Quickstart

1. Install

Pick the extra that matches your LLM library:

pip install "eldros-sdk[openai]"        # or [anthropic] / [claude-agent-sdk]

2. Initialize

Set your agent’s API key (generated from its Configuration → Trace API Keys page on the Eldros dashboard — one key per agent), then call init() once at agent startup — before your event loop:

export ELDROS_API_KEY=agt_...

import eldros_sdk

eldros_sdk.init(traffic_type="prod")

This resolves your config, turns the pipeline on, and auto-instruments your LLM library — every model call becomes a trace span with no change to your model code. The extra you installed in step 1 is the switch: installed means instrumented, and init() kwargs or env vars can override it — see LLM tracing.

3. Capture conversations

Wrap each user↔agent exchange in a turn:

with eldros_sdk.turn(user_msg, session_id=conversation_id) as t:
    reply = await agent.respond(user_msg)   # LLM call nests under the turn automatically
    t.reply(reply)                          # records the assistant turn

That’s it — every conversation is now assembled, judged, and surfaced in the Eldros dashboard, with each LLM call nested under its turn.

Verify it works

Send one message through your agent, then check the dashboard: you should see the conversation with its turn, and the LLM span nested underneath. If nothing appears, the SDK logs a warning explaining what’s missing — capture problems fail loudly, never silently.

Getting started

Capture

Integrations

Concepts

1. Install

2. Initialize

3. Capture conversations

Verify it works

​1. Install

​2. Initialize

​3. Capture conversations

​Verify it works

1. Install

2. Initialize

3. Capture conversations

Verify it works