remaned model_name or nodel_name_or_path to model

haystack/components/generators/chat/openai.py

@@ -63,19 +63,19 @@ class OpenAIChatGenerator:
     def __init__(
         self,
         api_key: Optional[str] = None,
-        model_name: str = "gpt-3.5-turbo",
+        model: str = "gpt-3.5-turbo",
         streaming_callback: Optional[Callable[[StreamingChunk], None]] = None,
         api_base_url: Optional[str] = None,
         organization: Optional[str] = None,
         generation_kwargs: Optional[Dict[str, Any]] = None,
     ):
         """
-        Creates an instance of OpenAIChatGenerator. Unless specified otherwise in the `model_name`, this is for OpenAI's
+        Creates an instance of OpenAIChatGenerator. Unless specified otherwise in the `model`, this is for OpenAI's
         GPT-3.5 model.
 
         :param api_key: The OpenAI API key. It can be explicitly provided or automatically read from the
             environment variable OPENAI_API_KEY (recommended).
-        :param model_name: The name of the model to use.
+        :param model: The name of the model to use.
         :param streaming_callback: A callback function that is called when a new token is received from the stream.
             The callback function accepts StreamingChunk as an argument.
         :param api_base_url: An optional base URL.
@@ -101,7 +101,7 @@ def __init__(
             - `logit_bias`: Add a logit bias to specific tokens. The keys of the dictionary are tokens, and the
                 values are the bias to add to that token.
         """
-        self.model_name = model_name
+        self.model = model
         self.generation_kwargs = generation_kwargs or {}
         self.streaming_callback = streaming_callback
         self.api_base_url = api_base_url
@@ -112,7 +112,7 @@ def _get_telemetry_data(self) -> Dict[str, Any]:
         """
         Data that is sent to Posthog for usage analytics.
         """
-        return {"model": self.model_name}
+        return {"model": self.model}
 
     def to_dict(self) -> Dict[str, Any]:
         """
@@ -122,7 +122,7 @@ def to_dict(self) -> Dict[str, Any]:
         callback_name = serialize_callback_handler(self.streaming_callback) if self.streaming_callback else None
         return default_to_dict(
             self,
-            model_name=self.model_name,
+            model=self.model,
             streaming_callback=callback_name,
             api_base_url=self.api_base_url,
             organization=self.organization,
@@ -162,7 +162,7 @@ def run(self, messages: List[ChatMessage], generation_kwargs: Optional[Dict[str,
         openai_formatted_messages = self._convert_to_openai_format(messages)
 
         chat_completion: Union[Stream[ChatCompletionChunk], ChatCompletion] = self.client.chat.completions.create(
-            model=self.model_name,
+            model=self.model,
             messages=openai_formatted_messages,  # type: ignore # openai expects list of specific message types
             stream=self.streaming_callback is not None,
             **generation_kwargs,

haystack/components/generators/hugging_face_local.py

@@ -67,7 +67,7 @@ class HuggingFaceLocalGenerator:
     ```python
     from haystack.components.generators import HuggingFaceLocalGenerator
 
-    generator = HuggingFaceLocalGenerator(model_name_or_path="google/flan-t5-large",
+    generator = HuggingFaceLocalGenerator(model="google/flan-t5-large",
                                           task="text2text-generation",
                                           generation_kwargs={
                                             "max_new_tokens": 100,
@@ -81,7 +81,7 @@ class HuggingFaceLocalGenerator:
 
     def __init__(
         self,
-        model_name_or_path: str = "google/flan-t5-base",
+        model: str = "google/flan-t5-base",
         task: Optional[Literal["text-generation", "text2text-generation"]] = None,
         device: Optional[str] = None,
         token: Optional[Union[str, bool]] = None,
@@ -90,7 +90,7 @@ def __init__(
         stop_words: Optional[List[str]] = None,
     ):
         """
-        :param model_name_or_path: The name or path of a Hugging Face model for text generation,
+        :param model: The name or path of a Hugging Face model for text generation,
             for example, "google/flan-t5-large".
             If the model is also specified in the `huggingface_pipeline_kwargs`, this parameter will be ignored.
         :param task: The task for the Hugging Face pipeline.
@@ -114,7 +114,7 @@ def __init__(
         :param huggingface_pipeline_kwargs: Dictionary containing keyword arguments used to initialize the
             Hugging Face pipeline for text generation.
             These keyword arguments provide fine-grained control over the Hugging Face pipeline.
-            In case of duplication, these kwargs override `model_name_or_path`, `task`, `device`, and `token` init parameters.
+            In case of duplication, these kwargs override `model`, `task`, `device`, and `token` init parameters.
             See Hugging Face's [documentation](https://huggingface.co/docs/transformers/en/main_classes/pipelines#transformers.pipeline.task)
             for more information on the available kwargs.
             In this dictionary, you can also include `model_kwargs` to specify the kwargs
@@ -132,7 +132,7 @@ def __init__(
 
         # check if the huggingface_pipeline_kwargs contain the essential parameters
         # otherwise, populate them with values from other init parameters
-        huggingface_pipeline_kwargs.setdefault("model", model_name_or_path)
+        huggingface_pipeline_kwargs.setdefault("model", model)
         huggingface_pipeline_kwargs.setdefault("token", token)
         if (
             device is not None

haystack/components/generators/openai.py

@@ -51,15 +51,15 @@ class OpenAIGenerator:
     def __init__(
         self,
         api_key: Optional[str] = None,
-        model_name: str = "gpt-3.5-turbo",
+        model: str = "gpt-3.5-turbo",
         streaming_callback: Optional[Callable[[StreamingChunk], None]] = None,
         api_base_url: Optional[str] = None,
         organization: Optional[str] = None,
         system_prompt: Optional[str] = None,
         generation_kwargs: Optional[Dict[str, Any]] = None,
     ):
         """
-        Creates an instance of OpenAIGenerator. Unless specified otherwise in the `model_name`, this is for OpenAI's
+        Creates an instance of OpenAIGenerator. Unless specified otherwise in the `model`, this is for OpenAI's
         GPT-3.5 model.
 
         :param api_key: The OpenAI API key. It can be explicitly provided or automatically read from the
@@ -92,7 +92,7 @@ def __init__(
             - `logit_bias`: Add a logit bias to specific tokens. The keys of the dictionary are tokens, and the
                 values are the bias to add to that token.
         """
-        self.model_name = model_name
+        self.model = model
         self.generation_kwargs = generation_kwargs or {}
         self.system_prompt = system_prompt
         self.streaming_callback = streaming_callback
@@ -105,7 +105,7 @@ def _get_telemetry_data(self) -> Dict[str, Any]:
         """
         Data that is sent to Posthog for usage analytics.
         """
-        return {"model": self.model_name}
+        return {"model": self.model}
 
     def to_dict(self) -> Dict[str, Any]:
         """
@@ -115,7 +115,7 @@ def to_dict(self) -> Dict[str, Any]:
         callback_name = serialize_callback_handler(self.streaming_callback) if self.streaming_callback else None
         return default_to_dict(
             self,
-            model_name=self.model_name,
+            model=self.model,
             streaming_callback=callback_name,
             api_base_url=self.api_base_url,
             generation_kwargs=self.generation_kwargs,
@@ -161,7 +161,7 @@ def run(self, prompt: str, generation_kwargs: Optional[Dict[str, Any]] = None):
         openai_formatted_messages = self._convert_to_openai_format(messages)
 
         completion: Union[Stream[ChatCompletionChunk], ChatCompletion] = self.client.chat.completions.create(
-            model=self.model_name,
+            model=self.model,
             messages=openai_formatted_messages,  # type: ignore
             stream=self.streaming_callback is not None,
             **generation_kwargs,

releasenotes/notes/renamed-model_name-and-model_name_or_path-as-model-e99c62be6daeb2bc.yaml

@@ -0,0 +1,4 @@
+---
+enhancements:
+  - |
+    Renamed model_name and model_name_or_path to model

test/components/generators/chat/test_openai.py

@@ -20,7 +20,7 @@ class TestOpenAIChatGenerator:
     def test_init_default(self):
         component = OpenAIChatGenerator(api_key="test-api-key")
         assert component.client.api_key == "test-api-key"
-        assert component.model_name == "gpt-3.5-turbo"
+        assert component.model == "gpt-3.5-turbo"
         assert component.streaming_callback is None
         assert not component.generation_kwargs
 
@@ -32,13 +32,13 @@ def test_init_fail_wo_api_key(self, monkeypatch):
     def test_init_with_parameters(self):
         component = OpenAIChatGenerator(
             api_key="test-api-key",
-            model_name="gpt-4",
+            model="gpt-4",
             streaming_callback=default_streaming_callback,
             api_base_url="test-base-url",
             generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
         )
         assert component.client.api_key == "test-api-key"
-        assert component.model_name == "gpt-4"
+        assert component.model == "gpt-4"
         assert component.streaming_callback is default_streaming_callback
         assert component.generation_kwargs == {"max_tokens": 10, "some_test_param": "test-params"}
 
@@ -48,7 +48,7 @@ def test_to_dict_default(self):
         assert data == {
             "type": "haystack.components.generators.chat.openai.OpenAIChatGenerator",
             "init_parameters": {
-                "model_name": "gpt-3.5-turbo",
+                "model": "gpt-3.5-turbo",
                 "organization": None,
                 "streaming_callback": None,
                 "api_base_url": None,
@@ -59,7 +59,7 @@ def test_to_dict_default(self):
     def test_to_dict_with_parameters(self):
         component = OpenAIChatGenerator(
             api_key="test-api-key",
-            model_name="gpt-4",
+            model="gpt-4",
             streaming_callback=default_streaming_callback,
             api_base_url="test-base-url",
             generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
@@ -68,7 +68,7 @@ def test_to_dict_with_parameters(self):
         assert data == {
             "type": "haystack.components.generators.chat.openai.OpenAIChatGenerator",
             "init_parameters": {
-                "model_name": "gpt-4",
+                "model": "gpt-4",
                 "organization": None,
                 "api_base_url": "test-base-url",
                 "streaming_callback": "haystack.components.generators.utils.default_streaming_callback",
@@ -79,7 +79,7 @@ def test_to_dict_with_parameters(self):
     def test_to_dict_with_lambda_streaming_callback(self):
         component = OpenAIChatGenerator(
             api_key="test-api-key",
-            model_name="gpt-4",
+            model="gpt-4",
             streaming_callback=lambda x: x,
             api_base_url="test-base-url",
             generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
@@ -88,7 +88,7 @@ def test_to_dict_with_lambda_streaming_callback(self):
         assert data == {
             "type": "haystack.components.generators.chat.openai.OpenAIChatGenerator",
             "init_parameters": {
-                "model_name": "gpt-4",
+                "model": "gpt-4",
                 "organization": None,
                 "api_base_url": "test-base-url",
                 "streaming_callback": "chat.test_openai.<lambda>",
@@ -100,14 +100,14 @@ def test_from_dict(self):
         data = {
             "type": "haystack.components.generators.chat.openai.OpenAIChatGenerator",
             "init_parameters": {
-                "model_name": "gpt-4",
+                "model": "gpt-4",
                 "api_base_url": "test-base-url",
                 "streaming_callback": "haystack.components.generators.utils.default_streaming_callback",
                 "generation_kwargs": {"max_tokens": 10, "some_test_param": "test-params"},
             },
         }
         component = OpenAIChatGenerator.from_dict(data)
-        assert component.model_name == "gpt-4"
+        assert component.model == "gpt-4"
         assert component.streaming_callback is default_streaming_callback
         assert component.api_base_url == "test-base-url"
         assert component.generation_kwargs == {"max_tokens": 10, "some_test_param": "test-params"}
@@ -117,7 +117,7 @@ def test_from_dict_fail_wo_env_var(self, monkeypatch):
         data = {
             "type": "haystack.components.generators.chat.openai.OpenAIChatGenerator",
             "init_parameters": {
-                "model_name": "gpt-4",
+                "model": "gpt-4",
                 "organization": None,
                 "api_base_url": "test-base-url",
                 "streaming_callback": "haystack.components.generators.utils.default_streaming_callback",
@@ -223,7 +223,7 @@ def test_live_run(self):
     @pytest.mark.integration
     def test_live_run_wrong_model(self, chat_messages):
         component = OpenAIChatGenerator(
-            model_name="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY")
+            model="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY")
         )
         with pytest.raises(OpenAIError):
             component.run(chat_messages)

test/components/generators/test_hugging_face_local_generator.py

@@ -23,7 +23,7 @@ def test_init_default(self, model_info_mock):
 
     def test_init_custom_token(self):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", token="test-token"
+            model="google/flan-t5-base", task="text2text-generation", token="test-token"
         )
 
         assert generator.huggingface_pipeline_kwargs == {
@@ -33,9 +33,7 @@ def test_init_custom_token(self):
         }
 
     def test_init_custom_device(self):
-        generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", device="cuda:0"
-        )
+        generator = HuggingFaceLocalGenerator(model="google/flan-t5-base", task="text2text-generation", device="cuda:0")
 
         assert generator.huggingface_pipeline_kwargs == {
             "model": "google/flan-t5-base",
@@ -65,7 +63,7 @@ def test_init_task_in_huggingface_pipeline_kwargs(self):
     @patch("haystack.components.generators.hugging_face_local.model_info")
     def test_init_task_inferred_from_model_name(self, model_info_mock):
         model_info_mock.return_value.pipeline_tag = "text2text-generation"
-        generator = HuggingFaceLocalGenerator(model_name_or_path="google/flan-t5-base")
+        generator = HuggingFaceLocalGenerator(model="google/flan-t5-base")
 
         assert generator.huggingface_pipeline_kwargs == {
             "model": "google/flan-t5-base",
@@ -91,7 +89,7 @@ def test_init_huggingface_pipeline_kwargs_override_other_parameters(self):
         }
 
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base",
+            model="google/flan-t5-base",
             task="text2text-generation",
             device="cpu",
             token="test-token",
@@ -147,7 +145,7 @@ def test_to_dict_default(self, model_info_mock):
 
     def test_to_dict_with_parameters(self):
         component = HuggingFaceLocalGenerator(
-            model_name_or_path="gpt2",
+            model="gpt2",
             task="text-generation",
             device="cuda:0",
             token="test-token",
@@ -173,7 +171,7 @@ def test_to_dict_with_parameters(self):
     @patch("haystack.components.generators.hugging_face_local.pipeline")
     def test_warm_up(self, pipeline_mock):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", token="test-token"
+            model="google/flan-t5-base", task="text2text-generation", token="test-token"
         )
         pipeline_mock.assert_not_called()
 
@@ -186,7 +184,7 @@ def test_warm_up(self, pipeline_mock):
     @patch("haystack.components.generators.hugging_face_local.pipeline")
     def test_warm_up_doesn_reload(self, pipeline_mock):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", token="test-token"
+            model="google/flan-t5-base", task="text2text-generation", token="test-token"
         )
 
         pipeline_mock.assert_not_called()
@@ -198,9 +196,7 @@ def test_warm_up_doesn_reload(self, pipeline_mock):
 
     def test_run(self):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base",
-            task="text2text-generation",
-            generation_kwargs={"max_new_tokens": 100},
+            model="google/flan-t5-base", task="text2text-generation", generation_kwargs={"max_new_tokens": 100}
         )
 
         # create the pipeline object (simulating the warm_up)
@@ -216,9 +212,7 @@ def test_run(self):
     @patch("haystack.components.generators.hugging_face_local.pipeline")
     def test_run_empty_prompt(self, pipeline_mock):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base",
-            task="text2text-generation",
-            generation_kwargs={"max_new_tokens": 100},
+            model="google/flan-t5-base", task="text2text-generation", generation_kwargs={"max_new_tokens": 100}
         )
 
         generator.warm_up()
@@ -229,9 +223,7 @@ def test_run_empty_prompt(self, pipeline_mock):
 
     def test_run_with_generation_kwargs(self):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base",
-            task="text2text-generation",
-            generation_kwargs={"max_new_tokens": 100},
+            model="google/flan-t5-base", task="text2text-generation", generation_kwargs={"max_new_tokens": 100}
         )
 
         # create the pipeline object (simulating the warm_up)
@@ -245,9 +237,7 @@ def test_run_with_generation_kwargs(self):
 
     def test_run_fails_without_warm_up(self):
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base",
-            task="text2text-generation",
-            generation_kwargs={"max_new_tokens": 100},
+            model="google/flan-t5-base", task="text2text-generation", generation_kwargs={"max_new_tokens": 100}
         )
 
         with pytest.raises(RuntimeError, match="The generation model has not been loaded."):
@@ -300,7 +290,7 @@ def test_warm_up_set_stopping_criteria_list(
         if `stop_words` is provided
         """
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", stop_words=["coca", "cola"]
+            model="google/flan-t5-base", task="text2text-generation", stop_words=["coca", "cola"]
         )
 
         generator.warm_up()
@@ -316,7 +306,7 @@ def test_run_stop_words_removal(self):
         (does not test stopping text generation)
         """
         generator = HuggingFaceLocalGenerator(
-            model_name_or_path="google/flan-t5-base", task="text2text-generation", stop_words=["world"]
+            model="google/flan-t5-base", task="text2text-generation", stop_words=["world"]
         )
 
         # create the pipeline object (simulating the warm_up)