@juspay/neurolink/dist/utils/videoAnalysisProcessor.js

The pipe layer of an AI nervous system: one interface connecting provider neurons to your application, across three inference types — generate, stream and decide. `decide` returns typed, calibrated judgements from a non-generative model (~400ms, ~$0.00002

import { AIProviderName } from "../constants/enums.js";
import { logger } from "./logger.js";
/**
 * Check if messages contain video frames (images)
 * Only checks user messages to match buildContentParts behavior
 *
 * @param messages - Array of ModelMessage objects
 * @returns true if video frames are present in user messages
 */
export function hasVideoFrames(messages) {
    return messages.some((msg) => {
        // Only check user messages to match buildContentParts behavior
        if (msg.role !== "user") {
            return false;
        }
        if (Array.isArray(msg.content)) {
            // Count image parts — only route to video analysis pipeline when there are
            // multiple frames (3+), indicating actual video frame extraction.
            // Single images or pairs should use the model's native vision capability.
            const imageCount = msg.content.filter((part) => typeof part === "object" &&
                part !== null &&
                "type" in part &&
                part.type === "image").length;
            return imageCount >= 3;
        }
        return false;
    });
}
/**
 * Execute video analysis on messages containing video frames
 *
 * @param messages - Array of ModelMessage objects with video frames
 * @param options - Video analysis options
 * @returns Video analysis text result
 * @throws Error if analysis fails
 */
export async function executeVideoAnalysis(messages, options) {
    logger.debug("[VideoAnalysisProcessor] Video frames detected, triggering analysis");
    const { analyzeVideo } = await import("../adapters/video/videoAnalyzer.js");
    const provider = options.provider === AIProviderName.GOOGLE_AI ||
        (options.provider === AIProviderName.AUTO && process.env.GOOGLE_AI_API_KEY)
        ? AIProviderName.GOOGLE_AI
        : options.provider === AIProviderName.VERTEX ||
            options.providerName === AIProviderName.VERTEX
            ? AIProviderName.VERTEX
            : AIProviderName.AUTO;
    const videoAnalysisText = await analyzeVideo(messages, {
        provider: provider,
        project: options.region
            ? undefined
            : process.env.GOOGLE_VERTEX_PROJECT || process.env.GOOGLE_CLOUD_PROJECT,
        location: options.region || process.env.GOOGLE_VERTEX_LOCATION,
        model: options.model || "gemini-2.5-flash",
    });
    logger.debug("[VideoAnalysisProcessor] Video analysis completed", {
        hasResult: !!videoAnalysisText,
        resultLength: videoAnalysisText?.length,
    });
    return videoAnalysisText;
}