brainy-lion-6334
06/01/2023, 11:41 PMastonishing-advantage-94636
06/26/2023, 4:52 PMastonishing-advantage-94636
06/26/2023, 4:53 PMgreen-napkin-55314
06/28/2023, 9:17 PMimport whylogs as why
from whylogs.api.writer.whylabs import WhyLabsWriter
from langkit.whylogs.rolling_logger import RollingLogger
from langkit import all_metrics
schema = all_metrics.init()
results = why.log({"David": "Hello,", "Emily": "Hey there!"}, schema=all_metrics).profile()
In the previous example, I am doing a simple upload of this text query using the schema from all_metrics to upload to whylab. My question is, how can I get the 'raw' output values from each UDF for every given input string? I know I can get the summary stats using view:
#See some initial metrics tabulated
view = results.view()
view.to_pandas()
But rather than summary statistics, I would like basically tabular data where each row is an input string, and there is a column for every UDF metric I've defined. Reason being I want to calculate the correlation between my metrics across all input samples .Please let me know if I should clarify more!strong-oil-75235
01/10/2024, 7:17 PMcolossal-army-36063
01/10/2024, 11:42 PMlively-journalist-92929
02/12/2024, 8:57 AMlively-journalist-92929
02/12/2024, 8:59 AMlively-journalist-92929
02/12/2024, 9:00 AMllm_metrics
please install it with pip install langkit[all]
."
17 )
20 def init() -> DeclarativeSchema:
21 regexes.init()
ImportError: To use llm_metrics
please install it with pip install langkit[all]
.strong-oil-75235
02/12/2024, 2:46 PMcurved-coat-90458
02/13/2024, 7:32 PMstrong-oil-75235
02/13/2024, 10:49 PMwide-action-22243
03/17/2024, 2:46 AMquiet-morning-29785
03/21/2024, 10:09 AM