ai: migrate LLM backbone from Kimi CLI to Codex CLI
Retires the Moonshot/Kimi subscription in favour of the already-paid ChatGPT plan. Both CLI wrappers now run `codex exec`; the kimi-agent container is gone. adolf-llm + hindsight-llm: - runKimi -> runCodex (`codex exec --json --skip-git-repo-check`), resume via `codex exec resume <thread_id>`. - MCP moves from a per-session .mcp.json (a workaround for Kimi having no --mcp-config-file flag) to a $CODEX_HOME/config.toml generated once at startup from shared-mcp.json. Field translation is load-bearing: bearerTokenEnvVar -> bearer_token_env_var, enabledTools -> enabled_tools. - approval_policy="never" + sandbox_mode required, or unattended turns block on an approval prompt nobody can answer. kimi-agent removed. It was the ONLY large-tier deployment behind LiteLLM, so deleting it outright would have silently degraded every large-tier request to the local 4B model via the existing fallbacks. tier-large, the auto_router complex-reasoning route and their fallbacks now point at the codex-backed adolf-llm wrapper (model_name: codex-agent). Three environment blockers fixed along the way: - OpenAI geo-blocks this host (403 unsupported_country_region_territory). Both containers now egress via the host xray proxy, with NO_PROXY keeping MCP and *.alogins.net traffic off the tunnel. - node:22-slim ships no system CA store; the Rust codex binary validates TLS against it, so every HTTPS call failed with a generic transport error while Node's own fetch worked. ca-certificates added to both images. - `codex exec resume` rejects -C/--cd (plain `codex exec` accepts it), which broke follow-up turns while first turns succeeded. Known regression: Kimi's managed-usage API has no Codex equivalent, so the /usage route returns 501 and there is no quota probe for the codex model. The two quota plugins degrade quietly to no output. Also: stop tracking cognee.env (live LLM + JWT secrets) and gitignore it. The secrets remain in earlier history and should be rotated. Verified live: plain turn, SSE streaming, session resume, MCP tool call, bearer-token MCP call, and completions through both LiteLLM routes. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014Y5QPagv4iun1ghpwM96Ff
This commit is contained in:
197
ai/hindsight-llm/server.js
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197
ai/hindsight-llm/server.js
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const http = require('http');
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const fs = require('fs');
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const path = require('path');
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const crypto = require('crypto');
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const { spawn } = require('child_process');
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const PORT = 8012;
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const MODEL_ID = 'hindsight-llm';
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const TIMEOUT_MS = 5 * 60 * 1000; // one-shot structured calls; generous but bounded
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// Bounded parallelism: SPIKE-FINDINGS.md gate 5 flagged the Kimi subscription as a
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// single-seat, interactive-oriented plan — batch cognify must not hammer it with
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// unbounded concurrent CLI spawns (rate-limit/throttle risk on a shared live account).
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const MAX_CONCURRENCY = 3;
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const WORKSPACE = '/workspace';
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fs.mkdirSync(WORKSPACE, { recursive: true });
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// The CLI has no raw sampling-temperature knob (it's an agent loop, not a
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// completions API) — "low temperature" for structured extraction is enforced
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// via an instruction preamble instead, prepended to whatever system prompt
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// the caller (Cognee) supplies.
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const STRUCTURED_SYSTEM_PREAMBLE = [
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'You are a stateless structured-extraction engine.',
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'This is a one-shot call with no memory of prior calls: do not reference earlier turns.',
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'Respond deterministically and concisely. When asked for JSON, output raw JSON only',
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'- no prose, no markdown code fences, no commentary before or after.',
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].join(' ');
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// --- message helpers ---------------------------------------------------------
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// Text only, no media parts: this wrapper's policy is no-media/no-MCP, unlike
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// adolf-llm which persists inbound images and lets the CLI's ReadMediaFile
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// tool read them.
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function textOf(msg) {
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const c = msg.content;
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if (Array.isArray(c)) return c.map(p => (typeof p.text === 'string' ? p.text : '')).join('\n');
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return c == null ? '' : String(c);
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}
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function buildPrompt(messages) {
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const systemParts = messages.filter(m => m.role === 'system').map(textOf);
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const rest = messages.filter(m => m.role !== 'system');
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const preamble = [STRUCTURED_SYSTEM_PREAMBLE, ...systemParts].join('\n\n');
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const transcript = rest
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.map(m => `${m.role === 'assistant' ? 'Assistant' : 'User'}: ${textOf(m)}`)
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.join('\n\n');
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return `${preamble}\n\n${transcript}`.trim();
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}
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// --- bounded concurrency queue -----------------------------------------------
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let active = 0;
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const queue = [];
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function drain() {
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if (queue.length && active < MAX_CONCURRENCY) queue.shift()();
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}
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function withSlot(fn) {
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return new Promise((resolve, reject) => {
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const run = () => {
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active++;
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fn().then(
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v => { active--; drain(); resolve(v); },
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e => { active--; drain(); reject(e); },
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);
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};
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if (active < MAX_CONCURRENCY) run();
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else queue.push(run);
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});
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}
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// --- codex invocation: stateless one-shot, no resume -------------------------
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// Fresh temp dir per call, no `exec resume`, discard the dir after.
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// Parses `codex exec --json`, which ships two event schemas depending on
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// release (see adolf-llm/server.js for the same dual handling):
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// legacy: {"msg":{"type":"agent_message_delta","delta":"..."}}
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// {"msg":{"type":"agent_message","message":"..."}}
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// newer: {"type":"item.completed","item":{"type":"agent_message","text":...}}
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// Deltas are preferred when present; the terminal full message is a fallback,
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// never an addition, or the extraction output would be duplicated.
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function runCodex({ prompt, cwd }) {
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return new Promise((resolve, reject) => {
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// --skip-git-repo-check: the per-call temp dir is not a git repo.
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const args = ['exec', '--json', '--skip-git-repo-check', '-C', cwd, prompt];
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// stdin 'ignore': otherwise codex waits for EOF on an unused pipe and the
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// call hangs until TIMEOUT_MS. See adolf-llm/server.js for detail.
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const child = spawn('codex', args, {
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cwd,
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timeout: TIMEOUT_MS,
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stdio: ['ignore', 'pipe', 'pipe'],
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});
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let stdout = '';
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let stderr = '';
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child.stdout.on('data', d => { stdout += d; });
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child.stderr.on('data', d => { stderr += d; });
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child.on('error', reject);
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child.on('close', code => {
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const parts = [];
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let finalText = null;
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for (const line of stdout.split('\n')) {
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const t = line.trim();
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if (!t) continue;
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let obj;
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try { obj = JSON.parse(t); } catch { continue; }
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const msg = obj.msg;
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if (msg && typeof msg.type === 'string') {
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if (msg.type === 'agent_message_delta' && msg.delta) parts.push(msg.delta);
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else if (msg.type === 'agent_message' && msg.message) finalText = msg.message;
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continue;
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}
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if (obj.type === 'item.completed' && obj.item && obj.item.type === 'agent_message') {
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const text = typeof obj.item.text === 'string' ? obj.item.text : obj.item.message;
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if (text) finalText = text;
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}
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}
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const text = (parts.join('').trim() || (finalText || '').trim());
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if (!text && code !== 0) {
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reject(new Error(`codex exited ${code}: ${stderr.slice(0, 2000)}`));
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} else {
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resolve(text);
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}
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});
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});
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}
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async function handleTurn(messages) {
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const prompt = buildPrompt(messages || []);
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const reqId = crypto.randomUUID();
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const dir = path.join(WORKSPACE, reqId);
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fs.mkdirSync(dir, { recursive: true });
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try {
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return await withSlot(() => runCodex({ prompt, cwd: dir }));
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} finally {
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// Stateless one-shot: nothing about this call is meant to survive it, so
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// the temp dir is discarded unconditionally, success or failure.
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fs.rm(dir, { recursive: true, force: true }, () => {});
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}
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}
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// --- OpenAI-compatible HTTP surface (non-streaming only) ---------------------
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function completionBody(text) {
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return {
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id: `chatcmpl-${Date.now()}`,
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object: 'chat.completion',
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created: Math.floor(Date.now() / 1000),
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model: MODEL_ID,
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choices: [{
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index: 0,
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message: { role: 'assistant', content: text },
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finish_reason: 'stop',
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}],
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usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
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};
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}
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const server = http.createServer((req, res) => {
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if (req.method === 'GET' && req.url === '/v1/models') {
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res.writeHead(200, { 'Content-Type': 'application/json' });
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res.end(JSON.stringify({
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object: 'list',
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data: [{ id: MODEL_ID, object: 'model', owned_by: 'openai' }],
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}));
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return;
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}
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if (req.method === 'POST' && req.url === '/v1/chat/completions') {
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let body = '';
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req.on('data', d => { body += d; });
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req.on('end', async () => {
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let parsed;
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try {
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parsed = JSON.parse(body);
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} catch {
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res.writeHead(400, { 'Content-Type': 'application/json' });
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res.end(JSON.stringify({ error: 'invalid JSON body' }));
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return;
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}
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try {
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const text = await handleTurn(parsed.messages || []);
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// Non-streaming policy: always return the full body even if the
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// caller sets stream:true. Cognee's batch cognify has no use for SSE,
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// and a one-shot call has nothing to incrementally stream anyway.
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res.writeHead(200, { 'Content-Type': 'application/json' });
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res.end(JSON.stringify(completionBody(text)));
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} catch (err) {
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res.writeHead(500, { 'Content-Type': 'application/json' });
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res.end(JSON.stringify({ error: String(err.message || err) }));
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}
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});
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return;
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}
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res.writeHead(404, { 'Content-Type': 'application/json' });
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res.end(JSON.stringify({ error: 'not found' }));
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});
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server.listen(PORT, () => console.log(`hindsight-llm wrapper listening on :${PORT}`));
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