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465 lines
18 KiB
TypeScript
465 lines
18 KiB
TypeScript
/**
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* Test context overflow error handling across providers.
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*
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* Context overflow occurs when the input (prompt + history) exceeds
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* the model's context window. This is different from output token limits.
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*
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* Expected behavior: All providers should return stopReason: "error"
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* with an errorMessage that indicates the context was too large,
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* OR (for z.ai) return successfully with usage.input > contextWindow.
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*
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* The isContextOverflow() function must return true for all providers.
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*/
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import type { ChildProcess } from "child_process";
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import { execSync, spawn } from "child_process";
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import { afterAll, beforeAll, describe, expect, it } from "vitest";
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import { getModel } from "../src/models.js";
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import { complete } from "../src/stream.js";
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import type { AssistantMessage, Context, Model, Usage } from "../src/types.js";
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import { isContextOverflow } from "../src/utils/overflow.js";
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// Lorem ipsum paragraph for realistic token estimation
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const LOREM_IPSUM = `Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. `;
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// Generate a string that will exceed the context window
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// Using chars/4 as token estimate (works better with varied text than repeated chars)
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function generateOverflowContent(contextWindow: number): string {
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const targetTokens = contextWindow + 10000; // Exceed by 10k tokens
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const targetChars = targetTokens * 4 * 1.5;
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const repetitions = Math.ceil(targetChars / LOREM_IPSUM.length);
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return LOREM_IPSUM.repeat(repetitions);
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}
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interface OverflowResult {
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provider: string;
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model: string;
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contextWindow: number;
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stopReason: string;
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errorMessage: string | undefined;
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usage: Usage;
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hasUsageData: boolean;
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response: AssistantMessage;
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}
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async function testContextOverflow(model: Model<any>, apiKey: string): Promise<OverflowResult> {
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const overflowContent = generateOverflowContent(model.contextWindow);
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const context: Context = {
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systemPrompt: "You are a helpful assistant.",
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messages: [
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{
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role: "user",
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content: overflowContent,
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timestamp: Date.now(),
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},
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],
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};
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const response = await complete(model, context, { apiKey });
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const hasUsageData = response.usage.input > 0 || response.usage.cacheRead > 0;
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return {
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provider: model.provider,
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model: model.id,
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contextWindow: model.contextWindow,
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stopReason: response.stopReason,
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errorMessage: response.errorMessage,
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usage: response.usage,
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hasUsageData,
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response,
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};
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}
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function logResult(result: OverflowResult) {
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console.log(`\n${result.provider} / ${result.model}:`);
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console.log(` contextWindow: ${result.contextWindow}`);
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console.log(` stopReason: ${result.stopReason}`);
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console.log(` errorMessage: ${result.errorMessage}`);
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console.log(` usage: ${JSON.stringify(result.usage)}`);
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console.log(` hasUsageData: ${result.hasUsageData}`);
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}
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// =============================================================================
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// Anthropic
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// Expected pattern: "prompt is too long: X tokens > Y maximum"
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// =============================================================================
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describe("Context overflow error handling", () => {
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic (API Key)", () => {
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it("claude-3-5-haiku - should detect overflow via isContextOverflow", async () => {
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const model = getModel("anthropic", "claude-3-5-haiku-20241022");
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const result = await testContextOverflow(model, process.env.ANTHROPIC_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/prompt is too long/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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describe.skipIf(!process.env.ANTHROPIC_OAUTH_TOKEN)("Anthropic (OAuth)", () => {
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it("claude-sonnet-4 - should detect overflow via isContextOverflow", async () => {
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const model = getModel("anthropic", "claude-sonnet-4-20250514");
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const result = await testContextOverflow(model, process.env.ANTHROPIC_OAUTH_TOKEN!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/prompt is too long/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// OpenAI
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// Expected pattern: "exceeds the context window"
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// =============================================================================
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions", () => {
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it("gpt-4o-mini - should detect overflow via isContextOverflow", async () => {
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const model = { ...getModel("openai", "gpt-4o-mini") };
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model.api = "openai-completions" as any;
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const result = await testContextOverflow(model, process.env.OPENAI_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/exceeds the context window/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses", () => {
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it("gpt-4o - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openai", "gpt-4o");
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const result = await testContextOverflow(model, process.env.OPENAI_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/exceeds the context window/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// Google
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// Expected pattern: "input token count (X) exceeds the maximum"
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// =============================================================================
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google", () => {
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it("gemini-2.0-flash - should detect overflow via isContextOverflow", async () => {
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const model = getModel("google", "gemini-2.0-flash");
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const result = await testContextOverflow(model, process.env.GEMINI_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/input token count.*exceeds the maximum/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// xAI
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// Expected pattern: "maximum prompt length is X but the request contains Y"
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// =============================================================================
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describe.skipIf(!process.env.XAI_API_KEY)("xAI", () => {
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it("grok-3-fast - should detect overflow via isContextOverflow", async () => {
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const model = getModel("xai", "grok-3-fast");
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const result = await testContextOverflow(model, process.env.XAI_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum prompt length is \d+/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// Groq
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// Expected pattern: "reduce the length of the messages"
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// =============================================================================
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describe.skipIf(!process.env.GROQ_API_KEY)("Groq", () => {
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it("llama-3.3-70b-versatile - should detect overflow via isContextOverflow", async () => {
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const model = getModel("groq", "llama-3.3-70b-versatile");
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const result = await testContextOverflow(model, process.env.GROQ_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/reduce the length of the messages/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// Cerebras
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// Expected: 400/413 status code with no body
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// =============================================================================
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describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras", () => {
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it("qwen-3-235b - should detect overflow via isContextOverflow", async () => {
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const model = getModel("cerebras", "qwen-3-235b-a22b-instruct-2507");
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const result = await testContextOverflow(model, process.env.CEREBRAS_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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// Cerebras returns status code with no body
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expect(result.errorMessage).toMatch(/4(00|13).*\(no body\)/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// z.ai
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// Special case: Sometimes accepts overflow silently, sometimes rate limits
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// Detection via usage.input > contextWindow when successful
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// =============================================================================
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describe.skipIf(!process.env.ZAI_API_KEY)("z.ai", () => {
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it("glm-4.5-flash - should detect overflow via isContextOverflow (silent overflow or rate limit)", async () => {
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const model = getModel("zai", "glm-4.5-flash");
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const result = await testContextOverflow(model, process.env.ZAI_API_KEY!);
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logResult(result);
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// z.ai behavior is inconsistent:
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// - Sometimes accepts overflow and returns successfully with usage.input > contextWindow
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// - Sometimes returns rate limit error
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// Either way, isContextOverflow should detect it (via usage check or we skip if rate limited)
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if (result.stopReason === "stop") {
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expect(result.hasUsageData).toBe(true);
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expect(result.usage.input).toBeGreaterThan(model.contextWindow);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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} else {
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// Rate limited or other error - just log and pass
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console.log(" z.ai returned error (possibly rate limited), skipping overflow detection");
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}
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}, 120000);
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});
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// =============================================================================
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// OpenRouter - Multiple backend providers
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// Expected pattern: "maximum context length is X tokens"
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// =============================================================================
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describe.skipIf(!process.env.OPENROUTER_API_KEY)("OpenRouter", () => {
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// Anthropic backend
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it("anthropic/claude-sonnet-4 via OpenRouter - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openrouter", "anthropic/claude-sonnet-4");
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const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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// DeepSeek backend
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it("deepseek/deepseek-v3.2 via OpenRouter - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openrouter", "deepseek/deepseek-v3.2");
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const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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// Mistral backend
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it("mistralai/mistral-large-2512 via OpenRouter - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openrouter", "mistralai/mistral-large-2512");
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const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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// Google backend
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it("google/gemini-2.5-flash via OpenRouter - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openrouter", "google/gemini-2.5-flash");
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const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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// Meta/Llama backend
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it("meta-llama/llama-4-maverick via OpenRouter - should detect overflow via isContextOverflow", async () => {
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const model = getModel("openrouter", "meta-llama/llama-4-maverick");
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const result = await testContextOverflow(model, process.env.OPENROUTER_API_KEY!);
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(result.errorMessage).toMatch(/maximum context length is \d+ tokens/i);
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// Ollama (local)
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// =============================================================================
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// Check if ollama is installed
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let ollamaInstalled = false;
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try {
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execSync("which ollama", { stdio: "ignore" });
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ollamaInstalled = true;
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} catch {
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ollamaInstalled = false;
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}
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describe.skipIf(!ollamaInstalled)("Ollama (local)", () => {
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let ollamaProcess: ChildProcess | null = null;
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let model: Model<"openai-completions">;
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beforeAll(async () => {
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// Check if model is available, if not pull it
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try {
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execSync("ollama list | grep -q 'gpt-oss:20b'", { stdio: "ignore" });
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} catch {
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console.log("Pulling gpt-oss:20b model for Ollama overflow tests...");
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try {
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execSync("ollama pull gpt-oss:20b", { stdio: "inherit" });
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} catch (e) {
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console.warn("Failed to pull gpt-oss:20b model, tests will be skipped");
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return;
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}
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}
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// Start ollama server
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ollamaProcess = spawn("ollama", ["serve"], {
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detached: false,
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stdio: "ignore",
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});
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// Wait for server to be ready
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await new Promise<void>((resolve) => {
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const checkServer = async () => {
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try {
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const response = await fetch("http://localhost:11434/api/tags");
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if (response.ok) {
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resolve();
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} else {
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setTimeout(checkServer, 500);
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}
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} catch {
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setTimeout(checkServer, 500);
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}
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};
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setTimeout(checkServer, 1000);
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});
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model = {
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id: "gpt-oss:20b",
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api: "openai-completions",
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provider: "ollama",
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baseUrl: "http://localhost:11434/v1",
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reasoning: true,
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input: ["text"],
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contextWindow: 128000,
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maxTokens: 16000,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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name: "Ollama GPT-OSS 20B",
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};
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}, 60000);
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afterAll(() => {
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if (ollamaProcess) {
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ollamaProcess.kill("SIGTERM");
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ollamaProcess = null;
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}
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});
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it("gpt-oss:20b - should detect overflow via isContextOverflow (ollama silently truncates)", async () => {
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const result = await testContextOverflow(model, "ollama");
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logResult(result);
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// Ollama silently truncates input instead of erroring
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// It returns stopReason "stop" with truncated usage
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// We cannot detect overflow via error message, only via usage comparison
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if (result.stopReason === "stop" && result.hasUsageData) {
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// Ollama truncated - check if reported usage is less than what we sent
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// This is a "silent overflow" - we can detect it if we know expected input size
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console.log(" Ollama silently truncated input to", result.usage.input, "tokens");
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// For now, we accept this behavior - Ollama doesn't give us a way to detect overflow
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} else if (result.stopReason === "error") {
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}
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}, 300000); // 5 min timeout for local model
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});
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// =============================================================================
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// LM Studio (local) - Skip if not running
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// =============================================================================
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let lmStudioRunning = false;
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try {
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execSync("curl -s --max-time 1 http://localhost:1234/v1/models > /dev/null", { stdio: "ignore" });
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lmStudioRunning = true;
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} catch {
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lmStudioRunning = false;
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}
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describe.skipIf(!lmStudioRunning)("LM Studio (local)", () => {
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it("should detect overflow via isContextOverflow", async () => {
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const model: Model<"openai-completions"> = {
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id: "local-model",
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api: "openai-completions",
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provider: "lm-studio",
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baseUrl: "http://localhost:1234/v1",
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reasoning: false,
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input: ["text"],
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contextWindow: 8192,
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maxTokens: 2048,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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name: "LM Studio Local Model",
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};
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const result = await testContextOverflow(model, "lm-studio");
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logResult(result);
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expect(result.stopReason).toBe("error");
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expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
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}, 120000);
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});
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// =============================================================================
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// llama.cpp server (local) - Skip if not running
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// =============================================================================
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let llamaCppRunning = false;
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try {
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execSync("curl -s --max-time 1 http://localhost:8081/health > /dev/null", { stdio: "ignore" });
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llamaCppRunning = true;
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} catch {
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llamaCppRunning = false;
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}
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describe.skipIf(!llamaCppRunning)("llama.cpp (local)", () => {
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it("should detect overflow via isContextOverflow", async () => {
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// Using small context (4096) to match server --ctx-size setting
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const model: Model<"openai-completions"> = {
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id: "local-model",
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api: "openai-completions",
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provider: "llama.cpp",
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baseUrl: "http://localhost:8081/v1",
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reasoning: false,
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input: ["text"],
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contextWindow: 4096,
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maxTokens: 2048,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
|
name: "llama.cpp Local Model",
|
|
};
|
|
|
|
const result = await testContextOverflow(model, "llama.cpp");
|
|
logResult(result);
|
|
|
|
expect(result.stopReason).toBe("error");
|
|
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
|
}, 120000);
|
|
});
|
|
});
|