app.py

from flask import Flask, render_template, request, jsonify
import os
import tempfile
from pathlib import Path
from langchain_community.llms import HuggingFaceHub
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
from datetime import datetime
import sqlite3
from contextlib import contextmanager
from werkzeug.utils import secure_filename
from huggingface_hub import InferenceClient
from langchain.llms.base import LLM
from typing import Optional, List, Any

# Initialize Flask application
app = Flask(__name__)

# Configuration
PORT = int(os.environ.get("PORT", 7860))
CACHE_DIR = "/tmp/huggingface_cache"
UPLOAD_DIR = "/tmp/uploads"
DATABASE_PATH = "/tmp/chat_database.db"

# Create necessary directories
for dir_path in [CACHE_DIR, UPLOAD_DIR]:
    Path(dir_path).mkdir(parents=True, exist_ok=True)

# Set environment variables
os.environ['TRANSFORMERS_CACHE'] = CACHE_DIR
os.environ['HUGGINGFACE_HUB_CACHE'] = CACHE_DIR

# Configure Flask app
app.config['UPLOAD_FOLDER'] = UPLOAD_DIR

# Initialize prompt template
prompt_template = """
Role: You are Figr Code Assistant, specializing in providing clear, error-free Python code solutions.

Context:
{important_info}

Previous Conversation:
{chat_history}

Current Request:
{user_request}

Output Guidelines:
1. Code Format:
   - Use ```python for code blocks
   - Use `code` for inline code references
   - Provide raw text without HTML formatting
   - Include explanations after code blocks

2. Code Organization:
   - Default to single, focused code snippets
   - Only split into multiple snippets if necessary
   - Mark critical information with [IMPORTANT] prefix

Please provide a clear and detailed response:
"""

prompt = PromptTemplate(
    input_variables=["user_request", "chat_history", "important_info"],
    template=prompt_template
)

class CustomHuggingFaceInference(LLM):
    client: Any
    model: str
    
    def __init__(self, token: str):
        super().__init__()
        self.client = InferenceClient(token=token)
        self.model = "mistralai/Mistral-7B-Instruct-v0.1"
    
    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
        response = self.client.text_generation(
            prompt,
            model=self.model,
            max_new_tokens=512,
            temperature=0.7,
            top_p=0.95,
            repetition_penalty=1.15
        )
        return response

    @property
    def _identifying_params(self):
        return {"model": self.model}
    
    @property
    def _llm_type(self):
        return "custom_huggingface"

        

@contextmanager
def get_db_connection():
    """Context manager for database connections"""
    conn = sqlite3.connect(DATABASE_PATH)
    conn.row_factory = sqlite3.Row
    try:
        yield conn
    finally:
        conn.close()

def init_db():
    """Initialize the database"""
    with get_db_connection() as conn:
        conn.execute('''
            CREATE TABLE IF NOT EXISTS chats (
                id TEXT PRIMARY KEY,
                title TEXT,
                date TEXT,
                last_message TEXT
            )
        ''')

        conn.execute('''
            CREATE TABLE IF NOT EXISTS messages (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                chat_id TEXT,
                role TEXT,
                content TEXT,
                timestamp TEXT,
                FOREIGN KEY (chat_id) REFERENCES chats (id)
            )
        ''')

        conn.execute('''
            CREATE TABLE IF NOT EXISTS important_info (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                chat_id TEXT,
                content TEXT,
                FOREIGN KEY (chat_id) REFERENCES chats (id)
            )
        ''')
        conn.commit()

def initialize_llm():
    """Initialize the model in the simplest way possible"""
    try:
        # Get API token
        api_token = os.environ.get('HF_TOKEN')
        if not api_token:
            raise ValueError("No API token found")

        # Initialize with minimal settings
        llm = HuggingFaceHub(
            repo_id="google/flan-t5-base",  # Using a simpler model for testing
            huggingfacehub_api_token=api_token
        )

        # Quick test
        test = llm("Say hello")
        print(f"Test response: {test}")

        return llm

    except Exception as e:
        print(f"LLM initialization error: {str(e)}")
        raise

        
class ChatSession:
    def __init__(self, session_id):
        self.session_id = session_id
        self.memory = ConversationBufferMemory(
            memory_key="chat_history",
            return_messages=True
        )
        self._load_chat_history()
        self._load_important_info()

    def _load_chat_history(self):
        """Load chat history from database"""
        with get_db_connection() as conn:
            messages = conn.execute(
                'SELECT role, content, timestamp FROM messages WHERE chat_id = ? ORDER BY timestamp',
                (self.session_id,)
            ).fetchall()

            self.chat_history = []
            for msg in messages:
                self.chat_history.append({
                    "role": msg['role'],
                    "content": msg['content'],
                    "timestamp": msg['timestamp']
                })
                if msg['role'] == "user":
                    self.memory.chat_memory.add_user_message(msg['content'])
                else:
                    self.memory.chat_memory.add_ai_message(msg['content'])

    def _load_important_info(self):
        """Load important info from database"""
        with get_db_connection() as conn:
            info = conn.execute(
                'SELECT content FROM important_info WHERE chat_id = ?',
                (self.session_id,)
            ).fetchall()
            self.important_info = [row['content'] for row in info]

    def add_message(self, role, content):
        timestamp = datetime.now().isoformat()
        message = {
            "role": role,
            "content": content,
            "timestamp": timestamp
        }

        # Store in database
        with get_db_connection() as conn:
            conn.execute(
                'INSERT INTO messages (chat_id, role, content, timestamp) VALUES (?, ?, ?, ?)',
                (self.session_id, role, content, timestamp)
            )
            conn.commit()

        self.chat_history.append(message)

        # Update memory
        if role == "user":
            self.memory.chat_memory.add_user_message(content)
        else:
            self.memory.chat_memory.add_ai_message(content)

    def add_important_info(self, content):
        """Add important information to database"""
        with get_db_connection() as conn:
            conn.execute(
                'INSERT INTO important_info (chat_id, content) VALUES (?, ?)',
                (self.session_id, content)
            )
            conn.commit()
        self.important_info.append(content)

    def get_memory_variables(self):
        return self.memory.load_memory_variables({})

    def clear_memory(self):
        """Clear all memory from database"""
        with get_db_connection() as conn:
            conn.execute('DELETE FROM messages WHERE chat_id = ?', (self.session_id,))
            conn.execute('DELETE FROM important_info WHERE chat_id = ?', (self.session_id,))
            conn.commit()

        self.memory.clear()
        self.chat_history = []
        self.important_info = []

    def clear_chat_history(self):
        """Clear chat history from database"""
        with get_db_connection() as conn:
            conn.execute('DELETE FROM messages WHERE chat_id = ?', (self.session_id,))
            conn.commit()

        self.chat_history = []
        self.memory.chat_memory.clear()

    def clear_important_info(self):
        """Clear important info from database"""
        with get_db_connection() as conn:
            conn.execute('DELETE FROM important_info WHERE chat_id = ?', (self.session_id,))
            conn.commit()

        self.important_info = []

print("Starting application initialization...")

try:
    print("Initializing database...")
    init_db()
    print("Database initialized successfully")

    print("Initializing LLM...")
    llm = initialize_llm()
    if llm is None:
        raise ValueError("LLM initialization failed")
    print("LLM initialized successfully")

    print("Creating LLM chain...")
    llm_chain = LLMChain(llm=llm, prompt=prompt)
    print("LLM chain created successfully")

except Exception as e:
    print(f"Fatal initialization error: {e}")
    raise

    
# Rest of the prompt template and other configurations remain the same
prompt_template = """
Role: You are Figr Code Assistant, specializing in providing clear, error-free Python code solutions.

Context:
{important_info}

Previous Conversation:
{chat_history}

Current Request:
{user_request}

Output Guidelines:
1. Code Format:
   - Use ```python for code blocks
   - Use `code` for inline code references
   - Provide raw text without HTML formatting
   - Strictly include explanation only after code blocks

2. Code Organization:
   - Default to single, focused code snippets for clarity
   - Only split into multiple snippets(each individually runnable) if:
     a) Multiple distinct concepts are requested
     b) Complex functionality requires modular explanation
     
   - Mark critical information with [IMPORTANT] prefix and give small explanations with some bold headings if required and in white font always.
"""

prompt = PromptTemplate(
    input_variables=["user_request", "chat_history", "important_info"],
    template=prompt_template
)
llm_chain = LLMChain(llm=llm, prompt=prompt)


def convert_to_html(raw_text):
    """Convert markdown to HTML while preserving code blocks with custom buttons"""
    try:
        # Create a temporary markdown file
        with tempfile.NamedTemporaryFile(delete=False, mode="w", suffix=".md") as temp_input:
            temp_input.write(raw_text)
            temp_input_path = temp_input.name

        # Use pandoc with specific options to preserve code blocks
        with tempfile.NamedTemporaryFile(delete=False, suffix=".html") as temp_output:
            temp_output_path = temp_output.name

        # Use pandoc with specific options
        cmd = [
            "pandoc",
            temp_input_path,
            "-f", "markdown",
            "-t", "html",
            "--highlight-style=pygments",
            "--no-highlight",  # Disable pandoc's highlighting
            "-o", temp_output_path
        ]

        result = subprocess.run(cmd, capture_output=True, text=True)

        if result.returncode == 0:
            with open(temp_output_path, "r") as f:
                html_content = f.read()

            # Add custom buttons to code blocks
            import re
            def replace_code_block(match):
                code_class = match.group(1) or ''
                code_content = match.group(2)
                return f'''
                    <div class="code-block-wrapper">
                        <button class="test-button">Test Code</button>
                        <button class="copy-button">Copy Code</button>
                        <pre><code class="hljs {code_class}">{code_content}</code></pre>
                        <div class="test-results"></div>
                    </div>
                '''

            # Replace <pre><code> blocks with our custom wrapper
            pattern = r'<pre><code class="([^"]*)">(.*?)</code></pre>'
            html_content = re.sub(pattern, replace_code_block, html_content, flags=re.DOTALL)

        else:
            html_content = f"Error: {result.stderr}"

    finally:
        # Clean up temporary files
        if os.path.exists(temp_input_path):
            os.remove(temp_input_path)
        if os.path.exists(temp_output_path):
            os.remove(temp_output_path)

    return html_content


def allowed_file(filename):
    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS


def extract_important_info(response):
    important_items = []
    for line in response.split('\n'):
        if '[IMPORTANT]' in line:
            important_items.append(line.replace('[IMPORTANT]', '').strip())
    return important_items

def create_new_chat(session_id: str):
    """Create a new chat session with metadata in database"""
    with get_db_connection() as conn:
        conn.execute(
            'INSERT INTO chats (id, title, date, last_message) VALUES (?, ?, ?, ?)',
            (session_id, "New Chat", datetime.now().isoformat(), None)
        )
        conn.commit()

    return {
        "id": session_id,
        "title": "New Chat",
        "date": datetime.now().isoformat(),
        "last_message": None
    }


def update_chat_metadata(session_id: str, last_message: str):
    """Update chat metadata in database"""
    title = last_message[:30] + "..." if len(last_message) > 30 else last_message
    with get_db_connection() as conn:
        conn.execute(
            'UPDATE chats SET title = ?, last_message = ? WHERE id = ?',
            (title, last_message, session_id)
        )
        conn.commit()


def format_response(response):
    """Format response with proper code block structure"""
    # First, handle code blocks with language specification
    formatted = re.sub(
        r'```(\w+)\n(.*?)\n```',
        lambda
            m: f'<div class="code-block-wrapper">\n<button class="test-button">Test Code</button>\n<button class="copy-button">Copy Code</button>\n<pre><code class="hljs {m.group(1)}">{m.group(2)}</code></pre>\n<div class="test-results"></div>\n</div>',
        response,
        flags=re.DOTALL
    )

    # Then handle code blocks without language specification
    formatted = re.sub(
        r'```\n(.*?)\n```',
        lambda
            m: f'<div class="code-block-wrapper">\n<button class="test-button">Test Code</button>\n<button class="copy-button">Copy Code</button>\n<pre><code class="hljs">{m.group(1)}</code></pre>\n<div class="test-results"></div>\n</div>',
        formatted,
        flags=re.DOTALL
    )

    # Handle inline code
    formatted = re.sub(
        r'`([^`]+)`',
        r'<code class="inline-code">\1</code>',
        formatted
    )

    return formatted


@app.route("/api/chat-list", methods=["GET"])
def get_chat_list():
    """Get list of all chats from database"""
    with get_db_connection() as conn:
        chats = conn.execute('SELECT * FROM chats ORDER BY date DESC').fetchall()
        return jsonify({
            "chats": [dict(chat) for chat in chats]
        })


# The rest of your route handlers (convert_to_html, extract_important_info, etc.) remain the same

@app.route("/api/chat", methods=["POST"])
def chat():
    try:
        # Get the user's message
        data = request.json
        user_input = data.get("message", "")
        print(f"Received message: {user_input}")

        # Very simple prompt for testing
        prompt = f"You are a helpful assistant. Keep your response short and simple. User says: {user_input}"

        try:
            # Get response directly from model
            response = llm(prompt)
            print(f"Raw response received: {response}")

            # Return whatever response we get
            return jsonify({
                "success": True,
                "response": response
            })

        except Exception as e:
            print(f"Model error: {str(e)}")
            # Return a simple error message
            return jsonify({
                "success": False,
                "response": "Sorry, I couldn't generate a response right now."
            })

    except Exception as e:
        print(f"Request error: {str(e)}")
        return jsonify({
            "success": False,
            "response": "Sorry, there was a problem with your request."
        })



@app.route("/api/new-chat", methods=["POST"])
def new_chat():
    """Create a new chat session"""
    session_id = str(datetime.now().timestamp())
    chat = create_new_chat(session_id)
    return jsonify({"success": True, "chat": chat})


@app.route("/api/chat-history", methods=["GET"])
def get_chat_history():
    """Get chat history for a specific session"""
    session_id = request.args.get("sessionId", "default")

    with get_db_connection() as conn:
        # Get messages
        messages = conn.execute(
            'SELECT role, content, timestamp FROM messages WHERE chat_id = ? ORDER BY timestamp',
            (session_id,)
        ).fetchall()

        # Format assistant messages if they aren't already formatted
        formatted_messages = []
        for msg in messages:
            message_dict = dict(msg)
            if message_dict['role'] == 'assistant' and '```' in message_dict['content']:
                # Format the response if it contains code blocks
                message_dict['content'] = format_response(message_dict['content'])
            formatted_messages.append(message_dict)

        # Get important info
        important_info = conn.execute(
            'SELECT content FROM important_info WHERE chat_id = ?',
            (session_id,)
        ).fetchall()

        return jsonify({
            "history": formatted_messages,
            "important_info": [info['content'] for info in important_info]
        })


@app.route('/api/upload', methods=['POST'])
def upload_file():
    if 'file' not in request.files:
        return jsonify({'success': False, 'error': 'No file part'})

    file = request.files['file']
    if file.filename == '':
        return jsonify({'success': False, 'error': 'No selected file'})

    if file and allowed_file(file.filename):
        filename = secure_filename(file.filename)
        filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
        file.save(filepath)

        # Read the file content
        with open(filepath, 'r') as f:
            content = f.read()

        # Analyze the code using the LLM
        analysis_prompt = f"""
        Please analyze this Python code:

        {content}

        Provide:
        1. A clear, small explanation
        2. Any potential errors or improvements
        3. Suggestions for better practices
        
        - Each in separate neat paragraphs with highlighted headings.
        """

        analysis = llm.predict(analysis_prompt)

        # Clean up the uploaded file
        os.remove(filepath)

        return jsonify({
            'success': True,
            'filename': filename,
            'content': content,
            'analysis': analysis
        })

    return jsonify({'success': False, 'error': 'Invalid file type'})


@app.route("/api/clear-memory", methods=["POST"])
def clear_memory():
    """Clear memory based on specified option"""
    session_id = request.json.get("sessionId", "default")
    clear_option = request.json.get("clearOption", "all")

    with get_db_connection() as conn:
        try:
            if clear_option == "all":
                conn.execute('DELETE FROM messages WHERE chat_id = ?', (session_id,))
                conn.execute('DELETE FROM important_info WHERE chat_id = ?', (session_id,))
                message = "All memory cleared successfully"
            elif clear_option == "chat":
                conn.execute('DELETE FROM messages WHERE chat_id = ?', (session_id,))
                message = "Chat history cleared successfully"
            elif clear_option == "important":
                conn.execute('DELETE FROM important_info WHERE chat_id = ?', (session_id,))
                message = "Important information cleared successfully"
            else:
                return jsonify({
                    "success": False,
                    "message": "Invalid clear option specified"
                })

            conn.commit()
            return jsonify({
                "success": True,
                "message": message
            })

        except Exception as e:
            return jsonify({
                "success": False,
                "message": f"Error clearing memory: {str(e)}"
            })


@app.route("/api/test-code", methods=["POST"])
def test_code():
    try:
        data = request.json
        code = data.get("code", "")

        # Create a temporary file to store the code
        with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
            f.write(code)
            temp_file = f.name

        try:
            # Run the code using Python
            result = subprocess.run(
                ['python', temp_file],
                capture_output=True,
                text=True,
                timeout=5  # 5 second timeout for safety
            )

            # Prepare the response
            success = result.returncode == 0
            output = result.stdout if success else result.stderr

            return jsonify({
                "success": success,
                "output": output
            })

        finally:
            # Clean up the temporary file
            os.unlink(temp_file)

    except Exception as e:
        return jsonify({
            "success": False,
            "output": f"Error executing code: {str(e)}"
        })


@app.route("/")
def home():
    """Serve the main application page"""
    return render_template("index.html")




if __name__ == "__main__":
    app.run(host="0.0.0.0", port=PORT)