mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-08 03:08:45 +00:00
perf: address GIL contention and hot-path bottlenecks from profiling data
Based on py-spy GIL profiling (38,800 samples, 2000 concurrent users) and
pyinstrument per-request timing, this commit addresses the top performance
bottlenecks identified:
1. _sanitize_request_body_for_spend_logs_payload (2.9% GIL):
- Remove redundant inner import (constants already imported at top-level)
- Remove dead-code branch (len check after already confirmed len > max)
- Pre-compute truncation ratios outside inner function
- Reorder isinstance checks: str first (most common leaf type)
2. Pydantic repr in logging (2.3% GIL):
- Guard print_deployment calls behind isEnabledFor(logging.INFO)
- Replace copy.deepcopy with shallow dict() copy in print_deployment
- Use %-style lazy formatting instead of f-strings for logger calls
- Remove kwargs from prometheus debug log message
3. Prometheus label_factory overhead (1.5% + 0.7% GIL):
- Cache model_dump() on UserAPIKeyLabelValues via get_label_dict()
- Convert supported_enum_labels to frozenset for O(1) membership tests
- Called 37 times per success event; caching avoids 36 redundant dumps
4. pre_call_utils header lookup (1.9% GIL):
- Replace dict comprehension over all headers with early-exit loop
- Only lowercase and compare the two target header names
5. safe_json_dumps (0.7% GIL):
- Replace stdlib json.dumps with orjson.dumps for final serialization
6. Hot-path debug logging:
- Convert f-string debug logs to %-style in litellm_logging.py
- Simplify prometheus print_verbose call
7. Cost calculator annotation checks:
- Optimize response_includes_annotation_type to handle both dict
and object annotation types without repeated __getattr__ calls
Estimated GIL time reduction: ~11-12% under concurrency.
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
This commit is contained in:
parent
7f4cbf4893
commit
a7b7a31b26
9 changed files with 100 additions and 91 deletions
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@ -887,7 +887,7 @@ class PrometheusLogger(CustomLogger):
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from litellm.types.utils import StandardLoggingPayload
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verbose_logger.debug(
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f"prometheus Logging - Enters success logging function for kwargs {kwargs}"
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"prometheus Logging - Enters success logging function"
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)
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# unpack kwargs
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@ -944,7 +944,8 @@ class PrometheusLogger(CustomLogger):
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_tags = []
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print_verbose(
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f"inside track_prometheus_metrics, model {model}, response_cost {response_cost}, tokens_used {tokens_used}, end_user_id {end_user_id}, user_api_key {user_api_key}"
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"inside track_prometheus_metrics, model %s, response_cost %s, tokens_used %s"
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% (model, response_cost, tokens_used)
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)
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enum_values = UserAPIKeyLabelValues(
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@ -3056,15 +3057,13 @@ def prometheus_label_factory(
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Ensures end_user param is not sent to prometheus if it is not supported.
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"""
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# Extract dictionary from Pydantic object
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enum_dict = enum_values.model_dump()
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enum_dict = enum_values.get_label_dict()
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# Filter supported labels and sanitize values to prevent breaking
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# the Prometheus text format (e.g. U+2028 Line Separator in label values)
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supported_set = frozenset(supported_enum_labels) if not isinstance(supported_enum_labels, (set, frozenset)) else supported_enum_labels
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filtered_labels = {
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label: _sanitize_prometheus_label_value(value)
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for label, value in enum_dict.items()
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if label in supported_enum_labels
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if label in supported_set
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}
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if UserAPIKeyLabelNames.END_USER.value in filtered_labels:
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@ -3079,14 +3078,14 @@ def prometheus_label_factory(
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for key, value in enum_values.custom_metadata_labels.items():
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# check sanitized key
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sanitized_key = _sanitize_prometheus_label_name(key)
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if sanitized_key in supported_enum_labels:
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if sanitized_key in supported_set:
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filtered_labels[sanitized_key] = _sanitize_prometheus_label_value(value)
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# Add custom tags if configured
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if enum_values.tags is not None:
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custom_tag_labels = get_custom_labels_from_tags(enum_values.tags)
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for key, value in custom_tag_labels.items():
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if key in supported_enum_labels:
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if key in supported_set:
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filtered_labels[key] = _sanitize_prometheus_label_value(value)
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for label in supported_enum_labels:
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@ -1476,7 +1476,7 @@ class Logging(LiteLLMLoggingBaseClass):
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**response_cost_calculator_kwargs
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)
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verbose_logger.debug(f"response_cost: {response_cost}")
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verbose_logger.debug("response_cost: %s", response_cost)
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return response_cost
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except Exception as e: # error calculating cost
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debug_info = StandardLoggingModelCostFailureDebugInformation(
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@ -387,11 +387,12 @@ class StandardBuiltInToolCostTracking:
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message: Optional[Message] = getattr(choice, "message", None)
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if message is None:
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continue
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if annotations := getattr(message, "annotations", None):
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if len(annotations) > 0:
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for annotation in annotations:
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if annotation.get("type", None) == annotation_type:
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return True
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annotations = getattr(message, "annotations", None)
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if annotations:
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for annotation in annotations:
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_type = annotation.get("type") if isinstance(annotation, dict) else getattr(annotation, "type", None)
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if _type == annotation_type:
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return True
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return False
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@staticmethod
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@ -1,6 +1,6 @@
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import json
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from typing import Any, Union
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import orjson
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from pydantic import BaseModel
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from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
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@ -13,13 +13,10 @@ def safe_dumps(data: Any, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH) -> str:
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"""
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def _serialize(obj: Any, seen: set, depth: int) -> Any:
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# Check for maximum depth.
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if depth > max_depth:
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return "MaxDepthExceeded"
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# Base-case: if it is a primitive, simply return it.
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if isinstance(obj, (str, int, float, bool, type(None))):
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return obj
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# Check for circular reference.
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if id(obj) in seen:
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return "CircularReference Detected"
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seen.add(id(obj))
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@ -27,7 +24,7 @@ def safe_dumps(data: Any, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH) -> str:
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if isinstance(obj, dict):
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result = {}
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for k, v in obj.items():
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if isinstance(k, (str)):
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if isinstance(k, str):
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result[k] = _serialize(v, seen, depth + 1)
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seen.remove(id(obj))
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return result
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@ -49,11 +46,10 @@ def safe_dumps(data: Any, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH) -> str:
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seen.remove(id(obj))
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return result
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else:
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# Fall back to string conversion for non-serializable objects.
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try:
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return str(obj)
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except Exception:
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return "Unserializable Object"
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safe_data = _serialize(data, set(), 0)
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return json.dumps(safe_data, default=str)
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return orjson.dumps(safe_data, default=str).decode()
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@ -102,10 +102,15 @@ def get_chain_id_from_headers(headers: Optional[Dict[str, str]]) -> Optional[str
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"""
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if not headers:
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return None
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normalized = {k.lower(): v for k, v in headers.items() if isinstance(k, str)}
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return normalized.get("x-litellm-trace-id") or normalized.get(
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"x-litellm-session-id"
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)
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session_id = None
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for k, v in headers.items():
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if isinstance(k, str):
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k_lower = k.lower()
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if k_lower == "x-litellm-trace-id":
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return v
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elif session_id is None and k_lower == "x-litellm-session-id":
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session_id = v
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return session_id
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def safe_add_api_version_from_query_params(data: dict, request: Request):
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@ -632,61 +632,37 @@ def _sanitize_request_body_for_spend_logs_payload(
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Recursively sanitize request body to prevent logging large base64 strings or other large values.
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Truncates strings longer than MAX_STRING_LENGTH_PROMPT_IN_DB characters and handles nested dictionaries.
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"""
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from litellm.constants import (
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LITELLM_TRUNCATED_PAYLOAD_FIELD,
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LITELLM_TRUNCATION_DB_SAFEGUARD_NOTE,
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)
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if visited is None:
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visited = set()
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if max_string_length_prompt_in_db is None:
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max_string_length_prompt_in_db = _get_max_string_length_prompt_in_db()
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# Get the object's memory address to track visited objects
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obj_id = id(request_body)
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if obj_id in visited:
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return {}
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visited.add(obj_id)
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_max_len = max_string_length_prompt_in_db
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_start_chars = int(_max_len * 0.35)
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_end_chars = min(int(_max_len * 0.65), _max_len - _start_chars)
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def _sanitize_value(value: Any) -> Any:
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if isinstance(value, dict):
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if isinstance(value, str):
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if len(value) > _max_len:
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skipped_chars = len(value) - _start_chars - _end_chars
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return (
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f"{value[:_start_chars]}"
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f"... ({LITELLM_TRUNCATED_PAYLOAD_FIELD} skipped {skipped_chars} chars. "
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f"{LITELLM_TRUNCATION_DB_SAFEGUARD_NOTE}) ..."
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f"{value[-_end_chars:]}"
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)
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return value
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elif isinstance(value, dict):
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return _sanitize_request_body_for_spend_logs_payload(
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value, visited, max_string_length_prompt_in_db
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value, visited, _max_len
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)
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elif isinstance(value, list):
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return [_sanitize_value(item) for item in value]
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elif isinstance(value, str):
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if len(value) > max_string_length_prompt_in_db:
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# Keep 35% from beginning and 65% from end (end is usually more important)
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# This split ensures we keep more context from the end of conversations
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start_ratio = 0.35
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end_ratio = 0.65
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# Calculate character distribution
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start_chars = int(max_string_length_prompt_in_db * start_ratio)
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end_chars = int(max_string_length_prompt_in_db * end_ratio)
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# Ensure we don't exceed the total limit
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total_keep = start_chars + end_chars
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if total_keep > max_string_length_prompt_in_db:
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end_chars = max_string_length_prompt_in_db - start_chars
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# If the string length is less than what we want to keep, just truncate normally
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if len(value) <= max_string_length_prompt_in_db:
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return value
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# Calculate how many characters are being skipped
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skipped_chars = len(value) - total_keep
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# Build the truncated string: beginning + truncation marker + end
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truncated_value = (
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f"{value[:start_chars]}"
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f"... ({LITELLM_TRUNCATED_PAYLOAD_FIELD} skipped {skipped_chars} chars. "
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f"{LITELLM_TRUNCATION_DB_SAFEGUARD_NOTE}) ..."
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f"{value[-end_chars:]}"
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)
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return truncated_value
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return value
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return value
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return {k: _sanitize_value(v) for k, v in request_body.items()}
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@ -1319,19 +1319,24 @@ class Router:
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Only returns 2 characters of the api key and masks the rest with * (10 *).
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"""
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try:
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_deployment_copy = copy.deepcopy(deployment)
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litellm_params: dict = _deployment_copy["litellm_params"]
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litellm_params: dict = deployment.get("litellm_params", {})
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if litellm.redact_user_api_key_info:
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masker = SensitiveDataMasker(visible_prefix=2, visible_suffix=0)
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_deployment_copy["litellm_params"] = masker.mask_dict(litellm_params)
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elif "api_key" in litellm_params:
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litellm_params["api_key"] = litellm_params["api_key"][:2] + "*" * 10
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return _deployment_copy
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masked_params = masker.mask_dict(dict(litellm_params))
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else:
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masked_params = dict(litellm_params)
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if "api_key" in masked_params:
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api_key = masked_params["api_key"]
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masked_params["api_key"] = (
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api_key[:2] + "*" * 10 if api_key else api_key
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)
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return {
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"model_name": deployment.get("model_name"),
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"litellm_params": masked_params,
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}
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except Exception as e:
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verbose_router_logger.debug(
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f"Error occurred while printing deployment - {str(e)}"
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"Error occurred while printing deployment - %s", str(e)
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)
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raise e
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@ -8925,9 +8930,13 @@ class Router:
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parent_otel_span=parent_otel_span,
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)
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raise exception
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verbose_router_logger.info(
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f"get_available_deployment for model: {model}, Selected deployment: {self.print_deployment(deployment)} for model: {model}"
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)
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if verbose_router_logger.isEnabledFor(logging.INFO):
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verbose_router_logger.info(
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"get_available_deployment for model: %s, Selected deployment: %s for model: %s",
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model,
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self.print_deployment(deployment),
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model,
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)
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end_time = time.time()
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_duration = end_time - start_time
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@ -9077,9 +9086,12 @@ class Router:
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)
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raise exception
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verbose_router_logger.info(
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f"async_get_available_deployment_for_pass_through model: {model}, selected deployment: {self.print_deployment(deployment)}"
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)
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if verbose_router_logger.isEnabledFor(logging.INFO):
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verbose_router_logger.info(
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"async_get_available_deployment_for_pass_through model: %s, selected deployment: %s",
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model,
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self.print_deployment(deployment),
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)
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end_time = time.perf_counter()
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_duration = end_time - start_time
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@ -9268,9 +9280,13 @@ class Router:
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enable_pre_call_checks=self.enable_pre_call_checks,
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cooldown_list=_cooldown_list,
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)
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verbose_router_logger.info(
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f"get_available_deployment for model: {model}, Selected deployment: {self.print_deployment(deployment)} for model: {model}"
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)
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if verbose_router_logger.isEnabledFor(logging.INFO):
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verbose_router_logger.info(
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"get_available_deployment for model: %s, Selected deployment: %s for model: %s",
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model,
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self.print_deployment(deployment),
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model,
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)
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return deployment
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def get_available_deployment_for_pass_through(
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@ -9431,9 +9447,12 @@ class Router:
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cooldown_list=_cooldown_list,
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)
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verbose_router_logger.info(
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f"get_available_deployment_for_pass_through model: {model}, selected deployment: {self.print_deployment(deployment)}"
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)
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if verbose_router_logger.isEnabledFor(logging.INFO):
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verbose_router_logger.info(
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"get_available_deployment_for_pass_through model: %s, selected deployment: %s",
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model,
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self.print_deployment(deployment),
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)
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return deployment
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def _filter_cooldown_deployments(
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@ -5,6 +5,7 @@ If weights are provided, it will return a deployment based on the weights.
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"""
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import logging
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import random
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from typing import TYPE_CHECKING, Any, Dict, List, Union
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@ -52,9 +53,13 @@ def simple_shuffle(
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selected_index = random.choices(range(len(weights)), weights=weights)[0]
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verbose_router_logger.debug(f"\n selected index, {selected_index}")
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deployment = healthy_deployments[selected_index]
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verbose_router_logger.info(
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f"get_available_deployment for model: {model}, Selected deployment: {llm_router_instance.print_deployment(deployment) or deployment[0]} for model: {model}"
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)
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if verbose_router_logger.isEnabledFor(logging.INFO):
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verbose_router_logger.info(
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"get_available_deployment for model: %s, Selected deployment: %s for model: %s",
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model,
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llm_router_instance.print_deployment(deployment) or deployment[0],
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model,
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)
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return deployment or deployment[0]
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@ -3,7 +3,7 @@ from dataclasses import dataclass
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from enum import Enum
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from typing import Any, Dict, List, Literal, Optional, Tuple
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from pydantic import BaseModel, Field, field_validator
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from pydantic import BaseModel, Field, PrivateAttr, field_validator
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from typing_extensions import Annotated
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import litellm
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@ -722,6 +722,8 @@ class UserAPIKeyLabelValues(BaseModel):
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Optional[str], Field(..., alias=UserAPIKeyLabelNames.STREAM.value)
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] = None
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_cached_dump: Optional[Dict[str, Any]] = PrivateAttr(default=None)
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@field_validator("stream", mode="before")
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@classmethod
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def coerce_stream_to_str(cls, v: Any) -> Optional[str]:
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@ -729,6 +731,12 @@ class UserAPIKeyLabelValues(BaseModel):
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return None
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return str(v)
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def get_label_dict(self) -> Dict[str, Any]:
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"""Return cached model_dump() dict to avoid re-serializing on every prometheus_label_factory call."""
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if self._cached_dump is None:
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self._cached_dump = self.model_dump()
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return self._cached_dump
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class PrometheusMetricsConfig(BaseModel):
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"""Configuration for filtering Prometheus metrics"""
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|
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