Files
opencode/packages/core/test/session-runner-recorded.test.ts
2026-07-21 13:44:10 -05:00

251 lines
10 KiB
TypeScript

import { HttpRecorder } from "@opencode-ai/http-recorder"
import * as OpenAIChat from "@opencode-ai/ai/protocols/openai-chat"
import { Auth, LLMClient, RequestExecutor } from "@opencode-ai/ai/route"
import { Catalog } from "@opencode-ai/core/catalog"
import { Database } from "@opencode-ai/core/database/database"
import { AppNodeBuilder } from "@opencode-ai/core/effect/app-node-builder"
import { LayerNodePlatform } from "@opencode-ai/core/effect/app-node-platform"
import { LayerNode } from "@opencode-ai/util/effect/layer-node"
import { EventV2 } from "@opencode-ai/core/event"
import { EventTable } from "@opencode-ai/core/event/sql"
import { Job } from "@opencode-ai/core/job"
import { PermissionV2 } from "@opencode-ai/core/permission"
import { AgentV2 } from "@opencode-ai/core/agent"
import { Config } from "@opencode-ai/core/config"
import { Project } from "@opencode-ai/core/project"
import { ProjectTable } from "@opencode-ai/core/project/sql"
import { AbsolutePath } from "@opencode-ai/core/schema"
import { SessionV2 } from "@opencode-ai/core/session"
import { Snapshot } from "@opencode-ai/core/snapshot"
import { SessionCompaction } from "@opencode-ai/core/session/compaction"
import { SessionTitle } from "@opencode-ai/core/session/title"
import { SessionProjector } from "@opencode-ai/core/session/projector"
import { SessionExecution } from "@opencode-ai/core/session/execution"
import { SessionRunCoordinator } from "@opencode-ai/core/session/run-coordinator"
import { SessionRunner } from "@opencode-ai/core/session/runner"
import * as SessionRunnerLLM from "@opencode-ai/core/session/runner/llm"
import { SessionRunnerModel } from "@opencode-ai/core/session/runner/model"
import { ToolRegistry } from "@opencode-ai/core/tool/registry"
import { ToolOutputStore } from "@opencode-ai/core/tool-output-store"
import { SessionTable } from "@opencode-ai/core/session/sql"
import { SessionStore } from "@opencode-ai/core/session/store"
import { Location } from "@opencode-ai/core/location"
import { InstructionBuiltIns } from "@opencode-ai/core/instructions/builtins"
import { InstructionDiscovery } from "@opencode-ai/core/instruction-discovery"
import { Instructions } from "@opencode-ai/core/instructions"
import { SkillInstructions } from "@opencode-ai/core/skill/instructions"
import { ReferenceInstructions } from "@opencode-ai/core/reference/instructions"
import { McpInstructions } from "@opencode-ai/core/mcp/instructions"
import { PluginSupervisor } from "@opencode-ai/core/plugin/supervisor"
import { PluginHooks } from "@opencode-ai/core/plugin/hooks"
import { SystemPromptPlugin } from "@opencode-ai/core/plugin/system-prompt"
import { describe, expect } from "bun:test"
import { eq } from "drizzle-orm"
import { Effect, Layer } from "effect"
import path from "node:path"
import { testEffect } from "./lib/effect"
import { agentHost, catalogHost, host } from "./plugin/host"
const cassetteName = "session-runner/openai-chat-streams-text"
const cassetteDirectory = path.resolve(import.meta.dir, "fixtures/recordings")
if (process.env.RECORD === "true") {
if (process.env.CI !== undefined) throw new Error("Unset CI before recording HTTP cassettes")
HttpRecorder.removeCassetteSync(cassetteName, { directory: cassetteDirectory })
}
const cassette = HttpRecorder.layerFetch(cassetteName, { directory: cassetteDirectory })
const executor = RequestExecutor.layer.pipe(Layer.provide(cassette))
const client = LLMClient.layer.pipe(Layer.provide(executor))
const permission = Layer.succeed(
PermissionV2.Service,
PermissionV2.Service.of({
assert: () => Effect.die("unused"),
ask: () => Effect.die("unused"),
reply: () => Effect.die("unused"),
get: () => Effect.die("unused"),
forSession: () => Effect.die("unused"),
list: () => Effect.die("unused"),
}),
)
const model = OpenAIChat.route
.with({
endpoint: { baseURL: "https://api.openai.com/v1" },
auth: Auth.bearer(process.env.OPENAI_API_KEY ?? "fixture"),
generation: { maxTokens: 20, temperature: 0 },
})
.model({ id: "gpt-4o-mini" })
const models = SessionRunnerModel.layerWith(() =>
Effect.succeed(
SessionRunnerModel.resolved(model, {
capabilities: { tools: true, input: ["text", "image"], output: ["text"] },
cost: [],
}),
),
)
const systemContext = Layer.mock(InstructionBuiltIns.Service, { load: () => Effect.succeed(Instructions.empty) })
const instructionContext = Layer.mock(InstructionDiscovery.Service, { load: () => Effect.succeed(Instructions.empty) })
const skillInstructions = Layer.mock(SkillInstructions.Service, { load: () => Effect.succeed(Instructions.empty) })
const referenceInstructions = Layer.mock(ReferenceInstructions.Service, {
load: () => Effect.succeed(Instructions.empty),
})
const mcpInstructions = Layer.mock(McpInstructions.Service, { load: () => Effect.succeed(Instructions.empty) })
const config = Layer.succeed(Config.Service, Config.Service.of({ entries: () => Effect.succeed([]) }))
const pluginSupervisor = Layer.succeed(PluginSupervisor.Service, PluginSupervisor.Service.of({ flush: Effect.void }))
const promptCatalog = Layer.mock(Catalog.Service, {
provider: {
get: () => Effect.succeed(undefined),
all: () => Effect.succeed([]),
available: () => Effect.succeed([]),
},
model: {
get: () => Effect.succeed(undefined),
all: () => Effect.succeed([]),
available: () => Effect.succeed([]),
default: () => Effect.succeed(undefined),
small: () => Effect.succeed(undefined),
},
})
const runnerLayer = AppNodeBuilder.build(SessionRunnerLLM.node, [
[Snapshot.node, Snapshot.noopLayer],
[LayerNodePlatform.llmClient, client],
[SessionRunnerModel.node, models],
[InstructionBuiltIns.node, systemContext],
[InstructionDiscovery.node, instructionContext],
[Location.node, Location.boundNode({ directory: AbsolutePath.make("/project") })],
[SkillInstructions.node, skillInstructions],
[ReferenceInstructions.node, referenceInstructions],
[McpInstructions.node, mcpInstructions],
[Config.node, config],
[PermissionV2.node, permission],
[ToolOutputStore.node, ToolOutputStore.nodeWithoutConfig],
[PluginSupervisor.node, pluginSupervisor],
])
const execution = Layer.effect(
SessionExecution.Service,
Effect.gen(function* () {
const sessionRunner = yield* SessionRunner.Service
const coordinator = yield* SessionRunCoordinator.make<SessionV2.ID, SessionRunner.RunError>({
drain: (sessionID, force) => sessionRunner.drain({ sessionID, force }),
})
return SessionExecution.Service.of({
active: coordinator.active,
resume: coordinator.run,
wake: coordinator.wake,
interrupt: coordinator.interrupt,
awaitIdle: coordinator.awaitIdle,
})
}),
).pipe(Layer.provide(runnerLayer))
const it = testEffect(
AppNodeBuilder.build(
LayerNode.group([
Database.node,
EventV2.node,
SessionProjector.node,
SessionStore.node,
AgentV2.node,
Catalog.node,
PluginHooks.node,
ToolRegistry.node,
SessionRunnerModel.node,
InstructionBuiltIns.node,
InstructionDiscovery.node,
SkillInstructions.node,
ReferenceInstructions.node,
Config.node,
Snapshot.node,
SessionRunnerLLM.node,
SessionV2.node,
]),
[
[LayerNodePlatform.llmClient, client],
[PermissionV2.node, permission],
[Catalog.node, promptCatalog],
[ToolOutputStore.node, ToolOutputStore.nodeWithoutConfig],
[SessionRunnerModel.node, models],
[InstructionBuiltIns.node, systemContext],
[InstructionDiscovery.node, instructionContext],
[Location.node, Location.boundNode({ directory: AbsolutePath.make("/project") })],
[SkillInstructions.node, skillInstructions],
[ReferenceInstructions.node, referenceInstructions],
[Config.node, config],
[Snapshot.node, Snapshot.noopLayer],
[PluginSupervisor.node, pluginSupervisor],
[SessionExecution.node, execution],
],
),
)
const sessionID = SessionV2.ID.make("ses_runner_recorded")
describe("SessionRunnerLLM recorded", () => {
it.effect("executes one recorded V2 prompt through the recorded HTTP transport", () =>
Effect.gen(function* () {
const agents = yield* AgentV2.Service
const catalog = yield* Catalog.Service
const hooks = yield* PluginHooks.Service
yield* agents.transform((draft) =>
draft.update(AgentV2.ID.make("build"), (agent) => {
agent.mode = "primary"
}),
)
const pluginHost = host({
agent: agentHost(agents),
catalog: catalogHost(catalog),
session: { hook: (name, callback) => hooks.register("session", name, callback) },
})
yield* Effect.forEach(SystemPromptPlugin.Plugins, (plugin) => plugin.effect(pluginHost), { discard: true })
const { db } = yield* Database.Service
yield* db
.insert(ProjectTable)
.values({ id: Project.ID.global, worktree: AbsolutePath.make("/project"), sandboxes: [] })
.onConflictDoNothing()
.run()
.pipe(Effect.orDie)
yield* db
.insert(SessionTable)
.values({
id: sessionID,
project_id: Project.ID.global,
slug: "test",
directory: "/project",
title: "test",
version: "test",
})
.onConflictDoNothing()
.run()
.pipe(Effect.orDie)
const session = yield* SessionV2.Service
const prompt = yield* session.prompt({
sessionID,
text: "Say hello in one short sentence.",
resume: false,
})
yield* session.resume(sessionID)
const messages = yield* session.context(sessionID)
expect(messages).toHaveLength(2)
expect(messages[0]).toMatchObject({ id: prompt.id, type: "user", text: "Say hello in one short sentence." })
expect(messages[1]).toMatchObject({ type: "assistant", agent: "build", finish: "stop" })
expect(messages[1]?.type === "assistant" ? messages[1].content : []).toMatchObject([
{ type: "text", text: "Hello!" },
])
expect(
(yield* db
.select({ type: EventTable.type })
.from(EventTable)
.where(eq(EventTable.aggregate_id, sessionID))
.orderBy(EventTable.seq)
.all()).map((event) => event.type),
).toEqual([
"session.input.admitted.1",
"session.instructions.updated.2",
"session.input.promoted.1",
"session.step.started.1",
"session.text.started.1",
"session.text.ended.1",
"session.step.ended.1",
])
}),
)
})