mirror of
https://github.com/tiennm99/litellm.git
synced 2026-06-25 01:39:16 +00:00
Krish Dholakia
24c2cd1bd9
* fix(handler.py): support routing custom llm's to chat completion handler Adds custom llm support for anthropic * test(test_anthropic_experimental_pass_through_messages_handler.py): add unit test confirming custom llm respected * docs(custom_llm_server.md): document anthropic custom llm translation * test(volcengine.py): map thinking in extra body Fixes https://github.com/BerriAI/litellm/issues/11879 * feat(main.py): support `azure/responses/<deployment-name>` model string this allows us to route the model correctly Closes https://github.com/BerriAI/litellm/issues/11879 * docs(azure_responses.md): document calling azure responses api models via chat completions bridge Closes https://github.com/BerriAI/litellm/issues/11917 * fix: fix custom provider check * test: update tests
84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
import os
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import sys
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from unittest.mock import MagicMock, patch
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from pydantic import BaseModel
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from litellm.llms.volcengine import VolcEngineConfig
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from litellm.utils import get_optional_params
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class TestVolcEngineConfig:
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def test_get_optional_params(self):
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config = VolcEngineConfig()
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supported_params = config.get_supported_openai_params(model="doubao-seed-1.6")
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assert "thinking" in supported_params
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mapped_params = config.map_openai_params(
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non_default_params={
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"thinking": {"type": "disabled"},
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},
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optional_params={},
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model="doubao-seed-1.6",
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drop_params=False,
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)
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assert mapped_params == {
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"extra_body": {
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"thinking": {"type": "disabled"},
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}
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}
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e2e_mapped_params = get_optional_params(
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model="doubao-seed-1.6",
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custom_llm_provider="volcengine",
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thinking={"type": "enabled"},
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drop_params=False,
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)
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assert "thinking" in e2e_mapped_params["extra_body"] and e2e_mapped_params[
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"extra_body"
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]["thinking"] == {
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"type": "enabled",
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}
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def test_e2e_completion(self):
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from openai import OpenAI
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from litellm import completion
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from litellm.types.utils import ModelResponse
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client = OpenAI(api_key="test_api_key")
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mock_raw_response = MagicMock()
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mock_raw_response.headers = {
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"x-request-id": "123",
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"openai-organization": "org-123",
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-requests": "99",
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}
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mock_raw_response.parse.return_value = ModelResponse()
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with patch.object(
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client.chat.completions.with_raw_response, "create", mock_raw_response
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) as mock_create:
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completion(
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model="volcengine/doubao-seed-1.6",
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messages=[
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{
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"role": "system",
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"content": "**Tell me your model detail information.**",
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}
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],
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user="guest",
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stream=True,
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thinking={"type": "disabled"},
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client=client,
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)
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mock_create.assert_called_once()
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print(mock_create.call_args.kwargs)
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assert mock_create.call_args.kwargs["extra_body"] == {
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"thinking": {"type": "disabled"},
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}
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