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feat(http-recorder): prepare public beta release (#31018)

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Kit Langton 2026-06-05 23:01:26 -04:00 • committed by GitHub
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15
packages/core/test/session-runner-recorded.test.ts
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@ -1,5 +1,5 @@
import { NodeFileSystem } from "@effect/platform-node"
import { HttpRecorder } from "@opencode-ai/http-recorder"
import { HttpRecorderInternal } from "@opencode-ai/http-recorder/internal"
import * as OpenAIChat from "@opencode-ai/llm/protocols/openai-chat"
import { Auth, LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
import { Database } from "@opencode-ai/core/database/database"
@ -35,10 +35,15 @@ const database = Database.layerFromPath(":memory:")
const events = EventV2.layer.pipe(Layer.provide(database))
const projector = SessionProjector.layer.pipe(Layer.provide(events), Layer.provide(database))
const store = SessionStore.layer.pipe(Layer.provide(database))
const cassette = HttpRecorder.cassetteLayer("session-runner/openai-chat-streams-text", {
directory: path.resolve(import.meta.dir, "fixtures/recordings"),
mode: process.env.RECORD === "true" ? "record" : "replay",
}).pipe(Layer.provide(NodeFileSystem.layer))
const cassette =
process.env.RECORD === "true"
? HttpRecorderInternal.cassetteLayer("session-runner/openai-chat-streams-text", {
directory: path.resolve(import.meta.dir, "fixtures/recordings"),
mode: "record",
})
: HttpRecorder.http("session-runner/openai-chat-streams-text", {
directory: path.resolve(import.meta.dir, "fixtures/recordings"),
})
const executor = RequestExecutor.layer.pipe(Layer.provide(cassette))
const client = LLMClient.layer.pipe(Layer.provide(executor))
const permission = Layer.succeed(