test(fusion_accounting_assets): local LLM useful-life smoke (skips without LLM)

Auto-detects LM Studio (:1234) or Ollama (:11434) on
host.docker.internal / localhost; skips silently when no server is
reachable so CI stays green. When a server is present it exercises the
full predict_useful_life path through the OpenAI-compatible adapter,
catching prompt / JSON-parsing regressions that mocked LLMs hide.

Tagged 'local_llm' so it can be selected explicitly when an LLM is
known-available.

Made-with: Cursor

fusion_accounting_assets/__manifest__.py

@@ -1,6 +1,6 @@
 {
     'name': 'Fusion Accounting Assets',
-    'version': '19.0.1.0.35',
+    'version': '19.0.1.0.36',
     'category': 'Accounting/Accounting',
     'summary': 'AI-augmented asset management with depreciation schedules.',
     'description': """

fusion_accounting_assets/tests/__init__.py

@@ -28,3 +28,4 @@ from . import test_audit_report
 from . import test_coexistence
 from . import test_assets_tours
 from . import test_perf_controller
+from . import test_local_llm_compat

fusion_accounting_assets/tests/test_local_llm_compat.py

@@ -0,0 +1,83 @@
+"""Local LLM compat smoke test for the useful_life_predictor service.
+
+Auto-detects an LM Studio (port 1234) or Ollama (port 11434) server on
+host.docker.internal or localhost. Skips silently when no local LLM is
+reachable, so CI runs stay green.
+
+When a server is present, this exercises the real OpenAI-compatible
+adapter end-to-end against a local model — i.e. it catches prompt /
+JSON-parsing regressions that only show up with a non-mocked LLM.
+"""
+
+import socket
+
+from odoo.tests.common import TransactionCase
+from odoo.tests import tagged
+
+
+def _server_reachable(host, port, timeout=1.0):
+    try:
+        with socket.create_connection((host, port), timeout=timeout):
+            return True
+    except (OSError, socket.timeout):
+        return False
+
+
+def _detect_local_llm():
+    candidates = [
+        ('host.docker.internal', 1234, 'local-model'),
+        ('host.docker.internal', 11434, 'llama3.1:8b'),
+        ('localhost', 1234, 'local-model'),
+        ('localhost', 11434, 'llama3.1:8b'),
+    ]
+    for host, port, default_model in candidates:
+        if _server_reachable(host, port, timeout=0.5):
+            return (f'http://{host}:{port}/v1', default_model)
+    return (None, None)
+
+
+@tagged('post_install', '-at_install', 'local_llm')
+class TestLocalLLMUsefulLife(TransactionCase):
+
+    def setUp(self):
+        super().setUp()
+        self.base_url, self.model = _detect_local_llm()
+        if not self.base_url:
+            self.skipTest("No local LLM server detected (LM Studio :1234 / Ollama :11434)")
+
+    def test_useful_life_with_local_llm(self):
+        params = self.env['ir.config_parameter'].sudo()
+        keys = [
+            'fusion_accounting.openai_base_url',
+            'fusion_accounting.openai_model',
+            'fusion_accounting.openai_api_key',
+            'fusion_accounting.provider.asset_useful_life',
+        ]
+        prior = {k: params.get_param(k) for k in keys}
+
+        params.set_param('fusion_accounting.openai_base_url', self.base_url)
+        params.set_param('fusion_accounting.openai_model', self.model)
+        params.set_param('fusion_accounting.openai_api_key', 'lm-studio')
+        params.set_param('fusion_accounting.provider.asset_useful_life', 'openai')
+
+        try:
+            from odoo.addons.fusion_accounting_assets.services.useful_life_predictor import (
+                predict_useful_life,
+            )
+            result = predict_useful_life(
+                self.env,
+                description='Dell laptop',
+                amount=2500,
+                partner_name='Dell Canada',
+            )
+            self.assertIn('useful_life_years', result)
+            self.assertIn('depreciation_method', result)
+            self.assertIsInstance(result['useful_life_years'], (int, float))
+            self.assertIn(
+                result['depreciation_method'],
+                ('straight_line', 'declining_balance', 'units_of_production'),
+            )
+        finally:
+            for k, v in prior.items():
+                if v is not None:
+                    params.set_param(k, v)