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FunctionGemmaModel

class FunctionGemmaModel(BaseModelBackend):
FunctionGemma model backend for Ollama with custom tool calling format. FunctionGemma is a specialized Gemma model fine-tuned for function calling. It uses a custom chat template format that differs from OpenAI’s format. This backend handles conversion between CAMEL’s OpenAI-style tool schemas and FunctionGemma’s native format. Parameters:
  • model_type (Union[ModelType, str]): Model for which a backend is created (e.g., “functiongemma”).
  • model_config_dict (Optional[Dict[str, Any]], optional): A dictionary of configuration options. If :obj:None, :obj:FunctionGemmaConfig().as_dict() will be used. (default: :obj:None)
  • api_key (Optional[str], optional): Not required for local Ollama. (default: :obj:None)
  • url (Optional[str], optional): The URL to the Ollama server. (default: :obj:http://localhost:11434)
  • token_counter (Optional[BaseTokenCounter], optional): Token counter to use for the model. If not provided, :obj:OpenAITokenCounter( ModelType.GPT_4O_MINI) will be used. (default: :obj:None)
  • timeout (Optional[float], optional): The timeout value in seconds for API calls. If not provided, will fall back to the MODEL_TIMEOUT environment variable or default to 180 seconds. (default: :obj:None)
  • max_retries (int, optional): Maximum number of retries for API calls. (default: :obj:3)

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init

def __init__(
    self,
    model_type: Union[ModelType, str],
    model_config_dict: Optional[Dict[str, Any]] = None,
    api_key: Optional[str] = None,
    url: Optional[str] = None,
    token_counter: Optional[BaseTokenCounter] = None,
    timeout: Optional[float] = None,
    max_retries: int = 3
):

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token_counter

def token_counter(self):
Returns: BaseTokenCounter: The token counter following the model’s tokenization style.

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_escape_string

def _escape_string(self, s: str):
Wrap string values in <escape> tags for FunctionGemma format. Parameters:
  • s (str): The string to escape.
Returns: str: The escaped string.

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_unescape_string

def _unescape_string(self, s: str):
Remove <escape> tags from string values. Parameters:
  • s (str): The string to unescape.
Returns: str: The unescaped string.

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_type_to_function_gemma

def _type_to_function_gemma(self, json_type: Union[str, List[str]]):
Convert JSON schema type to FunctionGemma type (uppercase). Parameters:
  • json_type (Union[str, List[str]]): The JSON schema type. Can be a string like “string” or a list like [“string”, “null”] for optional parameters.
Returns: str: The FunctionGemma type.

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_format_parameter_properties

def _format_parameter_properties(self, properties: Dict[str, Any], required: List[str]):
Format parameter properties for FunctionGemma declaration. Parameters:
  • properties (Dict[str, Any]): The properties dictionary.
  • required (List[str]): List of required parameter names.
Returns: str: Formatted properties string.

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_convert_tool_to_function_gemma

def _convert_tool_to_function_gemma(self, tool: Dict[str, Any]):
Convert OpenAI tool schema to FunctionGemma declaration format. Parameters:
  • tool (Dict[str, Any]): The OpenAI tool schema.
Returns: str: The FunctionGemma declaration string.

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_format_developer_turn

def _format_developer_turn(self, content: str, tools: Optional[List[Dict[str, Any]]] = None):
Format the developer/system turn with function declarations. Parameters:
  • content (str): The system message content.
  • tools (Optional[List[Dict[str, Any]]]): List of tool schemas.
Returns: str: Formatted developer turn.

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_format_user_turn

def _format_user_turn(self, content: str):
Format a user message turn. Parameters:
  • content (str): The user message content.
Returns: str: Formatted user turn.

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_format_model_turn

def _format_model_turn(self, message: OpenAIMessage):
Format an assistant/model message turn. Parameters:
  • message (OpenAIMessage): The assistant message.
Returns: str: Formatted model turn.

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_format_tool_response

def _format_tool_response(self, message: OpenAIMessage):
Format a tool response message. Parameters:
  • message (OpenAIMessage): The tool response message.
Returns: str: Formatted tool response.

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_format_messages

def _format_messages(
    self,
    messages: List[OpenAIMessage],
    tools: Optional[List[Dict[str, Any]]] = None
):
Format all messages into a FunctionGemma prompt string. Parameters:
  • messages (List[OpenAIMessage]): List of messages in OpenAI format.
  • tools (Optional[List[Dict[str, Any]]]): List of tool schemas.
Returns: str: Complete formatted prompt.

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_extract_function_calls

def _extract_function_calls(self, text: str, tools: Optional[List[Dict[str, Any]]] = None):
Extract function calls from model output. Parameters:
  • text (str): The model output text.
  • tools (Optional[List[Dict[str, Any]]]): Available tools to infer function names when the model outputs malformed calls.
Returns: Tuple[str, List[Dict[str, Any]]]: Tuple of (remaining_content, list_of_tool_calls).

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_infer_function_name

def _infer_function_name(self, args_str: str, tools: Optional[List[Dict[str, Any]]]):
Infer the function name from available tools. Parameters:
  • args_str (str): The arguments string from the model output.
  • tools (Optional[List[Dict[str, Any]]]): Available tools.
Returns: Optional[str]: The inferred function name, or None if not found.

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_parse_function_args

def _parse_function_args(self, args_str: str):
Parse function arguments from FunctionGemma format. Parameters:
  • args_str (str): The arguments string (e.g., “a:15,b:27”).
Returns: Dict[str, Any]: Parsed arguments dictionary.

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_parse_value

def _parse_value(self, value: str):
Parse a value string to appropriate Python type. Parameters:
  • value (str): The value string.
Returns: Any: Parsed value (int, float, bool, or str).

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_to_chat_completion

def _to_chat_completion(
    self,
    response_text: str,
    model: str,
    tools: Optional[List[Dict[str, Any]]] = None
):
Convert parsed response to OpenAI ChatCompletion format. Parameters:
  • response_text (str): The model response text.
  • model (str): The model name.
  • tools (Optional[List[Dict[str, Any]]]): Available tools for function name inference.
Returns: ChatCompletion: OpenAI-compatible ChatCompletion object.

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_call_ollama_generate

def _call_ollama_generate(self, prompt: str):
Call Ollama’s /api/generate endpoint with raw prompt. Parameters:
  • prompt (str): The formatted prompt string.
Returns: str: The model response text.

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_run

def _run(
    self,
    messages: List[OpenAIMessage],
    response_format: Optional[Type[BaseModel]] = None,
    tools: Optional[List[Dict[str, Any]]] = None
):
Run inference using FunctionGemma via Ollama. Parameters:
  • messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format.
  • response_format (Optional[Type[BaseModel]]): Not supported for FunctionGemma. (default: :obj:None)
  • tools (Optional[List[Dict[str, Any]]]): The schema of the tools to use for the request.
Returns: ChatCompletion: The model response in OpenAI ChatCompletion format.

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stream

def stream(self):
Returns: bool: Always False for FunctionGemma.