Files
opencode/packages/ai/test/compaction-http.test.ts

98 lines
4.2 KiB
TypeScript

import { expect } from "bun:test"
import { Effect } from "effect"
import { FetchHttpClient } from "effect/unstable/http"
import { LLM, LLMRequest, Message } from "../src/index.js"
import { LLMClient } from "../src/route/client.js"
import { OpenAI } from "../src/providers.js"
import { testEffect } from "./lib/effect.js"
import { runtimeLayer } from "./lib/http.js"
import { sseEvents } from "./lib/sse.js"
testEffect(runtimeLayer(FetchHttpClient.layer)).live("compaction and a tool loop work end to end over HTTP", () =>
Effect.gen(function* () {
const checkpoint = { type: "compaction", id: "cmp_local", encrypted_content: "opaque-local-state" }
const calls: string[] = []
const server = yield* Effect.acquireRelease(
Effect.sync(() =>
Bun.serve({
hostname: "127.0.0.1",
port: 0,
async fetch(request) {
const path = new URL(request.url).pathname
calls.push(path)
const body = await request.json()
expect(request.headers.get("authorization")).toBe("Bearer fixture")
if (path === "/v1/responses/compact") {
expect(body.stream).toBeUndefined()
return Response.json({
object: "response.compaction",
output: [checkpoint],
usage: { input_tokens: 100, output_tokens: 10, total_tokens: 110 },
})
}
expect(body.input[0]).toEqual(checkpoint)
expect(body.stream).toBe(true)
if (calls.length === 2)
return new Response(
sseEvents(
{
type: "response.output_item.done",
item: { type: "function_call", id: "fc_1", call_id: "call_1", name: "lookup", arguments: "{}" },
},
{ type: "response.completed", response: { id: "resp_1" } },
),
{ headers: { "content-type": "text/event-stream" } },
)
expect(body.input.at(-2)).toMatchObject({ type: "function_call", call_id: "call_1" })
expect(body.input.at(-1)).toEqual({ type: "function_call_output", call_id: "call_1", output: "42" })
const output = sseEvents(
{ type: "response.output_item.added", item: { type: "message", id: "msg_1" } },
{ type: "response.output_text.delta", item_id: "msg_1", delta: "The answer is 42." },
{
type: "response.output_item.done",
item: { type: "message", id: "msg_1", content: [{ type: "output_text", text: "The answer is 42." }] },
},
{ type: "response.completed", response: { id: "resp_2" } },
)
return new Response(
new ReadableStream({
start(controller) {
controller.enqueue(new TextEncoder().encode(output.slice(0, 37)))
controller.enqueue(new TextEncoder().encode(output.slice(37)))
controller.close()
},
}),
{ headers: { "content-type": "text/event-stream" } },
)
},
}),
),
(server) => Effect.sync(() => server.stop(true)),
)
const model = OpenAI.configure({ apiKey: "fixture", baseURL: `http://127.0.0.1:${server.port}/v1` }).responses(
"fixture",
)
const request = LLM.request({
model,
prompt: "original",
tools: [{ name: "lookup", description: "Lookup a number", inputSchema: { type: "object", properties: {} } }],
})
const compacted = yield* LLMClient.compact(request)
const messages = [...compacted.replacement, Message.user("Look up the answer")]
const first = yield* LLMClient.generate(LLMRequest.update(request, { messages }))
expect(first.toolCalls).toHaveLength(1)
const call = first.toolCalls[0]!
const last = yield* LLMClient.generate(
LLMRequest.update(request, {
messages: [
...messages,
first.message,
Message.tool({ id: call.id, name: call.name, result: "42", resultType: "text" }),
],
}),
)
expect(last.text).toBe("The answer is 42.")
expect(calls).toEqual(["/v1/responses/compact", "/v1/responses", "/v1/responses"])
}),
)