Make LLM Generator configurable

autointent/generation/utterances/generator.py

@@ -1,6 +1,7 @@
 """Wrapper class for accessing OpenAI API."""
 
 import os
+from typing import Any, ClassVar
 
 import openai
 from dotenv import load_dotenv
@@ -11,24 +12,43 @@
 class Generator:
     """Wrapper class for accessing OpenAI API."""
 
-    def __init__(self) -> None:
-        """Initialize."""
-        load_dotenv()
-        self.client = openai.OpenAI(base_url=os.environ["OPENAI_BASE_URL"], api_key=os.environ["OPENAI_API_KEY"])
-        self.async_client = openai.AsyncOpenAI(
-            base_url=os.environ["OPENAI_BASE_URL"], api_key=os.environ["OPENAI_API_KEY"]
-        )
-        self.model_name = os.environ["OPENAI_MODEL_NAME"]
+    _default_generation_params: ClassVar[dict[str, Any]] = {
+        "max_tokens": 150,
+        "n": 1,
+        "stop": None,
+        "temperature": 0.7,
+    }
+
+    def __init__(self, base_url: str | None = None, model_name: str | None = None, **generation_params: Any) -> None:  # noqa: ANN401
+        """
+        Initialize the wrapper for LLM.
+
+        :param base_url: HTTP-endpoint for sending API requests to OpenAI API compatible server.
+            Omit this to infer OPENAI_BASE_URL from environment.
+        :param model_name: Name of LLM. Omit this to infer OPENAI_MODEL_NAME from environment.
+        :param generation_params: kwargs that will be sent with a request to the endpoint.
+            Omit this to use AutoIntent's default parameters.
+        """
+        if not base_url:
+            load_dotenv()
+            base_url = os.environ["OPENAI_BASE_URL"]
+        if not model_name:
+            load_dotenv()
+            model_name = os.environ["OPENAI_MODEL_NAME"]
+        self.model_name = model_name
+        self.client = openai.OpenAI(base_url=base_url)
+        self.async_client = openai.AsyncOpenAI(base_url=base_url)
+        self.generation_params = {
+            **self._default_generation_params,
+            **generation_params,
+        }  #  https://stackoverflow.com/a/65539348
 
     def get_chat_completion(self, messages: list[Message]) -> str:
         """Prompt LLM and return its answer synchronously."""
         response = self.client.chat.completions.create(
             messages=messages,  # type: ignore[arg-type]
             model=self.model_name,
-            max_tokens=150,
-            n=1,
-            stop=None,
-            temperature=0.7,
+            **self.generation_params,
         )
         return response.choices[0].message.content  # type: ignore[return-value]
 
@@ -37,9 +57,6 @@ async def get_chat_completion_async(self, messages: list[Message]) -> str:
         response = await self.async_client.chat.completions.create(
             messages=messages,  # type: ignore[arg-type]
             model=self.model_name,
-            max_tokens=150,
-            n=1,
-            stop=None,
-            temperature=0.7,
+            **self.generation_params,
         )
         return response.choices[0].message.content  # type: ignore[return-value]