What to Install

This module is typically auto-installed as a dependency of llm_thread or llm_assistant.

For content generation features:

odoo-bin -d your_db -i llm_assistant,llm_openai

Auto-Installed Dependencies

These are pulled in automatically:

• llm (core infrastructure)
• llm_assistant (assistant framework)
• mail (Odoo messaging)

Optional Enhancements

Common Setups

Core Capabilities

• Unified Generation API - Single interface for text, image, audio, and other content types
• Dynamic Form Generation - Automatic UI generation based on model schemas
• Streaming Generation - Real-time content creation with live updates
• Race Condition Fixes - Comprehensive async handling and loading state management
• Schema Handling - Intelligent schema resolution and form field generation

Unified Generation Interface

# Text generation
response = thread.generate_response(
    user_input="Write a product description",
    generation_type="text"
)

# Image generation
image = thread.generate_response(
    user_input="A beautiful landscape",
    generation_type="image",
    model_id=dalle_model.id
)

Dynamic Form Generation

The system automatically generates forms based on AI model input schemas:

def get_input_schema(self):
    """Generate form schema with intelligent priority resolution"""
    # Priority: Assistant prompt > Thread prompt > Model default
    if self.assistant_id and self.assistant_id.prompt_id:
        return self.assistant_id.prompt_id.input_schema_json
    elif self.prompt_id:
        return self.prompt_id.input_schema_json
    else:
        return self.model_id.get_default_schema()

Streaming Generation

def generate_response_stream(self, user_input, **kwargs):
    """Generate content with real-time streaming updates"""
    message = self.message_post(body="", llm_role="assistant")

    stream = self.provider_id.generate_stream(
        prompt=user_input,
        model=self.model_id.name
    )

    for chunk in stream:
        message.body += chunk.content
        self._notify_message_update(message)

    return message

Text Generation

text_response = env['llm.thread'].generate_content(
    prompt="Write a professional email",
    content_type="text",
    parameters={'temperature': 0.7, 'max_tokens': 500}
)

Image Generation

image_result = env['llm.thread'].generate_content(
    prompt="A modern office building at sunset",
    content_type="image",
    parameters={'size': '1024x1024', 'style': 'photorealistic'}
)

Core Generation Methods

# Basic generation
def generate_response(self, user_input, generation_type="text", **kwargs):
    """Main generation method with unified interface"""

# Streaming generation
def generate_response_stream(self, user_input, **kwargs):
    """Generate with real-time streaming updates"""

# Template-based generation
def generate_from_template(self, template_id, context, **kwargs):
    """Generate using prompt template with context"""

# Batch generation
def generate_batch(self, prompts, content_type, **kwargs):
    """Generate multiple items in batch"""

Module Information

• Name: LLM Generate
• Version: 18.0.2.0.0
• Category: Productivity
• License: LGPL-3
• Dependencies: llm, llm_assistant, mail
• Author: Apexive Solutions LLC

Key Models

• ``llm.generation.job``: Background generation job management
• ``llm.generation.queue``: Provider-specific queue configuration
• Extensions to ``llm.thread``: Core generation methods

Frontend Components

• LLMMediaForm: Dynamic form generation component
• LLMGenerationWizard: Generation parameter configuration
• LLMStreamingDisplay: Real-time content updates
• LLMSchemaIndicator: Schema source transparency