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test(ai): Add empty message tests for all providers
- Test handling of empty content arrays - Test handling of empty string content - Test handling of whitespace-only content - All providers handle these edge cases gracefully
This commit is contained in:
Mario Zechner
parent
0fbb0921bb
commit
0ac05a0676
9 changed files with 256 additions and 18 deletions
238
packages/ai/test/empty.test.ts
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238
packages/ai/test/empty.test.ts
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import { describe, it, beforeAll, expect } from "vitest";
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import { GoogleLLM } from "../src/providers/google.js";
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import { OpenAICompletionsLLM } from "../src/providers/openai-completions.js";
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import { OpenAIResponsesLLM } from "../src/providers/openai-responses.js";
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import { AnthropicLLM } from "../src/providers/anthropic.js";
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import type { LLM, LLMOptions, Context, UserMessage } from "../src/types.js";
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import { getModel } from "../src/models.js";
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async function testEmptyMessage<T extends LLMOptions>(llm: LLM<T>, options: T = {} as T) {
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// Test with completely empty content array
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const emptyMessage: UserMessage = {
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role: "user",
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content: []
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};
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const context: Context = {
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messages: [emptyMessage]
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};
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const response = await llm.generate(context, options);
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// Should either handle gracefully or return an error
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expect(response).toBeDefined();
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expect(response.role).toBe("assistant");
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// Most providers should return an error or empty response
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if (response.stopReason === "error") {
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expect(response.error).toBeDefined();
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} else {
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// If it didn't error, it should have some content or gracefully handle empty
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expect(response.content).toBeDefined();
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}
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}
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async function testEmptyStringMessage<T extends LLMOptions>(llm: LLM<T>, options: T = {} as T) {
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// Test with empty string content
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const context: Context = {
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messages: [{
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role: "user",
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content: ""
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}]
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};
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const response = await llm.generate(context, options);
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expect(response).toBeDefined();
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expect(response.role).toBe("assistant");
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// Should handle empty string gracefully
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if (response.stopReason === "error") {
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expect(response.error).toBeDefined();
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} else {
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expect(response.content).toBeDefined();
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}
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}
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async function testWhitespaceOnlyMessage<T extends LLMOptions>(llm: LLM<T>, options: T = {} as T) {
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// Test with whitespace-only content
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const context: Context = {
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messages: [{
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role: "user",
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content: " \n\t "
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}]
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};
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const response = await llm.generate(context, options);
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expect(response).toBeDefined();
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expect(response.role).toBe("assistant");
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// Should handle whitespace-only gracefully
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if (response.stopReason === "error") {
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expect(response.error).toBeDefined();
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} else {
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expect(response.content).toBeDefined();
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}
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}
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describe("AI Providers Empty Message Tests", () => {
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Empty Messages", () => {
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let llm: GoogleLLM;
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beforeAll(() => {
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llm = new GoogleLLM(getModel("google", "gemini-2.5-flash")!, process.env.GEMINI_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Empty Messages", () => {
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let llm: OpenAICompletionsLLM;
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beforeAll(() => {
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llm = new OpenAICompletionsLLM(getModel("openai", "gpt-4o-mini")!, process.env.OPENAI_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Empty Messages", () => {
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let llm: OpenAIResponsesLLM;
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beforeAll(() => {
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const model = getModel("openai", "gpt-5-mini");
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if (!model) {
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throw new Error("Model gpt-5-mini not found");
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}
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llm = new OpenAIResponsesLLM(model, process.env.OPENAI_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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describe.skipIf(!process.env.ANTHROPIC_OAUTH_TOKEN)("Anthropic Provider Empty Messages", () => {
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let llm: AnthropicLLM;
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beforeAll(() => {
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llm = new AnthropicLLM(getModel("anthropic", "claude-3-5-haiku-20241022")!, process.env.ANTHROPIC_OAUTH_TOKEN!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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// Test with xAI/Grok if available
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describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider Empty Messages", () => {
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let llm: OpenAICompletionsLLM;
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beforeAll(() => {
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const model = getModel("xai", "grok-3");
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if (!model) {
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throw new Error("Model grok-3 not found");
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}
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llm = new OpenAICompletionsLLM(model, process.env.XAI_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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// Test with Groq if available
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describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider Empty Messages", () => {
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let llm: OpenAICompletionsLLM;
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beforeAll(() => {
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const model = getModel("groq", "llama-3.3-70b-versatile");
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if (!model) {
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throw new Error("Model llama-3.3-70b-versatile not found");
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}
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llm = new OpenAICompletionsLLM(model, process.env.GROQ_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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// Test with Cerebras if available
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describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider Empty Messages", () => {
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let llm: OpenAICompletionsLLM;
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beforeAll(() => {
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const model = getModel("cerebras", "gpt-oss-120b");
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if (!model) {
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throw new Error("Model gpt-oss-120b not found");
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}
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llm = new OpenAICompletionsLLM(model, process.env.CEREBRAS_API_KEY!);
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});
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it("should handle empty content array", async () => {
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await testEmptyMessage(llm);
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});
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it("should handle empty string content", async () => {
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await testEmptyStringMessage(llm);
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});
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it("should handle whitespace-only content", async () => {
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await testWhitespaceOnlyMessage(llm);
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});
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});
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});
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