import langwatch
df = langwatch.datasets.get_dataset("dataset-id").to_pandas()
experiment = langwatch.experiment.init("my-experiment")
for index, row in experiment.loop(df.iterrows()):
# your execution code here
experiment.evaluate(
"ragas/summarization_score",
index=index,
data={
"output": output,
"contexts": row["contexts"],
},
settings={}
)[
{
"score": 123,
"passed": true,
"label": "<string>",
"details": "<string>",
"cost": {
"currency": "<string>",
"amount": 123
}
}
]{
"detail": "<string>"
}{
"detail": "<string>"
}LLM as Judge
Summarization Score
Measures how well the summary captures important information from the retrieved contexts.
POST
/
ragas
/
summarization_score
/
evaluate
import langwatch
df = langwatch.datasets.get_dataset("dataset-id").to_pandas()
experiment = langwatch.experiment.init("my-experiment")
for index, row in experiment.loop(df.iterrows()):
# your execution code here
experiment.evaluate(
"ragas/summarization_score",
index=index,
data={
"output": output,
"contexts": row["contexts"],
},
settings={}
)[
{
"score": 123,
"passed": true,
"label": "<string>",
"details": "<string>",
"cost": {
"currency": "<string>",
"amount": 123
}
}
]{
"detail": "<string>"
}{
"detail": "<string>"
}Authorizations
API key for authentication
Body
application/json
Response
Successful evaluation
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