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
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gsinghpal
@@ -1,6 +1,6 @@
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{
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'name': 'Fusion Accounting AI',
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'version': '19.0.1.0.0',
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'version': '19.0.1.0.1',
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'category': 'Accounting/Accounting',
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'sequence': 26,
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'summary': 'AI Co-Pilot for Odoo accounting (Claude/GPT) with conversational interface, dashboard, rules.',
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@@ -1,2 +1,3 @@
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from . import claude
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from . import openai_adapter
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from ._base import LLMProvider
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44
fusion_accounting_ai/services/adapters/_base.py
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44
fusion_accounting_ai/services/adapters/_base.py
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@@ -0,0 +1,44 @@
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"""LLMProvider contract - every adapter must conform.
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Phase 1 generalisation: makes local LLM (Ollama, LM Studio, vLLM, llamafile,
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llama.cpp HTTP server) a one-config-line drop-in via the OpenAI-compatible
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HTTP API surface that all of them expose.
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"""
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class LLMProvider:
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"""Contract every LLM backend must satisfy. Adapters declare capabilities
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as class attributes; the engine inspects them before calling optional methods."""
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supports_tool_calling: bool = False
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supports_streaming: bool = False
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max_context_tokens: int = 4096
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supports_embeddings: bool = False
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def __init__(self, env):
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self.env = env
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def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
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"""Plain text completion. Required for ALL providers.
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Returns: {'content': str, 'tokens_used': int, 'model': str}
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"""
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raise NotImplementedError
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def complete_with_tools(self, *, system, messages, tools, max_tokens=2048) -> dict:
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"""Tool-calling completion. Optional - caller checks supports_tool_calling first.
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Returns: {'content': str, 'tool_calls': [{'name': str, 'arguments': dict}], ...}
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"""
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raise NotImplementedError(
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f"{type(self).__name__} does not support tool-calling. "
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f"Check supports_tool_calling before calling.")
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def embed(self, texts: list[str]) -> list[list[float]]:
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"""Embeddings. Optional - caller checks supports_embeddings first.
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Returns: list of float vectors, one per input text.
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"""
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raise NotImplementedError(
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f"{type(self).__name__} does not support embeddings. "
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f"Check supports_embeddings before calling.")
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@@ -4,6 +4,8 @@ import logging
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from odoo import models, api, _
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from odoo.exceptions import UserError
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from ._base import LLMProvider
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_logger = logging.getLogger(__name__)
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try:
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@@ -12,6 +14,64 @@ except ImportError:
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anthropic_sdk = None
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class ClaudeAdapter(LLMProvider):
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"""Plain-Python LLMProvider implementation for Anthropic Claude.
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Preserves all existing functionality (extended thinking, native tool_use
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blocks) used by the Odoo AbstractModel-based adapter -- this class is
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additive for the Phase 1 LLMProvider contract.
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"""
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supports_tool_calling = True
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supports_streaming = True
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max_context_tokens = 200000
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supports_embeddings = False
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def __init__(self, env):
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super().__init__(env)
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if anthropic_sdk is None:
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raise UserError(_("The 'anthropic' Python package is not installed."))
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ICP = env['ir.config_parameter'].sudo()
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try:
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api_key = env['fusion.api.service'].get_api_key(
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provider_type='anthropic',
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consumer='fusion_accounting',
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feature='chat_with_tools',
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)
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except Exception:
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api_key = ICP.get_param('fusion_accounting.anthropic_api_key', '')
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if not api_key:
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api_key = 'not-needed'
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self.client = anthropic_sdk.Anthropic(api_key=api_key)
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self.model = ICP.get_param(
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'fusion_accounting.claude_model', 'claude-sonnet-4-6')
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def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
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api_messages = [
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m for m in messages if m.get('role') in ('user', 'assistant')
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]
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try:
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response = self.client.messages.create(
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model=self.model,
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max_tokens=max_tokens,
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temperature=temperature,
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system=system,
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messages=api_messages,
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)
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except Exception as e:
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_logger.error("Claude complete error: %s", e)
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raise UserError(_("Claude API error: %s", str(e)))
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text_parts = [b.text for b in response.content if getattr(b, 'type', None) == 'text']
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return {
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'content': '\n'.join(text_parts),
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'tokens_used': (
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getattr(response.usage, 'input_tokens', 0)
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+ getattr(response.usage, 'output_tokens', 0)
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),
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'model': self.model,
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}
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class FusionAccountingAdapterClaude(models.AbstractModel):
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_name = 'fusion.accounting.adapter.claude'
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_description = 'Claude AI Adapter'
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@@ -4,6 +4,8 @@ import logging
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from odoo import models, api, _
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from odoo.exceptions import UserError
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from ._base import LLMProvider
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_logger = logging.getLogger(__name__)
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try:
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@@ -12,6 +14,71 @@ except ImportError:
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OpenAI = None
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DEFAULT_OPENAI_BASE_URL = 'https://api.openai.com/v1'
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class OpenAIAdapter(LLMProvider):
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"""Plain-Python LLMProvider implementation backed by an OpenAI-compatible
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HTTP endpoint.
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The OpenAI Python SDK speaks to any server that exposes the OpenAI
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Chat Completions surface: OpenAI itself, Ollama, LM Studio, vLLM,
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llamafile, llama.cpp HTTP server, etc. Configure the endpoint via
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the ``fusion_accounting.openai_base_url`` ir.config_parameter.
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"""
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supports_tool_calling = True
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supports_streaming = True
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max_context_tokens = 128000
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supports_embeddings = True
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def __init__(self, env):
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super().__init__(env)
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if OpenAI is None:
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raise UserError(_("The 'openai' Python package is not installed."))
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ICP = env['ir.config_parameter'].sudo()
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base_url = ICP.get_param(
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'fusion_accounting.openai_base_url', DEFAULT_OPENAI_BASE_URL,
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) or DEFAULT_OPENAI_BASE_URL
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try:
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api_key = env['fusion.api.service'].get_api_key(
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provider_type='openai',
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consumer='fusion_accounting',
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feature='chat_with_tools',
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)
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except Exception:
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api_key = ICP.get_param('fusion_accounting.openai_api_key', '')
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if not api_key:
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# Local LLM servers (Ollama, LM Studio, llama.cpp) usually do not
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# require a real key but the SDK insists on a non-empty string.
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api_key = 'not-needed'
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self.base_url = base_url
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self.client = OpenAI(api_key=api_key, base_url=base_url)
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self.model = ICP.get_param('fusion_accounting.openai_model', 'gpt-5.4-mini')
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def complete(self, *, system, messages, max_tokens=2048, temperature=0.0) -> dict:
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api_messages = [{'role': 'system', 'content': system}]
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for msg in messages:
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if msg.get('role') in ('user', 'assistant', 'tool'):
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api_messages.append(msg)
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try:
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response = self.client.chat.completions.create(
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model=self.model,
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messages=api_messages,
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max_tokens=max_tokens,
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temperature=temperature,
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)
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except Exception as e:
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_logger.error("OpenAI complete error: %s", e)
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raise UserError(_("OpenAI API error: %s", str(e)))
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choice = response.choices[0]
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return {
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'content': choice.message.content or '',
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'tokens_used': getattr(response.usage, 'total_tokens', 0),
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'model': self.model,
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}
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class FusionAccountingAdapterOpenAI(models.AbstractModel):
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_name = 'fusion.accounting.adapter.openai'
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_description = 'OpenAI AI Adapter'
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@@ -1,2 +1,3 @@
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from . import test_post_migration
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from . import test_data_adapters
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from . import test_llm_provider_contract
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45
fusion_accounting_ai/tests/test_llm_provider_contract.py
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45
fusion_accounting_ai/tests/test_llm_provider_contract.py
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@@ -0,0 +1,45 @@
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from odoo.tests.common import TransactionCase, tagged
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from odoo.addons.fusion_accounting_ai.services.adapters._base import LLMProvider
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@tagged('post_install', '-at_install')
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class TestLLMProviderContract(TransactionCase):
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"""Every LLM adapter must satisfy the LLMProvider contract."""
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def test_base_class_defines_capability_attrs(self):
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self.assertTrue(hasattr(LLMProvider, 'supports_tool_calling'))
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self.assertTrue(hasattr(LLMProvider, 'supports_streaming'))
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self.assertTrue(hasattr(LLMProvider, 'max_context_tokens'))
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self.assertTrue(hasattr(LLMProvider, 'supports_embeddings'))
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def test_openai_adapter_implements_contract(self):
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from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
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self.assertTrue(issubclass(OpenAIAdapter, LLMProvider))
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adapter = OpenAIAdapter(self.env)
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self.assertIsInstance(adapter.supports_tool_calling, bool)
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self.assertIsInstance(adapter.max_context_tokens, int)
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def test_claude_adapter_implements_contract(self):
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from odoo.addons.fusion_accounting_ai.services.adapters.claude import ClaudeAdapter
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self.assertTrue(issubclass(ClaudeAdapter, LLMProvider))
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adapter = ClaudeAdapter(self.env)
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self.assertIsInstance(adapter.supports_tool_calling, bool)
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self.assertIsInstance(adapter.max_context_tokens, int)
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def test_openai_adapter_uses_configurable_base_url(self):
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self.env['ir.config_parameter'].sudo().set_param(
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'fusion_accounting.openai_base_url', 'http://localhost:1234/v1')
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self.env['ir.config_parameter'].sudo().set_param(
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'fusion_accounting.openai_api_key', 'lm-studio-test-key')
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from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
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adapter = OpenAIAdapter(self.env)
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self.assertEqual(str(adapter.client.base_url).rstrip('/'),
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'http://localhost:1234/v1')
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def test_openai_adapter_default_base_url_when_unset(self):
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self.env['ir.config_parameter'].sudo().search([
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('key', '=', 'fusion_accounting.openai_base_url')
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]).unlink()
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from odoo.addons.fusion_accounting_ai.services.adapters.openai_adapter import OpenAIAdapter
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adapter = OpenAIAdapter(self.env)
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self.assertIn('api.openai.com', str(adapter.client.base_url))
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