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https://github.com/QwenLM/qwen-code.git
synced 2025-12-19 09:33:53 +00:00
Improve readability issues
This is only the first change of many changes. * Remove redundant autogenerated comments * Use the recommended file name style * Use camelCase for variable names * Don't introduce submodules for relevant types * Don't introduce constants like modules, these are implementation details * Remove empty files
This commit is contained in:
Jaana Dogan
committed by
N. Taylor Mullen
N. Taylor Mullen
parent
898a83031c
commit
81ba61df7f
383
packages/cli/src/core/gemini-client.ts
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383
packages/cli/src/core/gemini-client.ts
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import {
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GenerateContentConfig, GoogleGenAI, Part, Chat,
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Type,
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SchemaUnion,
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PartListUnion,
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Content
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} from '@google/genai';
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import { getApiKey } from '../config/env.js';
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import { CoreSystemPrompt } from './prompts.js';
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import { type ToolCallEvent, type ToolCallConfirmationDetails, ToolCallStatus } from '../ui/types.js';
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import process from 'node:process';
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import { toolRegistry } from '../tools/tool-registry.js';
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import { ToolResult } from '../tools/tool.js';
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import { getFolderStructure } from '../utils/getFolderStructure.js';
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import { GeminiEventType, GeminiStream } from './gemini-stream.js';
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type ToolExecutionOutcome = {
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callId: string;
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name: string;
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args: Record<string, any>;
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result?: ToolResult;
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error?: any;
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confirmationDetails?: ToolCallConfirmationDetails;
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};
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export class GeminiClient {
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private ai: GoogleGenAI;
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private defaultHyperParameters: GenerateContentConfig = {
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temperature: 0,
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topP: 1,
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};
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private readonly MAX_TURNS = 100;
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constructor() {
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const apiKey = getApiKey();
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this.ai = new GoogleGenAI({ apiKey });
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}
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public async startChat(): Promise<Chat> {
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const tools = toolRegistry.getToolSchemas();
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// --- Get environmental information ---
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const cwd = process.cwd();
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const today = new Date().toLocaleDateString(undefined, { // Use locale-aware date formatting
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weekday: 'long', year: 'numeric', month: 'long', day: 'numeric'
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});
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const platform = process.platform;
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// --- Format information into a conversational multi-line string ---
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const folderStructure = await getFolderStructure(cwd);
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// --- End folder structure formatting ---)
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const initialContextText = `
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Okay, just setting up the context for our chat.
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Today is ${today}.
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My operating system is: ${platform}
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I'm currently working in the directory: ${cwd}
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${folderStructure}
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`.trim();
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const initialContextPart: Part = { text: initialContextText };
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// --- End environmental information formatting ---
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try {
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const chat = this.ai.chats.create({
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model: 'gemini-2.0-flash',//'gemini-2.0-flash',
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config: {
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systemInstruction: CoreSystemPrompt,
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...this.defaultHyperParameters,
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tools,
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},
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history: [
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// --- Add the context as a single part in the initial user message ---
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{
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role: "user",
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parts: [initialContextPart] // Pass the single Part object in an array
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},
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// --- Add an empty model response to balance the history ---
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{
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role: "model",
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parts: [{ text: "Got it. Thanks for the context!" }] // A slightly more conversational model response
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}
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// --- End history modification ---
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],
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});
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return chat;
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} catch (error) {
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console.error("Error initializing Gemini chat session:", error);
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const message = error instanceof Error ? error.message : "Unknown error.";
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throw new Error(`Failed to initialize chat: ${message}`);
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}
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}
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public addMessageToHistory(chat: Chat, message: Content): void {
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const history = chat.getHistory();
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history.push(message);
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this.ai.chats
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chat
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}
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public async* sendMessageStream(
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chat: Chat,
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request: PartListUnion,
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signal?: AbortSignal
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): GeminiStream {
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let currentMessageToSend: PartListUnion = request;
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let turns = 0;
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try {
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while (turns < this.MAX_TURNS) {
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turns++;
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const resultStream = await chat.sendMessageStream({ message: currentMessageToSend });
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let functionResponseParts: Part[] = [];
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let pendingToolCalls: Array<{ callId: string; name: string; args: Record<string, any> }> = [];
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let yieldedTextInTurn = false;
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const chunksForDebug = [];
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for await (const chunk of resultStream) {
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chunksForDebug.push(chunk);
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if (signal?.aborted) {
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const abortError = new Error("Request cancelled by user during stream.");
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abortError.name = 'AbortError';
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throw abortError;
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}
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const functionCalls = chunk.functionCalls;
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if (functionCalls && functionCalls.length > 0) {
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for (const call of functionCalls) {
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const callId = call.id ?? `${call.name}-${Date.now()}-${Math.random().toString(16).slice(2)}`;
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const name = call.name || 'undefined_tool_name';
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const args = (call.args || {}) as Record<string, any>;
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pendingToolCalls.push({ callId, name, args });
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const evtValue: ToolCallEvent = {
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type: 'tool_call',
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status: ToolCallStatus.Pending,
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callId,
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name,
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args,
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resultDisplay: undefined,
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confirmationDetails: undefined,
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}
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yield {
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type: GeminiEventType.ToolCallInfo,
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value: evtValue,
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};
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}
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} else {
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const text = chunk.text;
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if (text) {
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yieldedTextInTurn = true;
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yield {
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type: GeminiEventType.Content,
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value: text,
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};
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}
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}
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}
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if (pendingToolCalls.length > 0) {
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const toolPromises: Promise<ToolExecutionOutcome>[] = pendingToolCalls.map(async pendingToolCall => {
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const tool = toolRegistry.getTool(pendingToolCall.name);
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if (!tool) {
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// Directly return error outcome if tool not found
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return { ...pendingToolCall, error: new Error(`Tool "${pendingToolCall.name}" not found or is not registered.`) };
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}
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try {
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const confirmation = await tool.shouldConfirmExecute(pendingToolCall.args);
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if (confirmation) {
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return { ...pendingToolCall, confirmationDetails: confirmation };
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}
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} catch (error) {
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return { ...pendingToolCall, error: new Error(`Tool failed to check tool confirmation: ${error}`) };
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}
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try {
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const result = await tool.execute(pendingToolCall.args);
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return { ...pendingToolCall, result };
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} catch (error) {
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return { ...pendingToolCall, error: new Error(`Tool failed to execute: ${error}`) };
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}
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});
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const toolExecutionOutcomes: ToolExecutionOutcome[] = await Promise.all(toolPromises);
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for (const executedTool of toolExecutionOutcomes) {
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const { callId, name, args, result, error, confirmationDetails } = executedTool;
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if (error) {
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const errorMessage = error?.message || String(error);
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yield {
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type: GeminiEventType.Content,
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value: `[Error invoking tool ${name}: ${errorMessage}]`,
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};
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} else if (result && typeof result === 'object' && result !== null && 'error' in result) {
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const errorMessage = String(result.error);
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yield {
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type: GeminiEventType.Content,
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value: `[Error executing tool ${name}: ${errorMessage}]`,
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};
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} else {
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const status = confirmationDetails ? ToolCallStatus.Confirming : ToolCallStatus.Invoked;
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const evtValue: ToolCallEvent = { type: 'tool_call', status, callId, name, args, resultDisplay: result?.returnDisplay, confirmationDetails }
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yield {
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type: GeminiEventType.ToolCallInfo,
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value: evtValue,
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};
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}
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}
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pendingToolCalls = [];
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const waitingOnConfirmations = toolExecutionOutcomes.filter(outcome => outcome.confirmationDetails).length > 0;
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if (waitingOnConfirmations) {
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// Stop processing content, wait for user.
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// TODO: Kill token processing once API supports signals.
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break;
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}
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functionResponseParts = toolExecutionOutcomes.map((executedTool: ToolExecutionOutcome): Part => {
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const { name, result, error } = executedTool;
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const output = { "output": result?.llmContent };
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let toolOutcomePayload: any;
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if (error) {
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const errorMessage = error?.message || String(error);
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toolOutcomePayload = { error: `Invocation failed: ${errorMessage}` };
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console.error(`[Turn ${turns}] Critical error invoking tool ${name}:`, error);
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} else if (result && typeof result === 'object' && result !== null && 'error' in result) {
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toolOutcomePayload = output;
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console.warn(`[Turn ${turns}] Tool ${name} returned an error structure:`, result.error);
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} else {
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toolOutcomePayload = output;
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}
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return {
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functionResponse: {
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name: name,
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id: executedTool.callId,
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response: toolOutcomePayload,
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},
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};
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});
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currentMessageToSend = functionResponseParts;
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} else if (yieldedTextInTurn) {
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const history = chat.getHistory();
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const checkPrompt = `Analyze *only* the content and structure of your immediately preceding response (your last turn in the conversation history). Based *strictly* on that response, determine who should logically speak next: the 'user' or the 'model' (you).
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**Decision Rules (apply in order):**
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1. **Model Continues:** If your last response explicitly states an immediate next action *you* intend to take (e.g., "Next, I will...", "Now I'll process...", "Moving on to analyze...", indicates an intended tool call that didn't execute), OR if the response seems clearly incomplete (cut off mid-thought without a natural conclusion), then the **'model'** should speak next.
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2. **Question to User:** If your last response ends with a direct question specifically addressed *to the user*, then the **'user'** should speak next.
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3. **Waiting for User:** If your last response completed a thought, statement, or task *and* does not meet the criteria for Rule 1 (Model Continues) or Rule 2 (Question to User), it implies a pause expecting user input or reaction. In this case, the **'user'** should speak next.
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**Output Format:**
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Respond *only* in JSON format according to the following schema. Do not include any text outside the JSON structure.
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\`\`\`json
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{
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"type": "object",
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"properties": {
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"reasoning": {
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"type": "string",
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"description": "Brief explanation justifying the 'next_speaker' choice based *strictly* on the applicable rule and the content/structure of the preceding turn."
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},
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"next_speaker": {
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"type": "string",
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"enum": ["user", "model"],
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"description": "Who should speak next based *only* on the preceding turn and the decision rules."
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}
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},
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"required": ["next_speaker", "reasoning"]
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\`\`\`
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}`;
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// Schema Idea
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const responseSchema: SchemaUnion = {
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type: Type.OBJECT,
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properties: {
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reasoning: {
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type: Type.STRING,
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description: "Brief explanation justifying the 'next_speaker' choice based *strictly* on the applicable rule and the content/structure of the preceding turn."
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},
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next_speaker: {
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type: Type.STRING,
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enum: ['user', 'model'], // Enforce the choices
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description: "Who should speak next based *only* on the preceding turn and the decision rules",
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},
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},
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required: ['reasoning', 'next_speaker']
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};
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try {
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// Use the new generateJson method, passing the history and the check prompt
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const parsedResponse = await this.generateJson([...history, { role: "user", parts: [{ text: checkPrompt }] }], responseSchema);
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// Safely extract the next speaker value
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const nextSpeaker: string | undefined = typeof parsedResponse?.next_speaker === 'string' ? parsedResponse.next_speaker : undefined;
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if (nextSpeaker === 'model') {
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currentMessageToSend = { text: 'alright' }; // Or potentially a more meaningful continuation prompt
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} else {
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// 'user' should speak next, or value is missing/invalid. End the turn.
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break;
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}
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} catch (error) {
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console.error(`[Turn ${turns}] Failed to get or parse next speaker check:`, error);
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// If the check fails, assume user should speak next to avoid infinite loops
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break;
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}
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} else {
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console.warn(`[Turn ${turns}] No text or function calls received from Gemini. Ending interaction.`);
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break;
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}
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}
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if (turns >= this.MAX_TURNS) {
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console.warn("sendMessageStream: Reached maximum tool call turns limit.");
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yield {
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type: GeminiEventType.Content,
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value: "\n\n[System Notice: Maximum interaction turns reached. The conversation may be incomplete.]",
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};
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}
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} catch (error: unknown) {
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if (error instanceof Error && error.name === 'AbortError') {
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console.log("Gemini stream request aborted by user.");
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throw error;
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} else {
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console.error(`Error during Gemini stream or tool interaction:`, error);
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const message = error instanceof Error ? error.message : String(error);
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yield {
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type: GeminiEventType.Content,
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value: `\n\n[Error: An unexpected error occurred during the chat: ${message}]`,
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};
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throw error;
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}
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}
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}
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/**
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* Generates structured JSON content based on conversational history and a schema.
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* @param contents The conversational history (Content array) to provide context.
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* @param schema The SchemaUnion defining the desired JSON structure.
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* @returns A promise that resolves to the parsed JSON object matching the schema.
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* @throws Throws an error if the API call fails or the response is not valid JSON.
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*/
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public async generateJson(contents: Content[], schema: SchemaUnion): Promise<any> {
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try {
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const result = await this.ai.models.generateContent({
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model: 'gemini-2.0-flash', // Using flash for potentially faster structured output
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config: {
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...this.defaultHyperParameters,
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systemInstruction: CoreSystemPrompt,
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responseSchema: schema,
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responseMimeType: 'application/json',
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},
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contents: contents, // Pass the full Content array
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});
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const responseText = result.text;
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if (!responseText) {
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throw new Error("API returned an empty response.");
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}
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try {
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const parsedJson = JSON.parse(responseText);
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// TODO: Add schema validation if needed
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return parsedJson;
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} catch (parseError) {
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console.error("Failed to parse JSON response:", responseText);
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throw new Error(`Failed to parse API response as JSON: ${parseError instanceof Error ? parseError.message : String(parseError)}`);
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}
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} catch (error) {
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console.error("Error generating JSON content:", error);
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const message = error instanceof Error ? error.message : "Unknown API error.";
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throw new Error(`Failed to generate JSON content: ${message}`);
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}
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}
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}
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Block a user