arch: re-work generator name param #1453

garak/generators/cohere.py

@@ -54,10 +54,12 @@ class CohereGenerator(Generator):
     generator_family_name = "Cohere"
 
     def __init__(self, name="command", config_root=_config):
-        self.name = name
+        self._load_config(config_root)
+        if name != "command" or not hasattr(self, "name"):  # "command" is the default
+            self.name = name
         self.fullname = f"Cohere {self.name}"
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         logging.debug(
             "Cohere generation request limit capped at %s", COHERE_GENERATION_LIMIT

garak/generators/function.py

@@ -73,8 +73,9 @@ def __init__(
     ):
         if len(kwargs) > 0:
             self.kwargs = kwargs.copy()
-        self.name = name  # if the user's function requires `name` it would have been extracted from kwargs and will not be passed later
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):  # name is required for function generators
+            self.name = name
 
         gen_module_name, gen_function_name = self.name.split("#")
 
@@ -89,7 +90,7 @@ def __init__(
                 'Incompatible function signature: "name" is incompatible with this Generator'
             )
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
     def _call_model(
         self, prompt: Conversation, generations_this_call: int = 1

garak/generators/ggml.py

@@ -71,8 +71,9 @@ def _command_args_list(self):
         return command_list
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
 
         if not hasattr(self, "path_to_ggml_main") or self.path_to_ggml_main is None:
             self.path_to_ggml_main = os.getenv(self.key_env_var)
@@ -100,7 +101,7 @@ def __init__(self, name="", config_root=_config):
                 if magic_num != GGUF_MAGIC:
                     raise RuntimeError(f"{self.name} is not in GGUF format")
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
     def _validate_env_var(self):
         pass  # suppress default behavior for api_key

garak/generators/guardrails.py

@@ -27,16 +27,17 @@ def __init__(self, name="", config_root=_config):
                 "You must first install NeMo Guardrails using `pip install nemoguardrails`."
             ) from e
 
-        self.name = name
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
         self.fullname = f"Guardrails {self.name}"
 
         # Currently, we use the target_name as the path to the config
         with redirect_stderr(io.StringIO()) as f:  # quieten the tqdm
             config = RailsConfig.from_path(self.name)
             self.rails = LLMRails(config=config)
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
     def _call_model(
         self, prompt: Conversation, generations_this_call: int = 1

garak/generators/huggingface.py

@@ -59,9 +59,11 @@ class Pipeline(Generator, HFCompatible):
     parallel_capable = False
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
+        self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         import torch.multiprocessing as mp
 
@@ -224,8 +226,10 @@ class InferenceAPI(Generator):
     }
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
-        super().__init__(self.name, config_root=config_root)
+        self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
+        super().__init__(name, config_root=config_root)
 
         self.uri = self.URI + self.name
 
@@ -555,7 +559,7 @@ def __init__(self, name="", config_root=_config):
             raise TargetNameMissingError(
                 f"Invalid model name {self.name}, current support: {self.supported_models}."
             )
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         from transformers import LlavaNextProcessor, LlavaNextForConditionalGeneration
 

garak/generators/langchain.py

@@ -47,11 +47,12 @@ class LangChainLLMGenerator(Generator):
     generator_family_name = "LangChain"
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
         self.fullname = f"LangChain LLM {self.name}"
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         try:
             # this might need some special handling to allow tests

garak/generators/litellm.py

@@ -110,21 +110,18 @@ class LiteLLMGenerator(Generator):
     )
 
     def __init__(self, name: str = "", generations: int = 10, config_root=_config):
-        self.name = name
         self.api_base = None
         self.provider = None
         self._load_config(config_root)
-
-        # Ensure suppressed_params is a set for efficient lookup
-        self.suppressed_params = set(self.suppressed_params)
-
+        if name or not hasattr(self, "name"):
+            self.name = name
         self.fullname = f"LiteLLM {self.name}"
         self.supports_multiple_generations = not any(
             self.name.startswith(provider)
             for provider in unsupported_multiple_gen_providers
         )
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
     @backoff.on_exception(backoff.fibo, litellm.exceptions.APIError, max_value=70)
     def _call_model(

garak/generators/nemo.py

@@ -40,12 +40,13 @@ class NeMoGenerator(Generator):
     generator_family_name = "NeMo"
 
     def __init__(self, name=None, config_root=_config):
-        self.name = name
         self.org_id = None
         self._load_config(config_root)
+        if name is not None or not hasattr(self, "name"):
+            self.name = name
         self.fullname = f"NeMo {self.name}"
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         self.nemo = nemollm.api.NemoLLM(
             api_host=self.api_uri, api_key=self.api_key, org_id=self.org_id

garak/generators/nvcf.py

@@ -38,8 +38,9 @@ class NvcfChat(Generator):
     generator_family_name = "NVCF"
 
     def __init__(self, name=None, config_root=_config):
-        self.name = name
         self._load_config(config_root)
+        if name is not None or not hasattr(self, "name"):
+            self.name = name
         self.fullname = (
             f"{self.generator_family_name} {self.__class__.__name__} {self.name}"
         )
@@ -54,7 +55,7 @@ def __init__(self, name=None, config_root=_config):
         if self.version_id is not None:
             self.invoke_uri += f"/versions/{self.version_id}"
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         self.headers = {
             "Authorization": f"Bearer {self.api_key}",

garak/generators/openai.py

@@ -174,8 +174,9 @@ def _validate_config(self):
         pass
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
         self.fullname = f"{self.generator_family_name} {self.name}"
         self.key_env_var = self.ENV_VAR
 
@@ -191,7 +192,7 @@ def __init__(self, name="", config_root=_config):
 
         self._validate_config()
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
         # clear client config to enable object to `pickle`
         self._clear_client()
@@ -335,12 +336,13 @@ def _load_client(self):
             raise garak.exception.BadGeneratorException("🛑 " + msg)
 
     def __init__(self, name="", config_root=_config):
-        self.name = name
         self._load_config(config_root)
+        if name or not hasattr(self, "name"):
+            self.name = name
         if self.name in context_lengths:
             self.context_len = context_lengths[self.name]
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(name, config_root=config_root)
 
 
 class OpenAIReasoningGenerator(OpenAIGenerator):

garak/generators/rest.py

@@ -151,7 +151,7 @@ def __init__(self, uri=None, config_root=_config):
                 )
                 raise e
 
-        super().__init__(self.name, config_root=config_root)
+        super().__init__(uri, config_root=config_root)
 
     def _validate_env_var(self):
         key_match = "$KEY"