refactor: capture plain-text CLI output, drop hardcoded provider schemas

The adapters parsed each vendor's proprietary JSON stream (Claude json,
Codex JSONL, Gemini stream-json) to extract tokens/tool-calls, and a
per-model pricing table turned tokens into cost. That coupling was the
brittle hardcoding GStack 2 exists to avoid — it broke every time a vendor
reshuffled its output, and it duplicated what any tool that instruments the
real model call already does. Braintrust owns scoring; it can't see a CLI
subprocess's tokens anyway, so computing cost ourselves meant maintaining
both a parser and a price table forever.

Now each adapter runs the CLI in plain-text mode and returns stdout. Scoring
is unchanged (Braintrust reads the text). RunResult drops tokens/toolCalls;
the comparison table drops the Tokens/Cost columns. Deletes pricing.ts, all
three JSON parsers, and the Gemini stream-schema parser + its test. Gemini
auth detection (env/OAuth/.env) is kept — that's not schema parsing.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Sinabina
2026-07-21 14:34:57 -07:00
co-authored by Claude Opus 4.8
parent 36f972f2e4
commit 7f4574e1d5
12 changed files with 84 additions and 441 deletions
+17 -76
View File
@@ -1,16 +1,13 @@
import type { ProviderAdapter, RunOpts, RunResult, AvailabilityCheck } from './types';
import { estimateCostUsd } from '../pricing';
import type { ProviderAdapter, RunOpts, RunResult, AvailabilityCheck, RunError } from './types';
import { execFileSync, spawnSync } from 'child_process';
import * as fs from 'fs';
import * as path from 'path';
import * as os from 'os';
/**
* GPT adapter — wraps the OpenAI `codex` CLI (codex exec with --json output).
* GPT adapter — wraps the OpenAI `codex` CLI (`codex exec`) in plain-text mode.
*
* Codex uses ~/.codex/ for auth (not OPENAI_API_KEY). The --json flag emits
* JSONL events; we parse `turn.completed` for usage and `agent_message` / etc.
* for output aggregation.
* Captures stdout as the answer; no JSON-event parsing. Scoring is Braintrust's job.
*/
export class GptAdapter implements ProviderAdapter {
readonly name = 'gpt';
@@ -36,7 +33,7 @@ export class GptAdapter implements ProviderAdapter {
// often run in temp dirs / non-git paths), so the read-only sandbox is now
// the only boundary preventing codex from mutating the workdir. If you ever
// remove `-s read-only`, drop `--skip-git-repo-check` too.
const args = ['exec', opts.prompt, '-C', opts.workdir, '-s', 'read-only', '--skip-git-repo-check', '--json'];
const args = ['exec', opts.prompt, '-C', opts.workdir, '-s', 'read-only', '--skip-git-repo-check'];
if (opts.model) args.push('-m', opts.model);
if (opts.extraArgs) args.push(...opts.extraArgs);
@@ -47,81 +44,25 @@ export class GptAdapter implements ProviderAdapter {
encoding: 'utf-8',
maxBuffer: 32 * 1024 * 1024,
});
const parsed = this.parseJsonl(out);
return {
output: parsed.output,
tokens: parsed.tokens,
output: out.trim(),
durationMs: Date.now() - start,
toolCalls: parsed.toolCalls,
modelUsed: parsed.modelUsed || opts.model || 'gpt-5.4',
modelUsed: opts.model ?? 'gpt',
};
} catch (err: unknown) {
const durationMs = Date.now() - start;
const e = err as { code?: string; stderr?: Buffer; signal?: string; message?: string };
const stderr = e.stderr?.toString() ?? '';
if (e.signal === 'SIGTERM' || e.code === 'ETIMEDOUT') {
return this.emptyResult(durationMs, { code: 'timeout', reason: `exceeded ${opts.timeoutMs}ms` }, opts.model);
}
if (/unauthorized|auth|login/i.test(stderr)) {
return this.emptyResult(durationMs, { code: 'auth', reason: stderr.slice(0, 400) }, opts.model);
}
if (/rate[- ]?limit|429/i.test(stderr)) {
return this.emptyResult(durationMs, { code: 'rate_limit', reason: stderr.slice(0, 400) }, opts.model);
}
return this.emptyResult(durationMs, { code: 'unknown', reason: (e.message ?? stderr ?? 'unknown').slice(0, 400) }, opts.model);
return this.errorResult(Date.now() - start, err, opts.model);
}
}
estimateCost(tokens: { input: number; output: number; cached?: number }, model?: string): number {
return estimateCostUsd(tokens, model ?? 'gpt-5.4');
}
/**
* Parse codex exec --json JSONL stream.
* Key events:
* - item.completed with item.type === 'agent_message' → text output
* - item.completed with item.type === 'command_execution' → tool call
* - turn.completed → usage.input_tokens, usage.output_tokens
* - thread.started → session id (not used here)
*/
private parseJsonl(raw: string): { output: string; tokens: { input: number; output: number }; toolCalls: number; modelUsed?: string } {
let output = '';
let input = 0;
let out = 0;
let toolCalls = 0;
let modelUsed: string | undefined;
for (const line of raw.split('\n')) {
const s = line.trim();
if (!s) continue;
try {
const obj = JSON.parse(s);
if (obj.type === 'item.completed' && obj.item) {
if (obj.item.type === 'agent_message' && typeof obj.item.text === 'string') {
output += (output ? '\n' : '') + obj.item.text;
} else if (obj.item.type === 'command_execution') {
toolCalls += 1;
}
} else if (obj.type === 'turn.completed') {
const u = obj.usage ?? {};
input += u.input_tokens ?? 0;
out += u.output_tokens ?? 0;
if (obj.model) modelUsed = obj.model;
}
} catch {
// skip malformed lines — codex stderr can leak in
}
}
return { output, tokens: { input, output: out }, toolCalls, modelUsed };
}
private emptyResult(durationMs: number, error: RunResult['error'], model?: string): RunResult {
return {
output: '',
tokens: { input: 0, output: 0 },
durationMs,
toolCalls: 0,
modelUsed: model ?? 'gpt-5.4',
error,
};
private errorResult(durationMs: number, err: unknown, model?: string): RunResult {
const e = err as { code?: string; stderr?: Buffer; signal?: string; message?: string };
const stderr = e.stderr?.toString() ?? '';
let code: RunError;
if (e.signal === 'SIGTERM' || e.code === 'ETIMEDOUT') code = 'timeout';
else if (/unauthorized|auth|login/i.test(stderr)) code = 'auth';
else if (/rate[- ]?limit|429/i.test(stderr)) code = 'rate_limit';
else code = 'unknown';
const reason = code === 'timeout' ? 'exceeded timeout' : (e.message ?? stderr ?? 'unknown').slice(0, 400);
return { output: '', durationMs, modelUsed: model ?? 'gpt', error: { code, reason } };
}
}