Files
openclaw/scripts/docs-chat/serve.mjs
Buns Enchantress 447a3d66c0 feat: add docs chat prototype and related scripts
- Introduced a minimal documentation chatbot that builds a search index from markdown files and serves responses via an API.
- Added scripts for building the index and serving the chat API.
- Updated package.json with new commands for chat index building and serving.
- Created a new Vercel configuration file for deployment.
- Added a README for the docs chat prototype detailing usage and integration.
2026-02-03 01:09:17 -06:00

194 lines
5.2 KiB
JavaScript

#!/usr/bin/env node
/**
* Minimal docs-chat API.
* Env: OPENAI_API_KEY, DOCS_CHAT_INDEX, PORT
*/
import fs from "node:fs";
import path from "node:path";
import { fileURLToPath } from "node:url";
import http from "node:http";
const __dirname = path.dirname(fileURLToPath(import.meta.url));
const defaultIndex = path.join(__dirname, "search-index.json");
const indexPath = process.env.DOCS_CHAT_INDEX || defaultIndex;
const port = Number(process.env.PORT || 3001);
let index = null;
function loadIndex() {
if (index) return index;
if (!fs.existsSync(indexPath)) {
console.error(
`Missing index at ${indexPath}. Run: node scripts/docs-chat/build-index.mjs --out ${defaultIndex}`
);
process.exit(1);
}
index = JSON.parse(fs.readFileSync(indexPath, "utf8"));
return index;
}
const corsHeaders = {
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Methods": "GET, POST, OPTIONS",
"Access-Control-Allow-Headers": "Content-Type",
};
function sendJson(res, status, body) {
res.writeHead(status, { ...corsHeaders, "Content-Type": "application/json" });
res.end(JSON.stringify(body));
}
function scoreChunk(query, chunk) {
const words = query.toLowerCase().split(/\s+/).filter(Boolean);
const text = `${chunk.title} ${chunk.content}`.toLowerCase();
let score = 0;
for (const word of words) {
if (word.length < 2) continue;
if (text.includes(word)) score += 1;
}
return score;
}
function retrieve(query, limit = 8) {
const { chunks } = loadIndex();
const scored = chunks.map((chunk) => ({
chunk,
score: scoreChunk(query, chunk),
}));
scored.sort((a, b) => b.score - a.score);
return scored
.filter((item) => item.score > 0)
.slice(0, limit)
.map((item) => item.chunk);
}
async function streamOpenAI(systemPrompt, userMessage, onToken) {
const apiKey = process.env.OPENAI_API_KEY;
if (!apiKey) throw new Error("OPENAI_API_KEY is required for /chat");
const res = await fetch("https://api.openai.com/v1/chat/completions", {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${apiKey}`,
},
body: JSON.stringify({
model: "gpt-4o-mini",
stream: true,
messages: [
{ role: "system", content: systemPrompt },
{ role: "user", content: userMessage },
],
}),
});
if (!res.ok || !res.body) {
const errorText = await res.text();
throw new Error(`OpenAI ${res.status}: ${errorText}`);
}
const decoder = new TextDecoder();
let buffer = "";
for await (const chunk of res.body) {
buffer += decoder.decode(chunk, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() ?? "";
for (const line of lines) {
const trimmed = line.trim();
if (!trimmed.startsWith("data:")) continue;
const data = trimmed.slice(5).trim();
if (data === "[DONE]") return;
try {
const json = JSON.parse(data);
const delta = json.choices?.[0]?.delta?.content;
if (delta) onToken(delta);
} catch {
// Ignore malformed SSE lines
}
}
}
}
async function handleChat(req, res) {
let body = "";
for await (const chunk of req) body += chunk;
let message = "";
try {
message = JSON.parse(body || "{}").message;
} catch {
sendJson(res, 400, { error: "Invalid JSON" });
return;
}
if (!message || typeof message !== "string") {
sendJson(res, 400, { error: "message required" });
return;
}
const chunks = retrieve(message);
if (chunks.length === 0) {
res.writeHead(200, {
...corsHeaders,
"Content-Type": "text/plain; charset=utf-8",
});
res.end(
"I couldn't find relevant documentation excerpts for that question. Try rephrasing or search the docs."
);
return;
}
const context = chunks
.map(
(chunk) =>
`[${chunk.title}](${chunk.url})\n${chunk.content.slice(0, 1200)}`
)
.join("\n\n---\n\n");
const systemPrompt =
"You are a helpful assistant for OpenClaw documentation. " +
"Answer only from the provided documentation excerpts. " +
"If the answer is not in the excerpts, say so and suggest checking the docs. " +
"Cite sources by name or URL when relevant.\n\nDocumentation excerpts:\n" +
context;
res.writeHead(200, {
...corsHeaders,
"Content-Type": "text/plain; charset=utf-8",
"Transfer-Encoding": "chunked",
});
try {
await streamOpenAI(systemPrompt, message, (token) => {
res.write(token);
});
res.end();
} catch (err) {
console.error(err);
res.end("\n\n[Error contacting OpenAI]");
}
}
const server = http.createServer(async (req, res) => {
if (req.method === "OPTIONS") {
res.writeHead(204, corsHeaders);
res.end();
return;
}
if (req.method === "GET" && (req.url === "/" || req.url === "/health")) {
loadIndex();
sendJson(res, 200, { ok: true, chunks: index.chunks.length });
return;
}
if (req.method === "POST" && req.url === "/chat") {
await handleChat(req, res);
return;
}
sendJson(res, 404, { error: "Not found" });
});
server.listen(port, () => {
loadIndex();
console.error(
`docs-chat API running at http://localhost:${port} (chunks: ${index.chunks.length})`
);
});