The foundational module for integrating Large Language Models into Odoo. This base module provides the core infrastructure, provider abstraction, and enhanced messaging system that enables all other LLM modules in the ecosystem.

Module Type: 📦 Infrastructure (Core Foundation)

Architecture

graph TD
    subgraph External AI Clients
        CD[Claude Desktop<br>Cursor · Windsurf]
        CC[Claude Code<br>Codex CLI]
    end

    subgraph Odoo AI Chat
        LA[llm_assistant]
        LT[llm_thread]
    end

    CD -->|MCP Protocol| MCP
    CC -->|MCP Protocol| MCP

    LA --> LLM
    LT --> LLM

    MCP[llm_mcp_server<br>MCP Server for Odoo] --> LLM

    LLM[⭐ llm — This Module ⭐<br>Provider Abstraction · Model Management<br>Enhanced mail.message · Security Framework]

    LLM --> TOOL[llm_tool<br>Tool Framework + Generic CRUD Tools]
    LLM --> PROV[AI Providers<br>llm_openai · llm_ollama<br>llm_mistral · ...]
    LLM --> INFRA[Infrastructure<br>llm_store · llm_generate]

    TOOL --> PACKS[Domain-Specific Tool Packs<br>llm_tool_account · 18 accounting tools<br>llm_tool_mis_builder · 44 MIS reporting tools<br>llm_tool_knowledge · RAG search tools<br>llm_tool_ocr_mistral · OCR via Mistral vision]

    style LLM fill:#f9f8fc,stroke:#71639e,stroke-width:3px,color:#71639e
    style MCP fill:#fff,stroke:#71639e,stroke-width:2px,color:#71639e
    style TOOL fill:#fff,stroke:#71639e,stroke-width:2px,color:#71639e
    style PACKS fill:#f9f8fc,stroke:#71639e,stroke-width:2px,color:#71639e
    style PROV fill:#fff,stroke:#dee2e6,stroke-width:2px
    style INFRA fill:#fff,stroke:#dee2e6,stroke-width:2px

Installation

What to Install

This module is auto-installed as a dependency. You typically don't install it directly. Choose a setup below based on your use case.

Common Setups

I want to...	Install
Use Claude/Cursor/Codex with Odoo (MCP)	`llm_mcp_server` (+ tool packs below)
Chat with AI inside Odoo	`llm_assistant` + `llm_openai`
Use local AI (privacy)	`llm_assistant` + `llm_ollama`
Add RAG/knowledge base	Above + `llm_knowledge` + `llm_pgvector`
AI-powered accounting via MCP or chat	`llm_tool_account` (+ `llm_mcp_server` for external AI)
AI-powered financial reporting (MIS Builder)	`llm_tool_mis_builder` (+ `llm_mcp_server`)

MCP Server — Connect External AI Clients

The llm_mcp_server module exposes all your Odoo tools to external AI clients via the Model Context Protocol (MCP). This lets you use Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, and Codex CLI to interact directly with your Odoo data.

odoo-bin -d your_db -i llm_mcp_server

After installing, each user generates their own API key from My Profile → Account Security → New MCP Key. The wizard provides ready-to-paste configurations for each client. See the llm_mcp_server README for full setup instructions.

Domain-Specific Tool Packs

Install tool packs to give AI assistants (both in-Odoo and external MCP clients) specialized capabilities:

Module	Tools	Description
`llm_tool_account`	18	Trial balance, journal entries, reconciliation, payments, tax reports, P&L
`llm_tool_mis_builder`	44	KPI management, report computation, drill-down, variance analysis, trends
`llm_tool_knowledge`	—	RAG search, semantic retrieval, source citations from your knowledge base
`llm_tool_ocr_mistral`	1	Extract text from images and PDFs using Mistral AI vision models
`llm_tool_demo`	6	Example tools showing `@llm_tool` decorator patterns for developers

The base llm_tool module also includes 6 generic CRUD tools out of the box: odoo_record_retriever, odoo_record_creator, odoo_record_updater, odoo_record_unlinker, odoo_model_method_executor, and odoo_model_inspector — enabling AI to read, create, update, and delete records in any Odoo model.

This Module Provides

Provider abstraction framework
Model and publisher management
Enhanced mail.message with llm_role field
Security groups and access control
Base configuration menus

Modules That Depend on This

Category	Modules
MCP Server	`llm_mcp_server`
Interfaces	`llm_assistant`, `llm_thread`
Tool Framework	`llm_tool` → `llm_tool_account`, `llm_tool_mis_builder`, `llm_tool_knowledge`, `llm_tool_ocr_mistral`
Providers	`llm_openai`, `llm_ollama`, `llm_mistral`, `llm_replicate`, `llm_fal_ai`
Infrastructure	`llm_store`, `llm_generate`

Overview

The LLM Integration Base serves as the foundation for building AI-powered features across Odoo applications. It extends Odoo's core messaging system with AI-specific capabilities and provides a unified framework for connecting with various AI providers.

Core Capabilities

Enhanced Messaging System - AI-optimized message handling with 10x performance improvement
Provider Abstraction - Unified interface for multiple AI services (OpenAI, Anthropic, Ollama, etc.)
Model Management - Centralized catalog of AI models with capabilities and metadata
Publisher Tracking - Management of AI model publishers and organizations
Security Framework - Role-based access control and API key management

Key Features

Enhanced Mail Message System

The module extends Odoo's mail.message model with LLM-specific fields:

# Performance-optimized role field (10x faster queries)
llm_role = fields.Selection([
    ('user', 'User'),
    ('assistant', 'Assistant'),
    ('tool', 'Tool'),
    ('system', 'System')
], compute='_compute_llm_role', store=True, index=True)

# Structured data for tool messages
body_json = fields.Json()

AI Message Subtypes

Integrated message subtypes for AI interactions:

llm.mt_user: User messages in AI conversations
llm.mt_assistant: AI-generated responses
llm.mt_tool: Tool execution results and data
llm.mt_system: System prompts and configuration messages

Provider Framework

Unified provider abstraction supporting multiple AI services:

# Dynamic method dispatch to service implementations
provider._dispatch('chat', messages=messages, model=model)
provider._dispatch('embedding', text=text)
provider._dispatch('generate', prompt=prompt, type='image')

Supported Providers:

OpenAI - GPT models, DALL-E, embeddings
Anthropic - Claude models with tool calling
Ollama - Local model deployment
Mistral - Mistral AI models
LiteLLM - Multi-provider proxy
Replicate - Model marketplace
FAL.ai - Fast inference API

Model Management

Comprehensive model catalog with automatic discovery:

Model Registry: Centralized tracking of available AI models
Capability Mapping: Model features (chat, embedding, multimodal, etc.)
Publisher Management: Organization tracking and official status
Auto-Discovery: "Fetch Models" functionality for automatic import
Default Selection: Configurable default models per use case

Performance Improvements

10x Faster Message Queries

The new llm_role field provides dramatic performance improvements:

Before: Complex subtype joins and computed fields
After: Direct indexed field access
Result: 10x faster conversation history queries

Optimized Database Operations

Indexed Role Field: Fast filtering and sorting of AI messages
Reduced Complexity: Elimination of expensive role lookups
Efficient Pagination: Optimized conversation history loading
Scalable Architecture: Performance maintained with large datasets

Getting Started

Installation

Install the module in your Odoo instance
Verify dependencies are satisfied (mail, web)
Install provider modules for your preferred AI services

Basic Configuration

Set up AI Provider:

Navigate to: LLM → Configuration → Providers
Create new provider with API credentials
Click "Fetch Models" to import available models

Configure Models:

Go to: LLM → Configuration → Models
Set default models for chat, embedding, etc.
Configure model parameters and capabilities

Security Setup:

Assign users to LLM User or LLM Manager groups
Configure API key access permissions
Set up tool consent requirements

Technical Specifications

Module Information

Name: LLM Integration Base
Version: 18.0.1.4.0
Category: Technical
License: LGPL-3
Dependencies: mail, web
Author: Apexive Solutions LLC

Key Models

`llm.provider`

Manages connections to AI service providers:

API authentication and configuration
Model discovery and import
Service-specific implementations
Usage tracking and monitoring

`llm.model`

Represents individual AI models:

Model capabilities and parameters
Publisher information and status
Default model configuration
Performance and cost metadata

`llm.publisher`

Tracks AI model publishers:

Organization information
Official status verification
Model portfolio management
Publisher-specific settings

`mail.message` (Extended)

Enhanced with LLM-specific fields:

llm_role: Performance-optimized role tracking
body_json: Structured data for tool messages
Computed role from message subtypes
AI-specific email handling

Multimodal Attachments

The module supports sending file attachments to LLM providers via enhanced mail.message:

Supported File Types

Category	Mimetypes
Images	JPEG, PNG, GIF, WebP
Documents	PDF
Text	Plain text, Markdown, CSV, HTML, CSS, JavaScript, XML, Python, JSON

API Methods

# Get formatted attachments from a message
images = message._get_image_attachments()  # Returns list of base64 images
pdfs = message._get_pdf_attachments()      # Returns list of base64 PDFs
texts = message._get_text_attachments()    # Returns decoded text content

# Prepare all attachments for multimodal LLM call
attachments = message._prepare_multimodal_attachments(is_multimodal=True)
# Returns: {"images": [...], "pdfs": [...], "texts": [...], "has_attachments": bool}

Non-multimodal models automatically skip images/PDFs while still processing text files.

Database Schema

-- Performance optimization: indexed role field
ALTER TABLE mail_message ADD COLUMN llm_role VARCHAR;
CREATE INDEX idx_mail_message_llm_role ON mail_message(llm_role);

-- Structured data storage for tools
ALTER TABLE mail_message ADD COLUMN body_json JSONB;

API Reference

Provider Methods

# Chat completion
response = provider.chat(
    messages=[{"role": "user", "content": "Hello"}],
    model="gpt-4",
    stream=False
)

# Text embedding
embedding = provider.embedding(
    text="Sample text to embed",
    model="text-embedding-ada-002"
)

# Content generation
content = provider.generate(
    prompt="A beautiful landscape",
    type="image",
    model="dall-e-3"
)

Message Posting

# AI-optimized message posting
thread.message_post(
    body="AI response content",
    llm_role="assistant",
    author_id=False
)

# Tool result with structured data
thread.message_post(
    body_json={
        "tool_call_id": "call_123",
        "function": "search_records",
        "result": {"count": 5, "records": [...]}
    },
    llm_role="tool"
)

Integration Patterns

Extending with New Providers

Create Provider Module:

class LLMProvider(models.Model):
    _inherit = "llm.provider"

    @api.model
    def _get_available_services(self):
        return super()._get_available_services() + [
            ('my_service', 'My AI Service')
        ]

Implement Service Methods:

def my_service_chat(self, messages, model=None, **kwargs):
    """Service-specific chat implementation"""
    # Implementation details

def my_service_embedding(self, text, model=None, **kwargs):
    """Service-specific embedding implementation"""
    # Implementation details

Custom Message Handling

class CustomThread(models.Model):
    _inherit = "llm.thread"

    def message_post(self, **kwargs):
        # Custom pre-processing
        if kwargs.get('llm_role') == 'custom':
            # Handle custom role logic
            pass

        return super().message_post(**kwargs)

Build complete AI solutions by combining with specialized modules:

External AI Integration

llm_mcp_server: MCP server exposing all Odoo tools to Claude Desktop, Claude Code, Cursor, Codex CLI, and any MCP-compatible client

Tool Packs

llm_tool: Tool framework with generic CRUD tools (retrieve, create, update, delete, inspect, execute)
llm_tool_account: 18 AI-powered accounting tools — trial balance, journal entries, reconciliation, payments, tax reports, P&L, period close
llm_tool_mis_builder: 44 tools for MIS Builder financial reporting — KPIs, periods, report computation, drill-down, variance analysis
llm_tool_knowledge: RAG tools for semantic search, knowledge retrieval, and source citations
llm_tool_ocr_mistral: OCR tool using Mistral vision models for invoices, receipts, scanned documents

Chat & Assistants

llm_assistant: AI assistants with custom prompts and personalities
llm_thread: Chat interfaces and conversation management

Infrastructure

llm_generate: Unified content generation API
llm_knowledge: RAG and knowledge base functionality
llm_store: Vector storage and similarity search

Support & Resources

Documentation: GitHub Repository
Architecture Guide: OVERVIEW.md
Community Support: GitHub Discussions
Bug Reports: GitHub Issues

License

This module is licensed under LGPL-3.

README.md

LLM Integration Base for Odoo

Architecture

Installation

What to Install

Common Setups

MCP Server — Connect External AI Clients

Domain-Specific Tool Packs

This Module Provides

Modules That Depend on This

Overview

Core Capabilities

Key Features

Enhanced Mail Message System

AI Message Subtypes

Provider Framework

Model Management

Performance Improvements

10x Faster Message Queries

Optimized Database Operations

Getting Started

Installation

Basic Configuration

Technical Specifications

Module Information

Key Models

llm.provider

llm.model

llm.publisher

mail.message (Extended)

Multimodal Attachments

Supported File Types

API Methods

Database Schema

API Reference

Provider Methods

Message Posting

Integration Patterns

Extending with New Providers

Custom Message Handling

Related Modules

External AI Integration

Tool Packs

Chat & Assistants

Infrastructure

Support & Resources

License

`llm.provider`

`llm.model`

`llm.publisher`

`mail.message` (Extended)