/**
 * @license
 * Copyright 2025 Google LLC
 * SPDX-License-Identifier: Apache-2.0
 */
import { DEFAULT_ARC_MODEL } from '../config/models.js';
import { isFunctionResponse } from './messageInspectors.js';
const CHECK_PROMPT = `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).
**Decision Rules (apply in order):**
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.
2.  **Question to User:** If your last response ends with a direct question specifically addressed *to the user*, then the **'user'** should speak next.
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.`;
const RESPONSE_SCHEMA = {
    type: 'object',
    properties: {
        reasoning: {
            type: 'string',
            description: "Brief explanation justifying the 'next_speaker' choice based *strictly* on the applicable rule and the content/structure of the preceding turn.",
        },
        next_speaker: {
            type: 'string',
            enum: ['user', 'model'],
            description: 'Who should speak next based *only* on the preceding turn and the decision rules',
        },
    },
    required: ['reasoning', 'next_speaker'],
};
export async function checkNextSpeaker(chat, config, abortSignal, promptId) {
    // We need to capture the curated history because there are many moments when the model will return invalid turns
    // that when passed back up to the endpoint will break subsequent calls. An example of this is when the model decides
    // to respond with an empty part collection if you were to send that message back to the server it will respond with
    // a 400 indicating that model part collections MUST have content.
    const curatedHistory = chat.getHistory(/* curated */ true);
    // Ensure there's a model response to analyze
    if (curatedHistory.length === 0) {
        // Cannot determine next speaker if history is empty.
        return null;
    }
    const comprehensiveHistory = chat.getHistory();
    // If comprehensiveHistory is empty, there is no last message to check.
    // This case should ideally be caught by the curatedHistory.length check earlier,
    // but as a safeguard:
    if (comprehensiveHistory.length === 0) {
        return null;
    }
    const lastComprehensiveMessage = comprehensiveHistory[comprehensiveHistory.length - 1];
    // If the last message is a user message containing only function_responses,
    // then the model should speak next.
    if (lastComprehensiveMessage &&
        isFunctionResponse(lastComprehensiveMessage)) {
        return {
            reasoning: 'The last message was a function response, so the model should speak next.',
            next_speaker: 'model',
        };
    }
    if (lastComprehensiveMessage &&
        lastComprehensiveMessage.role === 'model' &&
        lastComprehensiveMessage.parts &&
        lastComprehensiveMessage.parts.length === 0) {
        lastComprehensiveMessage.parts.push({ text: '' });
        return {
            reasoning: 'The last message was a filler model message with no content (nothing for user to act on), model should speak next.',
            next_speaker: 'model',
        };
    }
    // Things checked out. Let's proceed to potentially making an LLM request.
    const lastMessage = curatedHistory[curatedHistory.length - 1];
    if (!lastMessage || lastMessage.role !== 'model') {
        // Cannot determine next speaker if the last turn wasn't from the model
        // or if history is empty.
        return null;
    }
    const contents = [
        ...curatedHistory,
        { role: 'user', parts: [{ text: CHECK_PROMPT }] },
    ];
    try {
        const parsedResponse = (await config.getBaseLlmClient().generateJson({
            contents,
            schema: RESPONSE_SCHEMA,
            model: config.getModel() || DEFAULT_ARC_MODEL,
            abortSignal,
            promptId,
        }));
        if (parsedResponse &&
            parsedResponse.next_speaker &&
            ['user', 'model'].includes(parsedResponse.next_speaker)) {
            return parsedResponse;
        }
        return null;
    }
    catch (error) {
        console.warn('Failed to talk to Gemini endpoint when seeing if conversation should continue.', error);
        return null;
    }
}
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