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https://github.com/tiennm99/litellm.git
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[Feat] Add reasoning_effort support for perplexity models (#11562)
* fix: add reasoning_effort for pplx * docs pplx reasoning * [tests] add mock tests for pplx reasoning (#11564) * Add tests for Perplexity reasoning models and effort parameter * tests perplexity reasoning effort --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> * test pplx reasoning effort --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com>
This commit is contained in:
Ishaan Jaff
co-authored by
Cursor Agent
Cursor Agent
parent
9b87fde633
commit
cd8ec4556f
@@ -18,6 +18,7 @@ Supported Providers:
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- XAI (`xai/`)
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- Google AI Studio (`google/`)
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- Vertex AI (`vertex_ai/`)
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- Perplexity (`perplexity/`)
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LiteLLM will standardize the `reasoning_content` in the response and `thinking_blocks` in the assistant message.
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@@ -4,12 +4,18 @@ Translate from OpenAI's `/v1/chat/completions` to Perplexity's `/v1/chat/complet
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from typing import Optional, Tuple
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import litellm
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from litellm._logging import verbose_logger
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from litellm.secret_managers.main import get_secret_str
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from ...openai.chat.gpt_transformation import OpenAIGPTConfig
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class PerplexityChatConfig(OpenAIGPTConfig):
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@property
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def custom_llm_provider(self) -> Optional[str]:
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return "perplexity"
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def _get_openai_compatible_provider_info(
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self, api_base: Optional[str], api_key: Optional[str]
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) -> Tuple[Optional[str], Optional[str]]:
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@@ -29,7 +35,7 @@ class PerplexityChatConfig(OpenAIGPTConfig):
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Eg. Perplexity does not support tools, tool_choice, function_call, functions, etc.
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"""
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return [
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base_openai_params = [
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"frequency_penalty",
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"max_tokens",
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"max_completion_tokens",
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@@ -41,3 +47,12 @@ class PerplexityChatConfig(OpenAIGPTConfig):
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"max_retries",
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"extra_headers",
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]
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try:
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if litellm.supports_reasoning(
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model=model, custom_llm_provider=self.custom_llm_provider
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):
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base_openai_params.append("reasoning_effort")
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except Exception as e:
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verbose_logger.debug(f"Error checking if model supports reasoning: {e}")
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return base_openai_params
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@@ -439,6 +439,23 @@
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"gpt-4o-audio-preview-2025-06-03": {
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"max_tokens": 16384,
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"max_input_tokens": 128000,
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"max_output_tokens": 16384,
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"input_cost_per_token": 2.5e-06,
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"input_cost_per_audio_token": 4.0e-5,
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"output_cost_per_token": 1e-05,
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"output_cost_per_audio_token": 8.0e-5,
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"litellm_provider": "openai",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_audio_input": true,
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"supports_audio_output": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"gpt-4o-mini-audio-preview": {
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"max_tokens": 16384,
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"max_input_tokens": 128000,
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@@ -0,0 +1,207 @@
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import json
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import os
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import sys
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from unittest.mock import patch, MagicMock
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import pytest
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm import completion
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from litellm.utils import get_optional_params
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class TestPerplexityReasoning:
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"""
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Test suite for Perplexity Sonar reasoning models with reasoning_effort parameter
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"""
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@pytest.mark.parametrize(
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"model,reasoning_effort",
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[
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("perplexity/sonar-reasoning", "low"),
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("perplexity/sonar-reasoning", "medium"),
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("perplexity/sonar-reasoning", "high"),
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("perplexity/sonar-reasoning-pro", "low"),
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("perplexity/sonar-reasoning-pro", "medium"),
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("perplexity/sonar-reasoning-pro", "high"),
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]
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)
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def test_perplexity_reasoning_effort_parameter_mapping(self, model, reasoning_effort):
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"""
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Test that reasoning_effort parameter is correctly mapped for Perplexity Sonar reasoning models
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"""
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# Set up local model cost map
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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# Get provider and optional params
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_, provider, _, _ = litellm.get_llm_provider(model=model)
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optional_params = get_optional_params(
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model=model,
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custom_llm_provider=provider,
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reasoning_effort=reasoning_effort,
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)
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# Verify that reasoning_effort is preserved in optional_params for Perplexity
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assert "reasoning_effort" in optional_params
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assert optional_params["reasoning_effort"] == reasoning_effort
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@pytest.mark.parametrize(
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"model",
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[
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"perplexity/sonar-reasoning",
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"perplexity/sonar-reasoning-pro",
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]
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)
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def test_perplexity_reasoning_effort_mock_completion(self, model):
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"""
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Test that reasoning_effort is correctly passed in actual completion call (mocked)
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"""
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from openai import OpenAI
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from openai.types.chat.chat_completion import ChatCompletion
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litellm.set_verbose = True
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# Mock successful response with reasoning content
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response_object = {
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"id": "cmpl-test",
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"object": "chat.completion",
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"created": 1677652288,
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"model": model.split("/")[1],
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "This is a test response from the reasoning model.",
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"reasoning_content": "Let me think about this step by step...",
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},
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"finish_reason": "stop",
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}
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],
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"usage": {
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"prompt_tokens": 9,
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"completion_tokens": 20,
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"total_tokens": 29,
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"completion_tokens_details": {
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"reasoning_tokens": 15
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}
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},
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}
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pydantic_obj = ChatCompletion(**response_object)
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def _return_pydantic_obj(*args, **kwargs):
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new_response = MagicMock()
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new_response.headers = {"content-type": "application/json"}
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new_response.parse.return_value = pydantic_obj
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return new_response
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openai_client = OpenAI(api_key="fake-api-key")
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with patch.object(
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openai_client.chat.completions.with_raw_response, "create", side_effect=_return_pydantic_obj
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) as mock_client:
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response = completion(
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model=model,
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messages=[{"role": "user", "content": "Hello, please think about this carefully."}],
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reasoning_effort="high",
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client=openai_client,
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)
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# Verify the call was made
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assert mock_client.called
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# Get the request data from the mock call
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call_args = mock_client.call_args
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request_data = call_args.kwargs
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# Verify reasoning_effort was included in the request
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assert "reasoning_effort" in request_data
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assert request_data["reasoning_effort"] == "high"
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# Verify response structure
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assert response.choices[0].message.content is not None
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assert response.choices[0].message.content == "This is a test response from the reasoning model."
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def test_perplexity_reasoning_models_support_reasoning(self):
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"""
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Test that Perplexity Sonar reasoning models are correctly identified as supporting reasoning
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"""
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from litellm.utils import supports_reasoning
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# Set up local model cost map
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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reasoning_models = [
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"perplexity/sonar-reasoning",
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"perplexity/sonar-reasoning-pro",
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]
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for model in reasoning_models:
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assert supports_reasoning(model, None), f"{model} should support reasoning"
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def test_perplexity_non_reasoning_models_dont_support_reasoning(self):
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"""
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Test that non-reasoning Perplexity models don't support reasoning
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"""
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from litellm.utils import supports_reasoning
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# Set up local model cost map
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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non_reasoning_models = [
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"perplexity/sonar",
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"perplexity/sonar-pro",
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"perplexity/llama-3.1-sonar-large-128k-chat",
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"perplexity/mistral-7b-instruct",
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]
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for model in non_reasoning_models:
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# These models should not support reasoning (should return False or raise exception)
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try:
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result = supports_reasoning(model, None)
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# If it doesn't raise an exception, it should return False
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assert result is False, f"{model} should not support reasoning"
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except Exception:
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# If it raises an exception, that's also acceptable behavior
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pass
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@pytest.mark.parametrize(
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"model,expected_api_base",
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[
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("perplexity/sonar-reasoning", "https://api.perplexity.ai"),
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("perplexity/sonar-reasoning-pro", "https://api.perplexity.ai"),
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]
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)
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def test_perplexity_reasoning_api_base_configuration(self, model, expected_api_base):
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"""
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Test that Perplexity reasoning models use the correct API base
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"""
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from litellm.llms.perplexity.chat.transformation import PerplexityChatConfig
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config = PerplexityChatConfig()
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api_base, _ = config._get_openai_compatible_provider_info(
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api_base=None, api_key="test-key"
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)
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assert api_base == expected_api_base
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def test_perplexity_reasoning_effort_in_supported_params(self):
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"""
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Test that reasoning_effort is in the list of supported parameters for Perplexity
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"""
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from litellm.llms.perplexity.chat.transformation import PerplexityChatConfig
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config = PerplexityChatConfig()
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supported_params = config.get_supported_openai_params(model="perplexity/sonar-reasoning")
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assert "reasoning_effort" in supported_params
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