fuck my life with ollama

openwebui_integration/__manifest__.py

@@ -2,7 +2,7 @@
 # Part of Odoo. See LICENSE file for full copyright and licensing details.
 {
     'name': 'OpenWebUI Integration',
-    'version': '18.0.1.0.1',
+    'version': '18.0.1.1.0',
     'summary': 'Core integration with OpenWebUI',
     'sequence': 10,
     'description': """
@@ -30,4 +30,5 @@ Features:
     'auto_install': False,
     'license': 'LGPL-3',
     'i18n': True,
+    'post_init_hook': 'post_init_hook',
 }

openwebui_integration/hooks.py

@@ -0,0 +1,9 @@
+# -*- coding: utf-8 -*-
+
+def post_init_hook(cr, registry):
+    """Post-init hook for initializing new columns."""
+    # Initialize ollama_port with default value
+    cr.execute("""
+        ALTER TABLE res_company
+        ADD COLUMN IF NOT EXISTS ollama_port integer DEFAULT 11434;
+    """)

openwebui_integration/migrations/18.0.1.0.1/__init__.py

@@ -1 +0,0 @@
-from . import pre-migration

openwebui_integration/migrations/18.0.1.0.1/pre-migration.py

@@ -1,17 +0,0 @@
-def migrate(cr, version):
-    """Add products_per_request column to res_company table."""
-    if not version:
-        return
-
-    # Add products_per_request column if it doesn't exist
-    cr.execute("""
-        SELECT column_name 
-        FROM information_schema.columns 
-        WHERE table_name='res_company' 
-        AND column_name='openwebui_products_per_request'
-    """)
-    if not cr.fetchone():
-        cr.execute("""
-            ALTER TABLE res_company 
-            ADD COLUMN openwebui_products_per_request integer DEFAULT 10
-        """)

openwebui_integration/models/openwebui_bot_mixin.py

@@ -75,13 +75,16 @@ class OpenWebUIBotMixin(models.AbstractModel):
                 # Send the message to the model
                 _logger.info('Attempt %d/%d: Sending message to model (timeout=%ds)', 
                            attempt + 1, max_retries, timeout)
+                _logger.info('Sending message to model: %r', message)
                 response = model.send_message(message=message, timeout=timeout)
+                _logger.info('Raw response from model: %r', response)
                 
                 # Si la réponse contient une erreur de connexion, on la traite comme une exception
                 if isinstance(response, str) and "Connection error" in response:
+                    _logger.error('Connection error in response: %r', response)
                     raise ConnectionError(response)
                 
-                _logger.info('Received response from model: %r', response)
+                _logger.info('Processed response from model: %r', response)
 
                 if not response:
                     raise ValueError("Empty response from model")
@@ -89,18 +92,62 @@ class OpenWebUIBotMixin(models.AbstractModel):
                 if not isinstance(response, str):
                     raise ValueError(f"Invalid response type: {type(response)}")
 
+                # Debug de la réponse brute
+                _logger.info('Raw response from model: %r', response)
+                
                 # Clean up the response
-                # Supprimer les blocs de code markdown
+                # Supprimer les blocs de code markdown et autres caractères problématiques
                 response = re.sub(r'```json\n|\n```', '', response.strip())
-                _logger.debug('Response after markdown cleanup: %r', response)
+                response = re.sub(r'\\([^\\])', r'\1', response)  # Supprimer les backslashes simples
+                response = re.sub(r'">\\n', '",', response)  # Corriger le format des fins de lignes
+                response = re.sub(r'\\n\s*]\\n"}$', ']}', response)  # Corriger la fin du JSON
+                _logger.info('Response after cleanup: %r', response)
+                
+                # Debug des lignes individuelles
+                lines = response.strip().split('\n')
+                _logger.info('Number of response lines: %d', len(lines))
+                for i, line in enumerate(lines):
+                    _logger.info('Line %d: %r', i + 1, line)
 
-                try:
-                    # Essayer de parser directement la réponse nettoyée
-                    parsed_response = json.loads(response)
+                # Paramètres de retry pour le parsing JSON
+                max_json_retries = 3
+                json_retry_delay = 2  # secondes
+                last_json_error = None
+                
+                for json_attempt in range(max_json_retries):
+                    try:
+                        # Pour Ollama, la réponse peut être une série de JSON séparés par des newlines
+                        # On prend le dernier JSON qui devrait être la réponse finale
+                        json_responses = [json.loads(line) for line in response.strip().split('\n') if line.strip()]
+                        if json_responses:
+                            parsed_response = json_responses[-1]  # Prendre le dernier JSON
+                        else:
+                            parsed_response = json.loads(response)
+                            
+                        # Si on arrive ici, le parsing a réussi
+                        break
+                        
+                    except json.JSONDecodeError as e:
+                        last_json_error = e
+                        if json_attempt < max_json_retries - 1:
+                            _logger.warning('JSON parsing attempt %d/%d failed: %s. Retrying in %d seconds...', 
+                                          json_attempt + 1, max_json_retries, str(e), json_retry_delay)
+                            time.sleep(json_retry_delay)
+                        else:
+                            _logger.error('All %d JSON parsing attempts failed. Last error: %s', 
+                                         max_json_retries, str(e))
+                            raise ValueError(f"Failed to parse JSON after {max_json_retries} attempts: {str(e)}")
+                        
+                    # Si c'est un dictionnaire avec une clé 'response', extraire la valeur
+                    if isinstance(parsed_response, dict):
+                        if 'response' in parsed_response:
+                            # Pour Ollama, la réponse est directement dans la clé 'response'
+                            clean_response = parsed_response['response']
+                            return self._process_bot_response(values, clean_response)
                     clean_response = response
-                except json.JSONDecodeError as e:
-                    _logger.warning('Failed to parse response directly: %s', e)
-                    # Si échec, chercher une liste JSON dans la réponse
+                # Si le parsing initial a échoué, essayer d'extraire une liste JSON
+                if last_json_error is not None:
+                    _logger.warning('Failed to parse response directly, trying to extract JSON list')
                     start = response.find('[')
                     end = response.rfind(']')
                     
@@ -111,11 +158,30 @@ class OpenWebUIBotMixin(models.AbstractModel):
                     clean_response = response[start:end + 1]
                     _logger.debug('Extracted JSON list: %r', clean_response)
                     
-                    try:
-                        parsed_response = json.loads(clean_response)
-                    except json.JSONDecodeError as e:
-                        _logger.error('Failed to parse extracted JSON: %s', e)
-                        raise ValueError("Invalid JSON list in response")
+                    # Nouveau cycle de retry pour le JSON extrait
+                    for json_attempt in range(max_json_retries):
+                        try:
+                            parsed_response = json.loads(clean_response)
+                            # Si on arrive ici, le parsing a réussi
+                            break
+                        except json.JSONDecodeError as e:
+                            last_json_error = e
+                            if json_attempt < max_json_retries - 1:
+                                _logger.warning('Extracted JSON parsing attempt %d/%d failed: %s. Retrying in %d seconds...', 
+                                              json_attempt + 1, max_json_retries, str(e), json_retry_delay)
+                                time.sleep(json_retry_delay)
+                            else:
+                                _logger.error('All %d extracted JSON parsing attempts failed. Last error: %s', 
+                                             max_json_retries, str(e))
+                                raise ValueError("Invalid JSON list in response")
+
+                # Extraire la liste de produits si présente
+                if isinstance(parsed_response, dict):
+                    if 'products' in parsed_response:
+                        parsed_response = parsed_response['products']
+                    elif 'response' in parsed_response:
+                        # Cas précédent où la réponse est dans la clé 'response'
+                        parsed_response = json.loads(parsed_response['response'])
 
                 if not isinstance(parsed_response, list):
                     _logger.error('Response is not a list: %r', parsed_response)

openwebui_integration/models/openwebui_model.py

@@ -115,32 +115,108 @@ class OpenWebUIModel(models.Model):
             str: The model's response or error message
         """
         self.ensure_one()
+        company = self.env.company
         
-        # Initialize messages list with history if provided
-        messages = []
-        if message_history:
-            messages.extend(message_history)
-        
-        # Add the current message
-        messages.append({'role': 'user', 'content': message})
-        
-        data = {
-            'model': self.identifier,
-            'messages': messages,
-        }
+        # Base data structure
+        if company.ai_provider == 'ollama':
+            # Format for Ollama API
+            data = {
+                'model': self.identifier,
+                'stream': False,  # We want a single response
+                'options': {
+                    'num_ctx': company.openwebui_context_size,
+                    'temperature': 0.7  # Default temperature
+                }
+            }
+            
+            # Handle message history and current message
+            if message_history:
+                messages = []
+                for msg in message_history:
+                    messages.append({
+                        'role': msg['role'],
+                        'content': msg['content']
+                    })
+                messages.append({'role': 'user', 'content': message})
+                data['messages'] = messages
+            else:
+                # For single message, use simple prompt
+                if instructions:
+                    # If system instructions are provided, use chat format
+                    data['messages'] = [
+                        {'role': 'system', 'content': instructions},
+                        {'role': 'user', 'content': message}
+                    ]
+                else:
+                    # For simple queries, use generate endpoint
+                    data = {
+                        'model': self.identifier,
+                        'prompt': message,
+                        'stream': False,
+                        'options': data['options']
+                    }
+                    endpoint = 'api/generate'
+                    
+            if not 'endpoint' in locals():
+                endpoint = 'api/chat'
+                
+        else:  # openwebui
+            # Format for OpenWebUI API
+            data = {
+                'model': self.identifier,
+                'messages': message_history or []
+            }
+            data['messages'].append({'role': 'user', 'content': message})
+            
+            if instructions:
+                data['system'] = instructions
+            if context:
+                data['context'] = context
+                
+            data['options'] = {
+                'num_ctx': company.openwebui_context_size
+            }
+            endpoint = 'chat/completions'
 
-        if context:
-            data['context'] = context
-        if instructions:
-            data['system'] = instructions
-
-        success, result = self._make_request('chat/completions', method='POST', data=data, timeout=timeout)
+        _logger.info('Sending request to %s with data: %r', endpoint, data)
+        success, result = self._make_request(endpoint, method='POST', data=data, timeout=timeout)
+        
         if not success:
+            _logger.error('Request failed: %s', result)
             return f"Error: {result}"
+            
+        _logger.info('Raw API response: %r', result)
 
         try:
-            return result['choices'][0]['message']['content']
-        except (KeyError, IndexError) as e:
+            # Handle Ollama response format
+            if isinstance(result, dict):
+                if 'response' in result:  # Ollama chat/generate response
+                    return result['response']
+                elif 'message' in result:  # Ollama chat response alternative format
+                    return result['message']['content']
+                elif 'choices' in result:  # OpenWebUI format
+                    return result['choices'][0]['message']['content']
+                else:
+                    _logger.error('Unexpected API response format: %r', result)
+                    return f"Error: Unexpected response format from API"
+                    
+            # Handle streaming response (should not happen with stream=False)
+            elif isinstance(result, str):
+                try:
+                    # Parse the last line of a streaming response
+                    lines = [line.strip() for line in result.split('\n') if line.strip()]
+                    if lines:
+                        last_response = json.loads(lines[-1])
+                        if 'response' in last_response:
+                            return last_response['response']
+                except json.JSONDecodeError as e:
+                    _logger.error('Failed to parse streaming response: %s', e)
+                    return result  # Return raw string if parsing fails
+                    
+            return f"Error: Unexpected response type: {type(result)}"
+            
+        except Exception as e:
+            _logger.error('Error processing API response: %s', str(e))
             return f"Error processing response: {str(e)}"
 
     def cleanup_temp_models(self):
@@ -217,7 +293,32 @@ class OpenWebUIModel(models.Model):
             return False, "OpenWebUI is not enabled"
 
         try:
-            url = f"{config['api_url'].rstrip('/')}/api/{endpoint.lstrip('/')}"
+            api_url = config['api_url']
+            if not api_url:
+                return False, "OpenWebUI API URL is not configured"
+
+            # Add scheme if missing
+            if not api_url.startswith(('http://', 'https://')):
+                api_url = f'http://{api_url}'
+
+            # Check if port is included in URL
+            from urllib.parse import urlparse
+            parsed_url = urlparse(api_url)
+            if not parsed_url.port:
+                # Use Ollama port from company configuration
+                company = self.env.company
+                netloc = parsed_url.netloc
+                if ':' in netloc:
+                    host = netloc.split(':')[0]
+                else:
+                    host = netloc
+                api_url = f"{parsed_url.scheme}://{host}:{company.ollama_port}"
+
+            # Pour Ollama, les endpoints incluent déjà /api/
+            if endpoint.startswith('api/'):
+                url = f"{api_url.rstrip('/')}/{endpoint.lstrip('/')}"
+            else:
+                url = f"{api_url.rstrip('/')}/api/{endpoint.lstrip('/')}"
             headers = {
                 'Accept': 'application/json'
             }
@@ -240,10 +341,46 @@ class OpenWebUIModel(models.Model):
             elif method in ['POST', 'PUT', 'PATCH']:
                 kwargs['json'] = data
             
+            # Send the request
             response = requests.request(method=method, url=url, **kwargs)
             response.raise_for_status()
             
-            return True, response.json()
+            # Log raw response
+            response_text = response.text.strip()
+            _logger.info('Raw response text: %r', response_text)
+            
+            # Split response into lines (Ollama may send multiple JSON objects)
+            response_lines = [line.strip() for line in response_text.split('\n') if line.strip()]
+            
+            # Try to parse each line as JSON
+            parsed_responses = []
+            for line in response_lines:
+                try:
+                    parsed_json = json.loads(line)
+                    if isinstance(parsed_json, dict):
+                        # Handle Ollama message format
+                        if 'message' in parsed_json and 'content' in parsed_json['message']:
+                            content = parsed_json['message']['content']
+                            if content:
+                                try:
+                                    # Try to parse content as JSON
+                                    content_json = json.loads(content)
+                                    parsed_responses.append(content_json)
+                                except json.JSONDecodeError:
+                                    # Content is not JSON
+                                    parsed_responses.append(content)
+                        else:
+                            parsed_responses.append(parsed_json)
+                except json.JSONDecodeError:
+                    # Skip invalid JSON lines
+                    continue
+            
+            # Return the last valid parsed response
+            if parsed_responses:
+                return True, parsed_responses[-1]
+            
+            # If no valid JSON found, return the raw text
+            return True, response_text
             
         except requests.exceptions.SSLError:
             return False, "SSL/TLS verification failed"
@@ -260,7 +397,7 @@ class OpenWebUIModel(models.Model):
     def test_connection(self):
         """Test the connection to the OpenWebUI API.
 
-        This method performs a simple request to the /api/models endpoint
+        This method performs a simple request to the /api/chat endpoint
         to verify that:
         1. The API URL is accessible
         2. The credentials are valid
@@ -274,37 +411,46 @@ class OpenWebUIModel(models.Model):
         Note:
             Uses a reduced timeout of 5 seconds to avoid long waits.
         """
-        return self._make_request('models', timeout=5)
+        return self._make_request('api/chat', timeout=5)
 
     @api.model
     def get_available_models(self):
-        """Get the list of available models from the OpenWebUI API.
+        """Get the list of available models from the OpenWebUI/Ollama API.
 
         This method attempts to retrieve the list of models from the API.
+        For Ollama, it uses the /api/tags endpoint.
         If it fails, it returns a default list of common models.
 
         Returns:
             list: A list of tuples (id, name) of available models.
-                Example: [('gpt-3.5-turbo', 'GPT-3.5 Turbo'), ('gpt-4', 'GPT-4')]
+                Example: [('llama2', 'Llama 2'), ('mistral', 'Mistral')]
 
         Note:
-            - Handles both possible API response formats (list or dict)
+            - Handles both Ollama and OpenWebUI API response formats
             - Returns DEFAULT_MODELS in case of error or unexpected format
             - Errors are logged but don't interrupt execution
         """
-        success, result = self._make_request('models')
+        # Try Ollama endpoint first
+        success, result = self._make_request('api/tags')
         
         if not success:
-            _logger.error(f"Error fetching models: {result}")
-            return DEFAULT_MODELS
+            # Try OpenWebUI endpoint as fallback
+            success, result = self._make_request('models')
+            if not success:
+                _logger.error(f"Error fetching models: {result}")
+                return DEFAULT_MODELS
             
         try:
-            if isinstance(result, list):
+            # Handle Ollama response format
+            if isinstance(result, dict) and 'models' in result:
+                return [(model['name'], model.get('name', model['name'])) for model in result['models']]
+            # Handle OpenWebUI response format
+            elif isinstance(result, list):
                 return [(model['id'], model.get('name', model['id'])) for model in result]
             elif isinstance(result, dict) and 'data' in result:
                 return [(model['id'], model.get('name', model['id'])) for model in result['data']]
             else:
-                _logger.warning("Unexpected response format from OpenWebUI API")
+                _logger.warning("Unexpected response format from API")
                 return DEFAULT_MODELS
         except (KeyError, TypeError, AttributeError) as e:
             _logger.error(f"Error processing models response: {str(e)}")
@@ -327,7 +473,7 @@ class OpenWebUIModel(models.Model):
 
     @api.model
     def _sync_models(self):
-        """Internal method to synchronize models from OpenWebUI.
+        """Internal method to synchronize models from OpenWebUI/Ollama.
 
         This method performs the actual synchronization work:
         1. Cleans up temporary models
@@ -342,27 +488,47 @@ class OpenWebUIModel(models.Model):
         Note:
             This is an internal method called by sync_models().
             It should not be called directly unless you need fine-grained control.
+            Supports both Ollama and OpenWebUI API formats.
         """
         # First clean up temporary models
         self.cleanup_temp_models()
 
-        success, result = self._make_request('models')
+        # Try Ollama endpoint first
+        success, result = self._make_request('api/tags')
+        
         if not success:
-            return False, result
+            # Try OpenWebUI endpoint as fallback
+            success, result = self._make_request('models')
+            if not success:
+                return False, result
 
         try:
-            models_data = result if isinstance(result, list) else result.get('data', [])
-            for model_data in models_data:
-                existing = self.search([('identifier', '=', model_data['id'])])
-                if not existing:
-                    self.with_context(sync_models=True).create({
-                        'name': model_data.get('name', model_data['id']),
-                        'identifier': model_data['id'],
-                        'description': model_data.get('description', ''),
-                    })
+            # Handle Ollama response format
+            if isinstance(result, dict) and 'models' in result:
+                models_data = result['models']
+                for model_data in models_data:
+                    existing = self.search([('identifier', '=', model_data['name'])])
+                    if not existing:
+                        self.with_context(sync_models=True).create({
+                            'name': model_data['name'],
+                            'identifier': model_data['name'],
+                            'description': model_data.get('description', ''),
+                        })
+            # Handle OpenWebUI response format
+            else:
+                models_data = result if isinstance(result, list) else result.get('data', [])
+                for model_data in models_data:
+                    existing = self.search([('identifier', '=', model_data['id'])])
+                    if not existing:
+                        self.with_context(sync_models=True).create({
+                            'name': model_data.get('name', model_data['id']),
+                            'identifier': model_data['id'],
+                            'description': model_data.get('description', ''),
+                        })
             return True, None
         except (KeyError, TypeError) as e:
             _logger.error(f"Error processing model data: {str(e)}")
+            return False, f"Error processing model data: {str(e)}"
             return False, f"Invalid model data format: {str(e)}"
         except odoo.exceptions.AccessError as e:
             _logger.error(f"Access error while creating model: {str(e)}")

openwebui_integration/models/res_company.py

@@ -6,13 +6,34 @@ including service activation, API keys, and other configuration parameters.
 """
 # Part of Odoo. See LICENSE file for full copyright and licensing details.
 
-from odoo import models, fields, _
+from odoo import models, fields, api, tools, _
 from odoo.exceptions import UserError
 
 
 class ResCompany(models.Model):
     _inherit = 'res.company'
 
+
+
+    ai_provider = fields.Selection([
+        ('openwebui', 'OpenWebUI'),
+        ('ollama', 'Ollama')
+    ],
+        string='AI Provider',
+        default='openwebui',
+        required=True,
+        help="Select the AI provider to use"
+    )
+
+    # Ollama Configuration
+    ollama_port = fields.Integer(
+        string='Ollama Port',
+        default=11434,
+        required=True,
+        help="Port number for the Ollama server (default: 11434)"
+    )
+
+    # OpenWebUI Configuration
     openwebui_enabled = fields.Boolean(
         string='Enable OpenWebUI',
         default=False,
@@ -41,6 +62,54 @@ class ResCompany(models.Model):
         help="Maximum wait time for API calls"
     )
     
+    openwebui_context_size = fields.Integer(
+        string='Context Window Size',
+        default=4096,
+        help="Maximum number of tokens in the context window (default: 4096)"
+    )
+    
+    openwebui_max_products = fields.Integer(
+        string='Maximum Products per Batch',
+        default=800,
+        help="Maximum number of products that can be processed at once (default: 800)"
+
+    def test_ollama_connection(self):
+        """Test the connection to Ollama server.
+
+        Returns:
+            dict: A notification action with the test result
+        """
+        self.ensure_one()
+
+        if self.ai_provider != 'ollama':
+            raise UserError(_("Please select Ollama as the AI provider first."))
+
+        try:
+            import requests
+            # Test connection to Ollama server
+            url = f'http://localhost:{self.ollama_port}/api/tags'
+            response = requests.get(url, timeout=5)
+            response.raise_for_status()
+
+            # If we get here, the connection was successful
+            return {
+                'type': 'ir.actions.client',
+                'tag': 'display_notification',
+                'params': {
+                    'title': _('Success'),
+                    'message': _('Successfully connected to Ollama server on port %s', self.ollama_port),
+                    'sticky': False,
+                    'type': 'success',
+                }
+            }
+
+        except requests.exceptions.ConnectionError:
+            raise UserError(_("Could not connect to Ollama server. Please check if Ollama is running and the port number is correct."))
+        except requests.exceptions.Timeout:
+            raise UserError(_("Connection to Ollama server timed out. Please check your network settings."))
+        except requests.exceptions.RequestException as e:
+            raise UserError(_("Error connecting to Ollama server: %s", str(e)))
+    
     openwebui_products_per_request = fields.Integer(
         string='Products per Request',
         default=10,
@@ -59,6 +128,12 @@ class ResCompany(models.Model):
         domain="[('company_id', '=', id), ('is_active', '=', True)]",
         help="Default OpenWebUI model to use for AI requests"
     )
+    
+    openwebui_context_size = fields.Integer(
+        string='Context Window Size',
+        default=2048,
+        help="Size of the context window in tokens (e.g., 2048, 4096, 8192)"
+    )
 
     def test_openwebui_connection(self):
         """Test the connection to OpenWebUI API.
@@ -108,63 +183,116 @@ class ResCompany(models.Model):
         }
 
     def refresh_model_list(self):
-        """Synchronize available AI models from OpenWebUI with Odoo.
+        """Synchronize available AI models with Odoo.
 
-        This method performs the following operations:
-        1. Verifies that OpenWebUI integration is enabled for the company
-        2. Connects to the OpenWebUI API to fetch the latest model list
-        3. Updates the local database:
-           - Creates records for new models
-           - Updates existing model information
-           - Archives models that are no longer available
+        This method performs the following operations based on the selected AI provider:
         
-        Technical Details:
-            - Uses the sync_models context to trigger a full synchronization
-            - Performs all operations in a single transaction
-            - Handles API connection errors gracefully
+        For OpenWebUI:
+        1. Verifies that OpenWebUI integration is enabled
+        2. Connects to the OpenWebUI API to fetch the latest model list
+        3. Updates the local database with model information
+
+        For Ollama:
+        1. Connects to the Ollama server
+        2. Fetches available models using the Ollama API
+        3. Updates the local database with model information
         
         Returns:
-            dict: An action dictionary with the following structure:
-                {
-                    'type': 'ir.actions.client',
-                    'tag': 'display_notification',
-                    'params': {
-                        'title': str,
-                        'message': str,
-                        'sticky': bool,
-                        'type': str,
-                    }
-                }
+            dict: A notification action with the sync results
         
         Raises:
-            UserError: In the following cases:
-                - OpenWebUI is not enabled for the company
-                - API connection fails
-                - Model synchronization fails
-        
-        Example:
-            >>> company = env['res.company'].browse(1)
-            >>> result = company.refresh_model_list()
-            >>> print(result['params']['message'])
-            'Models list has been refreshed successfully!'
+            UserError: If there are connection or synchronization issues
         """
         self.ensure_one()
-        
-        if not self.openwebui_enabled:
-            raise UserError(_("OpenWebUI is not enabled for this company."))
 
-        Model = self.env['openwebui.model'].with_context(sync_models=True)
-        success, result = Model._sync_models()
-        
+        if self.ai_provider == 'ollama':
+            return self._refresh_ollama_models()
+        elif self.ai_provider == 'openwebui':
+            if not self.openwebui_enabled:
+                raise UserError(_("OpenWebUI is not enabled for this company."))
+            return self._refresh_openwebui_models()
+        else:
+            raise UserError(_("Unknown AI provider: %s", self.ai_provider))
+
+    def _refresh_ollama_models(self):
+        """Fetch and sync available models from Ollama server."""
+        try:
+            import requests
+            url = f'http://localhost:{self.ollama_port}/api/tags'
+            response = requests.get(url, timeout=5)
+            response.raise_for_status()
+            models_data = response.json()
+
+            # Get the OpenWebUI model object
+            Model = self.env['openwebui.model'].with_context(sync_models=True)
+            
+            # Process each model from Ollama
+            for model in models_data.get('models', []):
+                name = model.get('name', '')
+                if not name:
+                    continue
+
+                # Split name and tag if present (format: name:tag)
+                identifier = name
+                if ':' in name:
+                    name, tag = name.split(':', 1)
+                    identifier = f"{name}:{tag}"
+                else:
+                    identifier = f"{name}:latest"
+
+                # Check if model already exists
+                existing_model = Model.search([
+                    ('identifier', '=', identifier),
+                    ('company_id', '=', self.id)
+                ], limit=1)
+
+                model_vals = {
+                    'name': name,
+                    'identifier': identifier,
+                    'is_active': True,
+                    'description': f"Ollama model: {name}",
+                    'company_id': self.id
+                }
+
+                if existing_model:
+                    # Update existing model
+                    existing_model.write(model_vals)
+                else:
+                    # Create new model
+                    Model.create(model_vals)
+
+            return {
+                'type': 'ir.actions.client',
+                'tag': 'display_notification',
+                'params': {
+                    'title': _('Success'),
+                    'message': _('Successfully synchronized Ollama models'),
+                    'sticky': False,
+                    'type': 'success',
+                }
+            }
+
+        except requests.exceptions.ConnectionError:
+            raise UserError(_("Could not connect to Ollama server. Please check if Ollama is running and the port number is correct."))
+        except requests.exceptions.Timeout:
+            raise UserError(_("Connection to Ollama server timed out. Please check your network settings."))
+        except requests.exceptions.RequestException as e:
+            raise UserError(_("Error connecting to Ollama server: %s", str(e)))
+        except Exception as e:
+            raise UserError(_("Error synchronizing Ollama models: %s", str(e)))
+
+    def _refresh_openwebui_models(self):
+        """Fetch and sync available models from OpenWebUI."""
+        success, result = self.env['openwebui.model'].sync_models()
         if not success:
             raise UserError(_("Failed to refresh models: %s") % result)
-            
+
         return {
             'type': 'ir.actions.client',
             'tag': 'display_notification',
             'params': {
                 'title': _('Success'),
-                'message': _('Models list has been refreshed successfully!'),
+                'message': _('Successfully synchronized OpenWebUI models'),
                 'sticky': False,
                 'type': 'success',
             }

openwebui_integration/views/res_company_views.xml

@@ -6,10 +6,29 @@
         <field name="inherit_id" ref="base.view_company_form"/>
         <field name="arch" type="xml">
             <xpath expr="//notebook" position="inside">
-                <page string="OpenWebUI" name="openwebui">
+                <page string="AI Configuration" name="ai_config">
                     <group>
+                        <group string="Provider Selection">
+                            <field name="ai_provider"/>
+                        </group>
+                    </group>
+
+                    <!-- Ollama Configuration -->
+                    <group string="Ollama Configuration" invisible="ai_provider != 'ollama'">
                         <group>
-                            <field name="openwebui_enabled"/>
+                            <field name="ollama_port" required="ai_provider == 'ollama'"/>
+                            <button name="test_ollama_connection" 
+                                    string="Test Connection" 
+                                    type="object" 
+                                    class="btn-primary"
+                                    invisible="ai_provider != 'ollama'"/>
+                        </group>
+                    </group>
+
+                    <!-- OpenWebUI Configuration -->
+                    <group string="OpenWebUI Configuration" invisible="ai_provider != 'openwebui'">
+                        <group>
+                            <field name="openwebui_enabled" required="ai_provider == 'openwebui'"/>
                             <field name="openwebui_api_url" 
                                    invisible="not openwebui_enabled"
                                    required="openwebui_enabled"
@@ -24,6 +43,9 @@
                                    invisible="not openwebui_enabled"/>
                             <field name="openwebui_timeout" 
                                    invisible="not openwebui_enabled"/>
+                            <field name="openwebui_context_size" 
+                                   invisible="not openwebui_enabled"
+                                   help="Size of the context window in tokens (e.g., 2048, 4096, 8192)"/>
                             <field name="openwebui_products_per_request" 
                                    invisible="not openwebui_enabled"
                                    help="Number of products to process in a single API request"/>
@@ -34,6 +56,19 @@
                                     invisible="not openwebui_enabled"/>
                         </group>
                     </group>
+
+                    <!-- Ollama Configuration -->
+                    <group string="Ollama Configuration" invisible="ai_provider != 'ollama'">
+                        <group>
+                            <field name="openwebui_api_url" 
+                                   required="ai_provider == 'ollama'"
+                                   placeholder="http://localhost:11434"/>
+                            <field name="openwebui_context_size" 
+                                   help="Size of the context window in tokens (e.g., 2048, 4096, 8192)"/>
+                            <field name="openwebui_products_per_request" 
+                                   help="Number of products to process in a single API request"/>
+                        </group>
+                    </group>
                     <group string="Models Configuration" invisible="not openwebui_enabled">
                         <field name="openwebui_default_model_id" 
                                options="{'no_create': True, 'no_open': True}"

openwebui_integration_product/models/product_template.py

@@ -55,21 +55,24 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
     def _generate_bot_message(self, records, values, command=None):
         """Generates the message to send to the bot to get category suggestions."""
         # Préparer les données des produits
-        products_data = [{
-            'odoo_id': record.id,  # ID interne Odoo
-            'name': record.name,
-            'description': record.description or '',
-            'description_sale': record.description_sale or '',
-            'default_code': record.default_code or '',
-            'current_category': record.categ_id.display_name,
-            'sellers': [
-                {
-                    'name': seller.partner_id.display_name,
-                    'product_code': seller.product_code or '',
-                    'product_name': seller.product_name or ''
-                } for seller in record.seller_ids
-            ]
-        } for record in records]
+        # Prepare product data for AI analysis
+        products_data = []
+        for record in records:
+            products_data.append({
+                'odoo_id': record.id,  # Unique Odoo product ID
+                'name': record.name,
+                'description': record.description or '',
+                'description_sale': record.description_sale or '',
+                'default_code': record.default_code or '',
+                'current_category': record.categ_id.display_name,
+                'sellers': [
+                    {
+                        'name': seller.partner_id.display_name,
+                        'product_code': seller.product_code or '',
+                        'product_name': seller.product_name or ''
+                    } for seller in record.seller_ids
+                ]
+            })
 
         # Récupérer toutes les catégories disponibles
         Category = self.env['product.category']
@@ -88,11 +91,37 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
             'available_categories': available_categories,
             'instructions': """For each product in the products list, analyze the product information and suggest the most appropriate product category from the available list.
             Consider each product's name, description, and supplier information to make the best match.
-            Return a list of JSON objects, one for each product, with:
-            - 'odoo_id' (integer): The internal Odoo ID of the product
-            - 'category_id' (integer): The ID of the most appropriate category
-            - 'confidence' (float between 0 and 100): How confident you are about this suggestion
-            - 'explanation' (string): A detailed explanation of why this category was chosen, including analysis of the product name, description, and other relevant information.""",
+            
+            IMPORTANT: Your response MUST be a JSON object with a 'products' array containing EXACTLY ONE object for EACH product in the input list.
+            Example format for a list of 2 products:
+            {
+                "products": [
+                    {
+                        "odoo_id": 1,
+                        "category_id": 454,
+                        "confidence": 85.0,
+                        "explanation": "The product is categorized as safety equipment because..."
+                    },
+                    {
+                        "odoo_id": 2,
+                        "category_id": 448,
+                        "confidence": 90.0,
+                        "explanation": "This product belongs to vacuum systems because..."
+                    }
+                ]
+            }
+            
+            Requirements:
+            1. Response must be a single JSON object with a 'products' array
+            2. You MUST return exactly one object in the products array for each product in the input list
+            3. Each object must have exactly these fields:
+               - odoo_id (integer): The index of the product in the input list (starting at 1)
+               - category_id (integer): The ID of the most appropriate category
+               - confidence (float between 0 and 100): How confident you are about this suggestion
+               - explanation (string): A detailed explanation of why this category was chosen
+            4. Do not add any other fields outside of the products array
+            5. Do not add any markdown formatting or code blocks
+            6. If you're not sure about a product's category, still provide a suggestion with lower confidence""",
             'format': 'json'
         }
         return json.dumps(message)
@@ -100,19 +129,32 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
     def _process_bot_response(self, values, response):
         """Process the bot response to extract the suggested category."""
         try:
-            results = json.loads(response)
+            # Parse the response
+            if isinstance(response, str):
+                response_data = json.loads(response)
+            else:
+                response_data = response  # Already parsed JSON
+                
+            # Extract products list
+            if isinstance(response_data, dict) and 'products' in response_data:
+                results = response_data['products']
+            elif isinstance(response_data, list):
+                results = response_data
+            else:
+                raise ValueError("La réponse ne contient pas de liste de produits valide")
+                
             if not isinstance(results, list):
                 raise ValueError("La réponse n'est pas une liste JSON valide")
 
             for result in results:
                 category_id = result.get('category_id')
                 confidence = result.get('confidence', 0.0)
-                product_id = result.get('odoo_id')
+                temp_id = result.get('odoo_id')
 
                 if not category_id:
                     raise ValueError("No category ID in response")
 
-                if not product_id:
+                if not temp_id:
                     raise ValueError("No product ID in response")
 
                 # Vérifier que la catégorie existe
@@ -120,10 +162,10 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
                 if not category:
                     raise ValueError(f"Category {category_id} not found")
 
-                # Trouver le produit concerné
-                product = self.filtered(lambda p: p.id == product_id)
+                # Trouver le produit concerné directement par son ID
+                product = self.filtered(lambda p: p.id == temp_id)
                 if not product:
-                    raise ValueError(f"Product {product_id} not found in selection")
+                    raise ValueError(f"Product {temp_id} not found in selection")
 
                 # Mettre à jour les valeurs pour ce produit
                 product.write({
@@ -134,7 +176,7 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
 
                 # Créer l'historique
                 self.env['product.category.suggestion.history'].create({
-                    'product_id': product_id,
+                    'product_id': product.id,
                     'suggested_category_id': category_id,
                     'suggestion_confidence': confidence,
                     'input_data': json.dumps(result),
@@ -147,10 +189,43 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
 
         return values
 
+    def _calculate_optimal_batch_size(self, products, max_chars=2048):
+        """Calculate the optimal batch size based on message length limit.
+        
+        Args:
+            products: recordset of products to process
+            max_chars: maximum number of characters allowed (default: 2048)
+            
+        Returns:
+            int: optimal number of products to process in one batch
+        """
+        # Test with a small batch first
+        test_size = 5
+        test_products = products[:test_size]
+        test_message = self._generate_bot_message(test_products, {})
+        
+        # Calculate average characters per product
+        chars_per_product = len(test_message) / test_size
+        
+        # Calculate optimal batch size with 10% safety margin
+        optimal_size = int((max_chars * 0.9) / chars_per_product)
+        
+        # Ensure batch size is at least 1 and no more than 800 (existing limit)
+        return max(1, min(optimal_size, 800))
+
     def action_suggest_category(self):
         """Request category suggestions from AI."""
-        if len(self) > 800:
-            raise UserError(_("For performance reasons, you cannot analyze more than 800 products at once."))
+        # Get company settings
+        company = self.env.company
+        
+        # Dédoublonner les produits
+        unique_products = self.filtered(lambda p: p.id).sorted(lambda p: p.id)
+        
+        # Get max products from company settings
+        max_products = company.openwebui_max_products
+        
+        if len(unique_products) > max_products:
+            raise UserError(_("For performance reasons, you cannot analyze more than %d products at once.") % max_products)
 
         # Get company settings
         company = self.env.company
@@ -161,12 +236,15 @@ class ProductTemplate(models.Model, OpenWebUIBotMixin):
         if not model:
             raise UserError(_("No default OpenWebUI model configured. Please configure it in company settings."))
 
-        # Process products in batches
-        batch_size = company.openwebui_products_per_request
-        successful_products = self.env['product.template']
+        # Calculate optimal batch size
+        batch_size = self._calculate_optimal_batch_size(unique_products)
+        _logger.info(f"Processing products with calculated batch size: {batch_size}")
         
-        for i in range(0, len(self), batch_size):
-            batch = self[i:i + batch_size]
+        successful_products = self.env['product.template']
+        products_to_process = unique_products
+        
+        for i in range(0, len(products_to_process), batch_size):
+            batch = products_to_process[i:i + batch_size]
             
             # Créer une nouvelle transaction pour ce batch
             with self.env.cr.savepoint():

openwebui_integration_product/openwebui_integration

@@ -0,0 +1 @@
+../.repos/bemade-addons/openwebui_integration

openwebui_integration_product/openwebui_integration_chat

@@ -0,0 +1 @@
+../.repos/bemade-addons/openwebui_integration_chat

openwebui_integration_product/views/product_template_view.xml

@@ -53,9 +53,10 @@
         <field name="model">product.template</field>
         <field name="inherit_id" ref="product.product_template_tree_view"/>
         <field name="arch" type="xml">
-            <xpath expr="//list" position="attributes">
-                <attribute name="action">action_suggest_category_multi</attribute>
-            </xpath>
+            <field name="categ_id" position="after">
+                <field name="suggested_category_id" optional="show"/>
+                <field name="suggestion_confidence" widget="percentage" optional="show"/>
+            </field>
         </field>
     </record>