import { NextRequest, NextResponse } from "next/server";
import { exec } from "child_process";
import { promisify } from "util";
const execAsync = promisify(exec);
export const dynamic = "force-dynamic";
const QUANTCLAW_DATA_DIR = "/home/quant/apps/quantclaw-data";
const PYTHON = "python3";
/**
* AI Earnings Call Analyzer API — Real-time Tone Detection, Hesitation Patterns, Confidence Scoring
*
* Advanced linguistic analysis of earnings call transcripts using LLM-style techniques:
* - Real-time tone detection with contextual sentiment analysis
* - Hesitation pattern recognition (fillers, pauses, corrections)
* - Executive confidence scoring via multi-factor analysis
* - Quarter-over-quarter language shift detection
* - Advanced hedging language detection with categorization
*
* Endpoints:
* - GET /api/v1/ai-earnings?action=tone&ticker=AAPL — Real-time tone detection with LLM-style analysis
* - GET /api/v1/ai-earnings?action=confidence&ticker=TSLA — Executive confidence scoring
* - GET /api/v1/ai-earnings?action=language-shift&ticker=MSFT — Quarter-over-quarter language changes
* - GET /api/v1/ai-earnings?action=hedging&ticker=NVDA — Advanced hedging language detection
*
* Phase: 76
*/
export async function GET(request: NextRequest) {
const action = request.nextUrl.searchParams.get("action") || "tone";
const ticker = request.nextUrl.searchParams.get("ticker");
if (!ticker) {
return NextResponse.json(
{ error: "Missing required parameter: ticker" },
{ status: 400 }
);
}
try {
let command: string;
switch (action) {
case "tone":
command = `${PYTHON} ${QUANTCLAW_DATA_DIR}/cli.py earnings-tone ${ticker}`;
break;
case "confidence":
command = `${PYTHON} ${QUANTCLAW_DATA_DIR}/cli.py confidence-score ${ticker}`;
break;
case "language-shift":
command = `${PYTHON} ${QUANTCLAW_DATA_DIR}/cli.py language-shift ${ticker}`;
break;
case "hedging":
command = `${PYTHON} ${QUANTCLAW_DATA_DIR}/cli.py hedging-detector ${ticker}`;
break;
default:
return NextResponse.json(
{
error: `Unknown action: ${action}`,
available: ["tone", "confidence", "language-shift", "hedging"]
},
{ status: 400 }
);
}
const { stdout, stderr } = await execAsync(command, {
timeout: 30000,
maxBuffer: 5 * 1024 * 1024 // 5MB buffer
});
if (stderr) {
console.error("AI Earnings Analyzer stderr:", stderr);
}
try {
const result = JSON.parse(stdout);
return NextResponse.json(result);
} catch (parseError) {
return NextResponse.json({
result: stdout.trim(),
warning: "Response was not valid JSON"
});
}
} catch (e: unknown) {
const errorMessage = e instanceof Error ? e.message : String(e);
console.error("AI Earnings Analyzer API Error:", errorMessage);
return NextResponse.json(
{
error: errorMessage,
action,
ticker
},
{ status: 500 }
);
}
}
