feat(fusion_accounting_ai): add LLMProvider contract + configurable openai base_url

Phase 1 prerequisite for local LLM support. Adapters now declare
capability flags (supports_tool_calling, max_context_tokens, etc.) so
the engine can reason about what backend is available.

OpenAI adapter accepts fusion_accounting.openai_base_url config -- point
it at LM Studio (http://host.docker.internal:1234/v1) or Ollama
(http://host.docker.internal:11434/v1) and the existing OpenAI adapter
works unchanged.

Implementation note: existing Odoo AbstractModel adapters
(fusion.accounting.adapter.openai/claude) are preserved untouched to
avoid breaking the chat panel; the new plain-Python OpenAIAdapter and
ClaudeAdapter classes (LLMProvider subclasses) are added alongside them.

Made-with: Cursor

fusion_accounting_ai/services/adapters/openai_adapter.py

@@ -4,6 +4,8 @@ import logging
 from odoo import models, api, _
 from odoo.exceptions import UserError
 
+from ._base import LLMProvider
+
 _logger = logging.getLogger(__name__)
 
 try:
@@ -12,6 +14,71 @@ 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'