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| import streamlit as st | |
| import json | |
| from typing import Dict, List, Any | |
| def format_project_response(project: dict) -> str: | |
| """Format project details with clear separation""" | |
| response = [f"\n• {project['name']}:"] | |
| response.append(f" Description: {project['description']}") | |
| if 'skills_used' in project: | |
| response.append(f"\n Technologies Used:") | |
| response.append(f" {', '.join(project['skills_used'])}") | |
| if 'status' in project: | |
| response.append(f"\n Current Status: {project['status']}") | |
| if 'confidentiality_note' in project: | |
| response.append(f" Note: {project['confidentiality_note']}") | |
| return '\n'.join(response) + '\n' | |
| def get_philosophical_response(query: str, knowledge_base: dict) -> str: | |
| """Handle philosophical or market-related queries""" | |
| query_lower = query.lower() | |
| # Market-related response | |
| if any(word in query_lower for word in ['market', 'job', 'opportunity', 'down']): | |
| return """I believe success in any market comes down to quality of effort and preparation. While the market may have cycles, I focus on: | |
| • Continuous Skill Development: | |
| - Building practical projects that solve real problems | |
| - Staying updated with latest ML/AI trends | |
| - Enhancing my technical portfolio | |
| • Value Proposition: | |
| - Unique combination of business and technical skills | |
| - Focus on practical implementation | |
| - Strong problem-solving approach | |
| I see this period as an opportunity to strengthen my skills and build more impactful projects.""" | |
| # Off-topic response | |
| if any(word in query_lower for word in ['weather', 'temperature', 'climate']): | |
| return """I'm focused on discussing my ML/AI journey and projects. For weather information, I'd recommend checking local weather services. | |
| Would you like to know about: | |
| • My ML projects and technical skills? | |
| • My journey from commerce to tech? | |
| • My approach to the current job market?""" | |
| return None # Return None if not a philosophical query | |
| def generate_response(query: str, knowledge_base: dict) -> str: | |
| """Enhanced response generation with better handling of various queries""" | |
| query_lower = query.lower() | |
| # First check for philosophical/off-topic queries | |
| philosophical_response = get_philosophical_response(query, knowledge_base) | |
| if philosophical_response: | |
| return philosophical_response | |
| # Handle project listing requests | |
| if any(word in query_lower for word in ['list', 'project', 'portfolio', 'built', 'created', 'developed']): | |
| response_parts = ["Here are my key projects:"] | |
| # Major Projects | |
| response_parts.append("\nMajor Projects (In Development):") | |
| for project in knowledge_base['projects']['major_projects']: | |
| response_parts.append(format_project_response(project)) | |
| # Algorithm Projects | |
| response_parts.append("\nCompleted Algorithm Implementation Projects:") | |
| for project in knowledge_base['projects']['algorithm_practice_projects']: | |
| response_parts.append(format_project_response(project)) | |
| response = '\n'.join(response_parts) | |
| # Add relevant links | |
| if 'online_presence' in knowledge_base.get('personal_details', {}): | |
| response += f"\n\nView my complete portfolio: {knowledge_base['personal_details']['online_presence']['portfolio']}" | |
| return response | |
| # [Rest of your existing response handlers] | |
| def main(): | |
| st.title("💬 Chat with Manyue's Portfolio") | |
| # Initialize session state | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| if "knowledge_base" not in st.session_state: | |
| try: | |
| with open('knowledge_base.json', 'r', encoding='utf-8') as f: | |
| st.session_state.knowledge_base = json.load(f) | |
| except FileNotFoundError: | |
| st.error("Knowledge base file not found.") | |
| return | |
| # Display welcome message | |
| if "displayed_welcome" not in st.session_state: | |
| st.write(""" | |
| Hi! I'm Manyue's AI assistant. I can tell you about: | |
| - My journey from commerce to ML/AI | |
| - My technical skills and projects | |
| - My fit for ML/AI roles | |
| - You can also paste job descriptions to see how my profile matches! | |
| """) | |
| st.session_state.displayed_welcome = True | |
| # Create two columns with proper sizing | |
| col1, col2 = st.columns([3, 1]) | |
| with col1: | |
| # Chat container for better scrolling | |
| chat_container = st.container() | |
| with chat_container: | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # Chat input | |
| if prompt := st.chat_input("Ask me anything or paste a job description...", key="chat_input"): | |
| # Add user message | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| # Generate and display response | |
| with st.chat_message("assistant"): | |
| try: | |
| response = generate_response(prompt, st.session_state.knowledge_base) | |
| st.markdown(response) | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |
| except Exception as e: | |
| st.error(f"An error occurred: {str(e)}") | |
| with col2: | |
| st.subheader("Quick Questions") | |
| example_questions = [ | |
| "Tell me about your ML projects", | |
| "What are your technical skills?", | |
| "What makes you stand out?", | |
| "What's your journey into ML?", | |
| "Your view on the current market?" | |
| ] | |
| # Handle quick questions with proper keys | |
| for i, question in enumerate(example_questions): | |
| if st.button(question, key=f"btn_{i}"): | |
| with st.chat_message("user"): | |
| st.markdown(question) | |
| st.session_state.messages.append({"role": "user", "content": question}) | |
| with st.chat_message("assistant"): | |
| try: | |
| response = generate_response(question, st.session_state.knowledge_base) | |
| st.markdown(response) | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |
| except Exception as e: | |
| st.error(f"An error occurred: {str(e)}") | |
| st.rerun() | |
| st.markdown("---") | |
| if st.button("Clear Chat", key="clear_chat"): | |
| st.session_state.messages = [] | |
| st.rerun() | |
| if __name__ == "__main__": | |
| main() |