mirror of
https://github.com/anomalyco/opencode.git
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feat(native-llm): route Anthropic API-key models through native runtime (#28271)
This commit is contained in:
Kit Langton
@@ -37,13 +37,16 @@ type StreamInput = {
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}
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export function status(input: Pick<StreamInput, "model" | "provider" | "auth">): RuntimeStatus {
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if (input.model.providerID !== "openai" && !input.model.providerID.startsWith("opencode"))
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return { type: "unsupported", reason: "provider is not openai or opencode" }
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if (input.model.api.npm !== "@ai-sdk/openai") return { type: "unsupported", reason: "provider package is not OpenAI" }
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const providerID = input.model.providerID
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if (providerID !== "openai" && providerID !== "anthropic" && !providerID.startsWith("opencode"))
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return { type: "unsupported", reason: "provider is not openai, opencode, or anthropic" }
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const npm = input.model.api.npm
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if (npm !== "@ai-sdk/openai" && npm !== "@ai-sdk/anthropic")
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return { type: "unsupported", reason: "provider package is not OpenAI or Anthropic" }
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if (input.auth?.type === "oauth") return { type: "unsupported", reason: "OAuth auth is not supported" }
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const apiKey = typeof input.provider.options.apiKey === "string" ? input.provider.options.apiKey : input.provider.key
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if (!apiKey) return { type: "unsupported", reason: "OpenAI API key is not configured" }
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if (!apiKey) return { type: "unsupported", reason: "API key is not configured" }
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return {
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type: "supported",
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+53
@@ -0,0 +1,53 @@
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{
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"version": 1,
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"metadata": {
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"name": "session/native-anthropic-tool-loop",
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"recordedAt": "2026-05-19T01:40:12.788Z",
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"provider": "anthropic",
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"protocol": "anthropic-messages",
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"route": "anthropic-messages",
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"tags": [
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"opencode",
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"native",
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"tool-loop"
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]
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},
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"interactions": [
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{
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"transport": "http",
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"request": {
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"method": "POST",
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"url": "https://api.anthropic.com/v1/messages",
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"headers": {
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"content-type": "application/json"
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},
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"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Answer using tools when appropriate.\\nUse the get_weather tool exactly once to look up Paris, then reply with exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get the current weather for a city.\",\"input_schema\":{\"$schema\":\"http://json-schema.org/draft-07/schema#\",\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"max_tokens\":32000,\"temperature\":0}"
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},
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"response": {
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"status": 200,
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"headers": {
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"content-type": "text/event-stream; charset=utf-8"
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},
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"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01KSRzhxWxF38x5yYVYvktbc\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":622,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":54,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_01A8pEqifk2HVQfq1ZDNP6iY\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \\\"P\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"aris\\\"}\"} }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0 }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":622,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":54} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
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}
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},
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{
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"transport": "http",
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"request": {
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"method": "POST",
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"url": "https://api.anthropic.com/v1/messages",
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"headers": {
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"content-type": "application/json"
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},
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"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Answer using tools when appropriate.\\nUse the get_weather tool exactly once to look up Paris, then reply with exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\",\"cache_control\":{\"type\":\"ephemeral\"}}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"toolu_01A8pEqifk2HVQfq1ZDNP6iY\",\"name\":\"get_weather\",\"input\":{\"city\":{}}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"toolu_01A8pEqifk2HVQfq1ZDNP6iY\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get the current weather for a city.\",\"input_schema\":{\"$schema\":\"http://json-schema.org/draft-07/schema#\",\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"max_tokens\":32000,\"temperature\":0}"
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},
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"response": {
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"status": 200,
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"headers": {
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"content-type": "text/event-stream; charset=utf-8"
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},
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"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01UyghbuSVecMVozDny14vCD\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":697,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":1,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Paris\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\" is sunny.\"} }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0 }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":697,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":7} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
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}
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}
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]
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}
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-31
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File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -1,7 +1,7 @@
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import { NodeFileSystem } from "@effect/platform-node"
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import { HttpRecorder, Redactor } from "@opencode-ai/http-recorder"
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import { describe, expect } from "bun:test"
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import { tool } from "ai"
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import { tool, type ModelMessage, type JSONValue } from "ai"
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import { Effect, Layer, Stream } from "effect"
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import { FetchHttpClient } from "effect/unstable/http"
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import path from "node:path"
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@@ -12,6 +12,7 @@ import { Plugin } from "@/plugin"
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import { Provider } from "@/provider/provider"
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import { ModelID, ProviderID } from "@/provider/schema"
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import { Filesystem } from "@/util/filesystem"
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import { LLMEvent, LLMResponse } from "@opencode-ai/llm"
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import { LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
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import { RuntimeFlags } from "@/effect/runtime-flags"
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import type { Agent } from "../../src/agent/agent"
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@@ -22,22 +23,105 @@ import type { ModelsDev } from "@opencode-ai/core/models-dev"
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import { TestInstance } from "../fixture/fixture"
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import { testEffect } from "../lib/effect"
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const OPENAI_CASSETTE = "session/native-openai-tool-call"
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const ZEN_CASSETTE = "session/native-zen-tool-call"
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const FIXTURES_DIR = path.join(import.meta.dir, "../fixtures/recordings")
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const OPENAI_API_KEY = process.env.OPENCODE_RECORD_OPENAI_API_KEY ?? process.env.OPENAI_API_KEY
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const CONSOLE_TOKEN = process.env.OPENCODE_RECORD_CONSOLE_TOKEN
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const ZEN_ORG_ID = process.env.OPENCODE_RECORD_ZEN_ORG_ID
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const ZEN_API_URL =
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process.env.OPENCODE_RECORD_ZEN_API_URL ?? "https://console.opencode.ai/proxy/connections/fixture/v1"
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const zenURL = (connection: string) => `https://console.opencode.ai/proxy/connections/${connection}/v1`
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type ProviderSpec = {
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readonly providerID: ProviderID
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readonly modelID: string
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readonly cassette: string
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readonly protocol: string
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readonly tags: ReadonlyArray<string>
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readonly canRecord: boolean
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readonly config: (model: ModelsDev.Provider["models"][string]) => Partial<Config.Info>
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}
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const cloneModel = (model: ModelsDev.Provider["models"][string]) =>
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structuredClone(model) as NonNullable<NonNullable<Config.Info["provider"]>[string]["models"]>[string]
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const PROVIDERS = {
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openai: {
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providerID: ProviderID.openai,
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modelID: "gpt-4.1-mini",
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cassette: "session/native-openai-tool-loop",
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protocol: "openai-responses",
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tags: ["opencode", "native", "tool-loop"],
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canRecord: Boolean(process.env.OPENCODE_RECORD_OPENAI_API_KEY ?? process.env.OPENAI_API_KEY),
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config: (model) => ({
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enabled_providers: ["openai"],
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provider: {
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openai: {
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name: "OpenAI",
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env: ["OPENAI_API_KEY"],
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npm: "@ai-sdk/openai",
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api: "https://api.openai.com/v1",
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models: { [model.id]: cloneModel(model) },
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options: {
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apiKey: process.env.OPENCODE_RECORD_OPENAI_API_KEY ?? process.env.OPENAI_API_KEY ?? "fixture-openai-key",
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baseURL: "https://api.openai.com/v1",
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},
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},
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},
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}),
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},
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opencode: {
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providerID: ProviderID.opencode,
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modelID: "gpt-5.2-codex",
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cassette: "session/native-zen-tool-loop",
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protocol: "openai-responses",
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tags: ["opencode", "zen", "native", "tool-loop"],
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canRecord: Boolean(process.env.OPENCODE_RECORD_CONSOLE_TOKEN && process.env.OPENCODE_RECORD_ZEN_ORG_ID),
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config: (model) => ({
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enabled_providers: ["opencode"],
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provider: {
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opencode: {
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name: "OpenCode Zen",
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env: ["OPENCODE_CONSOLE_TOKEN"],
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npm: "@ai-sdk/openai-compatible",
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// The connection slug is account-specific; the cassette redactor
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// normalizes it to {connection} for replay. Set during recording.
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api: zenURL(process.env.OPENCODE_RECORD_ZEN_CONNECTION ?? "fixture"),
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models: { [model.id]: cloneModel(model) },
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options: {
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apiKey: process.env.OPENCODE_RECORD_CONSOLE_TOKEN ?? "fixture-console-token",
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headers: { "x-org-id": process.env.OPENCODE_RECORD_ZEN_ORG_ID ?? "fixture-org" },
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},
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},
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},
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}),
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},
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anthropic: {
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providerID: ProviderID.anthropic,
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modelID: "claude-haiku-4-5-20251001",
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cassette: "session/native-anthropic-tool-loop",
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protocol: "anthropic-messages",
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tags: ["opencode", "native", "tool-loop"],
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canRecord: Boolean(process.env.OPENCODE_RECORD_ANTHROPIC_API_KEY ?? process.env.ANTHROPIC_API_KEY),
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config: (model) => ({
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enabled_providers: ["anthropic"],
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provider: {
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anthropic: {
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name: "Anthropic",
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env: ["ANTHROPIC_API_KEY"],
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npm: "@ai-sdk/anthropic",
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api: "https://api.anthropic.com/v1",
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models: { [model.id]: cloneModel(model) },
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options: {
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apiKey:
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process.env.OPENCODE_RECORD_ANTHROPIC_API_KEY ?? process.env.ANTHROPIC_API_KEY ?? "fixture-anthropic-key",
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baseURL: "https://api.anthropic.com/v1",
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},
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},
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},
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}),
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},
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} satisfies Record<string, ProviderSpec>
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const shouldRecord = process.env.RECORD === "true"
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const canRunOpenAI = shouldRecord
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? Boolean(OPENAI_API_KEY)
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: HttpRecorder.hasCassetteSync(OPENAI_CASSETTE, { directory: FIXTURES_DIR })
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const canRunZen = shouldRecord
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? Boolean(CONSOLE_TOKEN && ZEN_ORG_ID)
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: HttpRecorder.hasCassetteSync(ZEN_CASSETTE, { directory: FIXTURES_DIR })
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const canRun = (spec: ProviderSpec) =>
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shouldRecord ? spec.canRecord : HttpRecorder.hasCassetteSync(spec.cassette, { directory: FIXTURES_DIR })
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async function loadFixture(providerID: string, modelID: string) {
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const data = await Filesystem.readJson<Record<string, ModelsDev.Provider>>(
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@@ -50,234 +134,140 @@ async function loadFixture(providerID: string, modelID: string) {
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return model
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}
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const openAIConfig = (model: ModelsDev.Provider["models"][string]): Partial<Config.Info> => ({
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enabled_providers: ["openai"],
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provider: {
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openai: {
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name: "OpenAI",
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env: ["OPENAI_API_KEY"],
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npm: "@ai-sdk/openai",
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api: "https://api.openai.com/v1",
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models: {
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[model.id]: JSON.parse(JSON.stringify(model)) as NonNullable<
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NonNullable<Config.Info["provider"]>[string]["models"]
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>[string],
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},
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options: {
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apiKey: OPENAI_API_KEY ?? "fixture-openai-key",
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baseURL: "https://api.openai.com/v1",
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},
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},
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},
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})
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const zenConfig = (model: ModelsDev.Provider["models"][string]): Partial<Config.Info> => ({
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enabled_providers: ["opencode"],
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provider: {
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opencode: {
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name: "OpenCode Zen",
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env: ["OPENCODE_CONSOLE_TOKEN"],
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npm: "@ai-sdk/openai-compatible",
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api: ZEN_API_URL,
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models: {
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[model.id]: JSON.parse(JSON.stringify(model)) as NonNullable<
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NonNullable<Config.Info["provider"]>[string]["models"]
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>[string],
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},
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options: {
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apiKey: CONSOLE_TOKEN ?? "fixture-console-token",
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headers: {
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"x-org-id": ZEN_ORG_ID ?? "fixture-org",
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},
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},
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},
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},
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})
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|
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function recordedNativeLLMLayer(cassette: string, metadata: Record<string, unknown>) {
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const cassetteService = HttpRecorder.Cassette.fileSystem({ directory: FIXTURES_DIR }).pipe(
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Layer.provide(NodeFileSystem.layer),
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)
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function recordedNativeLLMLayer(spec: ProviderSpec) {
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// Only the HTTP client is recorded; RequestExecutor and the opencode LLM stack remain real.
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const recorder = HttpRecorder.recordingLayer(cassette, {
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mode: shouldRecord ? "record" : "replay",
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metadata,
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redactor: Redactor.compose(
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Redactor.defaults({
|
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url: {
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transform: (url) => url.replace(/\/proxy\/connections\/[^/]+\/v1/, "/proxy/connections/{connection}/v1"),
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},
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}),
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{
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response: (snapshot) => ({ ...snapshot, body: snapshot.body.replace(/wrk_[A-Z0-9]+/g, "wrk_redacted") }),
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},
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const recordedClient = LLMClient.layer.pipe(
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Layer.provide(RequestExecutor.layer),
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Layer.provide(
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HttpRecorder.recordingLayer(spec.cassette, {
|
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mode: shouldRecord ? "record" : "replay",
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||||
metadata: { provider: spec.providerID, protocol: spec.protocol, route: spec.protocol, tags: spec.tags },
|
||||
redactor: Redactor.compose(
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Redactor.defaults({
|
||||
url: {
|
||||
transform: (url) => url.replace(/\/proxy\/connections\/[^/]+\/v1/, "/proxy/connections/{connection}/v1"),
|
||||
},
|
||||
}),
|
||||
{
|
||||
response: (snapshot) => ({ ...snapshot, body: snapshot.body.replace(/wrk_[A-Z0-9]+/g, "wrk_redacted") }),
|
||||
},
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||||
),
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||||
}).pipe(Layer.provide(FetchHttpClient.layer)),
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),
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||||
}).pipe(Layer.provide(FetchHttpClient.layer))
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||||
const executor = RequestExecutor.layer.pipe(Layer.provide(recorder))
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||||
const client = LLMClient.layer.pipe(Layer.provide(executor))
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||||
|
||||
const providerLayer = Provider.defaultLayer.pipe(
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||||
Layer.provide(Auth.defaultLayer),
|
||||
Layer.provide(Config.defaultLayer),
|
||||
Layer.provide(Plugin.defaultLayer),
|
||||
)
|
||||
const llmLayer = LLM.layer.pipe(
|
||||
Layer.provide(Auth.defaultLayer),
|
||||
Layer.provide(Config.defaultLayer),
|
||||
Layer.provide(Provider.defaultLayer),
|
||||
Layer.provide(Plugin.defaultLayer),
|
||||
Layer.provide(client),
|
||||
Layer.provide(cassetteService),
|
||||
Layer.provide(RuntimeFlags.layer({ experimentalNativeLlm: true })),
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||||
)
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||||
|
||||
return Layer.mergeAll(providerLayer, llmLayer)
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||||
return Layer.mergeAll(
|
||||
Provider.defaultLayer.pipe(
|
||||
Layer.provide(Auth.defaultLayer),
|
||||
Layer.provide(Config.defaultLayer),
|
||||
Layer.provide(Plugin.defaultLayer),
|
||||
),
|
||||
LLM.layer.pipe(
|
||||
Layer.provide(Auth.defaultLayer),
|
||||
Layer.provide(Config.defaultLayer),
|
||||
Layer.provide(Provider.defaultLayer),
|
||||
Layer.provide(Plugin.defaultLayer),
|
||||
Layer.provide(recordedClient),
|
||||
Layer.provide(HttpRecorder.Cassette.fileSystem({ directory: FIXTURES_DIR }).pipe(Layer.provide(NodeFileSystem.layer))),
|
||||
Layer.provide(RuntimeFlags.layer({ experimentalNativeLlm: true })),
|
||||
),
|
||||
)
|
||||
}
|
||||
|
||||
const openAIIt = testEffect(
|
||||
recordedNativeLLMLayer(OPENAI_CASSETTE, {
|
||||
provider: "openai",
|
||||
protocol: "openai-responses",
|
||||
route: "openai-responses",
|
||||
tags: ["opencode", "native", "tool-call"],
|
||||
}),
|
||||
)
|
||||
const zenIt = testEffect(
|
||||
recordedNativeLLMLayer(ZEN_CASSETTE, {
|
||||
provider: "opencode",
|
||||
protocol: "openai-responses",
|
||||
route: "openai-responses",
|
||||
tags: ["opencode", "zen", "native", "tool-call"],
|
||||
}),
|
||||
)
|
||||
const recordedOpenAIInstance = canRunOpenAI ? openAIIt.instance : openAIIt.instance.skip
|
||||
const recordedZenInstance = canRunZen ? zenIt.instance : zenIt.instance.skip
|
||||
|
||||
const writeConfig = (
|
||||
directory: string,
|
||||
model: ModelsDev.Provider["models"][string],
|
||||
config: (model: ModelsDev.Provider["models"][string]) => Partial<Config.Info> = openAIConfig,
|
||||
) =>
|
||||
const writeConfig = (directory: string, spec: ProviderSpec, model: ModelsDev.Provider["models"][string]) =>
|
||||
Effect.promise(() =>
|
||||
Bun.write(
|
||||
path.join(directory, "opencode.json"),
|
||||
JSON.stringify({ $schema: "https://opencode.ai/config.json", ...config(model) }),
|
||||
JSON.stringify({ $schema: "https://opencode.ai/config.json", ...spec.config(model) }),
|
||||
),
|
||||
)
|
||||
|
||||
const getModel = (providerID: ProviderID, modelID: ModelID) =>
|
||||
Effect.gen(function* () {
|
||||
const provider = yield* Provider.Service
|
||||
return yield* provider.getModel(providerID, modelID)
|
||||
})
|
||||
|
||||
const collect = (input: LLM.StreamInput) =>
|
||||
Effect.gen(function* () {
|
||||
const llm = yield* LLM.Service
|
||||
return Array.from(yield* llm.stream(input).pipe(Stream.runCollect))
|
||||
})
|
||||
|
||||
describe("session.llm native recorded", () => {
|
||||
recordedOpenAIInstance("uses real RequestExecutor with HTTP recorder for native OpenAI tools", () =>
|
||||
Effect.gen(function* () {
|
||||
const test = yield* TestInstance
|
||||
const model = yield* Effect.promise(() => loadFixture("openai", "gpt-4.1-mini"))
|
||||
yield* writeConfig(test.directory, model)
|
||||
const WEATHER_RESULT = { temperature: 22, condition: "sunny" } as const
|
||||
const WEATHER_SYSTEM =
|
||||
"Use the get_weather tool exactly once to look up Paris, then reply with exactly: Paris is sunny."
|
||||
const WEATHER_USER = "What is the weather in Paris?"
|
||||
|
||||
const sessionID = SessionID.make("session-recorded-native-tool")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
prompt: "Call tools exactly as instructed.",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
temperature: 0,
|
||||
} satisfies Agent.Info
|
||||
const resolved = yield* getModel(ProviderID.openai, ModelID.make(model.id))
|
||||
let executed: unknown
|
||||
const weatherTool = tool({
|
||||
description: "Get the current weather for a city.",
|
||||
inputSchema: z.object({ city: z.string() }),
|
||||
execute: async () => WEATHER_RESULT,
|
||||
})
|
||||
|
||||
const events = yield* collect({
|
||||
user: {
|
||||
id: MessageID.make("msg_user-recorded-native-tool"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: 0 },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.make("openai"), modelID: ModelID.make(model.id) },
|
||||
} satisfies MessageV2.User,
|
||||
const toolRoundtrip = (
|
||||
call: { readonly id: string; readonly name: string; readonly input: unknown },
|
||||
result: JSONValue,
|
||||
): ModelMessage[] => [
|
||||
{ role: "assistant", content: [{ type: "tool-call", toolCallId: call.id, toolName: call.name, input: call.input }] },
|
||||
{
|
||||
role: "tool",
|
||||
content: [{ type: "tool-result", toolCallId: call.id, toolName: call.name, output: { type: "json", value: result } }],
|
||||
},
|
||||
]
|
||||
|
||||
const driveToolLoop = (spec: ProviderSpec) =>
|
||||
Effect.gen(function* () {
|
||||
const test = yield* TestInstance
|
||||
const model = yield* Effect.promise(() => loadFixture(spec.providerID, spec.modelID))
|
||||
yield* writeConfig(test.directory, spec, model)
|
||||
|
||||
const sessionID = SessionID.make(`session-recorded-${spec.providerID}-loop`)
|
||||
const modelID = ModelID.make(model.id)
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
prompt: "Answer using tools when appropriate.",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
temperature: 0,
|
||||
} satisfies Agent.Info
|
||||
const provider = yield* Provider.Service
|
||||
const resolved = yield* provider.getModel(spec.providerID, modelID)
|
||||
|
||||
const userMessage = { role: "user", content: WEATHER_USER } satisfies ModelMessage
|
||||
const base = {
|
||||
user: {
|
||||
id: MessageID.make(`msg_user-recorded-${spec.providerID}-loop`),
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: ["You must call the lookup tool exactly once with query weather. Do not answer in text."],
|
||||
messages: [{ role: "user", content: "Use lookup." }],
|
||||
toolChoice: "required",
|
||||
tools: {
|
||||
lookup: tool({
|
||||
description: "Lookup data.",
|
||||
inputSchema: z.object({ query: z.string() }),
|
||||
execute: async (args, options) => {
|
||||
executed = { args, toolCallId: options.toolCallId }
|
||||
return { output: "looked up" }
|
||||
},
|
||||
}),
|
||||
},
|
||||
})
|
||||
role: "user",
|
||||
time: { created: 0 },
|
||||
agent: agent.name,
|
||||
model: { providerID: spec.providerID, modelID },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: [WEATHER_SYSTEM],
|
||||
tools: { get_weather: weatherTool },
|
||||
}
|
||||
|
||||
expect(events.filter((event) => event.type === "step-finish")).toHaveLength(1)
|
||||
expect(events.filter((event) => event.type === "finish")).toHaveLength(1)
|
||||
expect(events.some((event) => event.type === "tool-result")).toBe(true)
|
||||
expect(executed).toMatchObject({ args: { query: "weather" }, toolCallId: expect.any(String) })
|
||||
}),
|
||||
)
|
||||
const turn1 = yield* collect({ ...base, messages: [userMessage] })
|
||||
const toolCall = turn1.find(LLMEvent.is.toolCall)
|
||||
expect(toolCall).toBeDefined()
|
||||
expect(turn1.find(LLMEvent.is.toolResult)).toBeDefined()
|
||||
expect(toolCall!.name).toBe("get_weather")
|
||||
expect(toolCall!.input).toMatchObject({ city: expect.stringMatching(/Paris/i) })
|
||||
expect(turn1.filter(LLMEvent.is.stepFinish)).toHaveLength(1)
|
||||
|
||||
recordedZenInstance("uses console-managed Zen config with native OpenAI-compatible tools", () =>
|
||||
Effect.gen(function* () {
|
||||
const test = yield* TestInstance
|
||||
const model = yield* Effect.promise(() => loadFixture("opencode", "gpt-5.2-codex"))
|
||||
yield* writeConfig(test.directory, model, zenConfig)
|
||||
const turn2 = yield* collect({
|
||||
...base,
|
||||
messages: [userMessage, ...toolRoundtrip(toolCall!, WEATHER_RESULT)],
|
||||
})
|
||||
|
||||
const sessionID = SessionID.make("session-recorded-native-zen-tool")
|
||||
const agent = {
|
||||
name: "test",
|
||||
mode: "primary",
|
||||
prompt: "Call tools exactly as instructed.",
|
||||
options: {},
|
||||
permission: [{ permission: "*", pattern: "*", action: "allow" }],
|
||||
} satisfies Agent.Info
|
||||
const resolved = yield* getModel(ProviderID.opencode, ModelID.make(model.id))
|
||||
let executed: unknown
|
||||
|
||||
const events = yield* collect({
|
||||
user: {
|
||||
id: MessageID.make("msg_user-recorded-native-zen-tool"),
|
||||
sessionID,
|
||||
role: "user",
|
||||
time: { created: 0 },
|
||||
agent: agent.name,
|
||||
model: { providerID: ProviderID.opencode, modelID: ModelID.make(model.id) },
|
||||
} satisfies MessageV2.User,
|
||||
sessionID,
|
||||
model: resolved,
|
||||
agent,
|
||||
system: ["You must call the lookup tool exactly once with query weather. Do not answer in text."],
|
||||
messages: [{ role: "user", content: "Use lookup." }],
|
||||
toolChoice: "required",
|
||||
tools: {
|
||||
lookup: tool({
|
||||
description: "Lookup data.",
|
||||
inputSchema: z.object({ query: z.string() }),
|
||||
execute: async (args, options) => {
|
||||
executed = { args, toolCallId: options.toolCallId }
|
||||
return { output: "looked up" }
|
||||
},
|
||||
}),
|
||||
},
|
||||
})
|
||||
expect(LLMResponse.text({ events: turn2 })).toMatch(/Paris is sunny/i)
|
||||
expect(turn2.filter(LLMEvent.is.finish)).toHaveLength(1)
|
||||
expect(turn2.filter(LLMEvent.is.toolCall)).toHaveLength(0)
|
||||
})
|
||||
|
||||
expect(events.filter((event) => event.type === "step-finish")).toHaveLength(1)
|
||||
expect(events.filter((event) => event.type === "finish")).toHaveLength(1)
|
||||
expect(events.some((event) => event.type === "tool-result")).toBe(true)
|
||||
expect(executed).toMatchObject({ args: { query: "weather" }, toolCallId: expect.any(String) })
|
||||
}),
|
||||
)
|
||||
describe("session.llm native recorded", () => {
|
||||
for (const [name, spec] of Object.entries(PROVIDERS)) {
|
||||
const it = testEffect(recordedNativeLLMLayer(spec))
|
||||
const instance = canRun(spec) ? it.instance : it.instance.skip
|
||||
instance(`${name}: drives a tool loop to a final text answer`, () => driveToolLoop(spec))
|
||||
}
|
||||
})
|
||||
|
||||
@@ -262,11 +262,11 @@ describe("session.llm-native.request", () => {
|
||||
})
|
||||
expect(
|
||||
LLMNativeRuntime.status({
|
||||
model: { ...baseModel, providerID: ProviderID.make("anthropic") },
|
||||
provider: { ...providerInfo, id: ProviderID.make("anthropic") },
|
||||
model: { ...baseModel, providerID: ProviderID.make("google") },
|
||||
provider: { ...providerInfo, id: ProviderID.make("google") },
|
||||
auth: undefined,
|
||||
}),
|
||||
).toEqual({ type: "unsupported", reason: "provider is not openai or opencode" })
|
||||
).toEqual({ type: "unsupported", reason: "provider is not openai, opencode, or anthropic" })
|
||||
expect(
|
||||
LLMNativeRuntime.status({
|
||||
model: baseModel,
|
||||
@@ -277,11 +277,11 @@ describe("session.llm-native.request", () => {
|
||||
|
||||
expect(
|
||||
LLMNativeRuntime.status({
|
||||
model: { ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/anthropic" } },
|
||||
model: { ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/google" } },
|
||||
provider: providerInfo,
|
||||
auth: undefined,
|
||||
}),
|
||||
).toEqual({ type: "unsupported", reason: "provider package is not OpenAI" })
|
||||
).toEqual({ type: "unsupported", reason: "provider package is not OpenAI or Anthropic" })
|
||||
|
||||
expect(
|
||||
LLMNativeRuntime.status({
|
||||
@@ -289,7 +289,27 @@ describe("session.llm-native.request", () => {
|
||||
provider: { ...providerInfo, options: {} },
|
||||
auth: undefined,
|
||||
}),
|
||||
).toEqual({ type: "unsupported", reason: "OpenAI API key is not configured" })
|
||||
).toEqual({ type: "unsupported", reason: "API key is not configured" })
|
||||
})
|
||||
|
||||
test("enables native runtime for Anthropic API-key models", () => {
|
||||
expect(
|
||||
LLMNativeRuntime.status({
|
||||
model: {
|
||||
...baseModel,
|
||||
providerID: ProviderID.make("anthropic"),
|
||||
api: { ...baseModel.api, npm: "@ai-sdk/anthropic", url: "https://api.anthropic.com/v1" },
|
||||
},
|
||||
provider: {
|
||||
...providerInfo,
|
||||
id: ProviderID.make("anthropic"),
|
||||
name: "Anthropic",
|
||||
env: ["ANTHROPIC_API_KEY"],
|
||||
options: { apiKey: "test-anthropic-key" },
|
||||
},
|
||||
auth: undefined,
|
||||
}),
|
||||
).toMatchObject({ type: "supported", apiKey: "test-anthropic-key" })
|
||||
})
|
||||
|
||||
test("prefers console provider api key over stored opencode auth", () => {
|
||||
|
||||
Reference in New Issue
Block a user