f5b627256f
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
104 lines
3.3 KiB
Python
104 lines
3.3 KiB
Python
import json
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import logging
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import tiktoken
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from openai import OpenAI
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from tenacity import retry, stop_after_attempt, wait_exponential
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from ..models.constants import BLACKLISTED_WORDS
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_logger = logging.getLogger(__name__)
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TOKEN_RESERVE = 300
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MODEL_TOKEN_LIMIT = 4097
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class EncoachOpenAIService:
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def __init__(self, env):
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self.env = env
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api_key = (
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env["ir.config_parameter"]
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.sudo()
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.get_param("encoach.openai_api_key", "")
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)
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if not api_key:
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_logger.warning("OpenAI API key not configured (encoach.openai_api_key)")
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self.client = OpenAI(api_key=api_key)
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def prediction(
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self,
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model,
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messages,
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temperature=0.7,
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response_format=None,
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fields_to_check=None,
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check_blacklisted=True,
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max_retries=2,
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):
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"""Call OpenAI chat completion with validation and blacklist filtering.
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Returns parsed JSON dict on success or None on failure.
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"""
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if response_format is None:
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response_format = {"type": "json_object"}
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input_tokens = self._count_tokens(
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" ".join(m.get("content", "") for m in messages if isinstance(m.get("content"), str)),
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model,
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)
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max_tokens = max(MODEL_TOKEN_LIMIT - input_tokens - TOKEN_RESERVE, 256)
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attempt = 0
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while attempt <= max_retries:
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try:
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resp = self.client.chat.completions.create(
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model=model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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response_format=response_format,
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)
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content = resp.choices[0].message.content
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data = json.loads(content)
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if check_blacklisted:
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text_to_check = content
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if fields_to_check and isinstance(data, dict):
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text_to_check = " ".join(
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str(data.get(f, "")) for f in fields_to_check
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)
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if self._check_blacklisted(text_to_check):
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_logger.info(
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"Blacklisted content detected (attempt %d/%d)",
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attempt + 1,
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max_retries + 1,
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)
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attempt += 1
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continue
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return data
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except json.JSONDecodeError:
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_logger.warning("Invalid JSON from OpenAI (attempt %d)", attempt + 1)
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attempt += 1
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except Exception:
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_logger.exception("OpenAI API error (attempt %d)", attempt + 1)
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attempt += 1
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_logger.error("OpenAI prediction failed after %d attempts", max_retries + 1)
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return None
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@staticmethod
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def _check_blacklisted(text):
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lower = text.lower()
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return any(word in lower for word in BLACKLISTED_WORDS)
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@staticmethod
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def _count_tokens(text, model="gpt-4o"):
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try:
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encoding = tiktoken.encoding_for_model(model)
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except KeyError:
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encoding = tiktoken.get_encoding("cl100k_base")
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return len(encoding.encode(text))
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