For developers

Build against Eldric
like you would against OpenAI.

The public API is OpenAI-compatible. Tooling written for the OpenAI SDK works against an Eldric server with one line changed — the base URL. The full reference lives in the documents below.


Three documents

Pick the one that fits your level.

api-public

Edge-reachable endpoints only. One line per endpoint. The first place to look if you are integrating from outside the LAN.

api-endpoints

The complete endpoint surface, grouped by component (Edge, Controller, Router, Data, Agent, Media, Comm, Science, Training, IoT, Swarm, NOVA, etc.).

features-catalog

Eighteen domains, every shipped feature, what is currently work-in-progress. The catalogue behind every page on the site.


Talking to an Eldric server

Drop-in OpenAI replacement.

Assuming an Eldric server is reachable at https://eldric.local and you have an API key from the Admin Console, your existing OpenAI-shaped code works unchanged after pointing the base URL at Eldric.

Need to install Eldric first? Start at get-started; the post-install setup (admin signup, license, first KB) lives on first-run. This page assumes the server is already up.

Curl

curl https://eldric.local/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.3-70b",
    "messages": [{"role":"user","content":"Hello."}],
    "stream": true
  }'

OpenAI SDK (Python)

from openai import OpenAI
client = OpenAI(
    base_url="https://eldric.local/v1",
    api_key="$API_KEY",
)
resp = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role":"user","content":"Hello."}],
)

Existing tooling — LangChain, LlamaIndex, Continue, Cursor, anything that consumes the OpenAI API — works after pointing the base URL at Eldric.


Going deeper

Beyond chat.

Agents & workflows

Build a multi-step ReAct loop with /api/v1/agent/chat. Decompose complex queries with /api/v1/agent/decompose. Run multiple agents in parallel with /api/v1/agent/multi.

Training

Create a fine-tune job at /api/v1/jobs with LoRA, QLoRA, SFT, or DPO. The dataset can be local JSONL or pulled from a data worker.

Plugins

Plugins are Python or JavaScript add-ons that the chat shell loads at runtime. Five plugin types: Tool, Filter, Pipe, Action, Widget. Install from the marketplace at /api/v1/marketplace/catalog.

Webhooks

Subscribe to events at /api/v1/webhooks/subscriptions. Each outbound POST is signed with HMAC-SHA256. Failed deliveries auto-disable after the threshold.

xLSTM workloads

The xlstmd daemon hosts brain-inspired predictive workloads — policy execution, multi-horizon forecasting, vision encoding, associative retrieval — behind a single OpenAI-compatible endpoint. See xlstmd page.