EnCoach Odoo 19 custom modules

Full backend implementation with custom Odoo modules:
- encoach_api: Core API, user management, JWT auth
- encoach_exam: Exam generation (reading, writing, listening, speaking)
- encoach_evaluate: AI-powered evaluation (writing, speaking)
- encoach_training: Training tips and walkthrough
- encoach_storage: File storage management
- encoach_payment: Stripe, PayPal, Paymob integration
- encoach_mail: Email notifications

Made-with: Cursor

encoach_ai_media/services/polly_service.py

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+import io
+import logging
+import random
+import re
+
+import boto3
+
+_logger = logging.getLogger(__name__)
+
+POLLY_VOICES = {
+    "Danielle": {"gender": "Female", "accent": "US"},
+    "Gregory": {"gender": "Male", "accent": "US"},
+    "Kevin": {"gender": "Male", "accent": "US"},
+    "Ruth": {"gender": "Female", "accent": "US"},
+    "Stephen": {"gender": "Male", "accent": "US"},
+    "Arthur": {"gender": "Male", "accent": "GB"},
+    "Olivia": {"gender": "Female", "accent": "GB"},
+    "Ayanda": {"gender": "Female", "accent": "ZA"},
+    "Aria": {"gender": "Female", "accent": "NZ"},
+    "Kajal": {"gender": "Female", "accent": "IN"},
+    "Niamh": {"gender": "Female", "accent": "IE"},
+}
+
+FINAL_CUE_TEXT = (
+    "This audio recording, for the listening exercise, has finished."
+)
+FINAL_CUE_VOICE = "Stephen"
+
+MAX_CHUNK_SIZE = 3000
+
+
+class EncoachPollyService:
+
+    def __init__(self, env):
+        self.env = env
+        icp = env["ir.config_parameter"].sudo()
+        self.client = boto3.client(
+            "polly",
+            aws_access_key_id=icp.get_param("encoach.aws_access_key_id", ""),
+            aws_secret_access_key=icp.get_param("encoach.aws_secret_access_key", ""),
+            region_name=icp.get_param("encoach.aws_region", "us-east-1"),
+        )
+
+    def synthesize_speech(
+        self, text, voice, engine="neural", output_format="mp3"
+    ):
+        """Synthesize a single text block into MP3 bytes."""
+        chunks = self._chunk_text(text)
+        audio_parts = []
+        for chunk in chunks:
+            resp = self.client.synthesize_speech(
+                Text=chunk,
+                VoiceId=voice,
+                Engine=engine,
+                OutputFormat=output_format,
+            )
+            audio_parts.append(resp["AudioStream"].read())
+        return b"".join(audio_parts)
+
+    def text_to_speech(self, dialog, include_final_cue=True):
+        """Generate full MP3 audio from a conversation or monologue.
+
+        dialog: either a string (monologue) or a list of dicts with
+            'name', 'gender', 'text' keys.
+        """
+        audio_segments = []
+
+        if isinstance(dialog, str):
+            voice = random.choice(list(POLLY_VOICES.keys()))
+            audio_segments.append(self.synthesize_speech(dialog, voice))
+        else:
+            voice_map = self._assign_voices(dialog)
+            for line in dialog:
+                voice = voice_map.get(line["name"], "Stephen")
+                audio_segments.append(
+                    self.synthesize_speech(line["text"], voice)
+                )
+
+        if include_final_cue:
+            audio_segments.append(
+                self.synthesize_speech(FINAL_CUE_TEXT, FINAL_CUE_VOICE)
+            )
+
+        return b"".join(audio_segments)
+
+    @staticmethod
+    def _assign_voices(dialog):
+        """Assign distinct Polly voices to each speaker based on gender."""
+        speakers = {}
+        male_voices = [v for v, info in POLLY_VOICES.items() if info["gender"] == "Male"]
+        female_voices = [v for v, info in POLLY_VOICES.items() if info["gender"] == "Female"]
+        male_idx, female_idx = 0, 0
+
+        for line in dialog:
+            name = line.get("name", "")
+            if name in speakers:
+                continue
+            gender = (line.get("gender") or "").lower()
+            if gender == "female" and female_idx < len(female_voices):
+                speakers[name] = female_voices[female_idx]
+                female_idx += 1
+            elif male_idx < len(male_voices):
+                speakers[name] = male_voices[male_idx]
+                male_idx += 1
+            else:
+                speakers[name] = random.choice(list(POLLY_VOICES.keys()))
+        return speakers
+
+    @staticmethod
+    def _chunk_text(text, max_size=MAX_CHUNK_SIZE):
+        """Split text at sentence boundaries respecting max chunk size."""
+        if len(text) <= max_size:
+            return [text]
+
+        sentences = re.split(r"(?<=[.!?])\s+", text)
+        chunks = []
+        current = ""
+
+        for sentence in sentences:
+            if len(current) + len(sentence) + 1 > max_size:
+                if current:
+                    chunks.append(current.strip())
+                current = sentence
+            else:
+                current = f"{current} {sentence}" if current else sentence
+
+        if current:
+            chunks.append(current.strip())
+        return chunks