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add ragbench faithfulness cards #1598

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add ragbench faithfulness cards #1598

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3104bed
allow multi reference in hhem metric
lilacheden Feb 11, 2025
8144ebd
add ragbench faithfulness cards
lilacheden Feb 11, 2025
7e531ef
add "mistral-large-instruct" to provider
lilacheden Feb 11, 2025
16ebe42
add "mistral-large-instruct" classification engines
lilacheden Feb 11, 2025
56347a8
add rag judges that use mistral-large-instruct
lilacheden Feb 11, 2025
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41 changes: 41 additions & 0 deletions prepare/cards/ragbench_faithfulness.py
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from unitxt import add_to_catalog
from unitxt.blocks import (
LoadHF,
TaskCard,
)
from unitxt.operators import Copy, ExecuteExpression
from unitxt.templates import NullTemplate

for subset in [
"covidqa",
"cuad",
"delucionqa",
"emanual",
"expertqa",
"finqa",
"hagrid",
"hotpotqa",
"msmarco",
"pubmedqa",
"tatqa",
"techqa",
]:
card = TaskCard(
loader=LoadHF(
path="rungalileo/ragbench",
name=subset,
split="test"
),
preprocess_steps=[
Copy(field="response", to_field="answer"),
Copy(field="documents", to_field="contexts"),
ExecuteExpression(expression="int(adherence_score)", to_field="number_val"),
ExecuteExpression(expression="['yes' if adherence_score else 'no']", to_field="is_faithful"),
],
task="tasks.rag_eval.faithfulness.binary",
templates={"default": NullTemplate()},
)

add_to_catalog(
card, f"cards.rag_eval.faithfulness.ragbench.{subset}", overwrite=True
)
1 change: 1 addition & 0 deletions prepare/engines/classification/classification_engines.py
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Expand Up @@ -6,6 +6,7 @@
)

model_names_to_provider = {
"mistral-large-instruct": ["watsonx", "rits"],
"llama-3-3-70b-instruct": ["watsonx", "rits"],
"llama-3-1-70b-instruct": ["watsonx", "rits"],
"gpt-4o": ["open-ai"],
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2 changes: 2 additions & 0 deletions prepare/metrics/llm_as_judge/rag_judge.py
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Expand Up @@ -102,6 +102,8 @@ def get_prediction_field(metric_type):
"llama_3_3_70b_instruct_watsonx": "engines.classification.llama_3_3_70b_instruct_watsonx",
"llama_3_3_70b_instruct_rits": "engines.classification.llama_3_3_70b_instruct_rits",
"gpt_4o_azure": "engines.classification.gpt_4o_2024_08_06_azure_openai",
"mistral_large_instruct_watsonx": "engines.classification.mistral_large_watsonx",
"mistral_large_instruct_rits": "engines.classification.mistral_large_instruct_2407_rits",
generic_engine_label: GenericInferenceEngine(),
}

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37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/covidqa.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "covidqa",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/cuad.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "cuad",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/delucionqa.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "delucionqa",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/emanual.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "emanual",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/expertqa.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "expertqa",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/finqa.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "finqa",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/hagrid.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "hagrid",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
37 changes: 37 additions & 0 deletions src/unitxt/catalog/cards/rag_eval/faithfulness/ragbench/hotpotqa.json
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{
"__type__": "task_card",
"loader": {
"__type__": "load_hf",
"path": "rungalileo/ragbench",
"name": "hotpotqa",
"split": "test"
},
"preprocess_steps": [
{
"__type__": "copy",
"field": "response",
"to_field": "answer"
},
{
"__type__": "copy",
"field": "documents",
"to_field": "contexts"
},
{
"__type__": "execute_expression",
"expression": "int(adherence_score)",
"to_field": "number_val"
},
{
"__type__": "execute_expression",
"expression": "['yes' if adherence_score else 'no']",
"to_field": "is_faithful"
}
],
"task": "tasks.rag_eval.faithfulness.binary",
"templates": {
"default": {
"__type__": "null_template"
}
}
}
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