more scoring function for rag

This commit is contained in:
Xi Yan 2024-12-19 17:13:16 -08:00
parent 9aa4a405ca
commit 40b8ec3185
5 changed files with 132 additions and 0 deletions

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@ -19,6 +19,10 @@ from autoevals.ragas import (
AnswerCorrectness, AnswerCorrectness,
AnswerRelevancy, AnswerRelevancy,
AnswerSimilarity, AnswerSimilarity,
ContextEntityRecall,
ContextPrecision,
ContextRecall,
ContextRelevancy,
Faithfulness, Faithfulness,
) )
from pydantic import BaseModel from pydantic import BaseModel
@ -34,6 +38,10 @@ from .config import BraintrustScoringConfig
from .scoring_fn.fn_defs.answer_correctness import answer_correctness_fn_def from .scoring_fn.fn_defs.answer_correctness import answer_correctness_fn_def
from .scoring_fn.fn_defs.answer_relevancy import answer_relevancy_fn_def from .scoring_fn.fn_defs.answer_relevancy import answer_relevancy_fn_def
from .scoring_fn.fn_defs.answer_similarity import answer_similarity_fn_def from .scoring_fn.fn_defs.answer_similarity import answer_similarity_fn_def
from .scoring_fn.fn_defs.context_entity_recall import context_entity_recall_fn_def
from .scoring_fn.fn_defs.context_precision import context_precision_fn_def
from .scoring_fn.fn_defs.context_recall import context_recall_fn_def
from .scoring_fn.fn_defs.context_relevancy import context_relevancy_fn_def
from .scoring_fn.fn_defs.factuality import factuality_fn_def from .scoring_fn.fn_defs.factuality import factuality_fn_def
from .scoring_fn.fn_defs.faithfulness import faithfulness_fn_def from .scoring_fn.fn_defs.faithfulness import faithfulness_fn_def
@ -70,6 +78,26 @@ SUPPORTED_BRAINTRUST_SCORING_FN_ENTRY = [
evaluator=Faithfulness(), evaluator=Faithfulness(),
fn_def=faithfulness_fn_def, fn_def=faithfulness_fn_def,
), ),
BraintrustScoringFnEntry(
identifier="braintrust::context-entity-recall",
evaluator=ContextEntityRecall(),
fn_def=context_entity_recall_fn_def,
),
BraintrustScoringFnEntry(
identifier="braintrust::context-precision",
evaluator=ContextPrecision(),
fn_def=context_precision_fn_def,
),
BraintrustScoringFnEntry(
identifier="braintrust::context-recall",
evaluator=ContextRecall(),
fn_def=context_recall_fn_def,
),
BraintrustScoringFnEntry(
identifier="braintrust::context-relevancy",
evaluator=ContextRelevancy(),
fn_def=context_relevancy_fn_def,
),
] ]

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@ -0,0 +1,26 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.common.type_system import NumberType
from llama_stack.apis.scoring_functions import (
AggregationFunctionType,
BasicScoringFnParams,
ScoringFn,
)
context_entity_recall_fn_def = ScoringFn(
identifier="braintrust::context-entity-recall",
description=(
"Evaluates how well the context captures the named entities present in the "
"reference answer. See: github.com/braintrustdata/autoevals"
),
provider_id="braintrust",
provider_resource_id="context-entity-recall",
return_type=NumberType(),
params=BasicScoringFnParams(
aggregation_functions=[AggregationFunctionType.average]
),
)

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@ -0,0 +1,26 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.common.type_system import NumberType
from llama_stack.apis.scoring_functions import (
AggregationFunctionType,
BasicScoringFnParams,
ScoringFn,
)
context_precision_fn_def = ScoringFn(
identifier="braintrust::context-precision",
description=(
"Measures how much of the provided context is actually relevant to answering the "
"question. See: github.com/braintrustdata/autoevals"
),
provider_id="braintrust",
provider_resource_id="context-precision",
return_type=NumberType(),
params=BasicScoringFnParams(
aggregation_functions=[AggregationFunctionType.average]
),
)

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@ -0,0 +1,26 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.common.type_system import NumberType
from llama_stack.apis.scoring_functions import (
AggregationFunctionType,
BasicScoringFnParams,
ScoringFn,
)
context_recall_fn_def = ScoringFn(
identifier="braintrust::context-recall",
description=(
"Evaluates how well the context covers the information needed to answer the "
"question. See: github.com/braintrustdata/autoevals"
),
provider_id="braintrust",
provider_resource_id="context-recall",
return_type=NumberType(),
params=BasicScoringFnParams(
aggregation_functions=[AggregationFunctionType.average]
),
)

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@ -0,0 +1,26 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.common.type_system import NumberType
from llama_stack.apis.scoring_functions import (
AggregationFunctionType,
BasicScoringFnParams,
ScoringFn,
)
context_relevancy_fn_def = ScoringFn(
identifier="braintrust::context-relevancy",
description=(
"Assesses how relevant the provided context is to the given question. "
"See: github.com/braintrustdata/autoevals"
),
provider_id="braintrust",
provider_resource_id="context-relevancy",
return_type=NumberType(),
params=BasicScoringFnParams(
aggregation_functions=[AggregationFunctionType.average]
),
)