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/__manifest__.py

@@ -1,6 +1,6 @@
 {
     'name': 'Fusion Accounting AI',
-    'version': '19.0.1.0.0',
+    'version': '19.0.1.0.1',
     'category': 'Accounting/Accounting',
     'sequence': 26,
     'summary': 'AI Co-Pilot for Odoo accounting (Claude/GPT) with conversational interface, dashboard, rules.',

fusion_accounting_ai/services/adapters/__init__.py

@@ -1,2 +1,3 @@
 from . import claude
 from . import openai_adapter
+from ._base import LLMProvider

fusion_accounting_ai/services/adapters/_base.py

@@ -0,0 +1,44 @@
+"""LLMProvider contract - every adapter must conform.
+
+Phase 1 generalisation: makes local LLM (Ollama, LM Studio, vLLM, llamafile,
+llama.cpp HTTP server) a one-config-line drop-in via the OpenAI-compatible
+HTTP API surface that all of them expose.
+"""
+
+
+class LLMProvider:
+    """Contract every LLM backend must satisfy. Adapters declare capabilities
+    as class attributes; the engine inspects them before calling optional methods."""
+
+    supports_tool_calling: bool = False
+    supports_streaming: bool = False
+    max_context_tokens: int = 4096
+    supports_embeddings: bool = False
+
+    def __init__(self, env):
+        self.env = env
+
+    def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
+        """Plain text completion. Required for ALL providers.
+
+        Returns: {'content': str, 'tokens_used': int, 'model': str}
+        """
+        raise NotImplementedError
+
+    def complete_with_tools(self, *, system, messages, tools, max_tokens=2048) -> dict:
+        """Tool-calling completion. Optional - caller checks supports_tool_calling first.
+
+        Returns: {'content': str, 'tool_calls': [{'name': str, 'arguments': dict}], ...}
+        """
+        raise NotImplementedError(
+            f"{type(self).__name__} does not support tool-calling. "
+            f"Check supports_tool_calling before calling.")
+
+    def embed(self, texts: list[str]) -> list[list[float]]:
+        """Embeddings. Optional - caller checks supports_embeddings first.
+
+        Returns: list of float vectors, one per input text.
+        """
+        raise NotImplementedError(
+            f"{type(self).__name__} does not support embeddings. "
+            f"Check supports_embeddings before calling.")

fusion_accounting_ai/services/adapters/claude.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 +14,64 @@ except ImportError:
     anthropic_sdk = None
 
 
+class ClaudeAdapter(LLMProvider):
+    """Plain-Python LLMProvider implementation for Anthropic Claude.
+
+    Preserves all existing functionality (extended thinking, native tool_use
+    blocks) used by the Odoo AbstractModel-based adapter -- this class is
+    additive for the Phase 1 LLMProvider contract.
+    """
+
+    supports_tool_calling = True
+    supports_streaming = True
+    max_context_tokens = 200000
+    supports_embeddings = False
+
+    def __init__(self, env):
+        super().__init__(env)
+        if anthropic_sdk is None:
+            raise UserError(_("The 'anthropic' Python package is not installed."))
+        ICP = env['ir.config_parameter'].sudo()
+        try:
+            api_key = env['fusion.api.service'].get_api_key(
+                provider_type='anthropic',
+                consumer='fusion_accounting',
+                feature='chat_with_tools',
+            )
+        except Exception:
+            api_key = ICP.get_param('fusion_accounting.anthropic_api_key', '')
+        if not api_key:
+            api_key = 'not-needed'
+        self.client = anthropic_sdk.Anthropic(api_key=api_key)
+        self.model = ICP.get_param(
+            'fusion_accounting.claude_model', 'claude-sonnet-4-6')
+
+    def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
+        api_messages = [
+            m for m in messages if m.get('role') in ('user', 'assistant')
+        ]
+        try:
+            response = self.client.messages.create(
+                model=self.model,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                system=system,
+                messages=api_messages,
+            )
+        except Exception as e:
+            _logger.error("Claude complete error: %s", e)
+            raise UserError(_("Claude API error: %s", str(e)))
+        text_parts = [b.text for b in response.content if getattr(b, 'type', None) == 'text']
+        return {
+            'content': '\n'.join(text_parts),
+            'tokens_used': (
+                getattr(response.usage, 'input_tokens', 0)
+                + getattr(response.usage, 'output_tokens', 0)
+            ),
+            'model': self.model,
+        }
+
+
 class FusionAccountingAdapterClaude(models.AbstractModel):
     _name = 'fusion.accounting.adapter.claude'
     _description = 'Claude AI Adapter'

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'

fusion_accounting_ai/tests/__init__.py

@@ -1,2 +1,3 @@
 from . import test_post_migration
 from . import test_data_adapters
+from . import test_llm_provider_contract

fusion_accounting_ai/tests/test_llm_provider_contract.py

@@ -0,0 +1,45 @@
+from odoo.tests.common import TransactionCase, tagged
+from odoo.addons.fusion_accounting_ai.services.adapters._base import LLMProvider
+
+
+@tagged('post_install', '-at_install')
+class TestLLMProviderContract(TransactionCase):
+    """Every LLM adapter must satisfy the LLMProvider contract."""
+
+    def test_base_class_defines_capability_attrs(self):
+        self.assertTrue(hasattr(LLMProvider, 'supports_tool_calling'))
+        self.assertTrue(hasattr(LLMProvider, 'supports_streaming'))
+        self.assertTrue(hasattr(LLMProvider, 'max_context_tokens'))
+        self.assertTrue(hasattr(LLMProvider, 'supports_embeddings'))
+
+    def test_openai_adapter_implements_contract(self):
+        from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
+        self.assertTrue(issubclass(OpenAIAdapter, LLMProvider))
+        adapter = OpenAIAdapter(self.env)
+        self.assertIsInstance(adapter.supports_tool_calling, bool)
+        self.assertIsInstance(adapter.max_context_tokens, int)
+
+    def test_claude_adapter_implements_contract(self):
+        from odoo.addons.fusion_accounting_ai.services.adapters.claude import ClaudeAdapter
+        self.assertTrue(issubclass(ClaudeAdapter, LLMProvider))
+        adapter = ClaudeAdapter(self.env)
+        self.assertIsInstance(adapter.supports_tool_calling, bool)
+        self.assertIsInstance(adapter.max_context_tokens, int)
+
+    def test_openai_adapter_uses_configurable_base_url(self):
+        self.env['ir.config_parameter'].sudo().set_param(
+            'fusion_accounting.openai_base_url', 'http://localhost:1234/v1')
+        self.env['ir.config_parameter'].sudo().set_param(
+            'fusion_accounting.openai_api_key', 'lm-studio-test-key')
+        from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
+        adapter = OpenAIAdapter(self.env)
+        self.assertEqual(str(adapter.client.base_url).rstrip('/'),
+                         'http://localhost:1234/v1')
+
+    def test_openai_adapter_default_base_url_when_unset(self):
+        self.env['ir.config_parameter'].sudo().search([
+            ('key', '=', 'fusion_accounting.openai_base_url')
+        ]).unlink()
+        from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
+        adapter = OpenAIAdapter(self.env)
+        self.assertIn('api.openai.com', str(adapter.client.base_url))