[ REFERENCE ]
Agents
Agents are callable as models. Every agent on your platform is a model named assistiv-ai/<agent-slug> on the OpenAI-compatible endpoints — same request shape, same streaming, same governance as plain inference.
ℹProvisioning is invite-only
Agents are set up per platform during white-glove onboarding. If you don't have one yet, talk to the founders and we'll configure it with you — model, instructions, tools, and skills included.
Call an agent
Use the end-user's sk-eu_*key and the agent's model name. Works on /v1/chat/completions and /v1/responses.
curl -X POST https://api.assistiv.ai/v1/chat/completions \
-H "Authorization: Bearer $END_USER_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "assistiv-ai/support-bot",
"messages": [{"role":"user","content":"Summarize ticket #4812 and draft a reply"}],
"thread_id": "thread_4812",
"stream": true
}'What you get on every run
Multi-turn sessions
Pass thread_id to continue a conversation. Agent state persists server-side per thread — no message replay from your app.
Tools and skills
Agents use their configured tools, hosted MCP apps, and skills during a run. You can also pass request-level tools exactly as with plain inference.
Streaming
stream: true yields server-sent events, matching the OpenAI streaming format.
Governance built in
Budget pre-flight before the run, per-token and per-tool debits during it, and one audit-ready log row after it. A 402 means the wallet or budget gate fired — same semantics as any inference call.
Scope and limits
Agents are API-invoked: a run starts when you call the endpoint, and there is no scheduler or background trigger. Session memory is per-thread; agents do not learn across threads.