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/__init__.py

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+from . import models
+from . import services

encoach_ai/__manifest__.py

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+{
+    "name": "EnCoach AI",
+    "version": "19.0.1.0.0",
+    "category": "Education",
+    "summary": "Core AI services for the EnCoach IELTS platform",
+    "description": "OpenAI integration, constants, blacklist validation, token counting.",
+    "depends": ["encoach_core"],
+    "data": [
+        "security/ir.model.access.csv",
+    ],
+    "installable": True,
+    "license": "LGPL-3",
+    "external_dependencies": {
+        "python": ["openai", "tiktoken", "httpx", "tenacity", "numpy"],
+    },
+}

encoach_ai/models/__init__.py

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+from . import constants

encoach_ai/models/constants.py

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+BLACKLISTED_WORDS = [
+    "alcohol", "atheism", "beer", "bible", "blasphemy",
+    "buddha", "buddhism", "cannabis", "casino", "christ",
+    "christianity", "church", "cocaine", "communist", "condom",
+    "corruption", "crucifixion", "cult", "drug", "drugs",
+    "erotic", "extremism", "gambling", "gay", "god",
+    "gods", "gospel", "haram", "heresy", "heroin",
+    "hindu", "hinduism", "homosexual", "idol", "infidel",
+    "islam", "islamic", "israeli", "jesus", "jew",
+    "jewish", "jihad", "judaism", "lesbian", "liquor",
+    "marijuana", "mosque", "muhammad", "muslim", "naked",
+    "nazi", "nude", "pagan", "pig", "pork",
+    "porn", "pornography", "prayer", "priest", "prophet",
+    "prostitution", "quran", "rabbi", "rape", "religion",
+    "religious", "satan", "sex", "sexual", "sharia",
+    "shinto", "sikh", "strip", "suicide", "synagogue",
+    "temple", "terrorism", "terrorist", "torah", "vodka",
+    "whiskey", "wine", "worship", "zionism",
+]
+
+TOPICS = [
+    "Technology", "Education", "Health", "Environment", "Travel",
+    "Food and Nutrition", "Sports", "Music", "Art", "Science",
+    "History", "Geography", "Business", "Economy", "Media",
+    "Communication", "Fashion", "Architecture", "Transportation", "Energy",
+    "Water Resources", "Agriculture", "Space Exploration", "Wildlife",
+    "Climate Change", "Urbanization", "Rural Life", "Population Growth",
+    "Immigration", "Cultural Diversity", "Globalization", "Tourism",
+    "Employment", "Workplace Culture", "Leadership", "Innovation",
+    "Artificial Intelligence", "Social Media", "Advertising", "Cinema",
+    "Literature", "Languages", "Volunteering", "Charity",
+    "Mental Health", "Fitness", "Aging Population", "Childhood Development",
+    "Higher Education", "Online Learning", "Public Libraries",
+    "Museums", "Public Transport", "Cycling", "Renewable Energy",
+    "Recycling", "Waste Management", "Deforestation", "Ocean Conservation",
+    "Animal Rights", "Genetic Engineering", "Robotics", "Cybersecurity",
+    "Privacy", "Freedom of Speech", "Democracy", "Law Enforcement",
+    "Crime Prevention", "Housing", "Homelessness", "Poverty",
+    "Income Inequality", "Consumer Culture", "Minimalism", "Traditions",
+    "Festivals", "Cooking", "Gardening", "Photography",
+    "Podcasts", "Board Games", "Pet Ownership", "Astronomy",
+    "Archaeology", "Philosophy", "Psychology", "Sociology",
+    "Ecology", "Marine Biology", "Meteorology", "Geology",
+    "Time Management", "Stress Management", "Work-Life Balance",
+]
+
+CEFR_LEVELS = ["A1", "A2", "B1", "B2", "C1", "C2"]
+
+GPT_MODELS = {
+    "grading": "gpt-4o",
+    "generation": "gpt-4o",
+    "secondary": "gpt-3.5-turbo",
+}
+
+TEMPERATURE = {
+    "grading": 0.1,
+    "generation": 0.7,
+    "tips": 0.2,
+}

encoach_ai/security/ir.model.access.csv

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+id,name,model_id:id,group_id:id,perm_read,perm_write,perm_create,perm_unlink

encoach_ai/services/__init__.py

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+from . import openai_service

encoach_ai/services/openai_service.py

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+import json
+import logging
+
+import tiktoken
+from openai import OpenAI
+from tenacity import retry, stop_after_attempt, wait_exponential
+
+from ..models.constants import BLACKLISTED_WORDS
+
+_logger = logging.getLogger(__name__)
+
+TOKEN_RESERVE = 300
+MODEL_TOKEN_LIMIT = 4097
+
+
+class EncoachOpenAIService:
+
+    def __init__(self, env):
+        self.env = env
+        api_key = (
+            env["ir.config_parameter"]
+            .sudo()
+            .get_param("encoach.openai_api_key", "")
+        )
+        if not api_key:
+            _logger.warning("OpenAI API key not configured (encoach.openai_api_key)")
+        self.client = OpenAI(api_key=api_key)
+
+    def prediction(
+        self,
+        model,
+        messages,
+        temperature=0.7,
+        response_format=None,
+        fields_to_check=None,
+        check_blacklisted=True,
+        max_retries=2,
+    ):
+        """Call OpenAI chat completion with validation and blacklist filtering.
+
+        Returns parsed JSON dict on success or None on failure.
+        """
+        if response_format is None:
+            response_format = {"type": "json_object"}
+
+        input_tokens = self._count_tokens(
+            " ".join(m.get("content", "") for m in messages if isinstance(m.get("content"), str)),
+            model,
+        )
+        max_tokens = max(MODEL_TOKEN_LIMIT - input_tokens - TOKEN_RESERVE, 256)
+
+        attempt = 0
+        while attempt <= max_retries:
+            try:
+                resp = self.client.chat.completions.create(
+                    model=model,
+                    messages=messages,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    response_format=response_format,
+                )
+                content = resp.choices[0].message.content
+                data = json.loads(content)
+
+                if check_blacklisted:
+                    text_to_check = content
+                    if fields_to_check and isinstance(data, dict):
+                        text_to_check = " ".join(
+                            str(data.get(f, "")) for f in fields_to_check
+                        )
+                    if self._check_blacklisted(text_to_check):
+                        _logger.info(
+                            "Blacklisted content detected (attempt %d/%d)",
+                            attempt + 1,
+                            max_retries + 1,
+                        )
+                        attempt += 1
+                        continue
+
+                return data
+
+            except json.JSONDecodeError:
+                _logger.warning("Invalid JSON from OpenAI (attempt %d)", attempt + 1)
+                attempt += 1
+            except Exception:
+                _logger.exception("OpenAI API error (attempt %d)", attempt + 1)
+                attempt += 1
+
+        _logger.error("OpenAI prediction failed after %d attempts", max_retries + 1)
+        return None
+
+    @staticmethod
+    def _check_blacklisted(text):
+        lower = text.lower()
+        return any(word in lower for word in BLACKLISTED_WORDS)
+
+    @staticmethod
+    def _count_tokens(text, model="gpt-4o"):
+        try:
+            encoding = tiktoken.encoding_for_model(model)
+        except KeyError:
+            encoding = tiktoken.get_encoding("cl100k_base")
+        return len(encoding.encode(text))