diff --git a/docs/my-website/docs/observability/athina_integration.md b/docs/my-website/docs/observability/athina_integration.md
index 62c8897518..cd1442f35a 100644
--- a/docs/my-website/docs/observability/athina_integration.md
+++ b/docs/my-website/docs/observability/athina_integration.md
@@ -2,6 +2,15 @@ import Image from '@theme/IdealImage';
 
 # Athina
 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 [Athina](https://athina.ai/) is an evaluation framework and production monitoring platform for your LLM-powered app. Athina is designed to enhance the performance and reliability of AI applications through real-time monitoring, granular analytics, and plug-and-play evaluations.
 
 <Image img={require('../../img/athina_dashboard.png')} />
diff --git a/docs/my-website/docs/observability/greenscale_integration.md b/docs/my-website/docs/observability/greenscale_integration.md
index 0dd673226e..49eadc6453 100644
--- a/docs/my-website/docs/observability/greenscale_integration.md
+++ b/docs/my-website/docs/observability/greenscale_integration.md
@@ -1,5 +1,14 @@
 # Greenscale - Track LLM Spend and Responsible Usage
 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 [Greenscale](https://greenscale.ai/) is a production monitoring platform for your LLM-powered app that provides you granular key insights into your GenAI spending and responsible usage. Greenscale only captures metadata to minimize the exposure risk of personally identifiable information (PII).
 
 ## Getting Started
diff --git a/docs/my-website/docs/observability/helicone_integration.md b/docs/my-website/docs/observability/helicone_integration.md
index de89ba8da8..f7fd330c30 100644
--- a/docs/my-website/docs/observability/helicone_integration.md
+++ b/docs/my-website/docs/observability/helicone_integration.md
@@ -1,4 +1,13 @@
 # Helicone Tutorial 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 [Helicone](https://helicone.ai/) is an open source observability platform that proxies your OpenAI traffic and provides you key insights into your spend, latency and usage.
 
 ## Use Helicone to log requests across all LLM Providers (OpenAI, Azure, Anthropic, Cohere, Replicate, PaLM)
diff --git a/docs/my-website/docs/observability/langfuse_integration.md b/docs/my-website/docs/observability/langfuse_integration.md
index 0fb411dd3f..dbd03620dc 100644
--- a/docs/my-website/docs/observability/langfuse_integration.md
+++ b/docs/my-website/docs/observability/langfuse_integration.md
@@ -1,6 +1,6 @@
 import Image from '@theme/IdealImage';
 
-# Langfuse - Logging LLM Input/Output
+# 🔥 Langfuse - Logging LLM Input/Output
 
 LangFuse is open Source Observability & Analytics for LLM Apps
 Detailed production traces and a granular view on quality, cost and latency
diff --git a/docs/my-website/docs/observability/langsmith_integration.md b/docs/my-website/docs/observability/langsmith_integration.md
index b115866d54..c038abd821 100644
--- a/docs/my-website/docs/observability/langsmith_integration.md
+++ b/docs/my-website/docs/observability/langsmith_integration.md
@@ -1,6 +1,16 @@
 import Image from '@theme/IdealImage';
 
 # Langsmith - Logging LLM Input/Output
+
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 An all-in-one developer platform for every step of the application lifecycle
 https://smith.langchain.com/
 
diff --git a/docs/my-website/docs/observability/logfire_integration.md b/docs/my-website/docs/observability/logfire_integration.md
index c1f425f425..a2d406f9c6 100644
--- a/docs/my-website/docs/observability/logfire_integration.md
+++ b/docs/my-website/docs/observability/logfire_integration.md
@@ -1,6 +1,6 @@
 import Image from '@theme/IdealImage';
 
-# Logfire - Logging LLM Input/Output
+# 🔥 Logfire - Logging LLM Input/Output
 
 Logfire is open Source Observability & Analytics for LLM Apps
 Detailed production traces and a granular view on quality, cost and latency
@@ -14,10 +14,14 @@ join our [discord](https://discord.gg/wuPM9dRgDw)
 
 ## Pre-Requisites
 
-Ensure you have run `pip install logfire` for this integration
+Ensure you have installed the following packages to use this integration
 
 ```shell
-pip install logfire litellm
+pip install litellm
+
+pip install opentelemetry-api==1.25.0
+pip install opentelemetry-sdk==1.25.0
+pip install opentelemetry-exporter-otlp==1.25.0
 ```
 
 ## Quick Start
@@ -25,8 +29,7 @@ pip install logfire litellm
 Get your Logfire token from [Logfire](https://logfire.pydantic.dev/)
 
 ```python
-litellm.success_callback = ["logfire"]
-litellm.failure_callback = ["logfire"] # logs errors to logfire
+litellm.callbacks = ["logfire"]
 ```
 
 ```python
diff --git a/docs/my-website/docs/observability/lunary_integration.md b/docs/my-website/docs/observability/lunary_integration.md
index 9b8e90df7b..56e74132f7 100644
--- a/docs/my-website/docs/observability/lunary_integration.md
+++ b/docs/my-website/docs/observability/lunary_integration.md
@@ -1,5 +1,13 @@
 # Lunary - Logging and tracing LLM input/output
 
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 [Lunary](https://lunary.ai/) is an open-source AI developer platform providing observability, prompt management, and evaluation tools for AI developers.
 
 <video controls width='900' >
diff --git a/docs/my-website/docs/observability/promptlayer_integration.md b/docs/my-website/docs/observability/promptlayer_integration.md
index ffc0a32ec0..7f62a31697 100644
--- a/docs/my-website/docs/observability/promptlayer_integration.md
+++ b/docs/my-website/docs/observability/promptlayer_integration.md
@@ -2,6 +2,15 @@ import Image from '@theme/IdealImage';
 
 # Promptlayer Tutorial
 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 Promptlayer is a platform for prompt engineers. Log OpenAI requests. Search usage history. Track performance. Visually manage prompt templates.
 
 <Image img={require('../../img/promptlayer.png')} />
diff --git a/docs/my-website/docs/observability/sentry.md b/docs/my-website/docs/observability/sentry.md
index 5877db6610..59e43b8f76 100644
--- a/docs/my-website/docs/observability/sentry.md
+++ b/docs/my-website/docs/observability/sentry.md
@@ -1,5 +1,14 @@
 import Image from '@theme/IdealImage';
 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 # Sentry - Log LLM Exceptions
 [Sentry](https://sentry.io/) provides error monitoring for production. LiteLLM can add breadcrumbs and send exceptions to Sentry with this integration
 
diff --git a/docs/my-website/docs/observability/supabase_integration.md b/docs/my-website/docs/observability/supabase_integration.md
index a0897a2730..fd3f1c3d5a 100644
--- a/docs/my-website/docs/observability/supabase_integration.md
+++ b/docs/my-website/docs/observability/supabase_integration.md
@@ -1,4 +1,12 @@
 # Supabase Tutorial 
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
 [Supabase](https://supabase.com/) is an open source Firebase alternative.
 Start your project with a Postgres database, Authentication, instant APIs, Edge Functions, Realtime subscriptions, Storage, and Vector embeddings.
 
diff --git a/docs/my-website/docs/observability/wandb_integration.md b/docs/my-website/docs/observability/wandb_integration.md
index dfa7b46dd3..37057f43db 100644
--- a/docs/my-website/docs/observability/wandb_integration.md
+++ b/docs/my-website/docs/observability/wandb_integration.md
@@ -1,6 +1,16 @@
 import Image from '@theme/IdealImage';
 
 # Weights & Biases - Logging LLM Input/Output
+
+
+:::tip
+
+This is community maintained, Please make an issue if you run into a bug
+https://github.com/BerriAI/litellm
+
+:::
+
+
 Weights & Biases helps AI developers build better models faster https://wandb.ai
 
 <Image img={require('../../img/wandb.png')} />
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index b31ff9a2d4..b718818713 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -172,10 +172,8 @@ const sidebars = {
     "proxy/custom_pricing",
     "routing",
     "scheduler",
-    "rules",
     "set_keys",
     "budget_manager",
-    "contributing",
     "secret",
     "completion/token_usage",
     "load_test",
@@ -183,11 +181,11 @@ const sidebars = {
       type: "category",
       label: "Logging & Observability",
       items: [
+        "observability/langfuse_integration",
+        "observability/logfire_integration",
         "debugging/local_debugging",
         "observability/raw_request_response",
-        "observability/callbacks",
         "observability/custom_callback",
-        "observability/langfuse_integration",
         "observability/sentry",
         "observability/lago",
         "observability/openmeter",
@@ -233,6 +231,8 @@ const sidebars = {
       label: "Extras",
       items: [
         "extras/contributing",
+        "contributing",
+        "rules",
         "proxy_server",
         {
           type: "category",
diff --git a/litellm/__init__.py b/litellm/__init__.py
index 6aee920c50..a99ed20aa2 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -37,7 +37,7 @@ input_callback: List[Union[str, Callable]] = []
 success_callback: List[Union[str, Callable]] = []
 failure_callback: List[Union[str, Callable]] = []
 service_callback: List[Union[str, Callable]] = []
-_custom_logger_compatible_callbacks_literal = Literal["lago", "openmeter"]
+_custom_logger_compatible_callbacks_literal = Literal["lago", "openmeter", "logfire"]
 callbacks: List[Union[Callable, _custom_logger_compatible_callbacks_literal]] = []
 _langfuse_default_tags: Optional[
     List[
diff --git a/litellm/_logging.py b/litellm/_logging.py
index a98d85e1c4..b0935066bb 100644
--- a/litellm/_logging.py
+++ b/litellm/_logging.py
@@ -23,8 +23,12 @@ class JsonFormatter(Formatter):
         super(JsonFormatter, self).__init__()
 
     def format(self, record):
-        json_record = {}
-        json_record["message"] = record.getMessage()
+        json_record = {
+            "message": record.getMessage(),
+            "level": record.levelname,
+            "timestamp": self.formatTime(record, self.datefmt),
+        }
+
         return json.dumps(json_record)
 
 
diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py
index e41272c243..e4daff1218 100644
--- a/litellm/integrations/opentelemetry.py
+++ b/litellm/integrations/opentelemetry.py
@@ -1,20 +1,21 @@
 import os
 from dataclasses import dataclass
 from datetime import datetime
-import litellm
-
-from litellm.integrations.custom_logger import CustomLogger
-from litellm._logging import verbose_logger
-from litellm.types.services import ServiceLoggerPayload
 from functools import wraps
-from typing import Union, Optional, TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Optional, Union
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.types.services import ServiceLoggerPayload
 
 if TYPE_CHECKING:
     from opentelemetry.trace import Span as _Span
-    from litellm.proxy.proxy_server import UserAPIKeyAuth as _UserAPIKeyAuth
+
     from litellm.proxy._types import (
         ManagementEndpointLoggingPayload as _ManagementEndpointLoggingPayload,
     )
+    from litellm.proxy.proxy_server import UserAPIKeyAuth as _UserAPIKeyAuth
 
     Span = _Span
     UserAPIKeyAuth = _UserAPIKeyAuth
@@ -107,8 +108,9 @@ class OpenTelemetry(CustomLogger):
         start_time: Optional[datetime] = None,
         end_time: Optional[datetime] = None,
     ):
-        from opentelemetry import trace
         from datetime import datetime
+
+        from opentelemetry import trace
         from opentelemetry.trace import Status, StatusCode
 
         _start_time_ns = start_time
@@ -145,8 +147,9 @@ class OpenTelemetry(CustomLogger):
         start_time: Optional[datetime] = None,
         end_time: Optional[datetime] = None,
     ):
-        from opentelemetry import trace
         from datetime import datetime
+
+        from opentelemetry import trace
         from opentelemetry.trace import Status, StatusCode
 
         _start_time_ns = start_time
@@ -179,8 +182,8 @@ class OpenTelemetry(CustomLogger):
     async def async_post_call_failure_hook(
         self, original_exception: Exception, user_api_key_dict: UserAPIKeyAuth
     ):
-        from opentelemetry.trace import Status, StatusCode
         from opentelemetry import trace
+        from opentelemetry.trace import Status, StatusCode
 
         parent_otel_span = user_api_key_dict.parent_otel_span
         if parent_otel_span is not None:
@@ -202,8 +205,8 @@ class OpenTelemetry(CustomLogger):
             parent_otel_span.end(end_time=self._to_ns(datetime.now()))
 
     def _handle_sucess(self, kwargs, response_obj, start_time, end_time):
-        from opentelemetry.trace import Status, StatusCode
         from opentelemetry import trace
+        from opentelemetry.trace import Status, StatusCode
 
         verbose_logger.debug(
             "OpenTelemetry Logger: Logging kwargs: %s, OTEL config settings=%s",
@@ -253,9 +256,10 @@ class OpenTelemetry(CustomLogger):
         span.end(end_time=self._to_ns(end_time))
 
     def set_tools_attributes(self, span: Span, tools):
-        from litellm.proxy._types import SpanAttributes
         import json
 
+        from litellm.proxy._types import SpanAttributes
+
         if not tools:
             return
 
@@ -320,7 +324,7 @@ class OpenTelemetry(CustomLogger):
             )
 
         span.set_attribute(
-            SpanAttributes.LLM_IS_STREAMING, optional_params.get("stream", False)
+            SpanAttributes.LLM_IS_STREAMING, str(optional_params.get("stream", False))
         )
 
         if optional_params.get("tools"):
@@ -439,7 +443,7 @@ class OpenTelemetry(CustomLogger):
         #############################################
         ########## LLM Response Attributes ##########
         #############################################
-        if _raw_response:
+        if _raw_response and isinstance(_raw_response, str):
             # cast sr -> dict
             import json
 
@@ -478,10 +482,10 @@ class OpenTelemetry(CustomLogger):
         return _parent_context
 
     def _get_span_context(self, kwargs):
+        from opentelemetry import trace
         from opentelemetry.trace.propagation.tracecontext import (
             TraceContextTextMapPropagator,
         )
-        from opentelemetry import trace
 
         litellm_params = kwargs.get("litellm_params", {}) or {}
         proxy_server_request = litellm_params.get("proxy_server_request", {}) or {}
@@ -505,17 +509,17 @@ class OpenTelemetry(CustomLogger):
             return TraceContextTextMapPropagator().extract(carrier=carrier), None
 
     def _get_span_processor(self):
-        from opentelemetry.sdk.trace.export import (
-            SpanExporter,
-            SimpleSpanProcessor,
-            BatchSpanProcessor,
-            ConsoleSpanExporter,
+        from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
+            OTLPSpanExporter as OTLPSpanExporterGRPC,
         )
         from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
             OTLPSpanExporter as OTLPSpanExporterHTTP,
         )
-        from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
-            OTLPSpanExporter as OTLPSpanExporterGRPC,
+        from opentelemetry.sdk.trace.export import (
+            BatchSpanProcessor,
+            ConsoleSpanExporter,
+            SimpleSpanProcessor,
+            SpanExporter,
         )
 
         verbose_logger.debug(
@@ -574,8 +578,9 @@ class OpenTelemetry(CustomLogger):
         logging_payload: ManagementEndpointLoggingPayload,
         parent_otel_span: Optional[Span] = None,
     ):
-        from opentelemetry import trace
         from datetime import datetime
+
+        from opentelemetry import trace
         from opentelemetry.trace import Status, StatusCode
 
         _start_time_ns = logging_payload.start_time
@@ -619,8 +624,9 @@ class OpenTelemetry(CustomLogger):
         logging_payload: ManagementEndpointLoggingPayload,
         parent_otel_span: Optional[Span] = None,
     ):
-        from opentelemetry import trace
         from datetime import datetime
+
+        from opentelemetry import trace
         from opentelemetry.trace import Status, StatusCode
 
         _start_time_ns = logging_payload.start_time
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index f54bf1d2ff..71cc8e6ab9 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -10,7 +10,7 @@ import sys
 import time
 import traceback
 import uuid
-from typing import Callable, Optional
+from typing import Any, Callable, Dict, List, Optional
 
 import litellm
 from litellm import (
@@ -72,6 +72,8 @@ from ..integrations.supabase import Supabase
 from ..integrations.traceloop import TraceloopLogger
 from ..integrations.weights_biases import WeightsBiasesLogger
 
+_in_memory_loggers: List[Any] = []
+
 
 class Logging:
     global supabaseClient, liteDebuggerClient, promptLayerLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, capture_exception, add_breadcrumb, lunaryLogger, logfireLogger, prometheusLogger, slack_app
@@ -1612,6 +1614,7 @@ class Logging:
                             level=LogfireLevel.ERROR.value,
                             print_verbose=print_verbose,
                         )
+
                 except Exception as e:
                     print_verbose(
                         f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging with integrations {str(e)}"
@@ -1786,6 +1789,37 @@ def _init_custom_logger_compatible_class(
     logging_integration: litellm._custom_logger_compatible_callbacks_literal,
 ) -> Callable:
     if logging_integration == "lago":
-        return LagoLogger()  # type: ignore
+        for callback in _in_memory_loggers:
+            if isinstance(callback, LagoLogger):
+                return callback  # type: ignore
+
+        lago_logger = LagoLogger()
+        _in_memory_loggers.append(lago_logger)
+        return lago_logger  # type: ignore
     elif logging_integration == "openmeter":
-        return OpenMeterLogger()  # type: ignore
+        for callback in _in_memory_loggers:
+            if isinstance(callback, OpenMeterLogger):
+                return callback  # type: ignore
+
+        _openmeter_logger = OpenMeterLogger()
+        _in_memory_loggers.append(_openmeter_logger)
+        return _openmeter_logger  # type: ignore
+    elif logging_integration == "logfire":
+        if "LOGFIRE_TOKEN" not in os.environ:
+            raise ValueError("LOGFIRE_TOKEN not found in environment variables")
+        from litellm.integrations.opentelemetry import (
+            OpenTelemetry,
+            OpenTelemetryConfig,
+        )
+
+        otel_config = OpenTelemetryConfig(
+            exporter="otlp_http",
+            endpoint="https://logfire-api.pydantic.dev/v1/traces",
+            headers=f"Authorization={os.getenv('LOGFIRE_TOKEN')}",
+        )
+        for callback in _in_memory_loggers:
+            if isinstance(callback, OpenTelemetry):
+                return callback  # type: ignore
+        _otel_logger = OpenTelemetry(config=otel_config)
+        _in_memory_loggers.append(_otel_logger)
+        return _otel_logger  # type: ignore
diff --git a/litellm/main.py b/litellm/main.py
index 1d6f479d4d..f46a9578bb 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -107,19 +107,17 @@ from .llms.databricks import DatabricksChatCompletion
 from .llms.huggingface_restapi import Huggingface
 from .llms.openai import OpenAIChatCompletion, OpenAITextCompletion
 from .llms.predibase import PredibaseChatCompletion
-from .llms.bedrock_httpx import BedrockLLM, BedrockConverseLLM
-from .llms.vertex_httpx import VertexLLM
-from .llms.triton import TritonChatCompletion
-from .llms.text_completion_codestral import CodestralTextCompletion
 from .llms.prompt_templates.factory import (
     custom_prompt,
     function_call_prompt,
     map_system_message_pt,
     prompt_factory,
 )
+from .llms.text_completion_codestral import CodestralTextCompletion
 from .llms.triton import TritonChatCompletion
 from .llms.vertex_httpx import VertexLLM
 from .types.llms.openai import HttpxBinaryResponseContent
+from .types.utils import ChatCompletionMessageToolCall
 
 encoding = tiktoken.get_encoding("cl100k_base")
 from litellm.utils import (
@@ -431,6 +429,7 @@ def mock_completion(
     messages: List,
     stream: Optional[bool] = False,
     mock_response: Union[str, Exception] = "This is a mock request",
+    mock_tool_calls: Optional[List] = None,
     logging=None,
     custom_llm_provider=None,
     **kwargs,
@@ -499,6 +498,12 @@ def mock_completion(
         model_response["created"] = int(time.time())
         model_response["model"] = model
 
+        if mock_tool_calls:
+            model_response["choices"][0]["message"]["tool_calls"] = [
+                ChatCompletionMessageToolCall(**tool_call)
+                for tool_call in mock_tool_calls
+            ]
+
         setattr(
             model_response,
             "usage",
@@ -612,6 +617,7 @@ def completion(
     args = locals()
     api_base = kwargs.get("api_base", None)
     mock_response = kwargs.get("mock_response", None)
+    mock_tool_calls = kwargs.get("mock_tool_calls", None)
     force_timeout = kwargs.get("force_timeout", 600)  ## deprecated
     logger_fn = kwargs.get("logger_fn", None)
     verbose = kwargs.get("verbose", False)
@@ -930,12 +936,13 @@ def completion(
             litellm_params=litellm_params,
             custom_llm_provider=custom_llm_provider,
         )
-        if mock_response:
+        if mock_response or mock_tool_calls:
             return mock_completion(
                 model,
                 messages,
                 stream=stream,
                 mock_response=mock_response,
+                mock_tool_calls=mock_tool_calls,
                 logging=logging,
                 acompletion=acompletion,
                 mock_delay=kwargs.get("mock_delay", None),
diff --git a/litellm/proxy/_logging.py b/litellm/proxy/_logging.py
index 655da7b294..a3eb35180f 100644
--- a/litellm/proxy/_logging.py
+++ b/litellm/proxy/_logging.py
@@ -1,7 +1,8 @@
 import json
 import logging
-from logging import Formatter
 import os
+from logging import Formatter
+
 from litellm import json_logs
 
 # Set default log level to INFO
@@ -14,8 +15,11 @@ class JsonFormatter(Formatter):
         super(JsonFormatter, self).__init__()
 
     def format(self, record):
-        json_record = {}
-        json_record["message"] = record.getMessage()
+        json_record = {
+            "message": record.getMessage(),
+            "level": record.levelname,
+            "timestamp": self.formatTime(record, self.datefmt),
+        }
         return json.dumps(json_record)
 
 
diff --git a/litellm/proxy/_super_secret_config.yaml b/litellm/proxy/_super_secret_config.yaml
index 9f1709b5fe..b5946afd6d 100644
--- a/litellm/proxy/_super_secret_config.yaml
+++ b/litellm/proxy/_super_secret_config.yaml
@@ -79,6 +79,7 @@ litellm_settings:
   success_callback: ["langfuse"]
   failure_callback: ["langfuse"]
   cache: true
+  json_logs: true
 
 general_settings:
   alerting: ["slack"]
diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py
index 9a28478391..8c8059d704 100644
--- a/litellm/proxy/_types.py
+++ b/litellm/proxy/_types.py
@@ -1,13 +1,17 @@
-from pydantic import BaseModel, Extra, Field, model_validator, Json, ConfigDict
-from dataclasses import fields
 import enum
-from typing import Optional, List, Union, Dict, Literal, Any, TypedDict, TYPE_CHECKING
+import json
+import os
+import sys
+import uuid
+from dataclasses import fields
 from datetime import datetime
-import uuid, json, sys, os
-from litellm.types.router import UpdateRouterConfig
-from litellm.types.utils import ProviderField
+from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, TypedDict, Union
+
+from pydantic import BaseModel, ConfigDict, Extra, Field, Json, model_validator
 from typing_extensions import Annotated
 
+from litellm.types.router import UpdateRouterConfig
+from litellm.types.utils import ProviderField
 
 if TYPE_CHECKING:
     from opentelemetry.trace import Span as _Span
@@ -283,12 +287,16 @@ class LiteLLMRoutes(enum.Enum):
         "/metrics",
     ]
 
-    internal_user_routes: List = [
-        "/key/generate",
-        "/key/update",
-        "/key/delete",
-        "/key/info",
-    ] + spend_tracking_routes
+    internal_user_routes: List = (
+        [
+            "/key/generate",
+            "/key/update",
+            "/key/delete",
+            "/key/info",
+        ]
+        + spend_tracking_routes
+        + sso_only_routes
+    )
 
 
 # class LiteLLMAllowedRoutes(LiteLLMBase):
diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py
index c79b0a8f95..be3d801e72 100644
--- a/litellm/proxy/auth/user_api_key_auth.py
+++ b/litellm/proxy/auth/user_api_key_auth.py
@@ -7,59 +7,56 @@ Returns a UserAPIKeyAuth object if the API key is valid
 
 """
 
+import asyncio
 import json
+import secrets
+import traceback
 from datetime import datetime, timedelta, timezone
 from typing import Optional
-import secrets
 from uuid import uuid4
 
 import fastapi
-from fastapi import Request
-from pydantic import BaseModel
-import litellm
-import traceback
-import asyncio
 from fastapi import (
-    FastAPI,
-    Request,
-    HTTPException,
-    status,
-    Path,
     Depends,
-    Header,
-    Response,
-    Form,
-    UploadFile,
+    FastAPI,
     File,
+    Form,
+    Header,
+    HTTPException,
+    Path,
+    Request,
+    Response,
+    UploadFile,
+    status,
 )
-from fastapi.responses import (
-    StreamingResponse,
-    FileResponse,
-    ORJSONResponse,
-    JSONResponse,
-)
-from fastapi.openapi.utils import get_openapi
-from fastapi.responses import RedirectResponse
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.staticfiles import StaticFiles
+from fastapi.openapi.utils import get_openapi
+from fastapi.responses import (
+    FileResponse,
+    JSONResponse,
+    ORJSONResponse,
+    RedirectResponse,
+    StreamingResponse,
+)
 from fastapi.security.api_key import APIKeyHeader
-from litellm.proxy._types import *
-from litellm._logging import verbose_logger, verbose_proxy_logger
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel
 
+import litellm
+from litellm._logging import verbose_logger, verbose_proxy_logger
+from litellm.proxy._types import *
 from litellm.proxy.auth.auth_checks import (
+    allowed_routes_check,
     common_checks,
+    get_actual_routes,
     get_end_user_object,
     get_org_object,
     get_team_object,
     get_user_object,
-    allowed_routes_check,
-    get_actual_routes,
     log_to_opentelemetry,
 )
-
-from litellm.proxy.utils import _to_ns
 from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
-
+from litellm.proxy.utils import _to_ns
 
 api_key_header = APIKeyHeader(
     name="Authorization", auto_error=False, description="Bearer token"
@@ -88,20 +85,20 @@ async def user_api_key_auth(
 ) -> UserAPIKeyAuth:
 
     from litellm.proxy.proxy_server import (
-        litellm_proxy_admin_name,
+        allowed_routes_check,
         common_checks,
-        master_key,
-        prisma_client,
-        llm_model_list,
-        user_custom_auth,
         custom_db_client,
         general_settings,
-        proxy_logging_obj,
-        open_telemetry_logger,
-        user_api_key_cache,
-        jwt_handler,
-        allowed_routes_check,
         get_actual_routes,
+        jwt_handler,
+        litellm_proxy_admin_name,
+        llm_model_list,
+        master_key,
+        open_telemetry_logger,
+        prisma_client,
+        proxy_logging_obj,
+        user_api_key_cache,
+        user_custom_auth,
     )
 
     try:
@@ -1004,7 +1001,7 @@ async def user_api_key_auth(
                 ):
 
                     pass
-                elif _user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY:
+                elif _user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY.value:
                     if route in LiteLLMRoutes.openai_routes.value:
                         raise HTTPException(
                             status_code=status.HTTP_403_FORBIDDEN,
@@ -1031,7 +1028,7 @@ async def user_api_key_auth(
                                 detail=f"user not allowed to access this route, role= {_user_role}. Trying to access: {route}",
                             )
                 elif (
-                    _user_role == LitellmUserRoles.INTERNAL_USER
+                    _user_role == LitellmUserRoles.INTERNAL_USER.value
                     and route in LiteLLMRoutes.internal_user_routes.value
                 ):
                     pass
@@ -1059,6 +1056,7 @@ async def user_api_key_auth(
             # this token is only used for managing the ui
             allowed_routes = [
                 "/sso",
+                "/sso/get/logout_url",
                 "/login",
                 "/key/generate",
                 "/key/update",
@@ -1144,8 +1142,8 @@ async def user_api_key_auth(
             raise Exception()
     except Exception as e:
         verbose_proxy_logger.error(
-            "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - {}".format(
-                str(e)
+            "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - {}\n{}".format(
+                str(e), traceback.format_exc()
             )
         )
 
@@ -1156,7 +1154,6 @@ async def user_api_key_auth(
                 user_api_key_dict=UserAPIKeyAuth(parent_otel_span=parent_otel_span),
             )
 
-        verbose_proxy_logger.debug(traceback.format_exc())
         if isinstance(e, litellm.BudgetExceededError):
             raise ProxyException(
                 message=e.message, type="auth_error", param=None, code=400
diff --git a/litellm/proxy/proxy_config.yaml b/litellm/proxy/proxy_config.yaml
index 27d49a33dd..d5190455f1 100644
--- a/litellm/proxy/proxy_config.yaml
+++ b/litellm/proxy/proxy_config.yaml
@@ -24,9 +24,9 @@ general_settings:
 
 litellm_settings:
   success_callback: ["prometheus"]
+  callbacks: ["otel"]
   failure_callback: ["prometheus"]
   store_audit_logs: true
-  turn_off_message_logging: true
   redact_messages_in_exceptions: True
   enforced_params:  
     - user
diff --git a/litellm/tests/test_completion.py b/litellm/tests/test_completion.py
index 3425d6ac13..a94577032a 100644
--- a/litellm/tests/test_completion.py
+++ b/litellm/tests/test_completion.py
@@ -12,6 +12,7 @@ import os
 sys.path.insert(
     0, os.path.abspath("../..")
 )  # Adds the parent directory to the system path
+
 import os
 from unittest.mock import MagicMock, patch
 
diff --git a/litellm/tests/test_file_types.py b/litellm/tests/test_file_types.py
new file mode 100644
index 0000000000..db83ba0e74
--- /dev/null
+++ b/litellm/tests/test_file_types.py
@@ -0,0 +1,54 @@
+from litellm.types.files import (
+    FILE_EXTENSIONS,
+    FILE_MIME_TYPES,
+    FileType,
+    get_file_extension_from_mime_type,
+    get_file_type_from_extension,
+    get_file_extension_for_file_type,
+    get_file_mime_type_for_file_type,
+    get_file_mime_type_from_extension,
+)
+import pytest
+
+
+class TestFileConsts:
+    def test_all_file_types_have_extensions(self):
+        for file_type in FileType:
+            assert file_type in FILE_EXTENSIONS.keys()
+
+    def test_all_file_types_have_mime_types(self):
+        for file_type in FileType:
+            assert file_type in FILE_MIME_TYPES.keys()
+
+    def test_get_file_extension_from_mime_type(self):
+        assert get_file_extension_from_mime_type("audio/aac") == "aac"
+        assert get_file_extension_from_mime_type("application/pdf") == "pdf"
+        with pytest.raises(ValueError):
+            get_file_extension_from_mime_type("application/unknown")
+
+    def test_get_file_type_from_extension(self):
+        assert get_file_type_from_extension("aac") == FileType.AAC
+        assert get_file_type_from_extension("pdf") == FileType.PDF
+        with pytest.raises(ValueError):
+            get_file_type_from_extension("unknown")
+
+    def test_get_file_extension_for_file_type(self):
+        assert get_file_extension_for_file_type(FileType.AAC) == "aac"
+        assert get_file_extension_for_file_type(FileType.PDF) == "pdf"
+
+    def test_get_file_mime_type_for_file_type(self):
+        assert get_file_mime_type_for_file_type(FileType.AAC) == "audio/aac"
+        assert get_file_mime_type_for_file_type(FileType.PDF) == "application/pdf"
+
+    def test_get_file_mime_type_from_extension(self):
+        assert get_file_mime_type_from_extension("aac") == "audio/aac"
+        assert get_file_mime_type_from_extension("pdf") == "application/pdf"
+
+    def test_uppercase_extensions(self):
+        # Test that uppercase extensions return the correct file type
+        assert get_file_type_from_extension("AAC") == FileType.AAC
+        assert get_file_type_from_extension("PDF") == FileType.PDF
+
+        # Test that uppercase extensions return the correct MIME type
+        assert get_file_mime_type_from_extension("AAC") == "audio/aac"
+        assert get_file_mime_type_from_extension("PDF") == "application/pdf"
diff --git a/litellm/tests/test_logfire.py b/litellm/tests/test_logfire.py
index e3078f5954..34bd75ccae 100644
--- a/litellm/tests/test_logfire.py
+++ b/litellm/tests/test_logfire.py
@@ -1,12 +1,16 @@
-import sys
-import os
+import asyncio
 import json
+import logging
+import os
+import sys
 import time
 
-import logfire
-import litellm
 import pytest
-from logfire.testing import TestExporter, SimpleSpanProcessor
+
+import litellm
+from litellm._logging import verbose_logger, verbose_proxy_logger
+
+verbose_logger.setLevel(logging.DEBUG)
 
 sys.path.insert(0, os.path.abspath("../.."))
 
@@ -17,19 +21,13 @@ sys.path.insert(0, os.path.abspath("../.."))
 # 4. Test logfire logging for completion while streaming is enabled
 
 
-@pytest.mark.skip(reason="Breaks on ci/cd")
+@pytest.mark.skip(reason="Breaks on ci/cd but works locally")
 @pytest.mark.parametrize("stream", [False, True])
 def test_completion_logfire_logging(stream):
-    litellm.success_callback = ["logfire"]
-    litellm.set_verbose = True
+    from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig
 
-    exporter = TestExporter()
-    logfire.configure(
-        send_to_logfire=False,
-        console=False,
-        processors=[SimpleSpanProcessor(exporter)],
-        collect_system_metrics=False,
-    )
+    litellm.callbacks = ["logfire"]
+    litellm.set_verbose = True
     messages = [{"role": "user", "content": "what llm are u"}]
     temperature = 0.3
     max_tokens = 10
@@ -47,41 +45,16 @@ def test_completion_logfire_logging(stream):
             print(chunk)
 
     time.sleep(5)
-    exported_spans = exporter.exported_spans_as_dict()
-
-    assert len(exported_spans) == 1
-    assert (
-        exported_spans[0]["attributes"]["logfire.msg"]
-        == "Chat Completion with 'gpt-3.5-turbo'"
-    )
-
-    request_data = json.loads(exported_spans[0]["attributes"]["request_data"])
-
-    assert request_data["model"] == "gpt-3.5-turbo"
-    assert request_data["messages"] == messages
-
-    assert "completion_tokens" in request_data["usage"]
-    assert "prompt_tokens" in request_data["usage"]
-    assert "total_tokens" in request_data["usage"]
-    assert request_data["response"]["choices"][0]["message"]["content"]
-    assert request_data["modelParameters"]["max_tokens"] == max_tokens
-    assert request_data["modelParameters"]["temperature"] == temperature
 
 
-@pytest.mark.skip(reason="Breaks on ci/cd")
+@pytest.mark.skip(reason="Breaks on ci/cd but works locally")
 @pytest.mark.asyncio
 @pytest.mark.parametrize("stream", [False, True])
 async def test_acompletion_logfire_logging(stream):
-    litellm.success_callback = ["logfire"]
-    litellm.set_verbose = True
+    from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig
 
-    exporter = TestExporter()
-    logfire.configure(
-        send_to_logfire=False,
-        console=False,
-        processors=[SimpleSpanProcessor(exporter)],
-        collect_system_metrics=False,
-    )
+    litellm.callbacks = ["logfire"]
+    litellm.set_verbose = True
     messages = [{"role": "user", "content": "what llm are u"}]
     temperature = 0.3
     max_tokens = 10
@@ -90,30 +63,11 @@ async def test_acompletion_logfire_logging(stream):
         messages=messages,
         max_tokens=max_tokens,
         temperature=temperature,
+        stream=stream,
     )
     print(response)
     if stream:
-        for chunk in response:
+        async for chunk in response:
             print(chunk)
 
-    time.sleep(5)
-    exported_spans = exporter.exported_spans_as_dict()
-    print("exported_spans", exported_spans)
-
-    assert len(exported_spans) == 1
-    assert (
-        exported_spans[0]["attributes"]["logfire.msg"]
-        == "Chat Completion with 'gpt-3.5-turbo'"
-    )
-
-    request_data = json.loads(exported_spans[0]["attributes"]["request_data"])
-
-    assert request_data["model"] == "gpt-3.5-turbo"
-    assert request_data["messages"] == messages
-
-    assert "completion_tokens" in request_data["usage"]
-    assert "prompt_tokens" in request_data["usage"]
-    assert "total_tokens" in request_data["usage"]
-    assert request_data["response"]["choices"][0]["message"]["content"]
-    assert request_data["modelParameters"]["max_tokens"] == max_tokens
-    assert request_data["modelParameters"]["temperature"] == temperature
+    await asyncio.sleep(5)
diff --git a/litellm/types/files.py b/litellm/types/files.py
index 2da08e76c4..577b9b55cc 100644
--- a/litellm/types/files.py
+++ b/litellm/types/files.py
@@ -151,23 +151,16 @@ Util Functions
 """
 
 
-def get_file_mime_type_from_extension(extension: str) -> str:
-    for file_type, extensions in FILE_EXTENSIONS.items():
-        if extension in extensions:
-            return FILE_MIME_TYPES[file_type]
-    raise ValueError(f"Unknown mime type for extension: {extension}")
-
-
 def get_file_extension_from_mime_type(mime_type: str) -> str:
     for file_type, mime in FILE_MIME_TYPES.items():
-        if mime == mime_type:
+        if mime.lower() == mime_type.lower():
             return FILE_EXTENSIONS[file_type][0]
     raise ValueError(f"Unknown extension for mime type: {mime_type}")
 
 
 def get_file_type_from_extension(extension: str) -> FileType:
     for file_type, extensions in FILE_EXTENSIONS.items():
-        if extension in extensions:
+        if extension.lower() in extensions:
             return file_type
 
     raise ValueError(f"Unknown file type for extension: {extension}")
@@ -181,6 +174,11 @@ def get_file_mime_type_for_file_type(file_type: FileType) -> str:
     return FILE_MIME_TYPES[file_type]
 
 
+def get_file_mime_type_from_extension(extension: str) -> str:
+    file_type = get_file_type_from_extension(extension)
+    return get_file_mime_type_for_file_type(file_type)
+
+
 """
 FileType Type Groupings (Videos, Images, etc)
 """
diff --git a/litellm/utils.py b/litellm/utils.py
index 79269a4b83..882185ba8d 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -340,6 +340,7 @@ def function_setup(
     try:
         global callback_list, add_breadcrumb, user_logger_fn, Logging
         function_id = kwargs["id"] if "id" in kwargs else None
+
         if len(litellm.callbacks) > 0:
             for callback in litellm.callbacks:
                 # check if callback is a string - e.g. "lago", "openmeter"