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eb1202c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 | import { describe, expect, test } from "bun:test"
import { Effect, Schema } from "effect"
import { LLM } from "../src"
import * as OpenAIChat from "../src/protocols/openai-chat"
import { Auth } from "../src/route"
import { Tool, toDefinitions } from "../src/tool"
import { it } from "./lib/effect"
import { dynamicResponse } from "./lib/http"
import { finishChunk, toolCallChunk } from "./lib/openai-chunks"
import { sseEvents } from "./lib/sse"
type OpenAIChatBody = {
readonly tool_choice?: unknown
readonly tools?: ReadonlyArray<{
readonly function: {
readonly parameters: unknown
}
}>
}
const model = OpenAIChat.route
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
.model({ id: "gpt-4o-mini" })
const Json = Schema.fromJsonString(Schema.Unknown)
const decodeJson = Schema.decodeUnknownSync(Json)
const decodeBody = (text: string): OpenAIChatBody => decodeJson(text) as OpenAIChatBody
describe("Tool.make (dynamic JSON Schema)", () => {
test("forwards JSON Schema and description through toDefinitions", () => {
const jsonSchema = {
type: "object" as const,
properties: { city: { type: "string" } },
required: ["city"],
}
const lookup = Tool.make({
description: "Look up something",
jsonSchema,
execute: () => Effect.succeed({ ok: true }),
})
const [definition] = toDefinitions({ lookup })
expect(definition?.name).toBe("lookup")
expect(definition?.description).toBe("Look up something")
expect(definition?.inputSchema).toEqual(jsonSchema)
})
test("execute receives the raw input untouched", async () => {
const seen: unknown[] = []
const tool = Tool.make({
description: "echo",
jsonSchema: { type: "object" },
execute: (params) =>
Effect.sync(() => {
seen.push(params)
return { ok: true }
}),
})
const result = await Effect.runPromise(tool.execute({ hello: "world" }))
expect(seen).toEqual([{ hello: "world" }])
expect(result).toEqual({ ok: true })
})
})
describe("LLM.generateObject", () => {
it.effect("forces a synthetic tool call and decodes the input", () =>
Effect.gen(function* () {
const bodies: OpenAIChatBody[] = []
const layer = dynamicResponse((input) =>
Effect.sync(() => {
bodies.push(decodeBody(input.text))
return input.respond(
sseEvents(
toolCallChunk("call_1", "generate_object", '{"city":"Paris","temp":22}'),
finishChunk("tool_calls"),
),
{ headers: { "content-type": "text/event-stream" } },
)
}),
)
const response = yield* LLM.generateObject({
model,
prompt: "Return a structured weather report.",
schema: Schema.Struct({ city: Schema.String, temp: Schema.Number }),
}).pipe(Effect.provide(layer))
expect(response.object).toEqual({ city: "Paris", temp: 22 })
expect(response.response.toolCalls).toHaveLength(1)
expect(bodies).toHaveLength(1)
expect(bodies[0].tool_choice).toEqual({ type: "function", function: { name: "generate_object" } })
const tool = bodies[0].tools?.[0]
expect(bodies[0].tools).toHaveLength(1)
expect(tool).toMatchObject({
type: "function",
function: { name: "generate_object" },
})
const params = tool?.function.parameters as {
readonly type?: unknown
readonly required?: unknown
readonly properties?: Record<string, unknown>
}
expect(params.type).toBe("object")
expect(params.required).toEqual(["city", "temp"])
expect(params.properties?.city).toMatchObject({ type: "string" })
expect(params.properties?.temp).toBeDefined()
}),
)
it.effect("accepts a raw JSON Schema and returns the input untouched", () =>
Effect.gen(function* () {
const bodies: OpenAIChatBody[] = []
const layer = dynamicResponse((input) =>
Effect.sync(() => {
bodies.push(decodeBody(input.text))
return input.respond(
sseEvents(toolCallChunk("call_1", "generate_object", '{"name":"Ada","age":30}'), finishChunk("tool_calls")),
{ headers: { "content-type": "text/event-stream" } },
)
}),
)
const response = yield* LLM.generateObject({
model,
prompt: "Extract the user.",
jsonSchema: {
type: "object",
properties: { name: { type: "string" }, age: { type: "number" } },
required: ["name", "age"],
},
}).pipe(Effect.provide(layer))
expect(response.object).toEqual({ name: "Ada", age: 30 })
expect(bodies[0].tools?.[0]?.function.parameters).toEqual({
type: "object",
properties: { name: { type: "string" }, age: { type: "number" } },
required: ["name", "age"],
})
}),
)
it.effect("fails when the model does not call the synthetic tool", () =>
Effect.gen(function* () {
const layer = dynamicResponse((input) =>
Effect.sync(() =>
input.respond(sseEvents({ id: "x", choices: [{ delta: { content: "no thanks" }, finish_reason: "stop" }] }), {
headers: { "content-type": "text/event-stream" },
}),
),
)
const exit = yield* LLM.generateObject({
model,
prompt: "Return a structured value.",
schema: Schema.Struct({ value: Schema.Number }),
}).pipe(Effect.provide(layer), Effect.exit)
expect(exit._tag).toBe("Failure")
}),
)
it.effect("fails with a decode error when the tool input does not match the schema", () =>
Effect.gen(function* () {
const layer = dynamicResponse((input) =>
Effect.sync(() =>
input.respond(
sseEvents(
toolCallChunk("call_1", "generate_object", '{"value":"not-a-number"}'),
finishChunk("tool_calls"),
),
{ headers: { "content-type": "text/event-stream" } },
),
),
)
const exit = yield* LLM.generateObject({
model,
prompt: "Return a structured value.",
schema: Schema.Struct({ value: Schema.Number }),
}).pipe(Effect.provide(layer), Effect.exit)
expect(exit._tag).toBe("Failure")
}),
)
})
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