Add support for Hugging Face Inference Endpoint as LLM (#1143)

embedchain/config/llm/base.py

@@ -72,6 +72,8 @@ class BaseLlmConfig(BaseConfig):
         query_type: Optional[str] = None,
         callbacks: Optional[List] = None,
         api_key: Optional[str] = None,
+        endpoint: Optional[str] = None,
+        model_kwargs: Optional[Dict[str, Any]] = {},
     ):
         """
         Initializes a configuration class instance for the LLM.
@@ -105,6 +107,12 @@ class BaseLlmConfig(BaseConfig):
         :type system_prompt: Optional[str], optional
         :param where: A dictionary of key-value pairs to filter the database results., defaults to None
         :type where: Dict[str, Any], optional
+        :param api_key: The api key of the custom endpoint, defaults to None
+        :type api_key: Optional[str], optional
+        :param endpoint: The api url of the custom endpoint, defaults to None
+        :type endpoint: Optional[str], optional
+        :param model_kwargs: A dictionary of key-value pairs to pass to the model, defaults to None
+        :type model_kwargs: Optional[Dict[str, Any]], optional
         :param callbacks: Langchain callback functions to use, defaults to None
         :type callbacks: Optional[List], optional
         :raises ValueError: If the template is not valid as template should
@@ -132,7 +140,8 @@ class BaseLlmConfig(BaseConfig):
         self.query_type = query_type
         self.callbacks = callbacks
         self.api_key = api_key
-
+        self.endpoint = endpoint
+        self.model_kwargs = model_kwargs
         if type(prompt) is str:
             prompt = Template(prompt)