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community: callbacks guard_imports (#21173)

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Issue: we have several helper functions to import third-party libraries
like import_uptrain in
[community.callbacks](https://api.python.langchain.com/en/latest/callbacks/langchain_community.callbacks.uptrain_callback.import_uptrain.html#langchain_community.callbacks.uptrain_callback.import_uptrain).
And we have core.utils.utils.guard_import that works exactly for this
purpose.
The import_<package> functions work inconsistently and rather be private
functions.
Change: replaced these functions with the guard_import function.

Related to #21133
This commit is contained in:
Leonid Ganeline
2024-05-07 15:04:54 -07:00
committed by GitHub
parent 416549bed2
commit 791d59a2c8
13 changed files with 73 additions and 178 deletions
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23
libs/community/langchain_community/callbacks/uptrain_callback.py
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@@ -2,12 +2,12 @@
UpTrain Callback Handler
UpTrain is an open-source platform to evaluate and improve LLM applications. It provides
grades for 20+ preconfigured checks (covering language, code, embedding use cases),
performs root cause analyses on instances of failure cases and provides guidance for
grades for 20+ preconfigured checks (covering language, code, embedding use cases),
performs root cause analyses on instances of failure cases and provides guidance for
resolving them.
This module contains a callback handler for integrating UpTrain seamlessly into your
pipeline and facilitating diverse evaluations. The callback handler automates various
This module contains a callback handler for integrating UpTrain seamlessly into your
pipeline and facilitating diverse evaluations. The callback handler automates various
evaluations to assess the performance and effectiveness of the components within the
pipeline.
@@ -29,7 +29,7 @@ The evaluations conducted include:
3. Context Compression and Reranking:
Re-ranking involves reordering nodes based on relevance to the query and selecting
top n nodes.
top n nodes.
Due to the potential reduction in the number of nodes after re-ranking, the following
evaluations
are performed in addition to the RAG evaluations:
@@ -65,6 +65,7 @@ from uuid import UUID
from langchain_core.callbacks.base import BaseCallbackHandler
from langchain_core.documents import Document
from langchain_core.outputs import LLMResult
from langchain_core.utils import guard_import
logger = logging.getLogger(__name__)
handler = logging.StreamHandler(sys.stdout)
@@ -75,17 +76,7 @@ logger.addHandler(handler)
def import_uptrain() -> Any:
"""Import the `uptrain` package."""
try:
import uptrain
except ImportError as e:
raise ImportError(
"To use the UpTrainCallbackHandler, you need the"
"`uptrain` package. Please install it with"
"`pip install uptrain`.",
e,
)
return uptrain
return guard_import("uptrain")
class UpTrainDataSchema: