Added LiteLLM to the stack

Development/litellm/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py

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+import json
+import os
+import sys
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import httpx
+import pytest
+
+sys.path.insert(
+    0, os.path.abspath("../../../../..")
+)  # Adds the parent directory to the system path
+
+from litellm.llms.hosted_vllm.chat.transformation import HostedVLLMChatConfig
+
+
+def test_hosted_vllm_chat_transformation_file_url():
+    config = HostedVLLMChatConfig()
+    video_url = "https://example.com/video.mp4"
+    video_data = f"data:video/mp4;base64,{video_url}"
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "file",
+                    "file": {
+                        "file_data": video_data,
+                    },
+                }
+            ],
+        }
+    ]
+    transformed_response = config.transform_request(
+        model="hosted_vllm/llama-3.1-70b-instruct",
+        messages=messages,
+        optional_params={},
+        litellm_params={},
+        headers={},
+    )
+    assert transformed_response["messages"] == [
+        {
+            "role": "user",
+            "content": [{"type": "video_url", "video_url": {"url": video_data}}],
+        }
+    ]
+
+
+def test_hosted_vllm_chat_transformation_with_audio_url():
+    from litellm import completion
+    from litellm.llms.custom_httpx.http_handler import HTTPHandler
+
+    client = MagicMock()
+
+    with patch.object(
+        client.chat.completions.with_raw_response, "create", return_value=MagicMock()
+    ) as mock_post:
+        try:
+            response = completion(
+                model="hosted_vllm/llama-3.1-70b-instruct",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "audio_url",
+                                "audio_url": {"url": "https://example.com/audio.mp3"},
+                            },
+                        ],
+                    },
+                ],
+                client=client,
+            )
+        except Exception as e:
+            print(f"Error: {e}")
+
+        mock_post.assert_called_once()
+        print(f"mock_post.call_args.kwargs: {mock_post.call_args.kwargs}")
+        assert mock_post.call_args.kwargs["messages"] == [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "audio_url",
+                        "audio_url": {"url": "https://example.com/audio.mp3"},
+                    }
+                ],
+            }
+        ]
+
+
+def test_hosted_vllm_supports_reasoning_effort():
+    config = HostedVLLMChatConfig()
+    supported_params = config.get_supported_openai_params(
+        model="hosted_vllm/gpt-oss-120b"
+    )
+    assert "reasoning_effort" in supported_params
+    optional_params = config.map_openai_params(
+        non_default_params={"reasoning_effort": "high"},
+        optional_params={},
+        model="hosted_vllm/gpt-oss-120b",
+        drop_params=False,
+    )
+    assert optional_params["reasoning_effort"] == "high"

Development/litellm/tests/test_litellm/llms/hosted_vllm/test_hosted_vllm_rerank_transformation.py

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+import sys
+import os
+import pytest
+from litellm.llms.hosted_vllm.rerank.transformation import HostedVLLMRerankConfig
+from litellm.types.rerank import OptionalRerankParams, RerankResponse, RerankResponseResult, RerankResponseMeta, RerankBilledUnits, RerankTokens, RerankResponseDocument
+
+class TestHostedVLLMRerankTransform:
+    def setup_method(self):
+        self.config = HostedVLLMRerankConfig()
+        self.model = "hosted-vllm-model"
+
+    def test_map_cohere_rerank_params_basic(self):
+        params = self.config.map_cohere_rerank_params(
+            non_default_params=None,
+            model=self.model,
+            drop_params=False,
+            query="test query",
+            documents=["doc1", "doc2"],
+            top_n=2,
+            rank_fields=["field1"],
+            return_documents=True,
+        )
+        assert params["query"] == "test query"
+        assert params["documents"] == ["doc1", "doc2"]
+        assert params["top_n"] == 2
+        assert params["rank_fields"] == ["field1"]
+        assert params["return_documents"] is True
+
+    def test_map_cohere_rerank_params_raises_on_max_chunks_per_doc(self):
+        with pytest.raises(ValueError, match="Hosted VLLM does not support max_chunks_per_doc"):
+            self.config.map_cohere_rerank_params(
+                non_default_params=None,
+                model=self.model,
+                drop_params=False,
+                query="test query",
+                documents=["doc1"],
+                max_chunks_per_doc=5
+            )
+
+    def test_get_complete_url(self):
+        base = "https://api.example.com"
+        url = self.config.get_complete_url(base, self.model)
+        assert url == "https://api.example.com/v1/rerank"
+        # Already ends with /v1/rerank
+        url2 = self.config.get_complete_url("https://api.example.com/v1/rerank", self.model)
+        assert url2 == "https://api.example.com/v1/rerank"
+        # Raises if api_base is None
+        with pytest.raises(ValueError):
+            self.config.get_complete_url(None, self.model)
+
+    def test_transform_response(self):
+        response_dict = {
+            "id": "abc123",
+            "results": [
+                {"index": 0, "relevance_score": 0.9, "document": {"text": "doc1 text"}},
+                {"index": 1, "relevance_score": 0.7, "document": {"text": "doc2 text"}},
+            ],
+            "usage": {"total_tokens": 42}
+        }
+        result = self.config._transform_response(response_dict)
+        assert result.id == "abc123"
+        assert len(result.results) == 2
+        assert result.results[0]["index"] == 0
+        assert result.results[0]["relevance_score"] == 0.9
+        assert result.results[0]["document"]["text"] == "doc1 text"
+        assert result.meta["billed_units"]["total_tokens"] == 42
+        assert result.meta["tokens"]["input_tokens"] == 42
+
+    def test_transform_response_missing_results(self):
+        response_dict = {"id": "abc123", "usage": {"total_tokens": 10}}
+        with pytest.raises(ValueError, match="No results found in the response="):
+            self.config._transform_response(response_dict)
+
+    def test_transform_response_missing_required_fields(self):
+        response_dict = {
+            "id": "abc123",
+            "results": [{"relevance_score": 0.5}],
+            "usage": {"total_tokens": 10}
+        }
+        with pytest.raises(ValueError, match="Missing required fields in the result="):
+            self.config._transform_response(response_dict)