import type { StreamFn } from "@mariozechner/pi-agent-core"; import type { Context, Model, SimpleStreamOptions } from "@mariozechner/pi-ai"; import { describe, expect, it } from "vitest"; import { applyExtraParamsToAgent, resolveExtraParams } from "./pi-embedded-runner.js"; describe("resolveExtraParams", () => { it("returns undefined with no model config", () => { const result = resolveExtraParams({ cfg: undefined, provider: "zai", modelId: "glm-4.7", }); expect(result).toBeUndefined(); }); it("returns params for exact provider/model key", () => { const result = resolveExtraParams({ cfg: { agents: { defaults: { models: { "openai/gpt-4": { params: { temperature: 0.7, maxTokens: 2048, }, }, }, }, }, }, provider: "openai", modelId: "gpt-4", }); expect(result).toEqual({ temperature: 0.7, maxTokens: 2048, }); }); it("ignores unrelated model entries", () => { const result = resolveExtraParams({ cfg: { agents: { defaults: { models: { "openai/gpt-4": { params: { temperature: 0.7, }, }, }, }, }, }, provider: "openai", modelId: "gpt-4.1-mini", }); expect(result).toBeUndefined(); }); it("returns per-agent params when agentId matches", () => { const result = resolveExtraParams({ cfg: { agents: { list: [ { id: "risk-reviewer", params: { cacheRetention: "none" }, }, ], }, }, provider: "anthropic", modelId: "claude-opus-4-6", agentId: "risk-reviewer", }); expect(result).toEqual({ cacheRetention: "none" }); }); it("merges per-agent params over global model defaults", () => { const result = resolveExtraParams({ cfg: { agents: { defaults: { models: { "anthropic/claude-opus-4-6": { params: { temperature: 0.5, cacheRetention: "long", }, }, }, }, list: [ { id: "risk-reviewer", params: { cacheRetention: "none" }, }, ], }, }, provider: "anthropic", modelId: "claude-opus-4-6", agentId: "risk-reviewer", }); expect(result).toEqual({ temperature: 0.5, cacheRetention: "none", }); }); it("ignores per-agent params when agentId does not match", () => { const result = resolveExtraParams({ cfg: { agents: { list: [ { id: "risk-reviewer", params: { cacheRetention: "none" }, }, ], }, }, provider: "anthropic", modelId: "claude-opus-4-6", agentId: "main", }); expect(result).toBeUndefined(); }); }); describe("applyExtraParamsToAgent", () => { function createOptionsCaptureAgent() { const calls: Array = []; const baseStreamFn: StreamFn = (_model, _context, options) => { calls.push(options); return {} as ReturnType; }; return { calls, agent: { streamFn: baseStreamFn }, }; } function buildAnthropicModelConfig(modelKey: string, params: Record) { return { agents: { defaults: { models: { [modelKey]: { params }, }, }, }, }; } function runStoreMutationCase(params: { applyProvider: string; applyModelId: string; model: | Model<"openai-responses"> | Model<"openai-codex-responses"> | Model<"openai-completions">; options?: SimpleStreamOptions; }) { const payload = { store: false }; const baseStreamFn: StreamFn = (_model, _context, options) => { options?.onPayload?.(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, params.applyProvider, params.applyModelId); const context: Context = { messages: [] }; void agent.streamFn?.(params.model, context, params.options ?? {}); return payload; } function runAnthropicHeaderCase(params: { cfg: Record; modelId: string; options?: SimpleStreamOptions; }) { const { calls, agent } = createOptionsCaptureAgent(); applyExtraParamsToAgent(agent, params.cfg, "anthropic", params.modelId); const model = { api: "anthropic-messages", provider: "anthropic", id: params.modelId, } as Model<"anthropic-messages">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, params.options ?? {}); expect(calls).toHaveLength(1); return calls[0]?.headers; } it("does not inject reasoning when thinkingLevel is off (default) for OpenRouter", () => { // Regression: "off" is a truthy string, so the old code injected // reasoning: { effort: "none" }, causing a 400 on models that require // reasoning (e.g. deepseek/deepseek-r1). const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { model: "deepseek/deepseek-r1" }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent( agent, undefined, "openrouter", "deepseek/deepseek-r1", undefined, "off", ); const model = { api: "openai-completions", provider: "openrouter", id: "deepseek/deepseek-r1", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]).not.toHaveProperty("reasoning"); expect(payloads[0]).not.toHaveProperty("reasoning_effort"); }); it("injects reasoning.effort when thinkingLevel is non-off for OpenRouter", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = {}; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, "openrouter", "openrouter/auto", undefined, "low"); const model = { api: "openai-completions", provider: "openrouter", id: "openrouter/auto", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]?.reasoning).toEqual({ effort: "low" }); }); it("removes legacy reasoning_effort and keeps reasoning unset when thinkingLevel is off", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { reasoning_effort: "high" }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, "openrouter", "openrouter/auto", undefined, "off"); const model = { api: "openai-completions", provider: "openrouter", id: "openrouter/auto", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]).not.toHaveProperty("reasoning_effort"); expect(payloads[0]).not.toHaveProperty("reasoning"); }); it("does not inject effort when payload already has reasoning.max_tokens", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { reasoning: { max_tokens: 256 } }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, "openrouter", "openrouter/auto", undefined, "low"); const model = { api: "openai-completions", provider: "openrouter", id: "openrouter/auto", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]).toEqual({ reasoning: { max_tokens: 256 } }); }); it("normalizes thinking=off to null for SiliconFlow Pro models", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { thinking: "off" }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent( agent, undefined, "siliconflow", "Pro/MiniMaxAI/MiniMax-M2.1", undefined, "off", ); const model = { api: "openai-completions", provider: "siliconflow", id: "Pro/MiniMaxAI/MiniMax-M2.1", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]?.thinking).toBeNull(); }); it("keeps thinking=off unchanged for non-Pro SiliconFlow model IDs", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { thinking: "off" }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent( agent, undefined, "siliconflow", "deepseek-ai/DeepSeek-V3.2", undefined, "off", ); const model = { api: "openai-completions", provider: "siliconflow", id: "deepseek-ai/DeepSeek-V3.2", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]?.thinking).toBe("off"); }); it("removes invalid negative Google thinkingBudget and maps Gemini 3.1 to thinkingLevel", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { contents: [ { role: "user", parts: [ { text: "describe image" }, { inlineData: { mimeType: "image/png", data: "ZmFrZQ==", }, }, ], }, ], config: { thinkingConfig: { includeThoughts: true, thinkingBudget: -1, }, }, }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, "atproxy", "gemini-3.1-pro-high", undefined, "high"); const model = { api: "google-generative-ai", provider: "atproxy", id: "gemini-3.1-pro-high", } as Model<"google-generative-ai">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); const thinkingConfig = ( payloads[0]?.config as { thinkingConfig?: Record } | undefined )?.thinkingConfig; expect(thinkingConfig).toEqual({ includeThoughts: true, thinkingLevel: "HIGH", }); expect( ( payloads[0]?.contents as | Array<{ parts?: Array<{ inlineData?: { mimeType?: string; data?: string } }> }> | undefined )?.[0]?.parts?.[1]?.inlineData, ).toEqual({ mimeType: "image/png", data: "ZmFrZQ==", }); }); it("keeps valid Google thinkingBudget unchanged", () => { const payloads: Record[] = []; const baseStreamFn: StreamFn = (_model, _context, options) => { const payload: Record = { config: { thinkingConfig: { includeThoughts: true, thinkingBudget: 2048, }, }, }; options?.onPayload?.(payload); payloads.push(payload); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; applyExtraParamsToAgent(agent, undefined, "atproxy", "gemini-3.1-pro-high", undefined, "high"); const model = { api: "google-generative-ai", provider: "atproxy", id: "gemini-3.1-pro-high", } as Model<"google-generative-ai">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(payloads).toHaveLength(1); expect(payloads[0]?.config).toEqual({ thinkingConfig: { includeThoughts: true, thinkingBudget: 2048, }, }); }); it("adds OpenRouter attribution headers to stream options", () => { const { calls, agent } = createOptionsCaptureAgent(); applyExtraParamsToAgent(agent, undefined, "openrouter", "openrouter/auto"); const model = { api: "openai-completions", provider: "openrouter", id: "openrouter/auto", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, { headers: { "X-Custom": "1" } }); expect(calls).toHaveLength(1); expect(calls[0]?.headers).toEqual({ "HTTP-Referer": "https://openclaw.ai", "X-Title": "OpenClaw", "X-Custom": "1", }); }); it("disables prompt caching for non-Anthropic Bedrock models", () => { const { calls, agent } = createOptionsCaptureAgent(); applyExtraParamsToAgent(agent, undefined, "amazon-bedrock", "amazon.nova-micro-v1"); const model = { api: "openai-completions", provider: "amazon-bedrock", id: "amazon.nova-micro-v1", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(calls).toHaveLength(1); expect(calls[0]?.cacheRetention).toBe("none"); }); it("keeps Anthropic Bedrock models eligible for provider-side caching", () => { const { calls, agent } = createOptionsCaptureAgent(); applyExtraParamsToAgent(agent, undefined, "amazon-bedrock", "us.anthropic.claude-sonnet-4-5"); const model = { api: "openai-completions", provider: "amazon-bedrock", id: "us.anthropic.claude-sonnet-4-5", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(calls).toHaveLength(1); expect(calls[0]?.cacheRetention).toBeUndefined(); }); it("passes through explicit cacheRetention for Anthropic Bedrock models", () => { const { calls, agent } = createOptionsCaptureAgent(); const cfg = { agents: { defaults: { models: { "amazon-bedrock/us.anthropic.claude-opus-4-6-v1": { params: { cacheRetention: "long", }, }, }, }, }, }; applyExtraParamsToAgent(agent, cfg, "amazon-bedrock", "us.anthropic.claude-opus-4-6-v1"); const model = { api: "openai-completions", provider: "amazon-bedrock", id: "us.anthropic.claude-opus-4-6-v1", } as Model<"openai-completions">; const context: Context = { messages: [] }; void agent.streamFn?.(model, context, {}); expect(calls).toHaveLength(1); expect(calls[0]?.cacheRetention).toBe("long"); }); it("adds Anthropic 1M beta header when context1m is enabled for Opus/Sonnet", () => { const { calls, agent } = createOptionsCaptureAgent(); const cfg = buildAnthropicModelConfig("anthropic/claude-opus-4-6", { context1m: true }); applyExtraParamsToAgent(agent, cfg, "anthropic", "claude-opus-4-6"); const model = { api: "anthropic-messages", provider: "anthropic", id: "claude-opus-4-6", } as Model<"anthropic-messages">; const context: Context = { messages: [] }; // Simulate pi-agent-core passing apiKey in options (API key, not OAuth token) void agent.streamFn?.(model, context, { apiKey: "sk-ant-api03-test", headers: { "X-Custom": "1" }, }); expect(calls).toHaveLength(1); expect(calls[0]?.headers).toEqual({ "X-Custom": "1", // Includes pi-ai default betas (preserved to avoid overwrite) + context1m "anthropic-beta": "fine-grained-tool-streaming-2025-05-14,interleaved-thinking-2025-05-14,context-1m-2025-08-07", }); }); it("skips context1m beta for OAuth tokens but preserves OAuth-required betas", () => { const calls: Array = []; const baseStreamFn: StreamFn = (_model, _context, options) => { calls.push(options); return {} as ReturnType; }; const agent = { streamFn: baseStreamFn }; const cfg = { agents: { defaults: { models: { "anthropic/claude-sonnet-4-6": { params: { context1m: true, }, }, }, }, }, }; applyExtraParamsToAgent(agent, cfg, "anthropic", "claude-sonnet-4-6"); const model = { api: "anthropic-messages", provider: "anthropic", id: "claude-sonnet-4-6", } as Model<"anthropic-messages">; const context: Context = { messages: [] }; // Simulate pi-agent-core passing an OAuth token (sk-ant-oat-*) as apiKey void agent.streamFn?.(model, context, { apiKey: "sk-ant-oat01-test-oauth-token", headers: { "X-Custom": "1" }, }); expect(calls).toHaveLength(1); const betaHeader = calls[0]?.headers?.["anthropic-beta"] as string; // Must include the OAuth-required betas so they aren't stripped by pi-ai's mergeHeaders expect(betaHeader).toContain("oauth-2025-04-20"); expect(betaHeader).toContain("claude-code-20250219"); expect(betaHeader).not.toContain("context-1m-2025-08-07"); }); it("merges existing anthropic-beta headers with configured betas", () => { const cfg = buildAnthropicModelConfig("anthropic/claude-sonnet-4-5", { context1m: true, anthropicBeta: ["files-api-2025-04-14"], }); const headers = runAnthropicHeaderCase({ cfg, modelId: "claude-sonnet-4-5", options: { apiKey: "sk-ant-api03-test", headers: { "anthropic-beta": "prompt-caching-2024-07-31" }, }, }); expect(headers).toEqual({ "anthropic-beta": "prompt-caching-2024-07-31,fine-grained-tool-streaming-2025-05-14,interleaved-thinking-2025-05-14,files-api-2025-04-14,context-1m-2025-08-07", }); }); it("ignores context1m for non-Opus/Sonnet Anthropic models", () => { const cfg = buildAnthropicModelConfig("anthropic/claude-haiku-3-5", { context1m: true }); const headers = runAnthropicHeaderCase({ cfg, modelId: "claude-haiku-3-5", options: { headers: { "X-Custom": "1" } }, }); expect(headers).toEqual({ "X-Custom": "1" }); }); it("forces store=true for direct OpenAI Responses payloads", () => { const payload = runStoreMutationCase({ applyProvider: "openai", applyModelId: "gpt-5", model: { api: "openai-responses", provider: "openai", id: "gpt-5", baseUrl: "https://api.openai.com/v1", } as Model<"openai-responses">, }); expect(payload.store).toBe(true); }); it("does not force store for OpenAI Responses routed through non-OpenAI base URLs", () => { const payload = runStoreMutationCase({ applyProvider: "openai", applyModelId: "gpt-5", model: { api: "openai-responses", provider: "openai", id: "gpt-5", baseUrl: "https://proxy.example.com/v1", } as Model<"openai-responses">, }); expect(payload.store).toBe(false); }); it.each([ { name: "with openai-codex provider config", run: () => runStoreMutationCase({ applyProvider: "openai-codex", applyModelId: "codex-mini-latest", model: { api: "openai-codex-responses", provider: "openai-codex", id: "codex-mini-latest", baseUrl: "https://chatgpt.com/backend-api/codex/responses", } as Model<"openai-codex-responses">, }), }, { name: "without config via provider/model hints", run: () => runStoreMutationCase({ applyProvider: "openai-codex", applyModelId: "codex-mini-latest", model: { api: "openai-codex-responses", provider: "openai-codex", id: "codex-mini-latest", baseUrl: "https://chatgpt.com/backend-api/codex/responses", } as Model<"openai-codex-responses">, options: {}, }), }, ])( "does not force store=true for Codex responses (Codex requires store=false) ($name)", ({ run }) => { expect(run().store).toBe(false); }, ); });