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Use Case · AI Agents

Agents that stay up and stay in budget.

An autonomous agent fans out dozens of LLM calls per task. Nemo Router keeps a long run alive when a provider degrades, caps each agent with a per-key budget, and logs every tool call for audit.

agent-run · key sk-nemo-7f2a

One agent, one key, one budget

Steps this run24 calls
Fallback usedstep 11
Run statuscompleted
Budget$2.40 / $5.00
Tool calls logged24 / 24
Runaway protection402 ceiling
per-agent keyfailover-safeaudited
Long runs
Stay up

Fallback chains survive a provider blip

Per-agent spend
Budgeted

A 402 stops a runaway loop

Tool calls
100% logged

Every step in the request log

Catalog
97+

models on Anthropic, Google & OpenAI

Why Nemo for agents

Reliability, spend control, and a trail

Agents are unpredictable by design. The gateway makes them dependable: a run that survives a provider blip, a budget it cannot exceed, and a log of everything it did.

Auto-failover for long runs

Agents fan out dozens of calls per task. A provider hiccup at step 11 triggers the next fallback link transparently — step 12 never knows, and the failover is logged.

Per-agent budgets

One virtual key per agent with its own budget. A runaway reasoning loop hits a hard 402 ceiling instead of burning credits; per-key RPM/TPM throttles a misbehaving agent.

Every tool call audited

Planning, tool selection, reflection — every LLM call lands in the request log with model, latency, cost, and result. Filter by the agent’s key to replay a whole run.

Model choice per step

Strong reasoning model for planning, fast model for tool-argument extraction — pick per call from one catalog, no provider account, no SDK swap.

How it works

An agent run, end to end

Each agent carries its own virtual key. Every planning and tool-selection step is a separate LLM call — routed, failover-protected, budget-checked, and logged.

Agent run flow

  1. Agent key

    sk-nemo-... · per agent

    One virtual key per agent — its own budget and rate limit.

  2. Plan + tool calls

    many /chat/completions

    Each reasoning + tool-selection step is a separate call.

  3. Routing + failover

    fallback chain

    A degraded provider triggers the next link — the run survives.

  4. Budget check

    reserve + settle

    Out of budget → 402, before the call. No runaway spend.

  5. Logged per step

    request log

    Model, latency, cost, result — replay the whole run.

The budget check is a reserve-then-settle: credits are reserved before the call and settled at the real cost after. If an agent is out of budget, it gets a 402 — never a surprise overspend.

The code

Point your agent framework at one endpoint

Nemo Router speaks the OpenAI API, so any agent framework that targets the OpenAI SDK works with a base-URL and key change. These snippets are generated from the same SDK examples the playground uses — give each agent its own key and the per-key budget does the rest.

Installpip install openai
1# Cache: enabled (org default). Pass nemo_cache: false to skip.
2from openai import OpenAI
3import os
4
5client = OpenAI(
6 api_key=os.environ["NEMOROUTER_API_KEY"],
7 base_url="https://api.nemorouter.ai/v1",
8)
9
10response = client.chat.completions.create(
11 model="gemini-2.5-flash-lite",
12 temperature=1,
13 max_tokens=1024,
14 top_p=1,
15 messages=[
16 {"role": "user", "content": "Hello! What models do you support?"},
17 ],
18 extra_body={
19 # "nemo_cache": False, # Uncomment to skip cache
20 },
21)
22
23print(response.choices[0].message.content)

Issue one virtual key per agent — spend, rate limits, and the request log all scope to that key.

FAQ

Common agent questions

Reliable, bounded, auditable

Run agents on a gateway built for long runs

Auto-failover, per-agent budgets, and a full tool-call log — unlocked on every plan, behind one Nemo Router key.