(feat) Allow enabling logging message / response for specific virtual keys (#7071)

* redact_message_input_output_from_logging

* initialize_standard_callback_dynamic_params

* allow dynamically opting out of redaction

* test_redact_msgs_from_logs_with_dynamic_params

* fix AddTeamCallback

* _get_turn_off_message_logging_from_dynamic_params

* test_global_redaction_with_dynamic_params

* test_dynamic_turn_off_message_logging

* docs Disable/Enable Message redaction

* fix doe qual check

* _get_turn_off_message_logging_from_dynamic_params

tests/local_testing/test_utils.py

@@ -6,6 +6,8 @@ from unittest import mock
 
 from dotenv import load_dotenv
 
+from litellm.types.utils import StandardCallbackDynamicParams
+
 load_dotenv()
 import os
 
@@ -545,6 +547,92 @@ def test_redact_msgs_from_logs():
     print("Test passed")
 
 
+def test_redact_msgs_from_logs_with_dynamic_params():
+    """
+    Tests redaction behavior based on standard_callback_dynamic_params setting:
+    In all tests litellm.turn_off_message_logging is True
+
+
+    1. When standard_callback_dynamic_params.turn_off_message_logging is False (or not set): No redaction should occur. User has opted out of redaction.
+    2. When standard_callback_dynamic_params.turn_off_message_logging is True: Redaction should occur. User has opted in to redaction.
+    3. standard_callback_dynamic_params.turn_off_message_logging not set, litellm.turn_off_message_logging is True: Redaction should occur.
+    """
+    from litellm.litellm_core_utils.litellm_logging import Logging
+    from litellm.litellm_core_utils.redact_messages import (
+        redact_message_input_output_from_logging,
+    )
+
+    litellm.turn_off_message_logging = True
+    test_content = "I'm LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational manner."
+    response_obj = litellm.ModelResponse(
+        choices=[
+            {
+                "finish_reason": "stop",
+                "index": 0,
+                "message": {
+                    "content": test_content,
+                    "role": "assistant",
+                },
+            }
+        ]
+    )
+
+    litellm_logging_obj = Logging(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=False,
+        call_type="acompletion",
+        litellm_call_id="1234",
+        start_time=datetime.now(),
+        function_id="1234",
+    )
+
+    # Test Case 1: standard_callback_dynamic_params = False (or not set)
+    standard_callback_dynamic_params = StandardCallbackDynamicParams(
+        turn_off_message_logging=False
+    )
+    litellm_logging_obj.model_call_details["standard_callback_dynamic_params"] = (
+        standard_callback_dynamic_params
+    )
+    _redacted_response_obj = redact_message_input_output_from_logging(
+        result=response_obj,
+        model_call_details=litellm_logging_obj.model_call_details,
+    )
+    # Assert no redaction occurred
+    assert _redacted_response_obj.choices[0].message.content == test_content
+
+    # Test Case 2: standard_callback_dynamic_params = True
+    standard_callback_dynamic_params = StandardCallbackDynamicParams(
+        turn_off_message_logging=True
+    )
+    litellm_logging_obj.model_call_details["standard_callback_dynamic_params"] = (
+        standard_callback_dynamic_params
+    )
+    _redacted_response_obj = redact_message_input_output_from_logging(
+        result=response_obj,
+        model_call_details=litellm_logging_obj.model_call_details,
+    )
+    # Assert redaction occurred
+    assert _redacted_response_obj.choices[0].message.content == "redacted-by-litellm"
+
+    # Test Case 3: standard_callback_dynamic_params does not override litellm.turn_off_message_logging
+    # since litellm.turn_off_message_logging is True redaction should occur
+    standard_callback_dynamic_params = StandardCallbackDynamicParams()
+    litellm_logging_obj.model_call_details["standard_callback_dynamic_params"] = (
+        standard_callback_dynamic_params
+    )
+    _redacted_response_obj = redact_message_input_output_from_logging(
+        result=response_obj,
+        model_call_details=litellm_logging_obj.model_call_details,
+    )
+    # Assert no redaction occurred
+    assert _redacted_response_obj.choices[0].message.content == "redacted-by-litellm"
+
+    # Reset settings
+    litellm.turn_off_message_logging = False
+    print("Test passed")
+
+
 @pytest.mark.parametrize(
     "duration, unit",
     [("7s", "s"), ("7m", "m"), ("7h", "h"), ("7d", "d"), ("7mo", "mo")],