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/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'