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
109 lines
3.3 KiB
Python
109 lines
3.3 KiB
Python
"""ELAI avatar video generation 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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ELAI_BASE = "https://apis.elai.io/api/v1"
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class ElaiService:
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"""Generate avatar videos for listening exercises and instructional content."""
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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_token(self):
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token = self._get_param("encoach_ai.elai_token", "")
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if not token:
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import os
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token = os.environ.get("ELAI_TOKEN", "")
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if not token:
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raise RuntimeError("ELAI token not configured — set in AI Settings")
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return token
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def _headers(self):
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return {
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"Authorization": f"Bearer {self._get_token()}",
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"Content-Type": "application/json",
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}
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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": "elai",
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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 list_avatars(self):
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"""List available ELAI avatars."""
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if not _requests:
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raise RuntimeError("requests package not installed")
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resp = _requests.get(f"{ELAI_BASE}/avatars", headers=self._headers(), timeout=15)
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resp.raise_for_status()
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return resp.json()
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def create_video(self, script, *, avatar_id=None, title="EnCoach Video", language="en"):
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"""Create an avatar video from a script.
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Returns:
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dict with 'video_id', 'status'
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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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payload = {
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"name": title,
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"slides": [
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{
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"speech": script,
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"avatar": avatar_id or "default",
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"language": language,
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}
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],
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}
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t0 = time.time()
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try:
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resp = _requests.post(
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f"{ELAI_BASE}/videos",
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json=payload,
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headers=self._headers(),
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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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self._log("create_video", int((time.time() - t0) * 1000))
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return {"video_id": data.get("_id", data.get("id")), "status": data.get("status", "pending")}
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except Exception as exc:
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self._log("create_video", int((time.time() - t0) * 1000), "error", str(exc))
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raise
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def get_video_status(self, video_id):
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"""Check video generation status."""
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if not _requests:
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raise RuntimeError("requests package not installed")
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resp = _requests.get(
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f"{ELAI_BASE}/videos/{video_id}",
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headers=self._headers(),
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timeout=15,
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)
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resp.raise_for_status()
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data = resp.json()
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return {
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"video_id": video_id,
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"status": data.get("status", "unknown"),
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"url": data.get("url", ""),
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"duration": data.get("duration"),
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}
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