Instrument and observe your DSPy application

DSPy is a framework for automatically prompting and fine-tuning language models. It provides composable and declarative APIs that allow developers to describe the architecture of their LLM application in the form of a "module" (inspired by PyTorch's nn.Module). It them compiles these modules using "teleprompters" that optimize the module for a particular task. The term "teleprompter" is meant to evoke "prompting at a distance," and could involve selecting few-shot examples, generating prompts, or fine-tuning language models.

Phoenix makes your DSPy applications observable by visualizing the underlying structure of each call to your compiled DSPy module.


To trace your DSPy application, ensure that the following packages are installed in addition to DSPy:

pip install arize-phoenix openinference-instrumentation-dspy opentelemetry-exporter-otlp

Launch Phoenix as a collector in the background.

import phoenix as px


Configure your OpenTelemetry exporter, which will export spans and traces to Phoenix, and run the DSPy instrumentor to wrap calls to the relevant DSPy components.

from openinference.instrumentation.dspy import DSPyInstrumentor
from opentelemetry import trace as trace_api
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

endpoint = ""
resource = Resource(attributes={})
tracer_provider = trace_sdk.TracerProvider(resource=resource)
span_otlp_exporter = OTLPSpanExporter(endpoint=endpoint)

Now run invoke your compiled DSPy module. Your traces should appear inside of Phoenix.

For a full working example, check out the Colab.

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