fix(openai.py): deepinfra function calling - drop_params support for unsupported tool choice value

litellm/llms/openai.py

@@ -1,34 +1,41 @@
+import hashlib
+import json
+import time
+import traceback
+import types
 from typing import (
-    Optional,
-    Union,
     Any,
     BinaryIO,
-    Literal,
+    Callable,
+    Coroutine,
     Iterable,
+    Literal,
+    Optional,
+    Union,
 )
-import hashlib
-from typing_extensions import override, overload
-from pydantic import BaseModel
-import types, time, json, traceback
+
 import httpx
-from .base import BaseLLM
-from litellm.utils import (
-    ModelResponse,
-    Choices,
-    Message,
-    CustomStreamWrapper,
-    convert_to_model_response_object,
-    Usage,
-    TranscriptionResponse,
-    TextCompletionResponse,
-)
-from typing import Callable, Optional, Coroutine
-import litellm
-from .prompt_templates.factory import prompt_factory, custom_prompt
-from openai import OpenAI, AsyncOpenAI
-from ..types.llms.openai import *
 import openai
+from openai import AsyncOpenAI, OpenAI
+from pydantic import BaseModel
+from typing_extensions import overload, override
+
+import litellm
 from litellm.types.utils import ProviderField
+from litellm.utils import (
+    Choices,
+    CustomStreamWrapper,
+    Message,
+    ModelResponse,
+    TextCompletionResponse,
+    TranscriptionResponse,
+    Usage,
+    convert_to_model_response_object,
+)
+
+from ..types.llms.openai import *
+from .base import BaseLLM
+from .prompt_templates.factory import custom_prompt, prompt_factory
 
 
 class OpenAIError(Exception):
@@ -306,8 +313,12 @@ class DeepInfraConfig:
         ]
 
     def map_openai_params(
-        self, non_default_params: dict, optional_params: dict, model: str
-    ):
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
         supported_openai_params = self.get_supported_openai_params()
         for param, value in non_default_params.items():
             if (
@@ -316,7 +327,22 @@ class DeepInfraConfig:
                 and model == "mistralai/Mistral-7B-Instruct-v0.1"
             ):  # this model does no support temperature == 0
                 value = 0.0001  # close to 0
+            if param == "tool_choice":
+                if (
+                    value != "auto" and value != "none"
+                ):  # https://deepinfra.com/docs/advanced/function_calling
+                    ## UNSUPPORTED TOOL CHOICE VALUE
+                    if litellm.drop_params is True or drop_params is True:
+                        value = None
+                    else:
+                        raise litellm.utils.UnsupportedParamsError(
+                            message="Deepinfra doesn't support tool_choice={}. To drop unsupported openai params from the call, set `litellm.drop_params = True`".format(
+                                value
+                            ),
+                            status_code=400,
+                        )
             if param in supported_openai_params:
+                if value is not None:
                     optional_params[param] = value
         return optional_params
 

litellm/tests/test_completion.py

@@ -3355,16 +3355,53 @@ def test_completion_ai21():
 # test_completion_ai21()
 # test_completion_ai21()
 ## test deep infra
-def test_completion_deep_infra():
+@pytest.mark.parametrize("drop_params", [True, False])
+def test_completion_deep_infra(drop_params):
     litellm.set_verbose = False
     model_name = "deepinfra/meta-llama/Llama-2-70b-chat-hf"
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "get_current_weather",
+                "description": "Get the current weather in a given location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "type": "string",
+                            "description": "The city and state, e.g. San Francisco, CA",
+                        },
+                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
+                    },
+                    "required": ["location"],
+                },
+            },
+        }
+    ]
+    messages = [
+        {
+            "role": "user",
+            "content": "What's the weather like in Boston today in Fahrenheit?",
+        }
+    ]
     try:
         response = completion(
-            model=model_name, messages=messages, temperature=0, max_tokens=10
+            model=model_name,
+            messages=messages,
+            temperature=0,
+            max_tokens=10,
+            tools=tools,
+            tool_choice={
+                "type": "function",
+                "function": {"name": "get_current_weather"},
+            },
+            drop_params=drop_params,
         )
         # Add any assertions here to check the response
         print(response)
     except Exception as e:
+        if drop_params is True:
             pytest.fail(f"Error occurred: {e}")
 
 

litellm/utils.py

@@ -2950,6 +2950,11 @@ def get_optional_params(
             non_default_params=non_default_params,
             optional_params=optional_params,
             model=model,
+            drop_params=(
+                drop_params
+                if drop_params is not None and isinstance(drop_params, bool)
+                else False
+            ),
         )
     elif custom_llm_provider == "perplexity":
         supported_params = get_supported_openai_params(