progress-observability 1.4.3

Progress Observability instrumentation for Python agents

Progress Observability Instrumentation (Python)

Zero-intrusion telemetry for AI agents and LLM apps. Built on Traceloop SDK and OpenTelemetry with a simple one-line init and optional decorators.

Installation

pip install progress-observability

Or from wheel file:

pip install progress_observability-x.y.z-py3-none-any.whl

Quick Start

from progress.observability import Observability, ObservabilityInstruments

# Initialize once at process start
Observability.instrument(
    app_name="my-app",
    api_key="<your-api-key>",
    # endpoint="https://collector.observability.progress.com:443"  # Optional: has default
)

Configuration

Common options (for Observability.instrument):

• app_name - Application name for telemetry
• endpoint - OpenTelemetry collector endpoint
• api_key - Authentication key
• debug - Enable debug logging
• instruments / block_instruments - Control what gets traced via ObservabilityInstruments
• trace_content - when set to False will stop sending LLM prompt/responses as part of the telemetry data
• additional_tags - custom tags (see below)

Environment overrides (optional):

• OBSERVABILITY_APP_NAME sets the application name (e.g. "my-app")
• OBSERVABILITY_ENDPOINT sets a custom endpoint for collecting data (e.g. "https://collector.observability.progress.com:443")
• OBSERVABILITY_API_KEY sets the authentication key to use when sending data
• OBSERVABILITY_TRACE_CONTENT when set to false will stop sending LLM prompt/responses as part of the telemetry data

Auth headers are added automatically for HTTP(S) endpoints when api_key is provided.

Custom Tags

Tags are user-defined strings (max 200 characters each) attached to observations for filtering and grouping.

Global tags — applied to every span:

Observability.instrument(
    app_name="my-app",
    api_key="<your-api-key>",
    additional_tags=["production", "release:2.4.1"],
)

Scoped tags — applied to spans within a specific block via propagate_attributes:

from progress.observability import propagate_attributes

with propagate_attributes(tags=["tenant:acme", "experiment-v2"]):
    # All spans created here inherit these tags
    my_agent_function()

Nesting is supported — tags accumulate from outer to inner scopes.

Decorator tags — applied to a single decorated function:

from progress.observability import task

@task(tags=["cohort-a"])
def my_task():
    ...

Package Structure

src/progress/observability/
├── __init__.py                 # Package entry point
├── sdk.py                      # Main Observability SDK
├── decorators.py               # @task, @workflow, @agent, @tool decorators
├── constants.py                # Environment variables and constants
├── enums.py                    # ObservabilityInstruments enum
├── exceptions.py               # Custom exception types
├── genai_message_processor.py  # LLM span content normalization
├── helpers.py                  # Helper functions
├── model_fix_processor.py      # LLM span attribute repair
├── tags.py                     # Tag propagation span processor