Added LiteLLM to the stack

Development/litellm/tests/llm_translation/base_embedding_unit_tests.py

@@ -0,0 +1,95 @@
+import asyncio
+import httpx
+import json
+import pytest
+import sys
+from typing import Any, Dict, List
+from unittest.mock import MagicMock, Mock, patch
+import os
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import litellm
+from litellm import embedding
+from litellm.exceptions import BadRequestError
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+from litellm.utils import (
+    CustomStreamWrapper,
+    get_supported_openai_params,
+    get_optional_params,
+    get_optional_params_embeddings,
+)
+import requests
+import base64
+
+# test_example.py
+from abc import ABC, abstractmethod
+
+url = "https://dummyimage.com/100/100/fff&text=Test+image"
+response = requests.get(url)
+file_data = response.content
+
+encoded_file = base64.b64encode(file_data).decode("utf-8")
+base64_image = f"data:image/png;base64,{encoded_file}"
+
+
+class BaseLLMEmbeddingTest(ABC):
+    """
+    Abstract base test class that enforces a common test across all test classes.
+    """
+
+    @abstractmethod
+    def get_base_embedding_call_args(self) -> dict:
+        """Must return the base embedding call args"""
+        pass
+
+    @abstractmethod
+    def get_custom_llm_provider(self) -> litellm.LlmProviders:
+        """Must return the custom llm provider"""
+        pass
+
+    @pytest.mark.asyncio()
+    @pytest.mark.parametrize("sync_mode", [True, False])
+    async def test_basic_embedding(self, sync_mode):
+        litellm.set_verbose = True
+        embedding_call_args = self.get_base_embedding_call_args()
+        if sync_mode is True:
+            response = litellm.embedding(
+                **embedding_call_args,
+                input=["hello", "world"],
+            )
+
+            print("embedding response: ", response)
+        else:
+            response = await litellm.aembedding(
+                **embedding_call_args,
+                input=["hello", "world"],
+            )
+
+            print("async embedding response: ", response)
+
+        from openai.types.create_embedding_response import CreateEmbeddingResponse
+
+        CreateEmbeddingResponse.model_validate(response.model_dump())
+
+    def test_embedding_optional_params_max_retries(self):
+        embedding_call_args = self.get_base_embedding_call_args()
+        optional_params = get_optional_params_embeddings(
+            **embedding_call_args, max_retries=20
+        )
+        assert optional_params["max_retries"] == 20
+
+    def test_image_embedding(self):
+        litellm.set_verbose = True
+        from litellm.utils import supports_embedding_image_input
+
+        os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
+        litellm.model_cost = litellm.get_model_cost_map(url="")
+
+        base_embedding_call_args = self.get_base_embedding_call_args()
+        if not supports_embedding_image_input(base_embedding_call_args["model"], None):
+            print("Model does not support embedding image input")
+            pytest.skip("Model does not support embedding image input")
+
+        embedding(**base_embedding_call_args, input=[base64_image])