bd51cdba12
- Replace LLMError { module, method, reason } wrapper with a flat tagged
union: BadRequest, Authentication, PermissionDenied, NotFound, RateLimit,
QuotaExceeded, ContentPolicy, ContextOverflow, ServerError, APIError,
ConnectionError, TimeoutError, MalformedResponse, NoRoute.
- Delete the provider-error LLMEvent: streams carry output only and every
failure exits through the typed error channel.
- Add one shared classifyApiFailure classifier used by the HTTP executor,
protocol stream errors, and the AI SDK adapter so all routes classify
identically (including OpenAI in-stream rate_limit_exceeded and
internal_error codes).
- Enforce a terminal contract in LLMClient.stream for every route: EOF
without finish and output after finish fail as MalformedResponse.
- Classify AI SDK failures properly in core/aisdk.ts instead of collapsing
to UnknownProvider; preserve status, headers, body, and retry-after.
- Simplify the session runner: drop held-back overflow events, key overflow
recovery off LLM.ContextOverflow, retry RateLimit | ServerError |
ConnectionError | TimeoutError.
- Map new tags in toSessionError (provider.context-overflow,
provider.timeout, provider.not-found).
52 lines
2 KiB
TypeScript
52 lines
2 KiB
TypeScript
import { describe, expect } from "bun:test"
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import { Effect } from "effect"
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import { isLLMError, LLM, Message, ToolCallPart } from "../../src"
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import { LLMClient } from "../../src/route"
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import * as Anthropic from "../../src/providers/anthropic"
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import { weatherToolName } from "../recorded-scenarios"
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import { recordedTests } from "../recorded-test"
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const model = Anthropic.configure({
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apiKey: process.env.ANTHROPIC_API_KEY ?? "fixture",
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}).model("claude-haiku-4-5-20251001")
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const malformedToolOrderRequest = LLM.request({
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id: "recorded_anthropic_malformed_tool_order",
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model,
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messages: [
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Message.assistant([
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ToolCallPart.make({ id: "call_1", name: weatherToolName, input: { city: "Paris" } }),
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{ type: "text", text: "I will check the weather." },
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]),
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Message.tool({ id: "call_1", name: weatherToolName, result: { temperature: "72F" } }),
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Message.user("Use that result to answer briefly."),
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],
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tools: [{ name: weatherToolName, description: "Get weather", inputSchema: { type: "object", properties: {} } }],
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// The cassette predates the `cache: "auto"` default; pin the policy off so
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// the replayed request matches the recorded wire shape.
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cache: "none",
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})
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const recorded = recordedTests({
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prefix: "anthropic-messages",
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provider: "anthropic",
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protocol: "anthropic-messages",
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requires: ["ANTHROPIC_API_KEY"],
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options: { redact: { allowRequestHeaders: ["anthropic-version"] } },
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})
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describe("Anthropic Messages sad-path recorded", () => {
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recorded.effect.with(
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"rejects malformed assistant tool order",
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// The cassette predates a test rename; keep replaying the existing recording.
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{ id: "rejects-malformed-assistant-tool-order-without-patch", tags: ["tool", "sad-path"] },
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() =>
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Effect.gen(function* () {
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const error = yield* LLMClient.generate(malformedToolOrderRequest).pipe(Effect.flip)
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expect(isLLMError(error)).toBe(true)
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expect(error).toMatchObject({ _tag: "LLM.BadRequest" })
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expect(error.message).toContain("HTTP 400")
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}),
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)
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})
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