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* fix test_moderations_bad_model * use async_post_call_failure_hook * basic logging errors in DB * show status on ui * show status on ui * ui show request / response side by side * stash fixes * working, track raw request * track error info in metadata * fix showing error / request / response logs * show traceback on error viewer * ui with traceback of error * fix async_post_call_failure_hook * fix(http_parsing_utils.py): orjson can throw errors on some emoji's in text, default to json.loads * test_get_error_information * fix code quality * rename proxy track cost callback test * _should_store_errors_in_spend_logs * feature flag error logs * Revert "_should_store_errors_in_spend_logs" This reverts commit |
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.. | ||
audio_utils | ||
llm_cost_calc | ||
llm_response_utils | ||
prompt_templates | ||
specialty_caches | ||
tokenizers | ||
asyncify.py | ||
core_helpers.py | ||
dd_tracing.py | ||
default_encoding.py | ||
dot_notation_indexing.py | ||
duration_parser.py | ||
exception_mapping_utils.py | ||
fallback_utils.py | ||
get_litellm_params.py | ||
get_llm_provider_logic.py | ||
get_model_cost_map.py | ||
get_supported_openai_params.py | ||
health_check_utils.py | ||
initialize_dynamic_callback_params.py | ||
json_validation_rule.py | ||
litellm_logging.py | ||
llm_request_utils.py | ||
logging_callback_manager.py | ||
logging_utils.py | ||
mock_functions.py | ||
README.md | ||
realtime_streaming.py | ||
redact_messages.py | ||
response_header_helpers.py | ||
rules.py | ||
safe_json_dumps.py | ||
sensitive_data_masker.py | ||
streaming_chunk_builder_utils.py | ||
streaming_handler.py | ||
thread_pool_executor.py | ||
token_counter.py |
Folder Contents
This folder contains general-purpose utilities that are used in multiple places in the codebase.
Core files:
streaming_handler.py
: The core streaming logic + streaming related helper utilscore_helpers.py
: code used intypes/
- e.g.map_finish_reason
.exception_mapping_utils.py
: utils for mapping exceptions to openai-compatible error types.default_encoding.py
: code for loading the default encoding (tiktoken)get_llm_provider_logic.py
: code for inferring the LLM provider from a given model name.duration_parser.py
: code for parsing durations - e.g. "1d", "1mo", "10s"