"</li> |
| <li><strong>🌱 Sustainable Materials:</strong> "Latest trends in eco-friendly construction materials?"</li> |
| <li><strong>🔧 Equipment:</strong> "Heavy machinery recommendations for excavation projects?"</li> |
| <li><strong>📐 Structural Design:</strong> "Load-bearing calculations for steel frame buildings?"</li> |
| </ul> |
| </div> |
| |
| <div class="warning-box"> |
| <h4>❌ NON-CONSTRUCTION TOPICS (Will Be Politely Declined):</h4> |
| <ul> |
| <li>Sports, entertainment, cooking, general knowledge</li> |
| <li>Programming, medicine, finance (unless construction-related)</li> |
| <li>Personal advice, relationship help</li> |
| <li>Any topic not related to construction, building, or engineering</li> |
| </ul> |
| </div> |
| |
| <div class="info-box"> |
| <h4>💡 PRO TIPS FOR BEST RESULTS:</h4> |
| <ul> |
| <li><strong>🔍 Trigger Web Search:</strong> Use words like "current", "latest", "2024", "price", "cost" for real-time data</li> |
| <li><strong>📍 Be Specific:</strong> Mention location, building type, or specific materials for targeted advice</li> |
| <li><strong>📋 Multiple Questions:</strong> I remember our last 5 conversations for context</li> |
| <li><strong>🎯 Focus:</strong> Stay within construction topics for the best expert guidance</li> |
| </ul> |
| </div> |
| """ |
| |
| examples_display = gr.HTML(examples_html, visible=False) |
| |
|
|
| def update_memory_display(): |
| return get_status_info() |
| |
| def respond(message, history): |
| if not message.strip(): |
| return history, "", update_memory_display() |
| |
|
|
| if history is None: |
| history = [] |
| |
| |
| history.append({"role": "user", "content": message}) |
| |
|
|
| try: |
| response = chatbot.generate_response(message) |
| history.append({"role": "assistant", "content": response}) |
| except Exception as e: |
| error_response = f"🚨 I apologize, but I encountered an error while processing your construction query. Please try again or rephrase your question.\n\nError: {str(e)[:100]}..." |
| history.append({"role": "assistant", "content": error_response}) |
| |
| return history, "", update_memory_display() |
| |
| def clear_chat(): |
| chatbot.memory.clear() |
| return [], update_memory_display() |
| |
| def toggle_examples(current_visibility): |
| return not current_visibility |
| |
|
|
| msg_input.submit(respond, [msg_input, chatbot_interface], [chatbot_interface, msg_input, memory_status]) |
| send_btn.click(respond, [msg_input, chatbot_interface], [chatbot_interface, msg_input, memory_status]) |
| clear_btn.click(clear_chat, outputs=[chatbot_interface, memory_status]) |
| examples_btn.click(toggle_examples, inputs=examples_display, outputs=examples_display) |
| |
| |
| if chatbot.search_tool: |
| gr.HTML(f""" |
| <div class="success-box"> |
| <h4>🌐 WEB SEARCH ENABLED - REAL-TIME CONSTRUCTION DATA!</h4> |
| <p><strong>✅ Connected to Serper API</strong> - I can fetch the latest construction industry information including:</p> |
| <ul> |
| <li>Current material prices and market trends</li> |
| <li>Latest building codes and regulations</li> |
| <li>New construction technologies and methods</li> |
| <li>Industry news and safety updates</li> |
| <li>Equipment specifications and pricing</li> |
| </ul> |
| <p><small>💡 <strong>Tip:</strong> Ask questions with "current", "latest", "2024", "price" to automatically trigger web search!</small></p> |
| </div> |
| """) |
| else: |
| gr.HTML(f""" |
| <div class="warning-box"> |
| <h4>⚠️ WEB SEARCH CURRENTLY DISABLED</h4> |
| <p><strong>Reason:</strong> Serper API key not properly configured</p> |
| <p><strong>Impact:</strong> I can still answer construction questions using my knowledge base, but won't have access to real-time data.</p> |
| |
| <h5>🔧 To Enable Web Search:</h5> |
| <ol> |
| <li>Visit <a href="https://serper.dev" target="_blank">serper.dev</a> and get a free API key</li> |
| <li>Set environment variable: <code>export SERPER_API_KEY='your-key-here'</code></li> |
| <li>Restart the application</li> |
| </ol> |
| <p><small>💡 Even without web search, I'm still a comprehensive construction expert ready to help!</small></p> |
| </div> |
| """) |
| |
| |
| gr.HTML(f""" |
| <div class="info-box"> |
| <h4>🧠 POWERED BY DEEPSEEK R1 - ADVANCED REASONING AI</h4> |
| <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); gap: 15px; margin-top: 15px;"> |
| <div> |
| <h5>🔬 Model Capabilities:</h5> |
| <ul> |
| <li>Advanced reasoning and problem-solving</li> |
| <li>Deep construction industry knowledge</li> |
| <li>Complex calculation capabilities</li> |
| <li>Multi-step project planning</li> |
| </ul> |
| </div> |
| <div> |
| <h5>🎯 Specialized Features:</h5> |
| <ul> |
| <li>Construction-only query filtering</li> |
| <li>Memory of last 5 conversations</li> |
| <li>Web search integration for current data</li> |
| <li>Professional construction advice</li> |
| </ul> |
| </div> |
| <div> |
| <h5>🛡️ Safety & Compliance:</h5> |
| <ul> |
| <li>OSHA regulation expertise</li> |
| <li>Building code compliance</li> |
| <li>Fire safety standards</li> |
| <li>Risk assessment guidance</li> |
| </ul> |
| </div> |
| </div> |
| </div> |
| """) |
| |
| |
| gr.HTML(""" |
| <div style="text-align: center; margin-top: 30px; padding: 20px; background: linear-gradient(135deg, rgba(255, 107, 26, 0.1), rgba(255, 193, 7, 0.1)); border-radius: 15px; border: 2px solid var(--construction-orange);"> |
| <h5 style="color: var(--construction-orange); margin-bottom: 10px;">🏗️ PROFESSIONAL CONSTRUCTION AI ASSISTANT 🏗️</h5> |
| <p style="color: var(--construction-light-gray); margin: 0;"> |
| <strong>Specialized in:</strong> Building Safety • Material Costs • Project Management • Engineering • Regulations • Equipment |
| <br> |
| <small>⚡ Powered by DeepSeek R1 via OpenRouter • 🌐 Enhanced with Web Search • 🎯 Construction-Focused AI</small> |
| </p> |
| </div> |
| """) |
| |
| return interface |
|
|
|
|
| if __name__ == "__main__": |
| interface = create_interface() |
|
|
| if os.getenv("SPACE_ID"): |
| interface.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860))) |
| else: |
| interface.launch(inbrowser=True, server_name="0.0.0.0", server_port=7860) |
