> ## Documentation Index > Fetch the complete documentation index at: https://docs.latitude.so/llms.txt > Use this file to discover all available pages before exploring further. # Strands Agents > Connect your Strands Agents application to Latitude for observability. **Using an agent?** Install the [Latitude skills](/getting-started/skills) and let it handle the setup below. `latitude-setup` instruments your app or agent harness, verifies traces arrive, creates a temporary account if you don't have one yet (no signup), and ends by building your first [Artifact](/more/artifacts). ```text theme={"theme":{"light":"github-light","dark":"github-dark"}} theme={"theme":{"light":"github-light","dark":"github-dark"}} Install the `latitude-setup` skill from `github.com/latitude-dev/skills` and use it to set up Latitude tracing here. ``` ## Overview This guide shows you how to integrate **Latitude Telemetry** into an application that uses **Strands Agents** — AWS's open-source AI agents SDK. No Latitude account yet? Your agent can create a temporary one and do this whole setup with the [`latitude-setup` skill](/getting-started/skills), no signup. Strands Agents has first-class OpenTelemetry support built in (`strands-agents[otel]`). It emits standard `gen_ai.*` spans for every agent run, LLM call, and tool execution, so you can point Strands' OTLP exporter directly at Latitude's ingestion endpoint — no Latitude SDK required. You'll keep using Strands Agents exactly as you do today. The exporter simply sends your traces to Latitude alongside any other observability backend. The Strands Agents integration is **Python only**. *** ## Requirements * A **Latitude account** and **API key**, or none yet: your agent can create a temporary account with the [`latitude-setup` skill](/getting-started/skills), no signup * A **Latitude project slug** * A Python project that uses **Strands Agents** (`strands-agents`) *** ## Steps ```bash pip theme={"theme":{"light":"github-light","dark":"github-dark"}} pip install 'strands-agents[otel]' ``` ```bash uv theme={"theme":{"light":"github-light","dark":"github-dark"}} uv add 'strands-agents[otel]' ``` ```bash poetry theme={"theme":{"light":"github-light","dark":"github-dark"}} poetry add 'strands-agents[otel]' ``` Set the required environment variables so Strands sends traces to Latitude: ```bash theme={"theme":{"light":"github-light","dark":"github-dark"}} export OTEL_EXPORTER_OTLP_ENDPOINT="https://ingest.latitude.so" export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer YOUR_API_KEY,X-Latitude-Project=YOUR_PROJECT_SLUG" export OTEL_EXPORTER_OTLP_TRACES_PROTOCOL="http/protobuf" export OTEL_SEMCONV_STABILITY_OPT_IN="gen_ai_latest_experimental" ``` `OTEL_EXPORTER_OTLP_ENDPOINT` is the **base URL** — the OTel SDK automatically appends `/v1/traces`. Do not include the path yourself or traces will fail to reach Latitude. Then initialize telemetry before creating your agent: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from strands import Agent from strands.telemetry.config import StrandsTelemetry # Initialize and configure the OTLP exporter (reads env vars above) telemetry = StrandsTelemetry() telemetry.setup_otlp_exporter() # Your agent code is unchanged agent = Agent( system_prompt="You are a helpful assistant.", ) result = agent("Summarize the key features of AWS Strands Agents.") print(result) ``` Getting traces into Latitude is only half the job. For Latitude to display the model name, token counts, and input/output messages, your spans must carry the right `gen_ai.*` attributes in the format Latitude expects. `OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental` (set in the previous step) tells Strands to emit these attributes automatically. See [GenAI Span Attributes](/telemetry/otel-exporter#genai-span-attributes-llm-metadata) for the full list of required attributes and the exact message format Latitude expects. *** ## What you get Each agent run shows up as a trace with nested spans: * **Agent spans** — agent name, ID, description, user message, full response, total token usage * **Cycle spans** — one span per event-loop cycle with `event_loop.cycle_id` * **LLM spans** — model invocations with input/output messages, token counts (prompt, completion, cache), model parameters * **Tool spans** — tool name, input arguments, output result, and `tool.status` *** ## Seeing Your Traces Once connected, traces appear automatically in Latitude: 1. Open your **project** in the Latitude dashboard 2. Each agent run shows the full hierarchy: agent → LLM calls → tool executions 3. Token usage and latency are aggregated at every level ## See what was captured Once a real run has landed, your agent builds your first [Artifact](/more/artifacts): a single HTML page, in the Latitude look, with everything the telemetry captured from that session: model calls, tool calls, tokens, cost, timing, and the conversation as the model saw it. It is the fastest way to check the integration end to end and to see what Latitude will have to work with. The `latitude-setup` skill does this as its last step from its bundled `first-artifact.html` template, filling the page with the values the `latitude` CLI returns for the trace, and adds a **Claim your workspace** button when the account is temporary. If you set things up by hand, the same template and instructions live in the [skills repo](https://github.com/latitude-dev/skills/tree/main/skills/latitude-setup). Prompt, if you need to ask for it: ```text theme={"theme":{"light":"github-light","dark":"github-dark"}} theme={"theme":{"light":"github-light","dark":"github-dark"}} Build my first Latitude Artifact from the session that just landed, using the first-artifact.html template from the latitude-setup skill (github.com/latitude-dev/skills). ```