fix(watsonx.py): use common litellm params for api key, api base, etc.

litellm/llms/watsonx.py

@@ -13,7 +13,7 @@ from .prompt_templates import factory as ptf
 
 
 class WatsonXAIError(Exception):
-    def __init__(self, status_code, message, url: str = None):
+    def __init__(self, status_code, message, url: Optional[str] = None):
         self.status_code = status_code
         self.message = message
         url = url or "https://https://us-south.ml.cloud.ibm.com"
@@ -73,7 +73,6 @@ class IBMWatsonXAIConfig:
     repetition_penalty: Optional[float] = None
     truncate_input_tokens: Optional[int] = None
     include_stop_sequences: Optional[bool] = False
-    return_options: Optional[dict] = None
     return_options: Optional[Dict[str, bool]] = None
     random_seed: Optional[int] = None  # e.g 42
     moderations: Optional[dict] = None
@@ -161,6 +160,7 @@ def convert_messages_to_prompt(model, messages, provider, custom_prompt_dict):
         )
     return prompt
 
+
 class WatsonXAIEndpoint(str, Enum):
     TEXT_GENERATION = "/ml/v1/text/generation"
     TEXT_GENERATION_STREAM = "/ml/v1/text/generation_stream"
@@ -171,6 +171,7 @@ class WatsonXAIEndpoint(str, Enum):
     EMBEDDINGS = "/ml/v1/text/embeddings"
     PROMPTS = "/ml/v1/prompts"
 
+
 class IBMWatsonXAI(BaseLLM):
     """
     Class to interface with IBM Watsonx.ai API for text generation and embeddings.
@@ -180,7 +181,6 @@ class IBMWatsonXAI(BaseLLM):
 
     api_version = "2024-03-13"
 
-
     def __init__(self) -> None:
         super().__init__()
 
@@ -190,7 +190,7 @@ class IBMWatsonXAI(BaseLLM):
         prompt: str,
         stream: bool,
         optional_params: dict,
-        print_verbose: Callable = None,
+        print_verbose: Optional[Callable] = None,
     ) -> dict:
         """
         Get the request parameters for text generation.
@@ -224,9 +224,9 @@ class IBMWatsonXAI(BaseLLM):
                 )
             deployment_id = "/".join(model_id.split("/")[1:])
             endpoint = (
-                WatsonXAIEndpoint.DEPLOYMENT_TEXT_GENERATION_STREAM
+                WatsonXAIEndpoint.DEPLOYMENT_TEXT_GENERATION_STREAM.value
                 if stream
-                else WatsonXAIEndpoint.DEPLOYMENT_TEXT_GENERATION
+                else WatsonXAIEndpoint.DEPLOYMENT_TEXT_GENERATION.value
             )
             endpoint = endpoint.format(deployment_id=deployment_id)
         else:
@@ -239,27 +239,40 @@ class IBMWatsonXAI(BaseLLM):
             )
         url = api_params["url"].rstrip("/") + endpoint
         return dict(
-            method="POST", url=url, headers=headers, 
+            method="POST", url=url, headers=headers, json=payload, params=request_params
-            json=payload, params=request_params
         )
 
-    def _get_api_params(self, params: dict, print_verbose: Callable = None) -> dict:
+    def _get_api_params(
+        self, params: dict, print_verbose: Optional[Callable] = None
+    ) -> dict:
         """
         Find watsonx.ai credentials in the params or environment variables and return the headers for authentication.
         """
         # Load auth variables from params
-        url = params.pop("url", None)
+        url = params.pop("url", params.pop("api_base", params.pop("base_url", None)))
         api_key = params.pop("apikey", None)
         token = params.pop("token", None)
-        project_id = params.pop("project_id", None)  # watsonx.ai project_id
+        project_id = params.pop(
+            "project_id", params.pop("watsonx_project", None)
+        )  # watsonx.ai project_id - allow 'watsonx_project' to be consistent with how vertex project implementation works -> reduce provider-specific params
         space_id = params.pop("space_id", None)  # watsonx.ai deployment space_id
         region_name = params.pop("region_name", params.pop("region", None))
-        wx_credentials = params.pop("wx_credentials", None)
+        if region_name is None:
+            region_name = params.pop(
+                "watsonx_region_name", params.pop("watsonx_region", None)
+            )  # consistent with how vertex ai + aws regions are accepted
+        wx_credentials = params.pop(
+            "wx_credentials",
+            params.pop(
+                "watsonx_credentials", None
+            ),  # follow {provider}_credentials, same as vertex ai
+        )
         api_version = params.pop("api_version", IBMWatsonXAI.api_version)
         # Load auth variables from environment variables
         if url is None:
             url = (
-                get_secret("WATSONX_URL")
+                get_secret("WATSONX_API_BASE")  # consistent with 'AZURE_API_BASE'
+                or get_secret("WATSONX_URL")
                 or get_secret("WX_URL")
                 or get_secret("WML_URL")
             )
@@ -297,7 +310,12 @@ class IBMWatsonXAI(BaseLLM):
             api_key = wx_credentials.get(
                 "apikey", wx_credentials.get("api_key", api_key)
             )
-            token = wx_credentials.get("token", token)
+            token = wx_credentials.get(
+                "token",
+                wx_credentials.get(
+                    "watsonx_token", token
+                ),  # follow format of {provider}_token, same as azure - e.g. 'azure_ad_token=..'
+            )
 
         # verify that all required credentials are present
         if url is None:
@@ -342,10 +360,10 @@ class IBMWatsonXAI(BaseLLM):
         print_verbose: Callable,
         encoding,
         logging_obj,
-        optional_params: Optional[dict] = None,
+        optional_params: dict,
         litellm_params: Optional[dict] = None,
         logger_fn=None,
-        timeout: float = None,
+        timeout: Optional[float] = None,
     ):
         """
         Send a text generation request to the IBM Watsonx.ai API.
@@ -379,10 +397,14 @@ class IBMWatsonXAI(BaseLLM):
             model_response["finish_reason"] = json_resp["results"][0]["stop_reason"]
             model_response["created"] = int(time.time())
             model_response["model"] = model
-            model_response.usage = Usage(
+            setattr(
+                model_response,
+                "usage",
+                Usage(
                     prompt_tokens=prompt_tokens,
                     completion_tokens=completion_tokens,
                     total_tokens=prompt_tokens + completion_tokens,
+                ),
             )
             return model_response
 
@@ -525,7 +547,7 @@ class IBMWatsonXAI(BaseLLM):
         logging_obj: Any,
         stream: bool = False,
         input: Optional[Any] = None,
-        timeout: float = None,
+        timeout: Optional[float] = None,
     ):
         request_str = (
             f"response = {request_params['method']}(\n"
@@ -535,14 +557,14 @@ class IBMWatsonXAI(BaseLLM):
         )
         logging_obj.pre_call(
             input=input,
-            api_key=request_params['headers'].get("Authorization"),
+            api_key=request_params["headers"].get("Authorization"),
             additional_args={
-                "complete_input_dict": request_params['json'],
+                "complete_input_dict": request_params["json"],
                 "request_str": request_str,
             },
         )
         if timeout:
-            request_params['timeout'] = timeout
+            request_params["timeout"] = timeout
         try:
             if stream:
                 resp = requests.request(
@@ -560,10 +582,10 @@ class IBMWatsonXAI(BaseLLM):
         if not stream:
             logging_obj.post_call(
                 input=input,
-                api_key=request_params['headers'].get("Authorization"),
+                api_key=request_params["headers"].get("Authorization"),
                 original_response=json.dumps(resp.json()),
                 additional_args={
                     "status_code": resp.status_code,
-                    "complete_input_dict": request_params['json'],
+                    "complete_input_dict": request_params["json"],
                 },
             )

litellm/main.py

@@ -1872,7 +1872,7 @@ def completion(
                 model_response=model_response,
                 print_verbose=print_verbose,
                 optional_params=optional_params,
-                litellm_params=litellm_params,
+                litellm_params=litellm_params,  # type: ignore
                 logger_fn=logger_fn,
                 encoding=encoding,
                 logging_obj=logging,