6a62a43d61
Generation Page (complete rebuild): - Full production-parity exam generation wizard with 4 IELTS modules - Reading: AI passage gen, 5 exercise types (MCQ, Fill, Write, T/F, Match) - Listening: 4 section types, AI context gen, TTS audio gen (ElevenLabs) - Writing: Task 1/2, AI instruction gen, word limits, marks - Speaking: 3 parts, AI script gen, avatar video gen (7 avatars) - Per-module config: timer, CEFR difficulty, access, approval, rubrics - Exam submission workflow (draft/published) Exam Structures: - New encoach.exam.structure model + CRUD controller - ExamStructuresPage wired to real API AI Module (encoach_ai): - OpenAI service, ElevenLabs TTS, AWS Polly, ELAI avatars - AI settings model with Odoo config parameters - 7 generation endpoints (passage, exercises, instructions, scripts, context) Vector Module (encoach_vector): - pgvector integration for RAG-based content search - Embedding service with sentence-transformers Exam Session Fixes: - Fixed ExamSession.tsx field mapping (question_type→type, exam_title→title) - Fixed submit payload to include attempt_id and answers - Fixed normalizeType to handle null/undefined Tested: 12/12 API tests passed, browser-verified with real OpenAI calls Made-with: Cursor
88 lines
2.9 KiB
Python
88 lines
2.9 KiB
Python
"""GPTZero AI content detection service."""
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import logging
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import time
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_logger = logging.getLogger(__name__)
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try:
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import requests as _requests
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except ImportError:
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_requests = None
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GPTZERO_BASE = "https://api.gptzero.me/v2"
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class GPTZeroService:
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"""Detect AI-generated content in student submissions."""
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def __init__(self, env):
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self.env = env
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self._get_param = env["ir.config_parameter"].sudo().get_param
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def _get_key(self):
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key = self._get_param("encoach_ai.gptzero_api_key", "")
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if not key:
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import os
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key = os.environ.get("GPT_ZERO_API_KEY", "")
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if not key:
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raise RuntimeError("GPTZero API key not configured — set in AI Settings")
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return key
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def _log(self, action, latency, status="success", error=None):
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try:
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self.env["encoach.ai.log"].sudo().create({
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"service": "gptzero",
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"action": action,
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"latency_ms": latency,
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"status": status,
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"error_message": error,
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})
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except Exception:
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pass
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def detect(self, text):
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"""Check if text is AI-generated.
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Returns:
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dict with 'is_ai_generated' (bool), 'ai_probability' (float 0-1),
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'human_probability' (float), 'sentences' (list of per-sentence scores)
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"""
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if not _requests:
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raise RuntimeError("requests package not installed")
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key = self._get_key()
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t0 = time.time()
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try:
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resp = _requests.post(
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f"{GPTZERO_BASE}/predict/text",
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json={"document": text},
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headers={"x-api-key": key, "Content-Type": "application/json"},
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timeout=30,
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)
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resp.raise_for_status()
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data = resp.json()
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doc = data.get("documents", [{}])[0] if data.get("documents") else {}
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result = {
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"is_ai_generated": doc.get("completely_generated_prob", 0) > 0.5,
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"ai_probability": doc.get("completely_generated_prob", 0),
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"human_probability": 1 - doc.get("completely_generated_prob", 0),
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"mixed_probability": doc.get("average_generated_prob", 0),
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"sentences": [
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{
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"text": s.get("sentence", ""),
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"ai_probability": s.get("generated_prob", 0),
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"is_ai": s.get("generated_prob", 0) > 0.5,
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}
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for s in doc.get("sentences", [])
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],
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}
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self._log("detect", int((time.time() - t0) * 1000))
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return result
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except Exception as exc:
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self._log("detect", int((time.time() - t0) * 1000), "error", str(exc))
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raise
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def detect_batch(self, texts):
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"""Check multiple texts for AI generation."""
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return [self.detect(t) for t in texts]
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