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ci: stub out open AI key during CI to avoid embedding model downloads in llama_index #1661

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merged 4 commits into from
Oct 24, 2023
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ci: stub out open AI key during CI to avoid embedding model downloads in llama_index #1661

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d37a5a9
ci: high watermark on CI
mikeldking Oct 24, 2023
63ab5cd
Reformat text
mikeldking Oct 24, 2023
4b4ea05
adjust watermark
mikeldking Oct 24, 2023
ac4ef4b
fake openai key
mikeldking Oct 24, 2023
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1 change: 1 addition & 0 deletions .github/workflows/python-CI.yml
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Expand Up @@ -18,6 +18,7 @@ concurrency:

env:
pip-version: 23.1.2
PYTORCH_MPS_HIGH_WATERMARK_RATIO: 0.0 # disable memory warnings

jobs:
lint:
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6 changes: 3 additions & 3 deletions src/phoenix/trace/evaluation_conventions.py
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Expand Up @@ -14,13 +14,13 @@
EVAL_DOCUMENTS_PRECISION = "eval.documents_precision"
"""
The precision of a retriever.
This is the proportion (expressed as a value between 0 and 1) of relevant documents over the total
This is the proportion (expressed as a value between 0 and 1) of relevant documents over the total.
"""

EVAL_DOCUMENTS_PRECISION_AT_K_TEMPLATE = "eval.documents_precision_at_{k}"
"""
The prefix given to an evaluation metric that captures the precision of a
retriever up to K. E.x. you would have eval.documents_precision_at_1,
eval.documents_precision_at_2, etc. This value
would be computed on top of the document_relevancy attribute of each document.
eval.documents_precision_at_2, etc. This value would be computed on top of the
document_relevancy attribute of each document.
"""
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