Instrumenting Prompt Templates and Prompt Variables

Instrumenting prompt templates and variables allows you to track and visualize prompt changes. These can also be combined with Experiments to measure the performance changes driven by each of your prompts.

Python

We provide a using_prompt_template context manager to add a prompt template (including its version and variables) to the current OpenTelemetry Context. OpenInference auto-instrumentors will read this Context and pass the prompt template fields as span attributes, following the OpenInference semantic conventions. Its inputs must be of the following type:

• Template: non-empty string.

• Version: non-empty string.

• Variables: a dictionary with string keys. This dictionary will be serialized to JSON when saved to the OTEL Context and remain a JSON string when sent as a span attribute.

from openinference.instrumentation import using_prompt_template

prompt_template = "Please describe the weather forecast for {city} on {date}"
prompt_template_variables = {"city": "Johannesburg", "date":"July 11"}
with using_prompt_template(
    template=prompt_template,
    variables=prompt_template_variables,
    version="v1.0",
    ):
    # Commonly preceeds a chat completion to append templates to auto instrumentation
    # response = client.chat.completions.create()
    # Calls within this block will generate spans with the attributes:
    # "llm.prompt_template.template" = "Please describe the weather forecast for {city} on {date}"
    # "llm.prompt_template.version" = "v1.0"
    # "llm.prompt_template.variables" = "{\"city\": \"Johannesburg\", \"date\": \"July 11\"}" # JSON serialized
    ...

It can also be used as a decorator:

@using_prompt_template(
    template=prompt_template,
    variables=prompt_template_variables,
    version="v1.0",
)
def call_fn(*args, **kwargs):
    # Calls within this function will generate spans with the attributes:
    # "llm.prompt_template.template" = "Please describe the weather forecast for {city} on {date}"
    # "llm.prompt_template.version" = "v1.0"
    # "llm.prompt_template.variables" = "{\"city\": \"Johannesburg\", \"date\": \"July 11\"}" # JSON serialized
    ...