- Coalesce Qoder's empty finish-in-delta frame with the later choices:[] usage frame so OpenAI and Claude clients receive prompt_tokens, completion_tokens and cache-hit tokens (the dashboard already saw them) - Upload inlined images through /api/v2/image/upload like qodercli, and stub oversized non-image files instead of stuffing 30MB+ data URIs into agent_chat_generation - Emit response.completed -> response.usage for chat-native upstreams so /v1/responses clients (Codex CLI, sub2api) no longer log 0/0/0 - Keep Claude message_delta.usage working when usage arrives without choices[0] - Escalate to the smallest advertised Qoder context tier (200K/400K/1M) when the estimated prompt no longer fits max_input_tokens - Pass apiKey for PAT connections and list hidden enable:false catalog keys from /v1/models
234 lines
7.8 KiB
JavaScript
234 lines
7.8 KiB
JavaScript
/**
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* Unit tests for open-sse/translator/request/openai-to-claude.js
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*
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* Tests cover:
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* - openaiToClaudeRequest() - OpenAI to Claude request translation
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* - Response format handling (json_schema, json_object)
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*/
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import { describe, it, expect } from "vitest";
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import { openaiToClaudeRequest } from "../../open-sse/translator/request/openai-to-claude.js";
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import { openaiToClaudeResponse } from "../../open-sse/translator/response/openai-to-claude.js";
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describe("openaiToClaudeRequest", () => {
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describe("response_format handling", () => {
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it("should inject JSON schema instructions for json_schema type", () => {
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const body = {
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messages: [{ role: "user", content: "What is 2+2?" }],
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response_format: {
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type: "json_schema",
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json_schema: {
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name: "math_response",
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schema: {
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type: "object",
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properties: {
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answer: { type: "number" },
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explanation: { type: "string" }
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},
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required: ["answer", "explanation"]
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}
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}
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}
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};
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const result = openaiToClaudeRequest("claude-sonnet-4.5", body, false);
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// Should have system array with instructions
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expect(result.system).toBeDefined();
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expect(Array.isArray(result.system)).toBe(true);
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// Check that system prompt includes schema
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const systemText = result.system
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.filter(s => s.type === "text")
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.map(s => s.text)
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.join("\n");
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expect(systemText).toContain("You must respond with valid JSON");
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expect(systemText).toContain("\"answer\"");
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expect(systemText).toContain("\"explanation\"");
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expect(systemText).toContain("Respond ONLY with the JSON object");
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});
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it("should inject basic JSON instructions for json_object type", () => {
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const body = {
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messages: [{ role: "user", content: "Give me a JSON object" }],
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response_format: {
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type: "json_object"
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}
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};
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const result = openaiToClaudeRequest("claude-sonnet-4.5", body, false);
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// Should have system array with instructions
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expect(result.system).toBeDefined();
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expect(Array.isArray(result.system)).toBe(true);
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const systemText = result.system
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.filter(s => s.type === "text")
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.map(s => s.text)
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.join("\n");
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expect(systemText).toContain("You must respond with valid JSON");
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expect(systemText).toContain("Respond ONLY with a JSON object");
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});
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it("should not modify system prompt when response_format is missing", () => {
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const body = {
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messages: [{ role: "user", content: "Hello" }]
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};
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const result = openaiToClaudeRequest("claude-sonnet-4.5", body, false);
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// Should have system but without JSON instructions
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expect(result.system).toBeDefined();
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const systemText = result.system
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.filter(s => s.type === "text")
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.map(s => s.text)
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.join("\n");
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// Should NOT contain JSON-specific instructions
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expect(systemText).not.toContain("You must respond with valid JSON");
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});
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it("should preserve existing system messages when adding response_format", () => {
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const body = {
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messages: [
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{ role: "system", content: "You are a helpful math tutor." },
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{ role: "user", content: "What is 2+2?" }
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],
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response_format: {
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type: "json_schema",
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json_schema: {
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schema: {
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type: "object",
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properties: {
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result: { type: "number" }
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}
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}
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}
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}
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};
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const result = openaiToClaudeRequest("claude-sonnet-4.5", body, false);
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// Should preserve original system message
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const systemText = result.system
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.filter(s => s.type === "text")
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.map(s => s.text)
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.join("\n");
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expect(systemText).toContain("You are a helpful math tutor");
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expect(systemText).toContain("You must respond with valid JSON");
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});
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});
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describe("tool_choice handling", () => {
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const baseBody = {
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messages: [{ role: "user", content: "add a todo" }],
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tools: [{
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type: "function",
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function: { name: "todo_write", description: "write todos", parameters: { type: "object", properties: {} } }
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}]
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};
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const choiceOf = (tc) =>
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openaiToClaudeRequest("claude-sonnet-4.5", { ...baseBody, tool_choice: tc }, false).tool_choice;
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it("converts OpenAI forced tool ({type:'function'}) to Claude {type:'tool'}", () => {
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// Must NOT leak the OpenAI "function" type — Claude only accepts auto|any|tool|none.
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expect(choiceOf({ type: "function", function: { name: "todo_write" } }))
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.toEqual({ type: "tool", name: "todo_write" });
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});
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it("maps string tool_choice values", () => {
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expect(choiceOf("auto")).toEqual({ type: "auto" });
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expect(choiceOf("none")).toEqual({ type: "auto" });
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expect(choiceOf("required")).toEqual({ type: "any" });
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});
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it("passes through Claude-native tool_choice objects unchanged", () => {
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expect(choiceOf({ type: "tool", name: "todo_write" })).toEqual({ type: "tool", name: "todo_write" });
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expect(choiceOf({ type: "any" })).toEqual({ type: "any" });
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expect(choiceOf({ type: "none" })).toEqual({ type: "none" });
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});
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it("never leaks an invalid type (falls back to auto)", () => {
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// Malformed forced choice with no tool name, and unknown types, must not
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// pass an invalid `type` through to Claude.
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expect(choiceOf({ type: "function", function: {} })).toEqual({ type: "auto" });
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expect(choiceOf({ type: "function" })).toEqual({ type: "auto" });
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expect(choiceOf({ type: "bogus" })).toEqual({ type: "auto" });
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});
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it("omits tool_choice entirely when the request has none", () => {
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const result = openaiToClaudeRequest("claude-sonnet-4.5", baseBody, false);
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expect(result.tool_choice).toBeUndefined();
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});
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});
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});
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describe("openaiToClaudeResponse", () => {
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it("omits empty Read pages tool argument before emitting Claude input deltas", () => {
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const state = { toolCalls: new Map() };
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const chunk = {
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id: "chatcmpl-test",
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model: "gpt-test",
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choices: [{
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delta: {
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tool_calls: [{
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index: 0,
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id: "call_read",
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function: {
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name: "Read",
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arguments: JSON.stringify({
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file_path: "/tmp/example.txt",
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offset: 0,
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limit: 120,
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pages: ""
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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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const result = openaiToClaudeResponse(chunk, state);
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const inputDelta = result.find(event => event.delta?.type === "input_json_delta");
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expect(inputDelta).toBeDefined();
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expect(JSON.parse(inputDelta.delta.partial_json)).toEqual({
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file_path: "/tmp/example.txt",
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offset: 0,
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limit: 120
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});
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});
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it("records usage from a choices:[] frame so the finish chunk can emit it", () => {
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const state = { toolCalls: new Map() };
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expect(openaiToClaudeResponse({
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usage: {
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prompt_tokens: 90,
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completion_tokens: 7,
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prompt_tokens_details: { cached_tokens: 30 },
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},
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choices: [],
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}, state)).toBeNull();
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expect(state.usage).toEqual({
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input_tokens: 60,
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output_tokens: 7,
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cache_read_input_tokens: 30,
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});
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const events = openaiToClaudeResponse({
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id: "chatcmpl-qoder-finish",
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model: "qoder/auto",
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choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
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}, state);
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const delta = events.find((e) => e.type === "message_delta");
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expect(delta.usage.input_tokens).toBe(60);
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expect(delta.usage.output_tokens).toBe(7);
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expect(delta.usage.cache_read_input_tokens).toBe(30);
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});
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});
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