Logging traces (LlamaIndex, Langchain, etc.)
Users can log traces from their real-time (production) applications by invoking the Catalyst Tracer from their SDK. This allows Catalyst to read inferences in real-time and log them for instant evaluations. This way, users can avoid downloading and uploading in batches.
The Catalyst Tracer can be enabled with the following commands:
from ragaai_catalyst.tracers import Tracer
from ragaai_catalyst import (
RagaAICatalyst,
init_tracing
)
# Initialize Catalyst Object
catalyst = RagaAICatalyst(
access_key = "RNb1evdFRTKjb6I7bfhy",
secret_key = "HmFFbkNOoub7mIXAD3bhXJWdTF283dlBh6K1Ev3z",
base_url = "https://dev-ragaai.deephealthos.com/api"
)
# Start Tracing (Place this at the top of your code)
tracer = Tracer(
project_name="your-project-name",
dataset_name="your-dataset-name",
metadata={"key1": "value1", "key2": "value2"},
tracer_type="langchain"
)
init_tracing(catalyst=catalyst, tracer=tracer)
If successful, you can view the logged dataset by navigating to Project_Name -> Dataset_Name
Metrics can be run on logged datasets in the same fashion as for CSV uploads.
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