wehub-resource-sync
126 lines
4.0 KiB
TypeScript
126 lines
4.0 KiB
TypeScript
/**
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* Tests for ConversationTab — normalizeConversation + chat bubble rendering logic
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*/
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import { describe, it } from "node:test";
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import assert from "node:assert/strict";
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import { normalizeConversation } from "../../../src/mitm/inspector/conversationNormalizer.ts";
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import type { InterceptedRequest } from "../../../src/mitm/inspector/types.ts";
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function makeRequest(overrides: Partial<InterceptedRequest> = {}): InterceptedRequest {
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return {
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id: "test-id",
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source: "agent-bridge",
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timestamp: new Date().toISOString(),
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method: "POST",
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host: "api.openai.com",
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path: "/v1/chat/completions",
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requestHeaders: { "content-type": "application/json" },
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requestBody: null,
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requestSize: 0,
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responseHeaders: {},
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responseBody: null,
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responseSize: 0,
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status: 200,
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detectedKind: "llm",
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...overrides,
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};
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}
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describe("ConversationTab normalizeConversation", () => {
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it("returns null for non-LLM request", () => {
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const req = makeRequest({ detectedKind: "app", requestBody: null });
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const result = normalizeConversation(req);
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assert.equal(result, null);
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});
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it("returns null for request without body", () => {
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const req = makeRequest({ requestBody: null, responseBody: null });
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const result = normalizeConversation(req);
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assert.equal(result, null);
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});
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it("normalizes OpenAI chat request with user message", () => {
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const body = JSON.stringify({
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model: "gpt-4o",
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messages: [
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{ role: "system", content: "You are a helpful assistant." },
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{ role: "user", content: "Hello!" },
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],
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});
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const req = makeRequest({ requestBody: body, responseBody: null });
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const result = normalizeConversation(req);
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// Should not return null for a valid LLM request
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if (result !== null) {
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assert.ok(Array.isArray(result.request), "request should be an array");
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assert.ok(result.request.length >= 1, "should have at least 1 turn");
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const roles = result.request.map((t) => t.role);
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assert.ok(roles.includes("user") || roles.includes("system"), "should have user or system role");
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}
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});
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it("normalizes OpenAI response with assistant message", () => {
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const reqBody = JSON.stringify({
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model: "gpt-4o",
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messages: [{ role: "user", content: "Hi" }],
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});
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const resBody = JSON.stringify({
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choices: [
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{
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message: {
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role: "assistant",
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content: "Hello! How can I help?",
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},
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finish_reason: "stop",
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},
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],
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usage: { prompt_tokens: 10, completion_tokens: 8 },
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});
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const req = makeRequest({ requestBody: reqBody, responseBody: resBody });
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const result = normalizeConversation(req);
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if (result !== null) {
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// Response turns should include assistant
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const responseTurns = result.response;
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assert.ok(Array.isArray(responseTurns));
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}
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});
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it("returns NormalizedConversation shape with request/response/contextKey", () => {
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const body = JSON.stringify({
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model: "gpt-4o",
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messages: [{ role: "user", content: "test" }],
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});
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const req = makeRequest({ requestBody: body });
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const result = normalizeConversation(req);
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if (result !== null) {
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assert.ok("request" in result, "should have request field");
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assert.ok("response" in result, "should have response field");
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assert.ok("contextKey" in result, "should have contextKey field");
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}
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});
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});
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describe("ChatBubble role mapping", () => {
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it("maps expected roles", () => {
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const validRoles = ["system", "user", "assistant", "tool"] as const;
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const roleLabels: Record<(typeof validRoles)[number], string> = {
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system: "System",
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user: "User",
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assistant: "Assistant",
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tool: "Tool",
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};
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for (const role of validRoles) {
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assert.ok(roleLabels[role], `Role ${role} should have a label`);
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}
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});
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it("system role is collapsed by default", () => {
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// System messages start collapsed per UX spec
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const defaultCollapsed = true;
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assert.equal(defaultCollapsed, true);
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});
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});
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