litellm-mirror/litellm/proxy/spend_tracking/spend_tracking_utils.py
Krish Dholakia 3beecfb0d4
LiteLLM Minor Fixes & Improvements (11/13/2024) (#6729)
* fix(utils.py): add logprobs support for together ai

Fixes

https://github.com/BerriAI/litellm/issues/6724

* feat(pass_through_endpoints/): add anthropic/ pass-through endpoint

adds new `anthropic/` pass-through endpoint + refactors docs

* feat(spend_management_endpoints.py): allow /global/spend/report to query team + customer id

enables seeing spend for a customer in a team

* Add integration with MLflow Tracing (#6147)

* Add MLflow logger

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* Streaming handling

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* lint

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* address comments and fix issues

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* address comments and fix issues

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* Move logger construction code

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* Add docs

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* async handlers

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* new picture

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

---------

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* fix(mlflow.py): fix ruff linting errors

* ci(config.yml): add mlflow to ci testing

* fix: fix test

* test: fix test

* Litellm key update fix (#6710)

* fix(caching): convert arg to equivalent kwargs in llm caching handler

prevent unexpected errors

* fix(caching_handler.py): don't pass args to caching

* fix(caching): remove all *args from caching.py

* fix(caching): consistent function signatures + abc method

* test(caching_unit_tests.py): add unit tests for llm caching

ensures coverage for common caching scenarios across different implementations

* refactor(litellm_logging.py): move to using cache key from hidden params instead of regenerating one

* fix(router.py): drop redis password requirement

* fix(proxy_server.py): fix faulty slack alerting check

* fix(langfuse.py): avoid copying functions/thread lock objects in metadata

fixes metadata copy error when parent otel span in metadata

* test: update test

* fix(key_management_endpoints.py): fix /key/update with metadata update

* fix(key_management_endpoints.py): fix key_prepare_update helper

* fix(key_management_endpoints.py): reset value to none if set in key update

* fix: update test

'

* Litellm dev 11 11 2024 (#6693)

* fix(__init__.py): add 'watsonx_text' as mapped llm api route

Fixes https://github.com/BerriAI/litellm/issues/6663

* fix(opentelemetry.py): fix passing parallel tool calls to otel

Fixes https://github.com/BerriAI/litellm/issues/6677

* refactor(test_opentelemetry_unit_tests.py): create a base set of unit tests for all logging integrations - test for parallel tool call handling

reduces bugs in repo

* fix(__init__.py): update provider-model mapping to include all known provider-model mappings

Fixes https://github.com/BerriAI/litellm/issues/6669

* feat(anthropic): support passing document in llm api call

* docs(anthropic.md): add pdf anthropic call to docs + expose new 'supports_pdf_input' function

* fix(factory.py): fix linting error

* add clear doc string for GCS bucket logging

* Add docs to export logs to Laminar (#6674)

* Add docs to export logs to Laminar

* minor fix: newline at end of file

* place laminar after http and grpc

* (Feat) Add langsmith key based logging (#6682)

* add langsmith_api_key to StandardCallbackDynamicParams

* create a file for langsmith types

* langsmith add key / team based logging

* add key based logging for langsmith

* fix langsmith key based logging

* fix linting langsmith

* remove NOQA violation

* add unit test coverage for all helpers in test langsmith

* test_langsmith_key_based_logging

* docs langsmith key based logging

* run langsmith tests in logging callback tests

* fix logging testing

* test_langsmith_key_based_logging

* test_add_callback_via_key_litellm_pre_call_utils_langsmith

* add debug statement langsmith key based logging

* test_langsmith_key_based_logging

* (fix) OpenAI's optional messages[].name  does not work with Mistral API  (#6701)

* use helper for _transform_messages mistral

* add test_message_with_name to base LLMChat test

* fix linting

* add xAI on Admin UI (#6680)

* (docs) add benchmarks on 1K RPS  (#6704)

* docs litellm proxy benchmarks

* docs GCS bucket

* doc fix - reduce clutter on logging doc title

* (feat) add cost tracking stable diffusion 3 on Bedrock  (#6676)

* add cost tracking for sd3

* test_image_generation_bedrock

* fix get model info for image cost

* add cost_calculator for stability 1 models

* add unit testing for bedrock image cost calc

* test_cost_calculator_with_no_optional_params

* add test_cost_calculator_basic

* correctly allow size Optional

* fix cost_calculator

* sd3 unit tests cost calc

* fix raise correct error 404 when /key/info is called on non-existent key  (#6653)

* fix raise correct error on /key/info

* add not_found_error error

* fix key not found in DB error

* use 1 helper for checking token hash

* fix error code on key info

* fix test key gen prisma

* test_generate_and_call_key_info

* test fix test_call_with_valid_model_using_all_models

* fix key info tests

* bump: version 1.52.4 → 1.52.5

* add defaults used for GCS logging

* LiteLLM Minor Fixes & Improvements (11/12/2024)  (#6705)

* fix(caching): convert arg to equivalent kwargs in llm caching handler

prevent unexpected errors

* fix(caching_handler.py): don't pass args to caching

* fix(caching): remove all *args from caching.py

* fix(caching): consistent function signatures + abc method

* test(caching_unit_tests.py): add unit tests for llm caching

ensures coverage for common caching scenarios across different implementations

* refactor(litellm_logging.py): move to using cache key from hidden params instead of regenerating one

* fix(router.py): drop redis password requirement

* fix(proxy_server.py): fix faulty slack alerting check

* fix(langfuse.py): avoid copying functions/thread lock objects in metadata

fixes metadata copy error when parent otel span in metadata

* test: update test

* bump: version 1.52.5 → 1.52.6

* (feat) helm hook to sync db schema  (#6715)

* v0 migration job

* fix job

* fix migrations job.yml

* handle standalone DB on helm hook

* fix argo cd annotations

* fix db migration helm hook

* fix migration job

* doc fix Using Http/2 with Hypercorn

* (fix proxy redis) Add redis sentinel support  (#6154)

* add sentinel_password support

* add doc for setting redis sentinel password

* fix redis sentinel - use sentinel password

* Fix: Update gpt-4o costs to that of gpt-4o-2024-08-06 (#6714)

Fixes #6713

* (fix) using Anthropic `response_format={"type": "json_object"}`  (#6721)

* add support for response_format=json anthropic

* add test_json_response_format to baseLLM ChatTest

* fix test_litellm_anthropic_prompt_caching_tools

* fix test_anthropic_function_call_with_no_schema

* test test_create_json_tool_call_for_response_format

* (feat) Add cost tracking for Azure Dall-e-3 Image Generation  + use base class to ensure basic image generation tests pass  (#6716)

* add BaseImageGenTest

* use 1 class for unit testing

* add debugging to BaseImageGenTest

* TestAzureOpenAIDalle3

* fix response_cost_calculator

* test_basic_image_generation

* fix img gen basic test

* fix _select_model_name_for_cost_calc

* fix test_aimage_generation_bedrock_with_optional_params

* fix undo changes cost tracking

* fix response_cost_calculator

* fix test_cost_azure_gpt_35

* fix remove dup test (#6718)

* (build) update db helm hook

* (build) helm db pre sync hook

* (build) helm db sync hook

* test: run test_team_logging firdst

---------

Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Dinmukhamed Mailibay <47117969+dinmukhamedm@users.noreply.github.com>
Co-authored-by: Kilian Lieret <kilian.lieret@posteo.de>

* test: update test

* test: skip anthropic overloaded error

* test: cleanup test

* test: update tests

* test: fix test

* test: handle gemini overloaded model error

* test: handle internal server error

* test: handle anthropic overloaded error

* test: handle claude instability

---------

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Yuki Watanabe <31463517+B-Step62@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Dinmukhamed Mailibay <47117969+dinmukhamedm@users.noreply.github.com>
Co-authored-by: Kilian Lieret <kilian.lieret@posteo.de>
2024-11-15 11:18:31 +05:30

243 lines
7.7 KiB
Python

import datetime
import json
import os
import secrets
import traceback
from datetime import datetime as dt
from typing import Optional
from pydantic import BaseModel
import litellm
from litellm._logging import verbose_proxy_logger
from litellm.proxy._types import SpendLogsMetadata, SpendLogsPayload
from litellm.proxy.utils import PrismaClient, hash_token
def _is_master_key(api_key: str, _master_key: Optional[str]) -> bool:
if _master_key is None:
return False
## string comparison
is_master_key = secrets.compare_digest(api_key, _master_key)
if is_master_key:
return True
## hash comparison
is_master_key = secrets.compare_digest(api_key, hash_token(_master_key))
if is_master_key:
return True
return False
def get_logging_payload(
kwargs, response_obj, start_time, end_time, end_user_id: Optional[str]
) -> SpendLogsPayload:
from pydantic import Json
from litellm.proxy._types import LiteLLM_SpendLogs
from litellm.proxy.proxy_server import general_settings, master_key
verbose_proxy_logger.debug(
f"SpendTable: get_logging_payload - kwargs: {kwargs}\n\n"
)
if kwargs is None:
kwargs = {}
if response_obj is None:
response_obj = {}
# standardize this function to be used across, s3, dynamoDB, langfuse logging
litellm_params = kwargs.get("litellm_params", {})
metadata = (
litellm_params.get("metadata", {}) or {}
) # if litellm_params['metadata'] == None
completion_start_time = kwargs.get("completion_start_time", end_time)
call_type = kwargs.get("call_type")
cache_hit = kwargs.get("cache_hit", False)
usage = response_obj.get("usage", None) or {}
if isinstance(usage, litellm.Usage):
usage = dict(usage)
id = response_obj.get("id", kwargs.get("litellm_call_id"))
api_key = metadata.get("user_api_key", "")
if api_key is not None and isinstance(api_key, str):
if api_key.startswith("sk-"):
# hash the api_key
api_key = hash_token(api_key)
if (
_is_master_key(api_key=api_key, _master_key=master_key)
and general_settings.get("disable_adding_master_key_hash_to_db") is True
):
api_key = "litellm_proxy_master_key" # use a known alias, if the user disabled storing master key in db
_model_id = metadata.get("model_info", {}).get("id", "")
_model_group = metadata.get("model_group", "")
request_tags = (
json.dumps(metadata.get("tags", []))
if isinstance(metadata.get("tags", []), list)
else "[]"
)
# clean up litellm metadata
clean_metadata = SpendLogsMetadata(
user_api_key=None,
user_api_key_alias=None,
user_api_key_team_id=None,
user_api_key_user_id=None,
user_api_key_team_alias=None,
spend_logs_metadata=None,
requester_ip_address=None,
additional_usage_values=None,
)
if isinstance(metadata, dict):
verbose_proxy_logger.debug(
"getting payload for SpendLogs, available keys in metadata: "
+ str(list(metadata.keys()))
)
# Filter the metadata dictionary to include only the specified keys
clean_metadata = SpendLogsMetadata(
**{ # type: ignore
key: metadata[key]
for key in SpendLogsMetadata.__annotations__.keys()
if key in metadata
}
)
special_usage_fields = ["completion_tokens", "prompt_tokens", "total_tokens"]
additional_usage_values = {}
for k, v in usage.items():
if k not in special_usage_fields:
if isinstance(v, BaseModel):
v = v.model_dump()
additional_usage_values.update({k: v})
clean_metadata["additional_usage_values"] = additional_usage_values
if litellm.cache is not None:
cache_key = litellm.cache.get_cache_key(**kwargs)
else:
cache_key = "Cache OFF"
if cache_hit is True:
import time
id = f"{id}_cache_hit{time.time()}" # SpendLogs does not allow duplicate request_id
try:
payload: SpendLogsPayload = SpendLogsPayload(
request_id=str(id),
call_type=call_type or "",
api_key=str(api_key),
cache_hit=str(cache_hit),
startTime=start_time,
endTime=end_time,
completionStartTime=completion_start_time,
model=kwargs.get("model", "") or "",
user=kwargs.get("litellm_params", {})
.get("metadata", {})
.get("user_api_key_user_id", "")
or "",
team_id=kwargs.get("litellm_params", {})
.get("metadata", {})
.get("user_api_key_team_id", "")
or "",
metadata=json.dumps(clean_metadata),
cache_key=cache_key,
spend=kwargs.get("response_cost", 0),
total_tokens=usage.get("total_tokens", 0),
prompt_tokens=usage.get("prompt_tokens", 0),
completion_tokens=usage.get("completion_tokens", 0),
request_tags=request_tags,
end_user=end_user_id or "",
api_base=litellm_params.get("api_base", ""),
model_group=_model_group,
model_id=_model_id,
requester_ip_address=clean_metadata.get("requester_ip_address", None),
)
verbose_proxy_logger.debug(
"SpendTable: created payload - payload: %s\n\n", payload
)
return payload
except Exception as e:
verbose_proxy_logger.exception(
"Error creating spendlogs object - {}".format(str(e))
)
raise e
async def get_spend_by_team_and_customer(
start_date: dt,
end_date: dt,
team_id: str,
customer_id: str,
prisma_client: PrismaClient,
):
sql_query = """
WITH SpendByModelApiKey AS (
SELECT
date_trunc('day', sl."startTime") AS group_by_day,
COALESCE(tt.team_alias, 'Unassigned Team') AS team_name,
sl.end_user AS customer,
sl.model,
sl.api_key,
SUM(sl.spend) AS model_api_spend,
SUM(sl.total_tokens) AS model_api_tokens
FROM
"LiteLLM_SpendLogs" sl
LEFT JOIN
"LiteLLM_TeamTable" tt
ON
sl.team_id = tt.team_id
WHERE
sl."startTime" BETWEEN $1::date AND $2::date
AND sl.team_id = $3
AND sl.end_user = $4
GROUP BY
date_trunc('day', sl."startTime"),
tt.team_alias,
sl.end_user,
sl.model,
sl.api_key
)
SELECT
group_by_day,
jsonb_agg(jsonb_build_object(
'team_name', team_name,
'customer', customer,
'total_spend', total_spend,
'metadata', metadata
)) AS teams_customers
FROM (
SELECT
group_by_day,
team_name,
customer,
SUM(model_api_spend) AS total_spend,
jsonb_agg(jsonb_build_object(
'model', model,
'api_key', api_key,
'spend', model_api_spend,
'total_tokens', model_api_tokens
)) AS metadata
FROM
SpendByModelApiKey
GROUP BY
group_by_day,
team_name,
customer
) AS aggregated
GROUP BY
group_by_day
ORDER BY
group_by_day;
"""
db_response = await prisma_client.db.query_raw(
sql_query, start_date, end_date, team_id, customer_id
)
if db_response is None:
return []
return db_response