litellm/tests/logging_callback_tests/test_datadog_llm_obs.py
Krish Dholakia 5c55270740
LiteLLM Minor Fixes & Improvements (11/04/2024) (#6572)
* feat: initial commit for watsonx chat endpoint support

Closes https://github.com/BerriAI/litellm/issues/6562

* feat(watsonx/chat/handler.py): support tool calling for watsonx

Closes https://github.com/BerriAI/litellm/issues/6562

* fix(streaming_utils.py): return empty chunk instead of failing if streaming value is invalid dict

ensures streaming works for ibm watsonx

* fix(openai_like/chat/handler.py): ensure asynchttphandler is passed correctly for openai like calls

* fix: ensure exception mapping works well for watsonx calls

* fix(openai_like/chat/handler.py): handle async streaming correctly

* feat(main.py): Make it clear when a user is passing an invalid message

add validation for user content message

 Closes https://github.com/BerriAI/litellm/issues/6565

* fix: cleanup

* fix(utils.py): loosen validation check, to just make sure content types are valid

make litellm robust to future content updates

* fix: fix linting erro

* fix: fix linting errors

* fix(utils.py): make validation check more flexible

* test: handle langfuse list index out of range error

* Litellm dev 11 02 2024 (#6561)

* fix(dual_cache.py): update in-memory check for redis batch get cache

Fixes latency delay for async_batch_redis_cache

* fix(service_logger.py): fix race condition causing otel service logging to be overwritten if service_callbacks set

* feat(user_api_key_auth.py): add parent otel component for auth

allows us to isolate how much latency is added by auth checks

* perf(parallel_request_limiter.py): move async_set_cache_pipeline (from max parallel request limiter) out of execution path (background task)

reduces latency by 200ms

* feat(user_api_key_auth.py): have user api key auth object return user tpm/rpm limits - reduces redis calls in downstream task (parallel_request_limiter)

Reduces latency by 400-800ms

* fix(parallel_request_limiter.py): use batch get cache to reduce user/key/team usage object calls

reduces latency by 50-100ms

* fix: fix linting error

* fix(_service_logger.py): fix import

* fix(user_api_key_auth.py): fix service logging

* fix(dual_cache.py): don't pass 'self'

* fix: fix python3.8 error

* fix: fix init]

* bump: version 1.51.4 → 1.51.5

* build(deps): bump cookie and express in /docs/my-website (#6566)

Bumps [cookie](https://github.com/jshttp/cookie) and [express](https://github.com/expressjs/express). These dependencies needed to be updated together.

Updates `cookie` from 0.6.0 to 0.7.1
- [Release notes](https://github.com/jshttp/cookie/releases)
- [Commits](https://github.com/jshttp/cookie/compare/v0.6.0...v0.7.1)

Updates `express` from 4.20.0 to 4.21.1
- [Release notes](https://github.com/expressjs/express/releases)
- [Changelog](https://github.com/expressjs/express/blob/4.21.1/History.md)
- [Commits](https://github.com/expressjs/express/compare/4.20.0...4.21.1)

---
updated-dependencies:
- dependency-name: cookie
  dependency-type: indirect
- dependency-name: express
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* docs(virtual_keys.md): update Dockerfile reference (#6554)

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>

* (proxy fix) - call connect on prisma client when running setup (#6534)

* critical fix - call connect on prisma client when running setup

* fix test_proxy_server_prisma_setup

* fix test_proxy_server_prisma_setup

* Add 3.5 haiku (#6588)

* feat: add claude-3-5-haiku-20241022 entries

* feat: add claude-3-5-haiku-20241022 and vertex_ai/claude-3-5-haiku@20241022 models

* add missing entries, remove vision

* remove image token costs

* Litellm perf improvements 3 (#6573)

* perf: move writing key to cache, to background task

* perf(litellm_pre_call_utils.py): add otel tracing for pre-call utils

adds 200ms on calls with pgdb connected

* fix(litellm_pre_call_utils.py'): rename call_type to actual call used

* perf(proxy_server.py): remove db logic from _get_config_from_file

was causing db calls to occur on every llm request, if team_id was set on key

* fix(auth_checks.py): add check for reducing db calls if user/team id does not exist in db

reduces latency/call by ~100ms

* fix(proxy_server.py): minor fix on existing_settings not incl alerting

* fix(exception_mapping_utils.py): map databricks exception string

* fix(auth_checks.py): fix auth check logic

* test: correctly mark flaky test

* fix(utils.py): handle auth token error for tokenizers.from_pretrained

* build: fix map

* build: fix map

* build: fix json for model map

* Litellm dev 11 02 2024 (#6561)

* fix(dual_cache.py): update in-memory check for redis batch get cache

Fixes latency delay for async_batch_redis_cache

* fix(service_logger.py): fix race condition causing otel service logging to be overwritten if service_callbacks set

* feat(user_api_key_auth.py): add parent otel component for auth

allows us to isolate how much latency is added by auth checks

* perf(parallel_request_limiter.py): move async_set_cache_pipeline (from max parallel request limiter) out of execution path (background task)

reduces latency by 200ms

* feat(user_api_key_auth.py): have user api key auth object return user tpm/rpm limits - reduces redis calls in downstream task (parallel_request_limiter)

Reduces latency by 400-800ms

* fix(parallel_request_limiter.py): use batch get cache to reduce user/key/team usage object calls

reduces latency by 50-100ms

* fix: fix linting error

* fix(_service_logger.py): fix import

* fix(user_api_key_auth.py): fix service logging

* fix(dual_cache.py): don't pass 'self'

* fix: fix python3.8 error

* fix: fix init]

* Litellm perf improvements 3 (#6573)

* perf: move writing key to cache, to background task

* perf(litellm_pre_call_utils.py): add otel tracing for pre-call utils

adds 200ms on calls with pgdb connected

* fix(litellm_pre_call_utils.py'): rename call_type to actual call used

* perf(proxy_server.py): remove db logic from _get_config_from_file

was causing db calls to occur on every llm request, if team_id was set on key

* fix(auth_checks.py): add check for reducing db calls if user/team id does not exist in db

reduces latency/call by ~100ms

* fix(proxy_server.py): minor fix on existing_settings not incl alerting

* fix(exception_mapping_utils.py): map databricks exception string

* fix(auth_checks.py): fix auth check logic

* test: correctly mark flaky test

* fix(utils.py): handle auth token error for tokenizers.from_pretrained

* fix ImageObject conversion (#6584)

* (fix) litellm.text_completion raises a non-blocking error on simple usage (#6546)

* unit test test_huggingface_text_completion_logprobs

* fix return TextCompletionHandler convert_chat_to_text_completion

* fix hf rest api

* fix test_huggingface_text_completion_logprobs

* fix linting errors

* fix importLiteLLMResponseObjectHandler

* fix test for LiteLLMResponseObjectHandler

* fix test text completion

* fix allow using 15 seconds for premium license check

* testing fix bedrock deprecated cohere.command-text-v14

* (feat) add `Predicted Outputs` for OpenAI  (#6594)

* bump openai to openai==1.54.0

* add 'prediction' param

* testing fix bedrock deprecated cohere.command-text-v14

* test test_openai_prediction_param.py

* test_openai_prediction_param_with_caching

* doc Predicted Outputs

* doc Predicted Output

* (fix) Vertex Improve Performance when using `image_url`  (#6593)

* fix transformation vertex

* test test_process_gemini_image

* test_image_completion_request

* testing fix - bedrock has deprecated cohere.command-text-v14

* fix vertex pdf

* bump: version 1.51.5 → 1.52.0

* fix(lowest_tpm_rpm_routing.py): fix parallel rate limit check (#6577)

* fix(lowest_tpm_rpm_routing.py): fix parallel rate limit check

* fix(lowest_tpm_rpm_v2.py): return headers in correct format

* test: update test

* build(deps): bump cookie and express in /docs/my-website (#6566)

Bumps [cookie](https://github.com/jshttp/cookie) and [express](https://github.com/expressjs/express). These dependencies needed to be updated together.

Updates `cookie` from 0.6.0 to 0.7.1
- [Release notes](https://github.com/jshttp/cookie/releases)
- [Commits](https://github.com/jshttp/cookie/compare/v0.6.0...v0.7.1)

Updates `express` from 4.20.0 to 4.21.1
- [Release notes](https://github.com/expressjs/express/releases)
- [Changelog](https://github.com/expressjs/express/blob/4.21.1/History.md)
- [Commits](https://github.com/expressjs/express/compare/4.20.0...4.21.1)

---
updated-dependencies:
- dependency-name: cookie
  dependency-type: indirect
- dependency-name: express
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* docs(virtual_keys.md): update Dockerfile reference (#6554)

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>

* (proxy fix) - call connect on prisma client when running setup (#6534)

* critical fix - call connect on prisma client when running setup

* fix test_proxy_server_prisma_setup

* fix test_proxy_server_prisma_setup

* Add 3.5 haiku (#6588)

* feat: add claude-3-5-haiku-20241022 entries

* feat: add claude-3-5-haiku-20241022 and vertex_ai/claude-3-5-haiku@20241022 models

* add missing entries, remove vision

* remove image token costs

* Litellm perf improvements 3 (#6573)

* perf: move writing key to cache, to background task

* perf(litellm_pre_call_utils.py): add otel tracing for pre-call utils

adds 200ms on calls with pgdb connected

* fix(litellm_pre_call_utils.py'): rename call_type to actual call used

* perf(proxy_server.py): remove db logic from _get_config_from_file

was causing db calls to occur on every llm request, if team_id was set on key

* fix(auth_checks.py): add check for reducing db calls if user/team id does not exist in db

reduces latency/call by ~100ms

* fix(proxy_server.py): minor fix on existing_settings not incl alerting

* fix(exception_mapping_utils.py): map databricks exception string

* fix(auth_checks.py): fix auth check logic

* test: correctly mark flaky test

* fix(utils.py): handle auth token error for tokenizers.from_pretrained

* build: fix map

* build: fix map

* build: fix json for model map

* test: remove eol model

* fix(proxy_server.py): fix db config loading logic

* fix(proxy_server.py): fix order of config / db updates, to ensure fields not overwritten

* test: skip test if required env var is missing

* test: fix test

---------

Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: paul-gauthier <69695708+paul-gauthier@users.noreply.github.com>

* test: mark flaky test

* test: handle anthropic api instability

* test: update test

* test: bump num retries on langfuse tests - their api is quite bad

---------

Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: paul-gauthier <69695708+paul-gauthier@users.noreply.github.com>
2024-11-06 17:53:46 +05:30

143 lines
4.2 KiB
Python

"""
Test the DataDogLLMObsLogger
"""
import io
import os
import sys
sys.path.insert(0, os.path.abspath("../.."))
import asyncio
import gzip
import json
import logging
import time
from unittest.mock import AsyncMock, patch
import pytest
import litellm
from litellm import completion
from litellm._logging import verbose_logger
from litellm.integrations.datadog.datadog_llm_obs import DataDogLLMObsLogger
from datetime import datetime, timedelta
from litellm.types.integrations.datadog_llm_obs import *
from litellm.types.utils import (
StandardLoggingPayload,
StandardLoggingModelInformation,
StandardLoggingMetadata,
StandardLoggingHiddenParams,
)
verbose_logger.setLevel(logging.DEBUG)
def create_standard_logging_payload() -> StandardLoggingPayload:
return StandardLoggingPayload(
id="test_id",
call_type="completion",
response_cost=0.1,
response_cost_failure_debug_info=None,
status="success",
total_tokens=30,
prompt_tokens=20,
completion_tokens=10,
startTime=1234567890.0,
endTime=1234567891.0,
completionStartTime=1234567890.5,
model_map_information=StandardLoggingModelInformation(
model_map_key="gpt-3.5-turbo", model_map_value=None
),
model="gpt-3.5-turbo",
model_id="model-123",
model_group="openai-gpt",
api_base="https://api.openai.com",
metadata=StandardLoggingMetadata(
user_api_key_hash="test_hash",
user_api_key_org_id=None,
user_api_key_alias="test_alias",
user_api_key_team_id="test_team",
user_api_key_user_id="test_user",
user_api_key_team_alias="test_team_alias",
spend_logs_metadata=None,
requester_ip_address="127.0.0.1",
requester_metadata=None,
),
cache_hit=False,
cache_key=None,
saved_cache_cost=0.0,
request_tags=[],
end_user=None,
requester_ip_address="127.0.0.1",
messages=[{"role": "user", "content": "Hello, world!"}],
response={"choices": [{"message": {"content": "Hi there!"}}]},
error_str=None,
model_parameters={"stream": True},
hidden_params=StandardLoggingHiddenParams(
model_id="model-123",
cache_key=None,
api_base="https://api.openai.com",
response_cost="0.1",
additional_headers=None,
),
)
@pytest.mark.asyncio
async def test_datadog_llm_obs_logging():
datadog_llm_obs_logger = DataDogLLMObsLogger()
litellm.callbacks = [datadog_llm_obs_logger]
litellm.set_verbose = True
for _ in range(2):
response = await litellm.acompletion(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello testing dd llm obs!"}],
mock_response="hi",
)
print(response)
await asyncio.sleep(6)
@pytest.mark.asyncio
async def test_create_llm_obs_payload():
datadog_llm_obs_logger = DataDogLLMObsLogger()
standard_logging_payload = create_standard_logging_payload()
payload = datadog_llm_obs_logger.create_llm_obs_payload(
kwargs={
"model": "gpt-4",
"messages": [{"role": "user", "content": "Hello"}],
"standard_logging_object": standard_logging_payload,
},
response_obj=litellm.ModelResponse(
id="test_id",
choices=[{"message": {"content": "Hi there!"}}],
created=12,
model="gpt-4",
),
start_time=datetime.now(),
end_time=datetime.now() + timedelta(seconds=1),
)
print("dd created payload", payload)
assert payload["name"] == "litellm_llm_call"
assert payload["meta"]["kind"] == "llm"
assert payload["meta"]["input"]["messages"] == [
{"role": "user", "content": "Hello, world!"}
]
assert payload["meta"]["output"]["messages"] == [
{
"content": "Hi there!",
"role": "assistant",
"tool_calls": None,
"function_call": None,
}
]
assert payload["metrics"]["input_tokens"] == 20
assert payload["metrics"]["output_tokens"] == 10
assert payload["metrics"]["total_tokens"] == 30