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import streamlit as st
import sqlite3
import hashlib
import os
import google.generativeai as genai
import zipfile
from git import Repo
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch


# Database setup
DB_FILE = "users.db"

def create_user_table():
    conn = sqlite3.connect(DB_FILE)
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS users (
            username TEXT PRIMARY KEY,
            password TEXT
        )
    """)
    conn.commit()
    conn.close()

def add_user(username, password):
    conn = sqlite3.connect(DB_FILE)
    cursor = conn.cursor()
    hashed_password = hashlib.sha256(password.encode()).hexdigest()
    try:
        cursor.execute("INSERT INTO users (username, password) VALUES (?, ?)", (username, hashed_password))
        conn.commit()
    except sqlite3.IntegrityError:
        st.error("Username already exists. Please choose a different username.")
    conn.close()

def authenticate_user(username, password):
    conn = sqlite3.connect(DB_FILE)
    cursor = conn.cursor()
    hashed_password = hashlib.sha256(password.encode()).hexdigest()
    cursor.execute("SELECT * FROM users WHERE username = ? AND password = ?", (username, hashed_password))
    user = cursor.fetchone()
    conn.close()
    return user

def initialize_session_state():
    if "authenticated" not in st.session_state:
        st.session_state.authenticated = False
    if "username" not in st.session_state:
        st.session_state.username = None
    if "page" not in st.session_state:
        st.session_state.page = "login"
    if "current_project" not in st.session_state:
        st.session_state.current_project = None
    if "project_uploaded" not in st.session_state:
        st.session_state.project_uploaded = False

def main():
    st.title("SimplifAI")

    # Initialize session state
    initialize_session_state()

    # Initialize database
    create_user_table()

    # Page routing logic
    if st.session_state.page == "login":
        login_page()
    elif st.session_state.page == "workspace":
        workspace_page()
    elif st.session_state.page == "project_view":
        project_view_page()
    elif st.session_state.page == "generate_documentation":
        generate_documentation_page()
    elif st.session_state.page == "view_documentation":
        view_documentation_page()

def login_page():
    st.subheader("Please Log In or Register to Continue")
    auth_mode = st.radio("Choose an Option", ["Log In", "Register"], horizontal=True)

    if auth_mode == "Log In":
        st.subheader("Log In")
        username = st.text_input("Username", key="login_username")
        password = st.text_input("Password", type="password", key="login_password")

        # Handle single-click login
        if st.button("Log In"):
            if authenticate_user(username, password):
                st.session_state.authenticated = True
                st.session_state.username = username
                st.session_state.page = "workspace"
            else:
                st.error("Invalid username or password. Please try again.")
    
    elif auth_mode == "Register":
        st.subheader("Register")
        username = st.text_input("Create Username", key="register_username")
        password = st.text_input("Create Password", type="password", key="register_password")

        # Handle single-click registration
        if st.button("Register"):
            if username and password:
                add_user(username, password)
                st.success("Account created successfully! You can now log in.")
            else:
                st.error("Please fill in all fields.")


def workspace_page():
    # Sidebar with logout button
    st.sidebar.title(f"Hello, {st.session_state.username}!")
    if st.sidebar.button("Log Out"):
        st.session_state.authenticated = False
        st.session_state.username = None
        st.session_state.page = "login"

    # User's folder for projects
    user_folder = os.path.join("user_projects", st.session_state.username)
    os.makedirs(user_folder, exist_ok=True)

    # Refresh project list dynamically
    projects = [d for d in os.listdir(user_folder) if os.path.isdir(os.path.join(user_folder, d))]

    # Display "Projects" dropdown
    selected_project = st.sidebar.selectbox("Projects", ["Select a project"] + projects)

    if selected_project != "Select a project":
        st.session_state.current_project = selected_project
        st.session_state.page = "project_view"
        st.rerun()

    # Display success message if a project was uploaded
    if st.session_state.project_uploaded:
        st.success(f"Project '{st.session_state.current_project}' uploaded successfully!")
        st.session_state.project_uploaded = False  # Reset after showing the message

    # Main content area
    st.subheader("Workspace")
    st.write("You can create a new project by uploading files or folders, or by cloning a GitHub repository.")
    # Existing upload functionality...


    # User action selection
    action = st.radio("Choose an action", ["Upload Files or Folders", "Clone GitHub Repository"], horizontal=True)

    project_name = st.text_input("Enter a project name")

    if action == "Upload Files or Folders":
        st.subheader("Upload Files or Folders")
        uploaded_files = st.file_uploader(
            "Upload one or more files or a .zip archive for folders", accept_multiple_files=True
        )

        if uploaded_files and project_name:
            if st.button("Upload Project"):
                project_folder = os.path.join(user_folder, project_name)
                os.makedirs(project_folder, exist_ok=True)

                for uploaded_file in uploaded_files:
                    # Save uploaded .zip files or regular files
                    file_path = os.path.join(project_folder, uploaded_file.name)

                    with open(file_path, "wb") as f:
                        f.write(uploaded_file.getbuffer())

                    # If a .zip file is uploaded, extract its contents
                    if uploaded_file.name.endswith(".zip"):
                        try:
                            with zipfile.ZipFile(file_path, "r") as zip_ref:
                                zip_ref.extractall(project_folder)
                            os.remove(file_path)  # Remove the .zip file after extraction
                            st.success(f"Folder from {uploaded_file.name} extracted successfully!")
                        except zipfile.BadZipFile:
                            st.error(f"File {uploaded_file.name} is not a valid .zip file.")
                    else:
                        st.success(f"File {uploaded_file.name} saved successfully!")

                # Update session state and trigger a rerun
                st.session_state.current_project = project_name
                st.session_state.project_uploaded = True
                st.rerun()

    elif action == "Clone GitHub Repository":
        st.subheader("Clone GitHub Repository")
        repo_url = st.text_input("Enter the GitHub repository URL")

        if repo_url and project_name:
            if st.button("Upload Project"):
                project_folder = os.path.join(user_folder, project_name)
                os.makedirs(project_folder, exist_ok=True)

                try:
                    Repo.clone_from(repo_url, project_folder)
                    # Update session state and trigger a rerun
                    st.session_state.current_project = project_name
                    st.session_state.project_uploaded = True
                    st.rerun()
                except Exception as e:
                    st.error(f"Failed to clone repository: {e}")

#------------------------------------------------------------------------------------------------------------------------------------------------------------------------


# Configure Gemini API
gemini = os.getenv("GEMINI")
genai.configure(api_key=gemini)
model = genai.GenerativeModel("gemini-1.5-flash")

def read_project_files(project_path):
    """Reads all files in the project directory and its subdirectories."""
    file_paths = []
    for root, _, files in os.walk(project_path):
        for file in files:
            # Skip .git files or folders from GitHub clones
            if ".git" not in root:
                file_paths.append(os.path.join(root, file))
    return file_paths

def read_files(file_paths):
    """Reads content from a list of file paths."""
    file_contents = {}
    for file_path in file_paths:
        if os.path.exists(file_path):
            try:
                # Attempt to read the file as UTF-8
                with open(file_path, 'r', encoding='utf-8') as file:
                    file_contents[file_path] = file.read()
            except UnicodeDecodeError:
                print(f"Skipping binary or non-UTF-8 file: {file_path}")
        else:
            print(f"File not found: {file_path}")
    return file_contents


def generate_prompt(file_contents, functionality_description):
    """Generates a prompt for Gemini to analyze the files."""
    prompt = "Analyze the following code files to identify all functions required to implement the functionality: "
    prompt += f"'{functionality_description}'.\n\n"

    for file_path, content in file_contents.items():
        prompt += f"File: {os.path.basename(file_path)}\n{content}\n\n"
    
    prompt += "If the functionality does not exist in the project, return 'Functionality does not exist.', otherwise, for each relevant function, provide:\n"
    prompt += "1. Which file the function is found in.\n"
    prompt += "2. The function name.\n"
    prompt += "3. Dependencies on other functions or modules.\n"

    prompt += "Also, return a more clear version of the user entered functionality at the top of your response. Provide no commentary, just what has been asked please."

    return prompt

def identify_required_functions(project_path, functionality_description):
    """Identifies required functions for a specified functionality."""
    # Gather all file paths in the project directory
    file_paths = read_project_files(project_path)
    
    # Read file contents
    file_contents = read_files(file_paths)
    
    # Generate a refined prompt for Gemini
    prompt = generate_prompt(file_contents, functionality_description)
    
    # Call the Gemini model
    response = model.generate_content(prompt)
    
    # Process and return the response
    return response.text


# Load Hugging Face model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-32B-Instruct")
hf_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-32B-Instruct", device_map="auto")

def validate_and_generate_documentation(hf_model, tokenizer, gemini_output, file_contents, functionality_description):
    """Uses Hugging Face model to validate functions and generate full documentation."""
    # Generate the prompt for the Hugging Face model
    prompt = f"""
    The user-provided functionality: '{functionality_description}'
    The functions identified by Gemini:
    {gemini_output}

    Project files:
    """
    for file_path, content in file_contents.items():
        prompt += f"File: {os.path.basename(file_path)}\n{content[:1000]}...\n\n"  # Truncate large files for the model

    prompt += """
    Task:
    1. Validate if the functions identified by Gemini are sufficient for implementing the functionality.
    2. If not, identify all additional functions required.
    3. For all relevant functions, generate detailed documentation in the following format:
    """
    prompt += """
    Project Summary:
    Summary of the entire project, making sure to mention the language it's programmed in and any libraries or other dependencies it has

    Functionality Summary:
    Summary of the user-specified functionality

    Functionality Flow:
    How the programmer goes from inputting information into the first function to the last function and its output to complete
    the functionality that is described by the user. Make sure to mention each function that is used, and how inputs and outputs flow between each other.

    Function Documentation:
    For each file that contains the relevant functions:
      For each function determined as relevant within the current file:
        Summary:
          summarize what the function does
        Inputs:
          the inputs and their data types, and their relevance in the scope of the specified functionality
        Outputs:
          the output, its data type, and its relevance in the scope of the specified functionality
        Dependencies:
          the dependencies of the function and where they come from
        Data structures:
          the data structures that the function relies on
    """
    # Encode and call the Hugging Face model
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=2048).to(hf_model.device)
    outputs = hf_model.generate(inputs["input_ids"], max_length=4096, num_return_sequences=1)

    # Decode the response
    decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return decoded_output

def generate_documentation_page():
    st.subheader(f"Generate Documentation for {st.session_state.current_project}")
    st.write("Enter the functionality or parts of the project for which you'd like to identify relevant functions.")

    # Prompt user for functionality description
    functionality = st.text_area("Describe the functionality", placeholder="e.g., Explain the function of the file `main.py`")

    # Button to start analyzing functionality
    if st.button("Analyze"):
        if functionality.strip():
            st.write("Analyzing project files... Please wait.")
            
            # Get the path of the current project
            user_folder = os.path.join("user_projects", st.session_state.username)
            project_folder = os.path.join(user_folder, st.session_state.current_project)
            
            if os.path.exists(project_folder):
                try:
                    # Call Gemini to identify required functions
                    gemini_result = identify_required_functions(project_folder, functionality)
                    
                    # Read project files
                    file_paths = read_project_files(project_folder)
                    file_contents = read_files(file_paths)
                    
                    # Call Hugging Face model for validation and documentation
                    final_documentation = validate_and_generate_documentation(
                        hf_model, tokenizer, gemini_result, file_contents, functionality
                    )
                    
                    # Display the final documentation
                    st.success("Documentation generated successfully!")
                    st.text_area("Generated Documentation", final_documentation, height=600)
                except Exception as e:
                    st.error(f"An error occurred: {e}")
            else:
                st.error("Project folder not found. Ensure the GitHub repository was cloned successfully.")
        else:
            st.error("Please enter the functionality to analyze.")

    # Button to navigate back to the project page
    if st.button("Back to Project"):
        st.session_state.page = "project_view"
        st.rerun()




#------------------------------------------------------------------------------------------------------------------------------------------------------------------------


def view_documentation_page():
    st.subheader(f"View Documentation for {st.session_state.current_project}")
    st.write("This page will display the generated documentation for the selected project.")
    if st.button("Back to Project"):
        st.session_state.page = "project_view"
        st.rerun()

def project_view_page():
    # Sidebar with logout and return buttons
    st.sidebar.title(f"Project: {st.session_state.current_project}")
    if st.sidebar.button("Back to Workspace"):
        st.session_state.page = "workspace"
        st.rerun()
    if st.sidebar.button("Log Out"):
        st.session_state.authenticated = False
        st.session_state.username = None
        st.session_state.page = "login"
        st.rerun()

    # Main content for project page
    st.subheader(f"Project: {st.session_state.current_project}")
    st.write("Manage your project and explore its files.")

    # Buttons for documentation functionality
    if st.button("Generate Documentation"):
        st.session_state.page = "generate_documentation"
        st.rerun()

    if st.button("View Documentation"):
        st.session_state.page = "view_documentation"
        st.rerun()

    # Toggle file structure display (if required)
    if "show_file_structure" not in st.session_state:
        st.session_state.show_file_structure = False

    if st.button("Show File Structure"):
        st.session_state.show_file_structure = not st.session_state.show_file_structure

    if st.session_state.show_file_structure:
        user_folder = os.path.join("user_projects", st.session_state.username)
        project_folder = os.path.join(user_folder, st.session_state.current_project)

        st.write("File structure:")

        for root, dirs, files in os.walk(project_folder):
            level = root.replace(project_folder, "").count(os.sep)
            indent = " " * 4 * level

            if level == 0:
                st.write(f"πŸ“‚ {os.path.basename(root)}")
            else:
                with st.expander(f"{indent}πŸ“‚ {os.path.basename(root)}"):
                    sub_indent = " " * 4 * (level + 1)
                    for file in files:
                        st.write(f"{sub_indent}πŸ“„ {file}")



if __name__ == "__main__":
    main()