Documentation
Everything you need to take agents, models and automations to production with AICore. REST endpoints, typed SDKs, runnable examples and deployment best practices.
Quickstart
Install the SDK and make your first call in under 2 minutes.
# npm
npm install @aicore/sdk
# python
pip install aicorebashimport { AICore } from "@aicore/sdk";
const ai = new AICore({ apiKey: process.env.AICORE_KEY });
const res = await ai.chat.completions.create({
model: "atlas-70b",
messages: [{ role: "user", content: "Summarize this email" }],
});
console.log(res.choices[0].message.content);typescriptPlayground
Try the models right from the docs. Pick a model, ask a question and stream the response.
Prova una di queste domande:
Authentication
All requests require a Bearer token. Keys are managed from the workspace panel with per-environment scope (dev / staging / prod) and automatic rotation every 90 days.
curl https://api.aicore.dev/v1/chat/completions \
-H "Authorization: Bearer $AICORE_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"atlas-70b","messages":[{"role":"user","content":"hello"}]}'bashREST API
Base URL https://api.aicore.dev/v1. All endpoints support streaming via SSE, function calling and response_format JSON-schema.
/chat/completionsChat completion (optional streaming).
/embeddingsSemantic embeddings 1024d/3072d.
/agents/runsRun an agent with tool calling.
/agents/runs/:idStatus and trace of a run.
/filesUpload documents for RAG (PDF, MD, DOCX).
/evalsRun an eval suite.
SDKs
First-class official SDKs in TypeScript, Python and Go. Exponential retry, streaming, typed responses.
TypeScript
v2.4.1npm i @aicore/sdkPython
v2.4.0pip install aicoreGo
v1.8.2go get aicore.dev/sdkWebhooks
Receive real-time events for completed runs, failures and processed batches. HMAC-SHA256 signature.
{
"id": "evt_01J9Z7...",
"type": "agent.run.completed",
"data": {
"run_id": "run_xyz",
"agent": "sales-qualifier",
"duration_ms": 4318,
"tokens": { "in": 1240, "out": 410 }
},
"created_at": "2026-06-17T14:22:01Z"
}jsonModels
atlas-70bFrontier reasoning, advanced function calling.
helix-8bFast and cheap for high-volume tasks.
mosaic-visionMultimodal: documents, screenshots, OCR.
ember-embed-33072d embeddings for semantic retrieval.
Agents
Define agents with tool calling, persistent memory and guardrails. Run sandbox-isolated.
const agent = ai.agents.define({
name: "sales-qualifier",
model: "atlas-70b",
tools: [hubspot.getDeals, gmail.draftReply],
guardrails: ["no-pii-leak", "tone-professional"],
});
const run = await agent.run({ input: "Qualify today's leads" });typescriptCookbooks
RAG with verifiable citations
Cookbook · ~15 min
Sales agent on HubSpot
Cookbook · ~15 min
Document AI: invoice extraction
Cookbook · ~15 min
Evals with golden dataset
Cookbook · ~15 min
Fine-tuning on Helix 8B
Cookbook · ~15 min
Streaming with SSE in React
Cookbook · ~15 min