Sample Agents

The repository ships seven runnable agents under samples/, each demonstrating a different framework and a different way of getting traces into the Agent Manager. Start from whichever one is closest to what you are building rather than from an empty directory.

Choosing a Sample

Sample	Framework	Instrumentation	Start Here If You Want
crewai-agent	CrewAI	Zero-code	A multi-agent crew with sequential tasks
customer-support-agent	LangGraph	Zero-code	A multi-tool agent backed by a real database
dotnet-agent	Microsoft Agent Framework (.NET)	Native OpenTelemetry	An agent in a language AMP does not auto-instrument
hotel-booking-agent	LangGraph	Zero-code	Retrieval over your own documents, plus a second service
insurance-support-agent	Strands	Zero-code	A complete agent with a web UI and gateway login
it-helpdesk-agent	LangChain	Zero-code	Evaluation monitors and guardrails on a governed workflow
manual-instrumentation-agent	None (plain Python)	Manual	Full control over every span your agent emits

Zero-code means the Agent Manager injects instrumentation at deploy time and the sample contains no tracing code. Manual and native samples emit their own spans. See AMP Instrumentation for how the two paths differ.

Two of the seven run in CI

customer-support-agent and crewai-agent are deployed and trace-verified on every release by the instrumentation matrix (deployable_samples.py). The other five are maintained by hand, so pin versions yourself if you build on them.

Before You Start

Every sample needs an LLM key, and all the Python samples target Python 3.11:

export OPENAI_API_KEY="your-key"

Most samples are Platform-Hosted, meaning you point the Agent Manager at the sample's directory and it builds and runs the agent for you. Follow Create Your First Agent and set App Path to the path given below for each sample. Two samples run on your own machine as Externally-Hosted agents instead, and say so.

No sample uses MCP tools. To see those, follow Configure Agent MCP Proxies separately.

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crewai-agent

Two agents working in sequence. A researcher answers a question using a lookup tool, then an editor compresses the answer to a single sentence.

This is the smallest sample that produces agent and crewaitask spans, so it is the quickest way to see a multi-agent trace tree in the Console.

• App Path — /samples/crewai-agent
• Requires — OPENAI_API_KEY
• Installs — crewai==1.15.2

CrewAI writes under $HOME when it is imported and again when a crew is constructed, and the build container's default home is not writable. The sample already handles this: app.py sets CREWAI_STORAGE_DIR and falls back to HOME=/tmp when the real home is read-only, before CrewAI is imported. Keep that preamble if you adapt the sample, or set HOME and CREWAI_STORAGE_DIR to writable paths on the agent yourself.

Run it locally:

cd samples/crewai-agent
pip install -r requirements.txt
python main.py
# Serves on port 8000

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customer-support-agent

A travel support assistant covering flights, hotels, car rentals, and excursions, backed by a PostgreSQL dataset. It is based on the LangGraph customer-support tutorial, so it is the closest of the samples to a conventional production app.

• App Path — /samples/customer-support-agent
• Requires — OPENAI_API_KEY, TAVILY_API_KEY, and DATABASE_URL pointing at a PostgreSQL instance loaded with the bundled db_backup.sql
• Start Command — python main.py

Dependencies are unpinned

This sample's requirements.txt lists LangGraph and LangChain without version constraints, so a build resolves whatever is current that day. If you want a reproducible build, pin the versions before deploying.

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dotnet-agent

A weather assistant written in .NET that calls a GetWeather tool. It runs on your own machine and pushes traces to the Agent Manager over OTLP.

Pick this one when your agent is not written in Python. It shows the whole externally-hosted path: register the agent, take the API key, and point an OpenTelemetry exporter at the AMP endpoint. AmpTelemetry.cs is the part worth reading, since it is where the endpoint and the x-amp-api-key header get configured.

• Runs — externally hosted, on your machine
• Requires — .NET 10 SDK, OPENAI_API_KEY, plus AMP_OTEL_ENDPOINT and AMP_AGENT_API_KEY from a registered externally-hosted agent

cd samples/dotnet-agent
dotnet run
# Serves on http://localhost:8000

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hotel-booking-agent

A hotel assistant that searches availability, creates and cancels bookings, and answers policy questions from PDFs held in a Pinecone index.

This is the retrieval sample, and the only one split across two deployables: the agent itself plus a separate Hotel API service it calls over HTTP. Deploy the Hotel API first so the agent has something to talk to.

• App Path — /samples/hotel-booking-agent/agent, which is a subdirectory rather than the sample root
• Requires — OPENAI_API_KEY, PINECONE_API_KEY, PINECONE_SERVICE_URL, and HOTEL_API_BASE_URL

Pinecone is required for the agent, whatever the sample README says

The sample's own README describes Pinecone as optional. That is true of the Hotel API service, but the agent declares pinecone_api_key and pinecone_service_url as settings with no defaults, so it raises on startup when either is missing. Provide both.

Run the Hotel API first:

cd samples/hotel-booking-agent/services/hotel_api
pip install -r requirements.txt
python -m uvicorn service:app --host 0.0.0.0 --port 9091

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insurance-support-agent

An insurance support agent over in-memory policies and claims. It can list policies, check what a policy covers, look up claim status, and file a claim.

This is the most complete sample end to end: it ships a React chat client that logs in through the gateway, so it is the one to read if you want to see agent authentication and CORS configured together. It is also the only Strands sample.

• App Path — /samples/insurance-support-agent/agent
• Requires — OPENAI_API_KEY only, with no database or external service

The agent sets OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental before importing Strands. Leave that in place if you adapt this sample, because without it tool inputs and outputs never reach the span attributes and the Console shows tool calls with empty payloads.

cd samples/insurance-support-agent/agent
pip install -r requirements.txt
export CORS_ALLOW_ORIGINS="http://localhost:5173"
python main.py

Sessions are keyed on a caller-supplied value

This sample resumes a conversation from the session_id in the request rather than from the authenticated user, so anyone holding a valid token and a known session_id can continue someone else's conversation. Sessions are also in-process and capped. Treat it as demonstration code, not a session-handling pattern to copy.

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it-helpdesk-agent

An L1 IT helpdesk agent that handles password resets, software access requests, and ticketing. It verifies a caller's identity before acting, refuses admin password resets, detects duplicate tickets, and escalates to L2.

Pick this one to explore governance. Its rules make agent behaviour easy to assert against, and its README walks through building a Sequence Adherence monitor that checks the agent looked up an employee before verifying their identity. It can also route through an LLM Service Provider so you can attach a prompt-decorator guardrail.

• App Path — /samples/it-helpdesk-agent
• Requires — OPENAI_API_KEY. All data is JSON fixtures in the sample, so there is nothing external to set up
• Optional — set USE_LLM_PROVIDER=true with LLM_PROVIDER_URL and LLM_PROVIDER_KEY to route through a registered provider

See Evaluation Monitors for the monitor side of this.

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manual-instrumentation-agent

A small retrieval agent over a bundled knowledge base, written in plain Python with no agent framework, that emits every AMP span kind by hand.

This is the executable reference for the manual instrumentation contract. instrumentation.py has one helper per span kind, so if your framework is not covered by auto-instrumentation, this file shows exactly what to emit for the Console to render your traces correctly.

• Runs — either externally hosted or platform hosted
• Requires — OPENAI_API_KEY, AMP_OTEL_ENDPOINT, and AMP_AGENT_API_KEY
• App Path — /samples/manual-instrumentation-agent when platform hosted

Turn auto-instrumentation off for this one

When you deploy this sample to the platform, set instrumentation to Off in the agent's configuration. The sample calls init_otel() itself, and leaving auto-instrumentation on means both paths emit spans for the same operations.

cd samples/manual-instrumentation-agent
pip install -r requirements.txt
python main.py

Note there is no amp-instrument prefix here. That wrapper is for the automatic path.

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What's Next

Topic	Guide
Deploy one of these into your own environment	Create Your First Agent
See the traces a sample produces	Observe Your First Agent
Instrument an agent of your own	AMP Instrumentation
Score agent behaviour automatically	Evaluation Monitors