app.py

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
import re
import time

# 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": 10240,
}

model = genai.GenerativeModel(
    model_name="gemini-1.5-pro",
    generation_config=generation_config,
    system_instruction="""You are Ath, an advanced AI code assistant with expertise across multiple programming languages, frameworks, and paradigms. Your knowledge spans software architecture, design patterns, algorithms, and cutting-edge technologies. Provide high-quality, optimized code solutions with explanations when requested. Adapt your communication style based on the user's expertise level, offering additional context for beginners and diving into complex topics for experts. You can generate code, explain concepts, debug issues, and provide best practices. Always prioritize security, efficiency, and maintainability in your solutions."""
)

# Initialize session state for chat history
if 'chat_history' not in st.session_state:
    st.session_state.chat_history = []

def generate_response(user_input):
    try:
        # Add user message to chat history
        st.session_state.chat_history.append({"role": "user", "content": user_input})
        
        # Generate response
        response = model.generate_content(st.session_state.chat_history)
        
        # Add AI response to chat history
        st.session_state.chat_history.append({"role": "assistant", "content": response.text})
        
        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

def detect_language(code):
    # Simple language detection based on keywords or syntax
    if re.search(r'\b(def|import|class)\b', code):
        return 'python'
    elif re.search(r'\b(function|var|let|const)\b', code):
        return 'javascript'
    elif re.search(r'\b(public|private|class)\b', code):
        return 'java'
    else:
        return 'text'  # Default to plain text if language can't be determined

# Streamlit UI setup
st.set_page_config(page_title="Advanced AI Code Assistant", page_icon="💻", layout="wide")

# ... (Keep the existing CSS styles) ...

st.markdown('<div class="main-container">', unsafe_allow_html=True)
st.title("💻 Advanced AI Code Assistant")
st.markdown('<p class="subtitle">Powered by Google Gemini - Expert-level coding solutions</p>', unsafe_allow_html=True)

# Add a selectbox for different modes
mode = st.selectbox("Choose a mode:", ["Code Generation", "Code Explanation", "Debugging", "Best Practices"])

prompt = st.text_area(f"Enter your {mode.lower()} request:", height=100)

if st.button("Generate Response"):
    if prompt.strip() == "":
        st.error("Please enter a valid prompt.")
    else:
        with st.spinner(f"Generating {mode.lower()} response..."):
            completed_text = generate_response(prompt)
            if "An error occurred" in completed_text:
                st.error(completed_text)
            else:
                st.success(f"{mode} response generated successfully!")
                
                # Split the response into code and explanation
                code_blocks = re.split(r'```(\w+)?\n', completed_text)
                for i in range(1, len(code_blocks), 2):
                    language = code_blocks[i] if code_blocks[i] else detect_language(code_blocks[i+1])
                    code = code_blocks[i+1]
                    
                    highlighted_code, css = create_code_block(code, language)
                    
                    st.markdown(f'<style>{css}</style>', unsafe_allow_html=True)
                    st.markdown('<div class="output-container">', unsafe_allow_html=True)
                    st.markdown('<div class="code-block">', unsafe_allow_html=True)
                    st.markdown(highlighted_code, unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                    
                    # Add explanation if available
                    if i+2 < len(code_blocks):
                        st.markdown(code_blocks[i+2])

# Display chat history
st.subheader("Conversation History")
for message in st.session_state.chat_history:
    st.text(f"{message['role'].capitalize()}: {message['content']}")

# Add a clear button for chat history
if st.button("Clear Conversation History"):
    st.session_state.chat_history = []
    st.success("Conversation history cleared!")

# Add a feedback section
st.subheader("Feedback")
feedback = st.text_area("How can we improve? (Optional)")
if st.button("Submit Feedback"):
    # Here you would typically send this feedback to a database or email
    st.success("Thank you for your feedback!")

st.markdown("""
<div style='text-align: center; margin-top: 2rem; color: #6c757d;'>
    Crafted with ❤️ by Your Advanced AI Code Assistant
</div>
""", unsafe_allow_html=True)

st.markdown('</div>', unsafe_allow_html=True)