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chore: refurbish Python code by applying refurb linter rules (#8296)

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This commit is contained in:
Bowen Liang
2024-09-12 15:50:49 +08:00
committed by GitHub
parent c69f5b07ba
commit 40fb4d16ef
105 changed files with 220 additions and 276 deletions
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6
api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py
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@@ -160,7 +160,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
hit_callback.on_query(query, dataset.id)
# get retrieval model , if the model is not setting , using default
retrieval_model = dataset.retrieval_model if dataset.retrieval_model else default_retrieval_model
retrieval_model = dataset.retrieval_model or default_retrieval_model
if dataset.indexing_technique == "economy":
# use keyword table query
@@ -183,9 +183,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
reranking_model=retrieval_model.get("reranking_model", None)
if retrieval_model["reranking_enable"]
else None,
reranking_mode=retrieval_model.get("reranking_mode")
if retrieval_model.get("reranking_mode")
else "reranking_model",
reranking_mode=retrieval_model.get("reranking_mode") or "reranking_model",
weights=retrieval_model.get("weights", None),
)

6
api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py
View File

@@ -55,7 +55,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
hit_callback.on_query(query, dataset.id)
# get retrieval model , if the model is not setting , using default
retrieval_model = dataset.retrieval_model if dataset.retrieval_model else default_retrieval_model
retrieval_model = dataset.retrieval_model or default_retrieval_model
if dataset.indexing_technique == "economy":
# use keyword table query
documents = RetrievalService.retrieve(
@@ -76,9 +76,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
reranking_model=retrieval_model.get("reranking_model", None)
if retrieval_model["reranking_enable"]
else None,
reranking_mode=retrieval_model.get("reranking_mode")
if retrieval_model.get("reranking_mode")
else "reranking_model",
reranking_mode=retrieval_model.get("reranking_mode") or "reranking_model",
weights=retrieval_model.get("weights", None),
)
else: