changes

fusion_accounting/fusion_accounting_ai/services/adapters/openai_adapter.py

@@ -0,0 +1,204 @@
+import json
+import logging
+
+from odoo import models, api, _
+from odoo.exceptions import UserError
+
+from ._base import LLMProvider
+
+_logger = logging.getLogger(__name__)
+
+try:
+    from openai import OpenAI
+except ImportError:
+    OpenAI = None
+
+
+DEFAULT_OPENAI_BASE_URL = 'https://api.openai.com/v1'
+
+
+class OpenAIAdapter(LLMProvider):
+    """Plain-Python LLMProvider implementation backed by an OpenAI-compatible
+    HTTP endpoint.
+
+    The OpenAI Python SDK speaks to any server that exposes the OpenAI
+    Chat Completions surface: OpenAI itself, Ollama, LM Studio, vLLM,
+    llamafile, llama.cpp HTTP server, etc. Configure the endpoint via
+    the ``fusion_accounting.openai_base_url`` ir.config_parameter.
+    """
+
+    supports_tool_calling = True
+    supports_streaming = True
+    max_context_tokens = 128000
+    supports_embeddings = True
+
+    def __init__(self, env):
+        super().__init__(env)
+        if OpenAI is None:
+            raise UserError(_("The 'openai' Python package is not installed."))
+        ICP = env['ir.config_parameter'].sudo()
+        base_url = ICP.get_param(
+            'fusion_accounting.openai_base_url', DEFAULT_OPENAI_BASE_URL,
+        ) or DEFAULT_OPENAI_BASE_URL
+        try:
+            api_key = env['fusion.api.service'].get_api_key(
+                provider_type='openai',
+                consumer='fusion_accounting',
+                feature='chat_with_tools',
+            )
+        except Exception:
+            api_key = ICP.get_param('fusion_accounting.openai_api_key', '')
+        if not api_key:
+            # Local LLM servers (Ollama, LM Studio, llama.cpp) usually do not
+            # require a real key but the SDK insists on a non-empty string.
+            api_key = 'not-needed'
+        self.base_url = base_url
+        self.client = OpenAI(api_key=api_key, base_url=base_url)
+        self.model = ICP.get_param('fusion_accounting.openai_model', 'gpt-5.4-mini')
+
+    def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
+        api_messages = [{'role': 'system', 'content': system}]
+        for msg in messages:
+            if msg.get('role') in ('user', 'assistant', 'tool'):
+                api_messages.append(msg)
+        try:
+            response = self.client.chat.completions.create(
+                model=self.model,
+                messages=api_messages,
+                max_tokens=max_tokens,
+                temperature=temperature,
+            )
+        except Exception as e:
+            _logger.error("OpenAI complete error: %s", e)
+            raise UserError(_("OpenAI API error: %s", str(e)))
+        choice = response.choices[0]
+        return {
+            'content': choice.message.content or '',
+            'tokens_used': getattr(response.usage, 'total_tokens', 0),
+            'model': self.model,
+        }
+
+
+class FusionAccountingAdapterOpenAI(models.AbstractModel):
+    _name = 'fusion.accounting.adapter.openai'
+    _description = 'OpenAI AI Adapter'
+
+    def _get_client(self):
+        if OpenAI is None:
+            raise UserError(_("The 'openai' Python package is not installed."))
+        try:
+            key = self.env['fusion.api.service'].get_api_key(
+                provider_type='openai',
+                consumer='fusion_accounting',
+                feature='chat_with_tools',
+            )
+        except Exception:
+            ICP = self.env['ir.config_parameter'].sudo()
+            key = ICP.get_param('fusion_accounting.openai_api_key', '')
+            if not key:
+                raise UserError(_("No OpenAI API key configured."))
+        return OpenAI(api_key=key)
+
+    def _get_model_name(self):
+        ICP = self.env['ir.config_parameter'].sudo()
+        return ICP.get_param('fusion_accounting.openai_model', 'gpt-5.4-mini')
+
+    def _format_tools(self, tools):
+        formatted = []
+        for tool in tools:
+            formatted.append({
+                'type': 'function',
+                'function': {
+                    'name': tool['name'],
+                    'description': tool['description'],
+                    'parameters': tool.get('parameters', {'type': 'object', 'properties': {}}),
+                },
+            })
+        return formatted
+
+    def _is_reasoning_model(self, model):
+        return model.startswith('o1') or model.startswith('o3') or model.startswith('o4')
+
+    def call_with_tools(self, system_prompt, messages, tools=None, model_override=None):
+        client = self._get_client()
+        model = model_override or self._get_model_name()
+        is_reasoning = self._is_reasoning_model(model)
+
+        if is_reasoning:
+            api_messages = [{'role': 'developer', 'content': system_prompt}]
+        else:
+            api_messages = [{'role': 'system', 'content': system_prompt}]
+        for msg in messages:
+            if msg['role'] in ('user', 'assistant', 'tool'):
+                api_messages.append(msg)
+
+        kwargs = {
+            'model': model,
+            'messages': api_messages,
+        }
+        if is_reasoning:
+            kwargs['max_completion_tokens'] = 16384
+            kwargs['reasoning_effort'] = 'medium'
+        else:
+            kwargs['max_tokens'] = 4096
+
+        if tools:
+            kwargs['tools'] = self._format_tools(tools)
+
+        try:
+            response = client.chat.completions.create(**kwargs)
+        except Exception as e:
+            _logger.error("OpenAI API error: %s", e)
+            raise UserError(_("OpenAI API error: %s", str(e)))
+
+        choice = response.choices[0]
+        message = choice.message
+
+        tool_calls = []
+        if message.tool_calls:
+            for tc in message.tool_calls:
+                try:
+                    args = json.loads(tc.function.arguments)
+                except (json.JSONDecodeError, TypeError):
+                    _logger.warning("Malformed tool args from OpenAI: %s", tc.function.arguments)
+                    args = {}
+                tool_calls.append({
+                    'id': tc.id,
+                    'name': tc.function.name,
+                    'arguments': args,
+                })
+
+        return {
+            'text': message.content or '',
+            'tool_calls': tool_calls if tool_calls else None,
+            'tokens_in': response.usage.prompt_tokens,
+            'tokens_out': response.usage.completion_tokens,
+            'stop_reason': choice.finish_reason,
+            'raw_message': message,
+        }
+
+    def append_tool_results(self, messages, ai_response, tool_results):
+        raw_msg = ai_response.get('raw_message')
+        assistant_msg = {'role': 'assistant', 'content': raw_msg.content or ''}
+        if raw_msg.tool_calls:
+            assistant_msg['tool_calls'] = [
+                {
+                    'id': tc.id,
+                    'type': 'function',
+                    'function': {
+                        'name': tc.function.name,
+                        'arguments': tc.function.arguments,
+                    },
+                }
+                for tc in raw_msg.tool_calls
+            ]
+        messages.append(assistant_msg)
+
+        for tr in tool_results:
+            messages.append({
+                'role': 'tool',
+                'tool_call_id': tr['tool_call_id'],
+                'content': tr['result'],
+            })
+
+        return messages