@stackline/ai-server
Fetch-compatible HTTP backend handler for Stackline AI.
Documentation | npm | Issues | Repository
Current package version: 0.0.6
Why this package?
@stackline/ai-server gives the browser one safe backend API without exposing provider keys, Ollama targets, SQL, or memory paths. It is Fetch-compatible by design and can be adapted to Node HTTP, Express, or other runtimes that can create Web Request and Response objects.
What This Package Does
This package turns a StacklineAIServer from @stackline/ai into HTTP routes:
GET /api/ai/healthGET /api/ai/manifestGET /api/ai/modelsPOST /api/ai/chatOPTIONS /api/ai/*
It expects Web Fetch API Request objects and returns Web Fetch API
Response objects.
It is not an Express middleware by itself.
When To Use
Use this package when a browser UI needs one safe backend API for health, manifest, model listing, and chat.
Compatibility
| Item | Value |
|---|---|
| Package | @stackline/ai-server@0.0.6 |
| Supported Node.js | >=18.17.0 |
| Module entry | dist/index.js (ES modules) |
| Types | dist/index.d.ts |
| Runtime dependencies | 1 direct dependency |
Status
Initial public API, ESM-only, TypeScript declarations included.
Requirements
- Runtime: Node.js
>=18.17.0. - A
StacklineAIServerfrom@stackline/ai. - Web Fetch API
RequestandResponse.
When Not To Use
Do not pass this handler directly to Express as app.use(handleAI). Express
uses req/res, while this package expects Web Request and returns Web
Response.
Limitations
The current chat response is non-streaming. Request bodies are consumed as a
bounded stream, so maxBodyBytes stops oversized input before the complete
payload is buffered.
Installation
Install By Situation
HTTP Handler With A Custom Provider
npm init -y
npm pkg set type=module
npm install @stackline/ai @stackline/ai-server
HTTP API With Ollama
npm init -y
npm pkg set type=module
npm install @stackline/ai @stackline/ai-server @stackline/ai-ollama
HTTP API With Ollama And Browser UI
npm init -y
npm pkg set type=module
npm install @stackline/ai @stackline/ai-server @stackline/ai-ollama @stackline/ai-ui
npm install -D vite
mkdir -p src
Express Backend
npm init -y
npm pkg set type=module
npm install express @stackline/ai @stackline/ai-server @stackline/ai-ollama
Add @stackline/ai-ui and vite only if this Express backend also serves a
browser app.
Usage
Complete Node HTTP Example
import { createServer } from "node:http";
import { createStacklineAIServer } from "@stackline/ai/server";
import { createStacklineAIHttpHandler } from "@stackline/ai-server";
import { ollamaProvider } from "@stackline/ai-ollama";
async function requestFromNode(req) {
const chunks = [];
for await (const chunk of req) chunks.push(chunk);
return new Request(`http://${req.headers.host || "localhost"}${req.url}`, {
method: req.method,
headers: req.headers,
body: chunks.length ? Buffer.concat(chunks) : undefined,
});
}
async function writeNodeResponse(res, response) {
res.statusCode = response.status;
response.headers.forEach((value, key) => res.setHeader(key, value));
res.end(Buffer.from(await response.arrayBuffer()));
}
const model = process.env.OLLAMA_MODEL || "auto";
if (!model.trim()) throw new Error("OLLAMA_MODEL is empty.");
const ai = createStacklineAIServer({
provider: ollamaProvider({
target: process.env.OLLAMA_TARGET || "http://127.0.0.1:11434",
model,
}),
rag: false,
memory: false,
});
const handleAI = createStacklineAIHttpHandler({
server: ai,
basePath: "/api/ai",
allowedModels: process.env.STACKLINE_AI_ALLOWED_MODELS
? process.env.STACKLINE_AI_ALLOWED_MODELS.split(",").map((item) => item.trim()).filter(Boolean)
: undefined,
maxBodyBytes: 256 * 1024,
cors: {
origins: [process.env.WEB_ORIGIN || "http://localhost:4623"],
},
});
const server = createServer(async (req, res) => {
try {
const response = await handleAI(await requestFromNode(req));
await writeNodeResponse(res, response);
} catch (cause) {
const message = cause instanceof Error ? cause.message : "Unexpected server error.";
res.writeHead(500, { "content-type": "application/json; charset=utf-8" });
res.end(JSON.stringify({ error: { message, status: 500 } }));
}
});
server.listen(Number(process.env.PORT || 8787), () => {
console.log("Stackline AI API: http://127.0.0.1:8787/api/ai");
});
Express Adapter
Use an adapter that converts Express req/res to Web Request/Response.
Do not run express.json() before this route, because the Stackline handler
reads the request body.
import express from "express";
import { createStacklineAIServer } from "@stackline/ai/server";
import { createStacklineAIHttpHandler } from "@stackline/ai-server";
import { ollamaProvider } from "@stackline/ai-ollama";
async function requestFromExpress(req) {
const chunks = [];
for await (const chunk of req) chunks.push(chunk);
return new Request(`${req.protocol}://${req.get("host")}${req.originalUrl}`, {
method: req.method,
headers: req.headers,
body: chunks.length ? Buffer.concat(chunks) : undefined,
});
}
async function writeExpressResponse(res, response) {
res.status(response.status);
response.headers.forEach((value, key) => res.setHeader(key, value));
res.send(Buffer.from(await response.arrayBuffer()));
}
const ai = createStacklineAIServer({
provider: ollamaProvider({
target: process.env.OLLAMA_TARGET || "http://127.0.0.1:11434",
model: process.env.OLLAMA_MODEL || "auto",
}),
rag: false,
memory: false,
});
const handleAI = createStacklineAIHttpHandler({
server: ai,
basePath: "",
});
const app = express();
app.use("/api/ai", async (req, res, next) => {
try {
const response = await handleAI(await requestFromExpress(req));
await writeExpressResponse(res, response);
} catch (error) {
next(error);
}
});
app.listen(8788, () => {
console.log("Express API: http://127.0.0.1:8788/api/ai");
});
Verify The Routes
curl http://127.0.0.1:8787/api/ai/health
curl http://127.0.0.1:8787/api/ai/manifest
curl http://127.0.0.1:8787/api/ai/models
curl -i -X OPTIONS http://127.0.0.1:8787/api/ai/chat \
-H 'origin: http://localhost:4623' \
-H 'access-control-request-method: POST'
curl http://127.0.0.1:8787/api/ai/chat \
-H 'content-type: application/json' \
-d '{"model":"llama3.1","messages":[{"role":"user","content":"Hello"}]}'
Features
| Feature | Supported |
|---|---|
GET /health |
✅ |
GET /manifest |
✅ |
GET /models |
✅ |
POST /chat |
✅ |
| CORS handling | ✅ |
| Request body limit | ✅ |
| Allowed model policy | ✅ |
| Fetch-compatible handler | ✅ |
| Express adapter example | ✅ |
Security
Add authentication, authorization, rate limiting, restrictive CORS, body limits, and model allow-lists in production.
API Surface
Public API
createStacklineAIHttpHandler(options)StacklineAIHttpHandlerStacklineAIHttpHandlerOptionsStacklineAICorsOptions
Configuration
createStacklineAIHttpHandler({
server: ai,
basePath: "/api/ai",
allowedModels: ["llama3.1"],
maxBodyBytes: 256 * 1024,
cors: {
origins: ["https://app.example.com"],
credentials: true,
},
});
Request And Response Schemas
POST /chat accepts:
{
"model": "llama3.1",
"messages": [
{ "role": "user", "content": "Hello" }
],
"temperature": 0.2,
"metadata": {
"sessionId": "demo-session",
"userId": "user-1"
}
}
POST /chat returns:
{
"message": {
"role": "assistant",
"content": "Hello.",
"model": "llama3.1"
},
"content": "Hello.",
"model": "llama3.1"
}
Error Handling
Errors are JSON:
{ "error": { "message": "messages must be an array.", "status": 400 } }
Oversized bodies return 413, model allow-list failures return 403, and
other validation/provider failures return 400. When allowedModels is set,
the client must send an explicit model value.
The common Ollama model error:
Ollama chat requires a model. Use a model name or model: "auto".
means the request model and provider model were empty, or auto could not find
an installed model from Ollama /api/tags.
Documentation
- Full tutorial:
docs/getting-started/full-stack-tutorial.md - HTTP reference:
docs/reference/http-api.md
Local Development
Clone the monorepo and run from its root. Repository tooling requires Node.js >=22.13.0 and pnpm@11.22.0; release archives use official Node.js 24.20.0 and npm 11.19.0.
pnpm install --frozen-lockfile
pnpm --filter @stackline/ai-server build
pnpm --filter @stackline/ai-server test
pnpm run check
Consumer Smoke Test
Test The Example
pnpm --filter stackline-ai-example-express-adapter smoke
Pack the release family and validate a fresh consumer, including runtime exports and TypeScript declarations:
pnpm run pack:release
node scripts/consumer-smoke.mjs release-artifacts
Release Checklist
Versioning
Use the same release line as @stackline/ai.
- Update the package manifest, changelog, workspace references, and documentation together.
- Run the workspace checks plus
pnpm auditandpnpm audit --prod. - Use publish.yml and confirm
expected_manifest_sha512against the reviewedSHA512SUMSfile. - Verify each public package's exact bytes and GitHub Actions provenance.
License
MIT. Copyright notices and the credits above are retained.
Credits and original authors
- Stackline.
- Copyright (c) 2026 Alexandro Marques.
- Stackline maintenance: Alexandro Paixao Marques and Stackline contributors.
Original copyright, license notices and contributor acknowledgements remain part of this distribution. Stackline maintenance does not replace authorship of the original work.
Community and Links
Use this repository's issue tracker for reproducible bugs and feature requests. Join r/Stackline for examples, usage questions and release discussions.