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
103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
"""AWS Polly 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 boto3 as _boto3
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except ImportError:
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_boto3 = None
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VOICE_MAP = {
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"en-GB": {"female": "Amy", "male": "Brian"},
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"en-US": {"female": "Joanna", "male": "Matthew"},
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"en-AU": {"female": "Nicole", "male": "Russell"},
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"en-IN": {"female": "Aditi", "male": "Aditi"},
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}
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class PollyService:
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"""AWS Polly TTS for generating listening exam audio."""
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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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self._client = None
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def _get_client(self):
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if self._client:
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return self._client
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if not _boto3:
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raise RuntimeError("boto3 not installed — run: pip install boto3")
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access_key = self._get_param("encoach_ai.aws_access_key", "")
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secret_key = self._get_param("encoach_ai.aws_secret_key", "")
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region = self._get_param("encoach_ai.aws_region", "eu-west-1")
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if not access_key or not secret_key:
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import os
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access_key = access_key or os.environ.get("AWS_ACCESS_KEY_ID", "")
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secret_key = secret_key or os.environ.get("AWS_SECRET_ACCESS_KEY", "")
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if not access_key:
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raise RuntimeError("AWS credentials not configured — set in AI Settings")
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self._client = _boto3.client(
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"polly",
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aws_access_key_id=access_key,
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aws_secret_access_key=secret_key,
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region_name=region,
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)
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return self._client
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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": "polly",
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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=None, language="en-GB", gender="female",
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engine="neural", output_format="mp3"):
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"""Convert text to speech audio bytes.
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Returns:
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dict with 'audio' (bytes), 'content_type', 'voice', 'characters'
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"""
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client = self._get_client()
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if not voice:
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voice = VOICE_MAP.get(language, VOICE_MAP["en-GB"]).get(gender, "Amy")
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t0 = time.time()
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try:
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resp = client.synthesize_speech(
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Text=text,
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OutputFormat=output_format,
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VoiceId=voice,
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Engine=engine,
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LanguageCode=language,
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)
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audio = resp["AudioStream"].read()
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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": audio,
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"content_type": resp["ContentType"],
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"voice": voice,
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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, language="en-GB"):
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"""List available voices for a language."""
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client = self._get_client()
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resp = client.describe_voices(LanguageCode=language)
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return [
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{"id": v["Id"], "name": v["Name"], "gender": v["Gender"], "engine": v.get("SupportedEngines", [])}
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for v in resp.get("Voices", [])
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]
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