"""Create a new artifact version from parsed artifact data"""
        # Get the latest version for this conversation
        latest = self.search([

        """Load current settings from config parameters"""
        res = super().default_get(fields_list)
        if 'knowledge_visualizer_enabled' in fields_list:

        """Check if the required module is installed"""
        for record in self:
            if record.module_name:

        """Ensure technical name is lowercase and valid"""
        for record in self:
            if not record.technical_name.islower() or ' ' in record.technical_name:

        """
        Open canvas creation wizard for this branch type
        """

        """Import conversations from uploaded JSON file"""
        if not self.file_data:
            raise ValidationError(_('Please upload a JSON file first'))

        """Get list of installed modules"""
        Module = self.env['ir.module.module']
        modules = Module.search([

        """Format module list for prompt"""
        lines = []
        for module in modules:

        """Get important fields from record"""
        lines = []
        # Get field definitions

        """Check if conversation is shared in any workspace"""
        for record in self:
            record.is_shared = bool(record.workspace_ids)

        """Auto-detect if path is file or directory"""
        for record in self:
            if record.source_path and os.path.exists(record.source_path):

        """Create ai.conversation record"""
        # Claude export uses 'name', fallback to 'title' for other formats
        conv_name = conv_data.get('name') or conv_data.get('title') or 'Untitled Conversation'

        """Register built-in extractors on first use"""
        if AIDocumentExtractor._initialized:
            return

        """
        cls._extractors[extension.lower()] = handler
        _logger.debug(f"Registered extractor for {extension}")

        """Extract JSON files"""
        with open(file_path, 'r', encoding='utf-8') as f:
            data = json.load(f)

        """Extract PDF files"""
        try:
            import PyPDF2

        """Extract Excel files"""
        try:
            import openpyxl

        """
        prompt = f"""Generate a Python function to extract content from {extension} files.

"""
        conversation = self.env['ai.conversation'].create({
            'name': f'Extractor Generation: {extension}'

        """
        Get the graph structure for a conversation (nodes + relationships)
        Returns visualization data for the conversation and its connections

        """Override create to estimate tokens if not provided"""
        for vals in vals_list:
            if not vals.get('token_count') and vals.get('content'):

        """Override write to detect module state changes"""
        # Store old states
        old_states = {module.id: module.state for module in self}

        """
        # Log the change
        if new_state == 'installed':

        """
        # Check if there's a branch registered for this module
        Branch = self.env['ai.branch'].sudo()

        """
        if not config.api_key:
            _logger.warning("Cannot count tokens: API key not configured")

        """
        total_chars = 0
        # Count system prompt

        """
        # Rough approximation: 1 token ≈ 4 characters
        # Claude actually uses ~3.5 chars/token on average, but 4 is safer

        """
        # Exponential backoff: base_delay * (2 ^ (attempt - 1))
        delay = config.retry_base_delay * (2 ** (attempt - 1))

        """
        # Rate limit errors (429) - always retry with backoff
        if status_code == 429:

        """
        try:
            # Try to parse JSON error response

        """Set model_name based on provider on create"""
        for vals in vals_list:
            if 'api_provider' in vals:

        """
        config = self.search([('active', '=', True)], limit=1)
        if not config:

        """Create default configuration if none exists"""
        existing = self.search([], limit=1)
        if not existing:

        """Validate token limits"""
        for record in self:
            if record.daily_token_limit < 0 or record.user_token_limit < 0:

        """Validate max tokens"""
        for record in self:
            if record.max_tokens < 1 or record.max_tokens > 200000:

        """Validate token counting configuration"""
        for record in self:
            if record.token_warning_threshold < 0 or record.token_warning_threshold > 200000:

        """Compute API key status for display"""
        for record in self:
            if record.api_key and len(record.api_key) > 10:

        """Validate priority is positive"""
        for record in self:
            if record.priority < 0:

        """Calculate total tokens"""
        for record in self:
            record.total_tokens = record.input_tokens + record.output_tokens

        """Compute member count"""
        for workspace in self:
            workspace.member_count = len(workspace.member_ids)

        """Override create to validate credential data"""
        for vals in vals_list:
            if 'credential_data' in vals and vals['credential_data']:

        """Display name with code if available"""
        result = []
        for record in self:

        """Compute branch_id from branch_type"""
        for record in self:
            if record.branch_type:

        """Validate JSON structure"""
        for record in self:
            if record.json_definition:

            '        """Execute the complete workflow"""',
            "        try:",
        ]

        """Generate Python code for a specific node"""
        node_type = node.get('type', 'unknown')
        node_name = node.get('name', 'Unnamed Node')

"""
        elif node_type == 'n8n-nodes-base.emailSend':
            return f"""

"""
        else:
            return f"# Unknown node type: {node_type} ({node_name})"

        """
        _logger.info(f'📂 [Canvas Load] Loading canvas state for workflow {workflow_id}')
        try:

        """
        return self.write_sam_debug_log(log_data)
    @api.model

        """Override create to set last_saved timestamp"""
        for vals in vals_list:
            vals['last_saved'] = fields.Datetime.now()

        """Save canvas viewport state"""
        self.ensure_one()
        update_vals = {}

    """
    Canvas Connections Model for Knowledge Visualizer V2
    Stores node-to-node connections for workflow canvas

        """Scan docs folder and update records"""
        docs_path = self._get_docs_path()
        if not docs_path.exists():

        """Determine category from filename and path"""
        filename_lower = filename.lower()
        # Architecture & System Design

        """Generate user-friendly title from filename"""
        name = file_path.stem
        # Convert underscores/hyphens to spaces and title case

        """Get the full file path for the document"""
        self.ensure_one()
        docs_path = self._get_docs_path()

        """Execute workflow nodes"""
        # Create node lookup
        node_lookup = {node['id']: node for node in nodes}

        """Execute a chain of connected nodes"""
        node_id = node['id']
        # Skip if already executed

        """Get nodes connected to the output of given node"""
        connected_nodes = []
        for connection in connections:

        """Remove all dynamically generated N8N menu items that polluted the main menu"""
        _logger.info('🧹 CLEANUP: Removing all dynamic N8N menu items from main Odoo menu...')
        # Find all menu items with N8N node names or emojis

# node_l2_ids = fields.Many2many('n8n.nodes.l2', 'n8n_l2_category_rel', 'category_id', 'node_l2_id', string='L2 Nodes')

# def _compute_node_count(self):

"""
N8N Node Extractor - Direct from Filesystem Using N8N's Logic
This extracts node data DIRECTLY from the N8N node files and applies

    """
    Wizard to extract N8N nodes directly from filesystem.
    Uses N8N's actual logic for categorization.

        """Load all data for display - suppliers, nodes, and overlay preview"""
        for record in self:
            record.supplier_ids = self.env['n8n.simple.supplier'].search([])

        """Generate the new beautiful N8N Node Selection Overlay with REAL DATA"""
        _logger.info('Computing new overlay with real N8N data...')
        # Get node data from database

                '''
            return cards_html
        # Simplified version without script tags for Odoo sanitization

        '''
        return html
    @api.model

        """Compute node type from is_trigger flag"""
        for node in self:
            node.node_type = 'Trigger' if node.is_trigger else 'Action'

        """
        # Step 1: Check if Core Nodes with explicit subcategory
        if node.is_core_nodes and node.subcategories:

        """Custom display name"""
        result = []
        for node in self:

        """
        Parse trigger operations from .node.js files.
        For triggers, we return 1 card representing the trigger itself (not config options).

        """Validate connection JSON"""
        for record in self:
            for field_name in ['input_connections', 'output_connections']:

        """Set parameters from dictionary"""
        self.ensure_one()
        self.parameters = json.dumps(params_dict, indent=2)

        """Get output connections as list"""
        self.ensure_one()
        if self.output_connections:

        """Execute trigger node"""
        if self.node_type == 'trigger_manual':
            return {'status': 'success', 'data': input_data or {}}

        """Execute Odoo-specific node"""
        if self.node_type == 'odoo_create_record':
            return self._execute_odoo_create(params, input_data)

        """Execute data processing node"""
        if self.node_type == 'data_transform':
            return self._execute_data_transform(params, input_data)

        """Execute notification"""
        message = params.get('message', 'Workflow notification')
        self.env.user.notify_info(message)

        """Execute Odoo record update"""
        model = params.get('model', '')
        record_id = params.get('record_id', 0)

# knowledge_visualizer_enabled = fields.Boolean(

#     string='Enable AI Automator Features',

#     config_parameter='the_ai_automator.knowledge_visualizer_enabled',

#     help='Enable the AI Automator workflow and visualization features',

#     groups='base.group_no_one'  # Hide from main settings menu

        """
        message_lower = user_message.lower()
        # Check for explicit brain requests

        """
        # Get user context
        user_ctx = user_profile.get_user_context_for_sam()

"""
SAM AI Chat Session & Messages
================================

        """Compute file size and type from uploaded file"""
        for record in self:
            if record.file_data and record.file_name:

        """Generate preview from content"""
        for record in self:
            if record.content:

# server_url = self.env['ir.config_parameter'].sudo().get_param('sam.power_prompts_server')

        prompt += f"""
YOUR BOUNDARIES WITH {name}:
- Personal topics: {'✅ Allowed' if user_ctx['boundaries']['can_discuss_personal'] else '❌ Keep professional'}

        """Add SAM's context to the message before sending to AI"""
        enriched = f"{system_prompt}\n\n"
        # Add Odoo context if available

        """Extract what actions user is requesting"""
        actions = []
        message_lower = message.lower()

        """How SAM addresses the user"""
        for record in self:
            if record.preferred_name:

        """
        self.ensure_one()
        pending = []

        """Record an interaction and update trust score"""
        self.interaction_count += 1
        self.last_interaction = fields.Datetime.now()

        """
        self.ensure_one()
        approved = []

        """
        self.ensure_one()
        if not self.approved_file_paths:

        """Validate template JSON structure"""
        for record in self:
            if record.json_definition:

        """Get platform configuration for dynamic loading"""
        if not platform_id:
            return {'error': 'platform_id is required'}

        """Render canvas container with platform"""
        canvas = request.env['canvas'].browse(int(canvas_id))
        if not canvas.exists():

        """Load nodes for a canvas based on its platform"""
        import logging
        _logger = logging.getLogger(__name__)

    """Controller for SAM AI Developer Mode features."""
    def _get_tool_paths(self):
        """

        """Get existing session or create new one"""
        Session = request.env['sam.chat.session'].sudo()
        if session_id:

    """Controller for SAM AI chat session management."""
    @http.route('/sam/session/get_history', type='json', auth='user')
    def get_session_history(self, mode=None, limit=20, **kwargs):

    /**
     * Get relative time string (e.g., "2 hours ago", "Yesterday")
     */

/** @odoo-module **/
import { Component, useState } from "@odoo/owl";
import { rpc } from "@web/core/network/rpc";

    /**
     * Get icon for permission type
     */

/** @odoo-module **/
import { Component, useState, onMounted } from "@odoo/owl";
import { rpc } from "@web/core/network/rpc";

    /**
     * Detect artifact type based on language and content
     */

/** @odoo-module **/
import { Component, useState, onWillStart } from "@odoo/owl";
import { useService } from "@web/core/utils/hooks";

    """
    Creatives Platform Controller
    Handles all /creatives/* routes for the SAM Creative platform.

"""
Placeholder file for ai_sam_creatives module.
The actual creatives.landing.card model is defined in ai_brain module

        """Open file directly in browser"""
        try:
            doc = request.env['ai.automator.documentation'].browse(doc_id)

        """Get full path to documentation file"""
        from odoo.modules.module import get_module_path
        module_path = Path(get_module_path('the_ai_automator'))

        """Show first 500 characters as preview"""
        for record in self:
            if record.content:

        """Compute MD5 hash for change detection"""
        for record in self:
            if record.content:

        """Build rich system prompt from agent knowledge for SAM chat"""
        for agent in self:
            # Build knowledge summary

"""
    @api.depends('archetype', 'category')
    def _compute_capabilities(self):

        """Determine agent archetype from name and config"""
        name_lower = agent_name.lower()
        if any(x in name_lower for x in ['architect', 'cto', 'cmo', 'cfo', 'cos']):

        """Determine slash command from agent name"""
        # Map known agents to their slash commands
        command_map = {

        """
        self.ensure_one()
        if not self.knowledge_file_ids:

        """Get SAM AI base path"""
        # Traverse up from this module to ai_sam_odoo directory
        current_file = os.path.abspath(__file__)

        """
        base_path = self._get_base_path()
        modules = []

        Scan models/*.py for Odoo model definitions (_name = 'model.name')
        Returns list of model names
        """

        """Load previous state from JSON file"""
        if os.path.exists(self.state_file_path):
            try:

        """)
        return analysis
    def action_view_report(self):

        """SAM AI Chat Portal (paid members only)"""
        user = request.env.user
        # Check if user is paid member

        """
        Get graph visualization data from ai.conversation
        Returns nodes and edges for vis.js rendering

        """Auto-detect if path is file or directory"""
        for record in self:
            if record.source_path and os.path.exists(record.source_path):

        """Create ai.conversation record"""
        # Claude export uses 'name', fallback to 'title' for other formats
        conv_name = conv_data.get('name') or conv_data.get('title') or 'Untitled Conversation'

        """Register built-in extractors on first use"""
        if AIDocumentExtractor._initialized:
            return

        """
        cls._extractors[extension.lower()] = handler
        _logger.debug(f"Registered extractor for {extension}")

        """Extract JSON files"""
        with open(file_path, 'r', encoding='utf-8') as f:
            data = json.load(f)

        """Extract PDF files"""
        try:
            import PyPDF2

        """Extract Excel files"""
        try:
            import openpyxl

        """
        prompt = f"""Generate a Python function to extract content from {extension} files.

"""
        conversation = self.env['ai.conversation'].create({
            'name': f'Extractor Generation: {extension}'

        """
        Get the graph structure for a conversation (nodes + relationships)
        Returns visualization data for the conversation and its connections

/** @odoo-module **/
import { patch } from "@web/core/utils/patch";
import { FormController } from "@web/views/form/form_controller";

/** @odoo-module **/
import publicWidget from "@web/legacy/js/public/public_widget";
import { rpc } from "@web/core/network/rpc";

    """API endpoints for branch/canvas type selection"""
    @http.route('/canvas/api/branches/available', type='http', auth='user', methods=['GET'])
    def get_available_branches(self, **kwargs):

        """Open file directly in browser"""
        try:
            doc = request.env['ai.automator.documentation'].browse(doc_id)

        """Get full path to documentation file"""
        from odoo.modules.module import get_module_path
        module_path = Path(get_module_path('the_ai_automator'))

        """
        Save/update canvas connections for a workflow
        JSON API endpoint for AJAX calls

        """
        Load canvas connections for a workflow
        JSON API endpoint for AJAX calls

        """
        Get available Odoo apps for canvas menu dropdown
        Returns simplified menu data for Service Bridge

        """
        Get N8N nodes from n8n.simple.node model grouped by UI placement
        HTTP API endpoint for the node selector overlay - Uses new simplified model

        """
        Get operations for a specific n8n.simple.node
        Returns triggers/actions parsed from Description.js files on-demand

        """
        🎯 JSON Node Structure API - Get triggers and actions for nodes with has_node_json=True
        Called when user clicks a parent node that has actual .node.json files

        """
        📄 Get metadata for a single N8N node
        Used for detailed node information on-demand

        """
        📁 Get L1 children for hierarchical nodes like Google, Microsoft
        Called when user clicks a parent node that has sub-folders (has_node_json=False)

    /**
     * Find node by name (for loading connections from database)
     */

                    /** @deprecated for removal - replaced by getBinaryDataAsync() */
                    getBinaryData: () => {
                        if (mode === 'manual') {

    /**
     * Returns the given sheet data in a structured way
     */

            /* -------------------------------------------------------------------------- */
            /*               Get fields for create and update a destination               */

            /* -------------------------------------------------------------------------- */
            /*                         Get fields for create admin                        */

            /*                         Get fields for update admin                        */
            /* -------------------------------------------------------------------------- */

            /*                          Get fields for create hub                         */
            /* -------------------------------------------------------------------------- */

            /* -------------------------------------------------------------------------- */
            /*                          Get fields for update hub                         */

            /* -------------------------------------------------------------------------- */
            /*                        Get fields for create worker                        */

            /*                        Get fields for update worker                        */
            /* -------------------------------------------------------------------------- */

            /* -------------------------------------------------------------------------- */
            /*                    Get fields for get and getAll workers                   */

            /*                        Get fields for create webhook                       */
            /* -------------------------------------------------------------------------- */

            /* -------------------------------------------------------------------------- */
            const updateFields = this.getNodeParameter('updateFields', item);
            const taskData = {};

            /* -------------------------------------------------------------------------- */
            const filters = this.getNodeParameter('filters', item);
            const listTaskData = {};

            /*      Get driver time estimates for tasks that haven't been created yet     */
            /* -------------------------------------------------------------------------- */

                    /* -------------------------------------------------------------------------- */
                    /*      Get driver time estimates for tasks that haven't been created yet     */

/** Parses the given value in a number if it is one else returns a string */
function getParsedValue(value) {
    if (value.match(/^[\d\.]+$/) === null) {

# from github import Github

# print(repo.remotes.origin.pull())

# print(repo.remotes.origin.push())

# print(repo.remotes.origin.pull())

# print(repo.remotes.origin.push())