Reference Section

LLM Models

List of supported LLM providers and models in Stubber

# OpenAI

OpenAI models are used with their standard API format with the following modifications:

# O-Type Models

• o3-mini and o4-mini: We delete the temperature field as these models don't support it
• All O-type models: We convert image URLs into data URIs (some O-type models do not support images at all, e.g., o3-mini)

# OpenAI Models

# Anthropic (Claude)

Anthropic models require specific message format conversions:

# Message Processing

• Consecutive roles: Anthropic does not support consecutive roles, so we combine consecutive role messages into a single message with the messages.content into an array of the messages
• System messages: The system messages are extracted and concatenated to be a single top-level system message parameter as Anthropic does not support system messages in the conversation flow
• Conversation start: Anthropic calls have to start with a user message. If it doesn't start with one, we inject a simple one that just says "hi"

# Image Understanding

For Anthropic, Stubber accepts the normal OpenAI specification of image understanding messages:

Before these messages are sent to Anthropic, we convert them to their structure, which can be seen here.

# Claude Models

# Google Gemini

Gemini models have specific requirements and limitations:

# Message Processing

• System message limitation: Gemini models cannot be used with only a system message - they require at least one user message
• Image processing: We convert image URLs into data URIs for compatibility

# Gemini Models

# Other Providers

# Additional Models

# General Operations Applied to All Providers

# Function Method Determination

We determine which function method to use based on the model and the provider:

• Models released after May 2025: Default to supplying functions to providers as tools
• Models released before May 2025: Default to supplying functions to providers as functions

This is mostly abstracted for users and they do not need to worry about it, but you can specify a specific function method for a model as a parameter (see function_method).

If a specific chat already had a function call following a specific function method, then future iterations of that chat will also use that same function method. For example, if you use a new model (which uses tools) and then switch to an older function type model in the same chat, the older function type model would also use tools.

# Tool Result Injection

For tools, tool messages from LLMs must be followed by a tool result. If there is a scenario where users disable dynamic tasks (which we use to inject tool results after function calls), then Stubber will inject a simple tool result of:

# All Supported Models

The following table shows all supported models and their capabilities: