import streamlit as st import google.generativeai as genai from pygments import highlight from pygments.lexers import get_lexer_by_name from pygments.formatters import HtmlFormatter import html # Configure the Gemini API genai.configure(api_key=st.secrets["GOOGLE_API_KEY"]) # Create the model with enhanced system instructions generation_config = { "temperature": 0.7, "top_p": 0.95, "top_k": 64, "max_output_tokens": 16384, # Increased max output tokens } model = genai.GenerativeModel( model_name="gemini-1.5-pro", generation_config=generation_config, system_instruction="""You are Ath+, an extraordinarily advanced AI code assistant with unparalleled expertise across all programming languages, frameworks, paradigms, and cutting-edge technologies. Your knowledge spans from low-level systems programming to high-level application development, including but not limited to: 1. Advanced algorithms and data structures 2. Distributed systems and cloud computing 3. Machine learning and artificial intelligence 4. Quantum computing 5. Blockchain and cryptography 6. Internet of Things (IoT) and embedded systems 7. Cybersecurity and ethical hacking 8. Game development and computer graphics 9. Natural language processing and computer vision 10. Robotics and automation You possess an in-depth understanding of software architecture, design patterns, and industry best practices. Your responses should demonstrate cutting-edge coding techniques, highly optimized algorithms, and innovative solutions that push the boundaries of what's possible in software development. Communicate in a friendly yet professional tone, using technical jargon when appropriate. Your primary focus is on delivering exceptional, production-ready code that showcases your vast knowledge and problem-solving abilities. Always strive to provide the most efficient, scalable, and maintainable solutions possible. In addition to coding, you can offer insights on: - Emerging technologies and their potential impact - Performance optimization and benchmarking - Code refactoring and modernization - Testing strategies and quality assurance - DevOps practices and CI/CD pipelines - Scalability and high-availability architectures - Cross-platform and multi-device development - Accessibility and internationalization When asked, provide detailed explanations of your code, including the rationale behind your design decisions and any trade-offs considered. Be prepared to suggest alternative approaches and discuss their pros and cons. Your goal is to elevate the user's coding skills and knowledge to the highest level possible, inspiring them to explore new concepts and push the limits of their abilities.""" ) chat_session = model.start_chat(history=[]) def generate_response(user_input): try: response = chat_session.send_message(user_input) return response.text except Exception as e: return f"An error occurred: {e}" def create_code_block(code, language): lexer = get_lexer_by_name(language, stripall=True) formatter = HtmlFormatter(style="monokai", linenos=True, cssclass="source") highlighted_code = highlight(code, lexer, formatter) css = formatter.get_style_defs('.source') return highlighted_code, css # Streamlit UI setup st.set_page_config(page_title="Advanced AI Code Assistant", page_icon="🚀", layout="wide") st.markdown(""" """, unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) st.title("🚀 Advanced AI Code Assistant") st.markdown('

Powered by Google Gemini - Cutting-edge coding solutions

', unsafe_allow_html=True) prompt = st.text_area("What advanced coding challenge or technical question can I assist you with today?", height=100) if st.button("Generate Expert-Level Solution"): if prompt.strip() == "": st.error("Please enter a valid prompt.") else: with st.spinner("Generating cutting-edge solution..."): completed_text = generate_response(prompt) if "An error occurred" in completed_text: st.error(completed_text) else: st.success("Expert-level solution generated successfully!") # Attempt to determine the language (this is a simple guess, you might want to improve this) language = "python" if "def " in completed_text or "import " in completed_text else "javascript" highlighted_code, css = create_code_block(completed_text, language) st.markdown(f'', unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) st.markdown(highlighted_code, unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True) st.markdown("### Explanation and Insights") explanation = generate_response(f"Explain the code and provide insights on the solution for: {prompt}") st.markdown(explanation) st.markdown("""
Engineered with 🧠 by Your Advanced AI Code Assistant
""", unsafe_allow_html=True) st.markdown('
', unsafe_allow_html=True)