diff --git a/litellm/integrations/aispend.py b/litellm/integrations/aispend.py
deleted file mode 100644
index 3a62c646f..000000000
--- a/litellm/integrations/aispend.py
+++ /dev/null
@@ -1,167 +0,0 @@
-#### What this does ####
-#    On success + failure, log events to aispend.io
-import datetime
-import os
-import traceback
-
-import dotenv
-
-model_cost = {
-    "gpt-3.5-turbo": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-35-turbo": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },  # azure model name
-    "gpt-3.5-turbo-0613": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-3.5-turbo-0301": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-3.5-turbo-16k": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },
-    "gpt-35-turbo-16k": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },  # azure model name
-    "gpt-3.5-turbo-16k-0613": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },
-    "gpt-4": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.00006,
-    },
-    "gpt-4-0613": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.00006,
-    },
-    "gpt-4-32k": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.00006,
-        "output_cost_per_token": 0.00012,
-    },
-    "claude-instant-1": {
-        "max_tokens": 100000,
-        "input_cost_per_token": 0.00000163,
-        "output_cost_per_token": 0.00000551,
-    },
-    "claude-2": {
-        "max_tokens": 100000,
-        "input_cost_per_token": 0.00001102,
-        "output_cost_per_token": 0.00003268,
-    },
-    "text-bison-001": {
-        "max_tokens": 8192,
-        "input_cost_per_token": 0.000004,
-        "output_cost_per_token": 0.000004,
-    },
-    "chat-bison-001": {
-        "max_tokens": 4096,
-        "input_cost_per_token": 0.000002,
-        "output_cost_per_token": 0.000002,
-    },
-    "command-nightly": {
-        "max_tokens": 4096,
-        "input_cost_per_token": 0.000015,
-        "output_cost_per_token": 0.000015,
-    },
-}
-
-
-class AISpendLogger:
-    # Class variables or attributes
-    def __init__(self):
-        # Instance variables
-        self.account_id = os.getenv("AISPEND_ACCOUNT_ID")
-        self.api_key = os.getenv("AISPEND_API_KEY")
-
-    def price_calculator(self, model, response_obj, start_time, end_time):
-        # try and find if the model is in the model_cost map
-        # else default to the average of the costs
-        prompt_tokens_cost_usd_dollar = 0
-        completion_tokens_cost_usd_dollar = 0
-        if model in model_cost:
-            prompt_tokens_cost_usd_dollar = (
-                model_cost[model]["input_cost_per_token"]
-                * response_obj["usage"]["prompt_tokens"]
-            )
-            completion_tokens_cost_usd_dollar = (
-                model_cost[model]["output_cost_per_token"]
-                * response_obj["usage"]["completion_tokens"]
-            )
-        elif "replicate" in model:
-            # replicate models are charged based on time
-            # llama 2 runs on an nvidia a100 which costs $0.0032 per second - https://replicate.com/replicate/llama-2-70b-chat
-            model_run_time = end_time - start_time  # assuming time in seconds
-            cost_usd_dollar = model_run_time * 0.0032
-            prompt_tokens_cost_usd_dollar = cost_usd_dollar / 2
-            completion_tokens_cost_usd_dollar = cost_usd_dollar / 2
-        else:
-            # calculate average input cost
-            input_cost_sum = 0
-            output_cost_sum = 0
-            for model in model_cost:
-                input_cost_sum += model_cost[model]["input_cost_per_token"]
-                output_cost_sum += model_cost[model]["output_cost_per_token"]
-            prompt_tokens_cost_usd_dollar = (
-                model_cost[model]["input_cost_per_token"]
-                * response_obj["usage"]["prompt_tokens"]
-            )
-            completion_tokens_cost_usd_dollar = (
-                model_cost[model]["output_cost_per_token"]
-                * response_obj["usage"]["completion_tokens"]
-            )
-        return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar
-
-    def log_event(self, model, response_obj, start_time, end_time, print_verbose):
-        # Method definition
-        try:
-            print_verbose(
-                f"AISpend Logging - Enters logging function for model {model}"
-            )
-
-            response_timestamp = datetime.datetime.fromtimestamp(
-                int(response_obj["created"])
-            ).strftime("%Y-%m-%d")
-
-            (
-                prompt_tokens_cost_usd_dollar,
-                completion_tokens_cost_usd_dollar,
-            ) = self.price_calculator(model, response_obj, start_time, end_time)
-            prompt_tokens_cost_usd_cent = prompt_tokens_cost_usd_dollar * 100
-            completion_tokens_cost_usd_cent = completion_tokens_cost_usd_dollar * 100
-            data = [
-                {
-                    "requests": 1,
-                    "requests_context": 1,
-                    "context_tokens": response_obj["usage"]["prompt_tokens"],
-                    "requests_generated": 1,
-                    "generated_tokens": response_obj["usage"]["completion_tokens"],
-                    "recorded_date": response_timestamp,
-                    "model_id": response_obj["model"],
-                    "generated_tokens_cost_usd_cent": prompt_tokens_cost_usd_cent,
-                    "context_tokens_cost_usd_cent": completion_tokens_cost_usd_cent,
-                }
-            ]
-
-            print_verbose(f"AISpend Logging - final data object: {data}")
-        except Exception:
-            print_verbose(f"AISpend Logging Error - {traceback.format_exc()}")
-            pass
diff --git a/litellm/integrations/berrispend.py b/litellm/integrations/berrispend.py
deleted file mode 100644
index a1ad2e6a2..000000000
--- a/litellm/integrations/berrispend.py
+++ /dev/null
@@ -1,86 +0,0 @@
-#### What this does ####
-#    On success + failure, log events to aispend.io
-import datetime
-import os
-import traceback
-
-import dotenv
-import requests  # type: ignore
-
-model_cost = {
-    "gpt-3.5-turbo": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-35-turbo": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },  # azure model name
-    "gpt-3.5-turbo-0613": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-3.5-turbo-0301": {
-        "max_tokens": 4000,
-        "input_cost_per_token": 0.0000015,
-        "output_cost_per_token": 0.000002,
-    },
-    "gpt-3.5-turbo-16k": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },
-    "gpt-35-turbo-16k": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },  # azure model name
-    "gpt-3.5-turbo-16k-0613": {
-        "max_tokens": 16000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.000004,
-    },
-    "gpt-4": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.00006,
-    },
-    "gpt-4-0613": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.000003,
-        "output_cost_per_token": 0.00006,
-    },
-    "gpt-4-32k": {
-        "max_tokens": 8000,
-        "input_cost_per_token": 0.00006,
-        "output_cost_per_token": 0.00012,
-    },
-    "claude-instant-1": {
-        "max_tokens": 100000,
-        "input_cost_per_token": 0.00000163,
-        "output_cost_per_token": 0.00000551,
-    },
-    "claude-2": {
-        "max_tokens": 100000,
-        "input_cost_per_token": 0.00001102,
-        "output_cost_per_token": 0.00003268,
-    },
-    "text-bison-001": {
-        "max_tokens": 8192,
-        "input_cost_per_token": 0.000004,
-        "output_cost_per_token": 0.000004,
-    },
-    "chat-bison-001": {
-        "max_tokens": 4096,
-        "input_cost_per_token": 0.000002,
-        "output_cost_per_token": 0.000002,
-    },
-    "command-nightly": {
-        "max_tokens": 4096,
-        "input_cost_per_token": 0.000015,
-        "output_cost_per_token": 0.000015,
-    },
-}
diff --git a/litellm/integrations/litedebugger.py b/litellm/integrations/litedebugger.py
deleted file mode 100644
index 6af8810bf..000000000
--- a/litellm/integrations/litedebugger.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import json
-import os
-import traceback
-import types
-
-import requests
-
-
-class LiteDebugger:
-    user_email = None
-    dashboard_url = None
-
-    def __init__(self, email=None):
-        self.api_url = "https://api.litellm.ai/debugger"
-        self.validate_environment(email)
-        pass
-
-    def validate_environment(self, email):
-        try:
-            self.user_email = (
-                email or os.getenv("LITELLM_TOKEN") or os.getenv("LITELLM_EMAIL")
-            )
-            if (
-                self.user_email is None
-            ):  # if users are trying to use_client=True but token not set
-                raise ValueError(
-                    "litellm.use_client = True but no token or email passed. Please set it in litellm.token"
-                )
-            self.dashboard_url = "https://admin.litellm.ai/" + self.user_email
-            if self.user_email is None:
-                raise ValueError(
-                    "[Non-Blocking Error] LiteLLMDebugger: Missing LITELLM_TOKEN. Set it in your environment. Eg.: os.environ['LITELLM_TOKEN']= <your_email>"
-                )
-        except Exception:
-            raise ValueError(
-                "[Non-Blocking Error] LiteLLMDebugger: Missing LITELLM_TOKEN. Set it in your environment. Eg.: os.environ['LITELLM_TOKEN']= <your_email>"
-            )
-
-    def input_log_event(
-        self,
-        model,
-        messages,
-        end_user,
-        litellm_call_id,
-        call_type,
-        print_verbose,
-        litellm_params,
-        optional_params,
-    ):
-        """
-        This integration is not implemented yet.
-        """
-        return
-
-    def post_call_log_event(
-        self, original_response, litellm_call_id, print_verbose, call_type, stream
-    ):
-        """
-        This integration is not implemented yet.
-        """
-        return
-
-    def log_event(
-        self,
-        end_user,
-        response_obj,
-        start_time,
-        end_time,
-        litellm_call_id,
-        print_verbose,
-        call_type,
-        stream=False,
-    ):
-        """
-        This integration is not implemented yet.
-        """
-        return
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 8a80f9b96..0a298d33b 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -58,7 +58,6 @@ from litellm.utils import (
     prompt_token_calculator,
 )
 
-from ..integrations.aispend import AISpendLogger
 from ..integrations.argilla import ArgillaLogger
 from ..integrations.arize_ai import ArizeLogger
 from ..integrations.athina import AthinaLogger
@@ -73,7 +72,6 @@ from ..integrations.lago import LagoLogger
 from ..integrations.langfuse.langfuse import LangFuseLogger
 from ..integrations.langfuse.langfuse_handler import LangFuseHandler
 from ..integrations.langsmith import LangsmithLogger
-from ..integrations.litedebugger import LiteDebugger
 from ..integrations.literal_ai import LiteralAILogger
 from ..integrations.logfire_logger import LogfireLevel, LogfireLogger
 from ..integrations.lunary import LunaryLogger
@@ -124,7 +122,6 @@ s3Logger = None
 genericAPILogger = None
 greenscaleLogger = None
 lunaryLogger = None
-aispendLogger = None
 supabaseClient = None
 callback_list: Optional[List[str]] = []
 user_logger_fn = None
@@ -2044,7 +2041,7 @@ def set_callbacks(callback_list, function_id=None):  # noqa: PLR0915
     """
     Globally sets the callback client
     """
-    global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, aispendLogger, supabaseClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger
+    global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, supabaseClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger
 
     try:
         for callback in callback_list:
@@ -2124,8 +2121,6 @@ def set_callbacks(callback_list, function_id=None):  # noqa: PLR0915
                 weightsBiasesLogger = WeightsBiasesLogger()
             elif callback == "logfire":
                 logfireLogger = LogfireLogger()
-            elif callback == "aispend":
-                aispendLogger = AISpendLogger()
             elif callback == "supabase":
                 print_verbose("instantiating supabase")
                 supabaseClient = Supabase()