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https://github.com/BerriAI/litellm.git
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fix(groq): strip assistant provider_specific_fields in message transform
This commit is contained in:
Utsab Dahal
parent
5544803b35
commit
fe656d8d4f
2 changed files with 76 additions and 27 deletions
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@ -1,6 +1,7 @@
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"""
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Translate from OpenAI's `/v1/chat/completions` to Groq's `/v1/chat/completions`
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"""
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from typing import (
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Any,
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Coroutine,
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@ -115,8 +116,7 @@ class GroqChatConfig(OpenAILikeChatConfig):
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@overload
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def _transform_messages(
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self, messages: List[AllMessageValues], model: str, is_async: Literal[True]
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) -> Coroutine[Any, Any, List[AllMessageValues]]:
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...
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) -> Coroutine[Any, Any, List[AllMessageValues]]: ...
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@overload
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def _transform_messages(
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@ -124,8 +124,7 @@ class GroqChatConfig(OpenAILikeChatConfig):
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messages: List[AllMessageValues],
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model: str,
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is_async: Literal[False] = False,
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) -> List[AllMessageValues]:
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...
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) -> List[AllMessageValues]: ...
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def _transform_messages(
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self, messages: List[AllMessageValues], model: str, is_async: bool = False
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@ -133,6 +132,8 @@ class GroqChatConfig(OpenAILikeChatConfig):
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for idx, message in enumerate(messages):
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"""
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1. Don't pass 'null' function_call assistant message to groq - https://github.com/BerriAI/litellm/issues/5839
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2. Strip LiteLLM-internal provider_specific_fields from assistant history
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before sending to Groq, which rejects unknown assistant properties.
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"""
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if isinstance(message, BaseModel):
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_message = message.model_dump()
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@ -142,6 +143,8 @@ class GroqChatConfig(OpenAILikeChatConfig):
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if assistant_message:
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new_message = ChatCompletionAssistantMessage(role="assistant")
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for k, v in _message.items():
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if k == "provider_specific_fields":
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continue
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if v is not None:
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new_message[k] = v # type: ignore
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messages[idx] = new_message
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@ -293,10 +296,10 @@ class GroqChatConfig(OpenAILikeChatConfig):
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json_mode=json_mode,
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)
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mapped_service_tier: Literal[
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"auto", "default", "flex"
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] = self._map_groq_service_tier(
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original_service_tier=getattr(model_response, "service_tier")
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mapped_service_tier: Literal["auto", "default", "flex"] = (
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self._map_groq_service_tier(
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original_service_tier=getattr(model_response, "service_tier")
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)
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)
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setattr(model_response, "service_tier", mapped_service_tier)
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return model_response
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@ -1,5 +1,6 @@
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import os
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import sys
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from typing import List, cast
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import pytest
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@ -15,6 +16,8 @@ from litellm.llms.groq.chat.transformation import (
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GroqChatConfig,
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GroqChatCompletionStreamingHandler,
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)
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from litellm.types.llms.openai import AllMessageValues
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class TestGroq(BaseLLMChatTest):
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def get_base_completion_call_args(self) -> dict:
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@ -29,12 +32,41 @@ class TestGroq(BaseLLMChatTest):
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def test_tool_call_with_empty_enum_property(self):
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pass
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@pytest.mark.parametrize("model", ["groq/qwen/qwen3-32b", "groq/openai/gpt-oss-20b", "groq/openai/gpt-oss-120b"])
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@pytest.mark.parametrize(
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"model",
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["groq/qwen/qwen3-32b", "groq/openai/gpt-oss-20b", "groq/openai/gpt-oss-120b"],
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)
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def test_reasoning_effort_in_supported_params(self, model):
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"""Test that reasoning_effort is in the list of supported parameters for Groq"""
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supported_params = GroqChatConfig().get_supported_openai_params(model=model)
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assert "reasoning_effort" in supported_params
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def test_transform_messages_strips_assistant_provider_specific_fields(self):
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"""Groq rejects unknown assistant fields like provider_specific_fields."""
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config = GroqChatConfig()
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messages = cast(
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List[AllMessageValues],
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[
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{
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"role": "assistant",
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"content": "Tool metadata",
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"provider_specific_fields": {
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"mcp_list_tools": [{"name": "weather"}],
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"mcp_tool_calls": [{"id": "call_123"}],
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},
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}
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],
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)
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transformed = cast(
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List[AllMessageValues],
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config._transform_messages(messages=messages, model="qwen/qwen3-32b"),
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)
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assert transformed[0]["role"] == "assistant"
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assert transformed[0].get("content") == "Tool metadata"
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assert "provider_specific_fields" not in transformed[0]
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class TestGroqStructuredOutputs:
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"""
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@ -66,19 +98,19 @@ class TestGroqStructuredOutputs:
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"schema": {
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"type": "object",
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"properties": {"name": {"type": "string"}},
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"required": ["name"]
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}
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}
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"required": ["name"],
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},
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},
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},
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"tools": [
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"parameters": {"type": "object", "properties": {}}
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}
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"parameters": {"type": "object", "properties": {}},
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},
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}
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]
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],
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}
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with pytest.raises(litellm.BadRequestError) as exc_info:
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@ -92,7 +124,9 @@ class TestGroqStructuredOutputs:
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assert "does not support native structured outputs" in str(exc_info.value)
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assert "incompatible with user-provided tools" in str(exc_info.value)
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def test_structured_output_without_tools_uses_workaround_for_non_native_models(self):
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def test_structured_output_without_tools_uses_workaround_for_non_native_models(
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self,
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):
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"""
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Test that structured outputs without tools works using the json_tool_call workaround
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for models that don't support native json_schema.
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@ -109,9 +143,9 @@ class TestGroqStructuredOutputs:
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"schema": {
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"type": "object",
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"properties": {"name": {"type": "string"}},
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"required": ["name"]
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}
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}
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"required": ["name"],
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},
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},
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}
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}
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@ -147,9 +181,9 @@ class TestGroqStructuredOutputs:
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"schema": {
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"type": "object",
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"properties": {"name": {"type": "string"}},
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"required": ["name"]
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}
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}
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"required": ["name"],
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},
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},
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}
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}
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@ -172,7 +206,7 @@ class TestGroqStructuredOutputs:
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class TestGroqReasoning:
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"""
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Tests for Groq reasoning field mapping.
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Groq returns 'reasoning' field in delta, but LiteLLM expects 'reasoning_content'.
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"""
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@ -207,7 +241,10 @@ class TestGroqReasoning:
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parsed_chunk = handler.chunk_parser(groq_chunk)
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# Verify that reasoning was mapped to reasoning_content
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assert parsed_chunk.choices[0].delta.reasoning_content == "This is reasoning content"
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assert (
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parsed_chunk.choices[0].delta.reasoning_content
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== "This is reasoning content"
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)
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# Verify that the original 'reasoning' field was removed
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assert not hasattr(parsed_chunk.choices[0].delta, "reasoning")
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@ -268,7 +305,10 @@ class TestGroqReasoning:
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{
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"index": 0,
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"id": "call_123",
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"function": {"name": "test_function", "arguments": "{}"},
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"function": {
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"name": "test_function",
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"arguments": "{}",
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},
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"type": "function",
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}
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],
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@ -283,8 +323,14 @@ class TestGroqReasoning:
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parsed_chunk = handler.chunk_parser(groq_chunk)
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# Verify that reasoning was mapped to reasoning_content
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assert parsed_chunk.choices[0].delta.reasoning_content == "Reasoning before tool call"
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assert (
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parsed_chunk.choices[0].delta.reasoning_content
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== "Reasoning before tool call"
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)
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# Verify tool_calls are still present
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assert parsed_chunk.choices[0].delta.tool_calls is not None
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assert len(parsed_chunk.choices[0].delta.tool_calls) == 1
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assert parsed_chunk.choices[0].delta.tool_calls[0]["function"]["name"] == "test_function"
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assert (
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parsed_chunk.choices[0].delta.tool_calls[0]["function"]["name"]
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== "test_function"
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)
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