uptimes-agents 0.1.0

Uptimes Agents — OpenTelemetry-based observability for AI agents. Three-line init, ships to local uptimes-monitor or direct to api.uptimes.ai.

uptimes-agents (Python)

OpenTelemetry-based observability SDK for AI agents — three-line install, ships to the local uptimes-monitor daemon or direct to api.uptimes.ai.

Install

pip install uptimes-agents
# Add provider extras for auto-instrumentation:
pip install 'uptimes-agents[anthropic]'    # or [openai], or [all]

Quick start

import uptimes_agents
import anthropic

uptimes_agents.init(service_name="rca-agent")

client = anthropic.Anthropic()
client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=256,
    messages=[{"role": "user", "content": "hi"}],
)
# → one chat span lands in your Uptimes dashboard within ~5s.

Custom spans

For non-LLM work — init() activates auto-instrumentation for known provider SDKs; for everything else, wrap your code in a span:

with uptimes_agents.span("execute_plan", hypothesis="db_slow"):
    ...
    uptimes_agents.current_span().set_attribute("steps_taken", 4)

Configuration

Arg / env var	Default	Notes
service_name (kwarg)	required	Becomes agent_name in Uptimes
endpoint / UPTIMES_OTLP_ENDPOINT	http://localhost:4318	OTLP/HTTP target
api_key / UPTIMES_API_KEY	none	Required only on direct-to-cloud
resource_attributes	{}	Extra OTel resource attrs
auto_instrument_providers	True	Set False to manage your own instrumentations

Standard OTel env vars (OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_TRACES_ENDPOINT) are honored — drop-in for existing OTel-instrumented apps.

Routing modes

Default is via the local monitor: spans go to http://localhost:4318 on the host. uptimes-monitor enriches them with host context, batches, and forwards over a single TLS connection to api.uptimes.ai. No API key needed in your app — the monitor's token stamps org_id.

For containerised environments without a host daemon, point straight at the cloud:

uptimes_agents.init(
    service_name="my-agent",
    endpoint="https://api.uptimes.ai/v1/traces/otlp",
    api_key="<your-org-token>",
)

What gets captured

Auto-instrumentation produces OTel-GenAI spans for every Anthropic / OpenAI LLM call:

• Provider, model, token usage, cost
• Latency, time-to-first-chunk, stop reason
• Tool calls (when the provider returns tool_use content)
• Input / output content (governable via OTel content-capture toggles)

Custom span(...) blocks produce regular OTel spans you can group by name in the dashboard.

Versioning

V0.1 — Anthropic + OpenAI auto-instrumentation. Bedrock / Vertex / Gemini land in V0.2.