From e4f106ea623598dc0c9856be4a9ebab28a9325e1 Mon Sep 17 00:00:00 2001
From: ccurme <chester.curme@gmail.com>
Date: Thu, 13 Feb 2025 15:49:50 -0800
Subject: [PATCH] groq[patch]: remove xfails (#29794)

These appear to pass.
---
 .../integration_tests/test_chat_models.py     | 37 -------------------
 .../tests/integration_tests/test_standard.py  | 23 ------------
 2 files changed, 60 deletions(-)

diff --git a/libs/partners/groq/tests/integration_tests/test_chat_models.py b/libs/partners/groq/tests/integration_tests/test_chat_models.py
index 9ee5bccca8a..9113c829871 100644
--- a/libs/partners/groq/tests/integration_tests/test_chat_models.py
+++ b/libs/partners/groq/tests/integration_tests/test_chat_models.py
@@ -13,7 +13,6 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, LLMResult
-from langchain_core.tools import tool
 from pydantic import BaseModel, Field
 
 from langchain_groq import ChatGroq
@@ -394,42 +393,6 @@ def test_json_mode_structured_output() -> None:
     assert len(result.punchline) != 0
 
 
-def test_tool_calling_no_arguments() -> None:
-    # Note: this is a variant of a test in langchain_tests
-    # that as of 2024-08-19 fails with "Failed to call a function. Please
-    # adjust your prompt." when `tool_choice="any"` is specified, but
-    # passes when `tool_choice` is not specified.
-    model = ChatGroq(model="llama-3.3-70b-versatile", temperature=0)  # type: ignore[call-arg]
-
-    @tool
-    def magic_function_no_args() -> int:
-        """Calculates a magic function."""
-        return 5
-
-    model_with_tools = model.bind_tools([magic_function_no_args])
-    query = "What is the value of magic_function()? Use the tool."
-    result = model_with_tools.invoke(query)
-    assert isinstance(result, AIMessage)
-    assert len(result.tool_calls) == 1
-    tool_call = result.tool_calls[0]
-    assert tool_call["name"] == "magic_function_no_args"
-    assert tool_call["args"] == {}
-    assert tool_call["id"] is not None
-    assert tool_call["type"] == "tool_call"
-
-    # Test streaming
-    full: Optional[BaseMessageChunk] = None
-    for chunk in model_with_tools.stream(query):
-        full = chunk if full is None else full + chunk  # type: ignore
-    assert isinstance(full, AIMessage)
-    assert len(full.tool_calls) == 1
-    tool_call = full.tool_calls[0]
-    assert tool_call["name"] == "magic_function_no_args"
-    assert tool_call["args"] == {}
-    assert tool_call["id"] is not None
-    assert tool_call["type"] == "tool_call"
-
-
 # Groq does not currently support N > 1
 # @pytest.mark.scheduled
 # def test_chat_multiple_completions() -> None:
diff --git a/libs/partners/groq/tests/integration_tests/test_standard.py b/libs/partners/groq/tests/integration_tests/test_standard.py
index b62982e4ec9..fe91a614dd7 100644
--- a/libs/partners/groq/tests/integration_tests/test_standard.py
+++ b/libs/partners/groq/tests/integration_tests/test_standard.py
@@ -48,26 +48,3 @@ class TestGroqLlama(BaseTestGroq):
     @property
     def supports_json_mode(self) -> bool:
         return False  # Not supported in streaming mode
-
-    @pytest.mark.xfail(
-        reason=("Fails with 'Failed to call a function. Please adjust your prompt.'")
-    )
-    def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None:
-        super().test_tool_calling_with_no_arguments(model)
-
-    @pytest.mark.xfail(
-        reason=("Fails with 'Failed to call a function. Please adjust your prompt.'")
-    )
-    def test_tool_message_histories_string_content(
-        self, model: BaseChatModel, my_adder_tool: BaseTool
-    ) -> None:
-        super().test_tool_message_histories_string_content(model, my_adder_tool)
-
-    @pytest.mark.xfail(
-        reason=(
-            "Sometimes fails with 'Failed to call a function. "
-            "Please adjust your prompt.'"
-        )
-    )
-    def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None:
-        super().test_bind_runnables_as_tools(model)