Get started with LangWatch Skills in seconds: Set up evals, scenario tests, and tracing just by asking your AI coding assistant.
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(
"presidio/pii_detection",
index=index,
data={
"input": row["input"],
"output": output,
},
settings={}
)[
{
"score": 123,
"passed": true,
"label": "<string>",
"details": "<string>",
"cost": {
"currency": "<string>",
"amount": 123
}
}
]Detects personally identifiable information in text, including phone numbers, email addresses, and social security numbers. It allows customization of the detection threshold and the specific types of PII to check.
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(
"presidio/pii_detection",
index=index,
data={
"input": row["input"],
"output": output,
},
settings={}
)[
{
"score": 123,
"passed": true,
"label": "<string>",
"details": "<string>",
"cost": {
"currency": "<string>",
"amount": 123
}
}
]Documentation Index
Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
API key for authentication
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