From 6d9d79d12b1a4373647a25f90a97bfbfab0d2250 Mon Sep 17 00:00:00 2001
From: ishaan-jaff <ishaanjaffer0324@gmail.com>
Date: Wed, 15 Nov 2023 16:58:54 -0800
Subject: [PATCH] (chore) remove bloat old testing.py file

---
 litellm/testing.py | 146 ---------------------------------------------
 1 file changed, 146 deletions(-)
 delete mode 100644 litellm/testing.py

diff --git a/litellm/testing.py b/litellm/testing.py
deleted file mode 100644
index 5daba6a705c..00000000000
--- a/litellm/testing.py
+++ /dev/null
@@ -1,146 +0,0 @@
-# +-----------------------------------------------+
-# |                                               |
-# |           Give Feedback / Get Help            |
-# | https://github.com/BerriAI/litellm/issues/new |
-# |                                               |
-# +-----------------------------------------------+
-#
-#  Thank you users! We ❤️ you! - Krrish & Ishaan
-
-import litellm
-import time
-from concurrent.futures import ThreadPoolExecutor
-import traceback
-
-
-def testing_batch_completion(*args, **kwargs):
-    try:
-        batch_models = (
-            args[0] if len(args) > 0 else kwargs.pop("models")
-        )  ## expected input format- ["gpt-3.5-turbo", {"model": "qvv0xeq", "custom_llm_provider"="baseten"}...]
-        batch_messages = args[1] if len(args) > 1 else kwargs.pop("messages")
-        results = []
-        completions = []
-        exceptions = []
-        times = []
-        with ThreadPoolExecutor() as executor:
-            for model in batch_models:
-                kwargs_modified = dict(kwargs)
-                args_modified = list(args)
-                if len(args) > 0:
-                    args_modified[0] = model["model"]
-                else:
-                    kwargs_modified["model"] = (
-                        model["model"]
-                        if isinstance(model, dict) and "model" in model
-                        else model
-                    )  # if model is a dictionary get it's value else assume it's a string
-                    kwargs_modified["custom_llm_provider"] = (
-                        model["custom_llm_provider"]
-                        if isinstance(model, dict) and "custom_llm_provider" in model
-                        else None
-                    )
-                    kwargs_modified["api_base"] = (
-                        model["api_base"]
-                        if isinstance(model, dict) and "api_base" in model
-                        else None
-                    )
-                for message_list in batch_messages:
-                    if len(args) > 1:
-                        args_modified[1] = message_list
-                        future = executor.submit(
-                            litellm.completion, *args_modified, **kwargs_modified
-                        )
-                    else:
-                        kwargs_modified["messages"] = message_list
-                        future = executor.submit(
-                            litellm.completion, *args_modified, **kwargs_modified
-                        )
-                    completions.append((future, message_list))
-
-        # Retrieve the results and calculate elapsed time for each completion call
-        for completion in completions:
-            future, message_list = completion
-            start_time = time.time()
-            try:
-                result = future.result()
-                end_time = time.time()
-                elapsed_time = end_time - start_time
-                result_dict = {
-                    "status": "succeeded",
-                    "response": future.result(),
-                    "prompt": message_list,
-                    "response_time": elapsed_time,
-                }
-                results.append(result_dict)
-            except Exception as e:
-                end_time = time.time()
-                elapsed_time = end_time - start_time
-                result_dict = {
-                    "status": "failed",
-                    "response": e,
-                    "response_time": elapsed_time,
-                }
-                results.append(result_dict)
-        return results
-    except:
-        traceback.print_exc()
-
-
-def duration_test_model(original_function):
-    def wrapper_function(*args, **kwargs):
-        # Code to be executed before the original function
-        duration = kwargs.pop("duration", None)
-        interval = kwargs.pop("interval", None)
-        results = []
-        if duration and interval:
-            start_time = time.time()
-            end_time = start_time + duration  # default to 1hr duration
-            while time.time() < end_time:
-                result = original_function(*args, **kwargs)
-                results.append(result)
-                time.sleep(interval)
-        else:
-            result = original_function(*args, **kwargs)
-            results = result
-        return results
-
-    # Return the wrapper function
-    return wrapper_function
-
-
-@duration_test_model
-def load_test_model(models: list, prompt: str = "", num_calls: int = 0):
-    test_calls = 100
-    if num_calls:
-        test_calls = num_calls
-    input_prompt = prompt if prompt else "Hey, how's it going?"
-    messages = (
-        [{"role": "user", "content": prompt}]
-        if prompt
-        else [{"role": "user", "content": input_prompt}]
-    )
-    full_message_list = [
-        messages for _ in range(test_calls)
-    ]  # call it as many times as set by user to load test models
-    start_time = time.time()
-    try:
-        results = testing_batch_completion(models=models, messages=full_message_list)
-        end_time = time.time()
-        response_time = end_time - start_time
-        return {
-            "total_response_time": response_time,
-            "calls_made": test_calls,
-            "prompt": input_prompt,
-            "results": results,
-        }
-    except Exception as e:
-        traceback.print_exc()
-        end_time = time.time()
-        response_time = end_time - start_time
-        return {
-            "total_response_time": response_time,
-            "calls_made": test_calls,
-            "prompt": input_prompt,
-            "exception": e,
-        }