feat(aircoding): AirCoding V2 baseline — deterministic multi-agent architecture

Forked from OpenCode v1.17.4 with multi-agent system:
- 5 agents: aircoding, scheduler, worker, architect, reviewer
- Deterministic DAG scheduling engine (coordinator_tick)
- Tool whitelists as hard enforcement
- AirCoding validation plugin
- System prompt injection for routing
- V1 requirements: C4 docs, ADR, AGENTS.md, debug-log.md
- Design documents in docs/
This commit is contained in:
airlongdian
2026-06-13 21:41:54 +08:00
commit af3016fe27
5757 changed files with 1170017 additions and 0 deletions

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import { describe, expect, test } from "bun:test"
import type { ZenData } from "@opencode-ai/console-core/model.js"
import type { ProviderHelper } from "../src/routes/zen/util/provider/provider"
import { anthropicHelper } from "../src/routes/zen/util/provider/anthropic"
import { googleHelper } from "../src/routes/zen/util/provider/google"
import { oaCompatHelper } from "../src/routes/zen/util/provider/openai-compatible"
import { openaiHelper } from "../src/routes/zen/util/provider/openai"
const providers = {
anthropic: anthropicHelper({ reqModel: "claude-haiku-4-5", providerModel: "claude-haiku-4-5" }),
google: googleHelper({ reqModel: "gemini-3-flash", providerModel: "gemini-3-flash" }),
openai: openaiHelper({ reqModel: "gpt-5", providerModel: "gpt-5" }),
"oa-compat": oaCompatHelper({ reqModel: "gpt-5-nano", providerModel: "gpt-5-nano" }),
} satisfies Record<ZenData.Format, ReturnType<ProviderHelper>>
describe("provider usage extraction", () => {
test("extracts Google non-stream usage metadata", () => {
const usage = providers.google.extractUsage({
usageMetadata: {
promptTokenCount: 10,
candidatesTokenCount: 3,
thoughtsTokenCount: 2,
cachedContentTokenCount: 4,
},
})
expect(providers.google.normalizeUsage(usage)).toEqual({
inputTokens: 6,
outputTokens: 3,
reasoningTokens: 2,
cacheReadTokens: 4,
cacheWrite5mTokens: undefined,
cacheWrite1hTokens: undefined,
})
})
test("parses Google stream usage metadata", () => {
const usageParser = providers.google.createUsageParser()
usageParser.parse(
'data: {"usageMetadata":{"promptTokenCount":10,"candidatesTokenCount":3,"thoughtsTokenCount":2,"cachedContentTokenCount":4}}',
)
expect(providers.google.normalizeUsage(usageParser.retrieve())).toEqual({
inputTokens: 6,
outputTokens: 3,
reasoningTokens: 2,
cacheReadTokens: 4,
cacheWrite5mTokens: undefined,
cacheWrite1hTokens: undefined,
})
})
test("extracts nested OpenAI Responses usage", () => {
expect(
providers.openai.extractUsage({
response: {
usage: {
input_tokens: 5,
output_tokens: 7,
},
},
}),
).toEqual({
input_tokens: 5,
output_tokens: 7,
})
})
})

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import { describe, expect, test } from "bun:test"
import { getRetryAfterDay } from "../src/routes/zen/util/ipRateLimiter"
describe("getRetryAfterDay", () => {
test("returns full day at midnight UTC", () => {
const midnight = Date.UTC(2026, 0, 15, 0, 0, 0, 0)
expect(getRetryAfterDay(midnight)).toBe(86_400)
})
test("returns remaining seconds until next UTC day", () => {
const noon = Date.UTC(2026, 0, 15, 12, 0, 0, 0)
expect(getRetryAfterDay(noon)).toBe(43_200)
})
test("rounds up to nearest second", () => {
const almost = Date.UTC(2026, 0, 15, 23, 59, 59, 500)
expect(getRetryAfterDay(almost)).toBe(1)
})
})