Logging traces (LlamaIndex, Langchain, etc.)

Learn how to log execution traces from LlamaIndex or LangChain into RagaAI Catalyst. Capture prompts, responses, and steps for easier debugging and evaluation.

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.