refactor: move all testing to top-level of repo

Closes https://github.com/BerriAI/litellm/issues/486

tests/local_testing/test_get_model_info.py

@@ -0,0 +1,70 @@
+# What is this?
+## Unit testing for the 'get_model_info()' function
+import os
+import sys
+import traceback
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import pytest
+
+import litellm
+from litellm import get_model_info
+
+
+def test_get_model_info_simple_model_name():
+    """
+    tests if model name given, and model exists in model info - the object is returned
+    """
+    model = "claude-3-opus-20240229"
+    litellm.get_model_info(model)
+
+
+def test_get_model_info_custom_llm_with_model_name():
+    """
+    Tests if {custom_llm_provider}/{model_name} name given, and model exists in model info, the object is returned
+    """
+    model = "anthropic/claude-3-opus-20240229"
+    litellm.get_model_info(model)
+
+
+def test_get_model_info_custom_llm_with_same_name_vllm():
+    """
+    Tests if {custom_llm_provider}/{model_name} name given, and model exists in model info, the object is returned
+    """
+    model = "command-r-plus"
+    provider = "openai"  # vllm is openai-compatible
+    try:
+        litellm.get_model_info(model, custom_llm_provider=provider)
+        pytest.fail("Expected get model info to fail for an unmapped model/provider")
+    except Exception:
+        pass
+
+
+def test_get_model_info_shows_correct_supports_vision():
+    info = litellm.get_model_info("gemini/gemini-1.5-flash")
+    print("info", info)
+    assert info["supports_vision"] is True
+
+
+def test_get_model_info_shows_assistant_prefill():
+    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
+    litellm.model_cost = litellm.get_model_cost_map(url="")
+    info = litellm.get_model_info("deepseek/deepseek-chat")
+    print("info", info)
+    assert info.get("supports_assistant_prefill") is True
+
+
+def test_get_model_info_shows_supports_prompt_caching():
+    os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
+    litellm.model_cost = litellm.get_model_cost_map(url="")
+    info = litellm.get_model_info("deepseek/deepseek-chat")
+    print("info", info)
+    assert info.get("supports_prompt_caching") is True
+
+
+def test_get_model_info_finetuned_models():
+    info = litellm.get_model_info("ft:gpt-3.5-turbo:my-org:custom_suffix:id")
+    print("info", info)
+    assert info["input_cost_per_token"] == 0.000003