feat: Generation Page AI workflows + AI/Vector modules + exam session fixes
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
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103
custom_addons/encoach_ai/services/elevenlabs_service.py
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103
custom_addons/encoach_ai/services/elevenlabs_service.py
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"""ElevenLabs text-to-speech 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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ELEVENLABS_BASE = "https://api.elevenlabs.io/v1"
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DEFAULT_VOICES = {
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"female_british": "21m00Tcm4TlvDq8ikWAM", # Rachel
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"male_british": "VR6AewLTigWG4xSOukaG", # Arnold
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"female_american": "EXAVITQu4vr4xnSDxMaL", # Bella
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"male_american": "TxGEqnHWrfWFTfGW9XjX", # Josh
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}
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class ElevenLabsService:
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"""ElevenLabs TTS — higher quality multilingual voices."""
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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.elevenlabs_api_key", "")
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if not key:
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import os
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key = os.environ.get("ELEVENLABS_API_KEY", "")
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if not key:
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raise RuntimeError("ElevenLabs 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": "elevenlabs",
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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 synthesize(self, text, *, voice_id=None, voice_key="female_british",
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model=None, output_format="mp3_44100_128"):
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"""Convert text to speech using ElevenLabs.
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Returns:
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dict with 'audio' (bytes), 'content_type', 'voice_id', 'characters'
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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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voice_id = voice_id or DEFAULT_VOICES.get(voice_key, list(DEFAULT_VOICES.values())[0])
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model = model or self._get_param("encoach_ai.elevenlabs_model", "eleven_multilingual_v2")
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url = f"{ELEVENLABS_BASE}/text-to-speech/{voice_id}"
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t0 = time.time()
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try:
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resp = _requests.post(
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url,
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json={
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"text": text,
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"model_id": model,
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"voice_settings": {"stability": 0.5, "similarity_boost": 0.75},
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},
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headers={"xi-api-key": key, "Accept": "audio/mpeg"},
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params={"output_format": output_format},
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timeout=60,
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)
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resp.raise_for_status()
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latency = int((time.time() - t0) * 1000)
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self._log("synthesize", latency)
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return {
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"audio": resp.content,
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"content_type": "audio/mpeg",
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"voice_id": voice_id,
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"characters": len(text),
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}
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except Exception as exc:
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self._log("synthesize", int((time.time() - t0) * 1000), "error", str(exc))
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raise
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def list_voices(self):
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"""List available ElevenLabs voices."""
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key = self._get_key()
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resp = _requests.get(
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f"{ELEVENLABS_BASE}/voices",
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headers={"xi-api-key": key},
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timeout=15,
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)
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resp.raise_for_status()
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return [
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{"voice_id": v["voice_id"], "name": v["name"], "labels": v.get("labels", {})}
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for v in resp.json().get("voices", [])
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]
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