mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 15:29:36 +00:00
141f10db76
Continuing Phase 3-6 implementation: - AI: conversation_intelligence.py (Arabic dialogue analysis, buying signals) - AI: message_writer.py (Arabic/English multi-channel message generation) - AI: sales_agent.py (autonomous WhatsApp qualification bot) - API: compliance.py (PDPL consent & data rights endpoints) - API: inbox.py (unified multi-channel inbox) - API: proposals.py (CPQ quote management endpoints) - API: sequences.py (multi-channel sequence management) - Services: territory_manager.py (Saudi region-based lead routing) - Seeds: contracting_template.json (Saudi contracting industry template) - Updated: router.py, consent_manager.py, data_rights.py https://claude.ai/code/session_01LsnvBa7HwF5hs99VZbgLGj
437 lines
18 KiB
Python
437 lines
18 KiB
Python
"""
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AI Message Writer — Generates personalized WhatsApp, Email, and SMS messages
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in Arabic and English with tone control, A/B variants, and Saudi business-hour awareness.
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"""
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import json
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import logging
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from dataclasses import dataclass, field
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from datetime import datetime, timezone, timedelta
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from typing import Optional
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from app.services.llm.provider import get_llm
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logger = logging.getLogger(__name__)
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# ---------------------------------------------------------------------------
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# Data models
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# ---------------------------------------------------------------------------
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@dataclass
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class MessageVariant:
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content: str
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subject: Optional[str] = None # for email only
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variant_label: str = "A"
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estimated_read_time_sec: int = 0
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@dataclass
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class MessageDraft:
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channel: str # "whatsapp", "email", "sms"
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language: str # "ar", "en"
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tone: str
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variants: list[MessageVariant] = field(default_factory=list)
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best_send_time: Optional[str] = None
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best_send_day: Optional[str] = None
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personalization_used: list[str] = field(default_factory=list)
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metadata: dict = field(default_factory=dict)
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# ---------------------------------------------------------------------------
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# Constants
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# ---------------------------------------------------------------------------
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CHANNEL_LIMITS = {
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"whatsapp": 4096,
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"sms": 160,
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"email": 10000,
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}
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TONE_INSTRUCTIONS = {
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"formal": {
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"ar": (
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"استخدم لغة رسمية واحترافية. خاطب العميل بـ'حضرتكم'. "
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"ابدأ بالسلام الرسمي. تجنب العامية."
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),
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"en": "Use formal, professional language. Address the recipient respectfully.",
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},
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"friendly": {
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"ar": (
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"استخدم لغة ودية وعفوية. خاطب العميل بـ'أنت'. "
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"استخدم تعبيرات سعودية طبيعية مثل 'هلا والله' و'يعطيك العافية'."
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),
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"en": "Use a warm, friendly tone. Be conversational and approachable.",
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},
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"urgent": {
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"ar": (
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"استخدم لغة مباشرة تحث على الإسراع. "
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"أكد على محدودية العرض أو ضرورة التصرف السريع بدون مبالغة."
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),
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"en": "Create urgency without being pushy. Emphasize time-limited opportunity.",
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},
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"follow_up": {
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"ar": (
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"ذكّر العميل بالمحادثة السابقة بلطف. "
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"اسأل إذا عنده أسئلة. كن مهذب وغير ملح."
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),
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"en": "Gently remind about previous conversation. Ask if they have questions.",
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},
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}
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INDUSTRY_CONTEXT = {
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"real_estate": {
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"ar": "القطاع العقاري — استخدم مصطلحات مثل: وحدة سكنية، مخطط، صك، موقع استراتيجي، عائد استثماري",
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"en": "Real estate — use terms like: residential unit, strategic location, ROI, property value",
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},
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"healthcare": {
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"ar": "القطاع الصحي — استخدم مصطلحات مثل: عيادة، مجمع طبي، تأمين، موعد، رعاية صحية",
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"en": "Healthcare — use terms like: clinic, medical complex, insurance, appointment, care quality",
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},
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"retail": {
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"ar": "قطاع التجزئة — استخدم مصطلحات مثل: نقاط البيع، المخزون، تجربة العميل، موسم التخفيضات",
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"en": "Retail — use terms like: POS, inventory, customer experience, sales season",
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},
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"education": {
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"ar": "قطاع التعليم — استخدم مصطلحات مثل: تسجيل، رسوم دراسية، منهج، فصل دراسي",
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"en": "Education — use terms like: enrollment, tuition, curriculum, academic term",
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},
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"automotive": {
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"ar": "قطاع السيارات — استخدم مصطلحات مثل: معرض، وكالة، تمويل، صيانة، موديل",
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"en": "Automotive — use terms like: showroom, dealership, financing, maintenance, model",
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},
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"hospitality": {
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"ar": "قطاع الضيافة — استخدم مصطلحات مثل: حجز، جناح، باقة، تجربة ضيافة، موسم سياحي",
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"en": "Hospitality — use terms like: booking, suite, package, guest experience, peak season",
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},
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}
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# Saudi Arabia timezone: UTC+3
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SAUDI_TZ_OFFSET = timedelta(hours=3)
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# Optimal send windows (Saudi time, 24h)
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SEND_WINDOWS = {
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"whatsapp": {"start": 9, "end": 21, "peak": [10, 14, 19]},
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"email": {"start": 8, "end": 17, "peak": [9, 11, 14]},
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"sms": {"start": 9, "end": 20, "peak": [10, 13, 18]},
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}
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# Saudi work week: Sunday (6) through Thursday (3)
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SAUDI_WORK_DAYS = {6, 0, 1, 2, 3} # Sunday=6, Mon=0, Tue=1, Wed=2, Thu=3
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# ---------------------------------------------------------------------------
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# Service
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# ---------------------------------------------------------------------------
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class MessageWriter:
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"""Generates personalized, culturally-aware sales messages."""
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def __init__(self):
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self._llm = get_llm()
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async def write_message(
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self,
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channel: str,
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tone: str,
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lead_data: dict,
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context: Optional[dict] = None,
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language: str = "ar",
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) -> MessageDraft:
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"""
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Generate a sales message with A/B variants.
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Args:
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channel: "whatsapp", "email", or "sms"
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tone: "formal", "friendly", "urgent", "follow_up"
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lead_data: {"name", "company", "industry", "stage", "city", "last_contact"}
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context: Optional {"deal_value", "product", "previous_topic", "objection"}
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language: "ar" or "en"
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Returns:
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MessageDraft with two A/B variants and send-time recommendation.
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"""
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context = context or {}
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channel = channel.lower()
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tone = tone.lower()
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language = language.lower() if language else "ar"
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if channel not in CHANNEL_LIMITS:
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channel = "whatsapp"
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if tone not in TONE_INSTRUCTIONS:
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tone = "friendly"
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if language not in ("ar", "en"):
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language = "ar"
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# Build the prompt
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system_prompt = self._build_system_prompt(channel, tone, lead_data, context, language)
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user_prompt = self._build_user_prompt(channel, tone, lead_data, context, language)
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# Generate both variants in one LLM call
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try:
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response = await self._llm.complete(
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system_prompt=system_prompt,
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user_message=user_prompt,
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json_mode=True,
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temperature=0.7,
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max_tokens=2048,
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)
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parsed = response.parse_json()
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if parsed:
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variants = self._parse_variants(parsed, channel)
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else:
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raise ValueError("Failed to parse LLM response")
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except Exception as e:
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logger.warning(f"LLM message generation failed: {e}")
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variants = self._fallback_variants(channel, tone, lead_data, language)
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# Calculate best send time
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best_time, best_day = self._calculate_best_send_time(channel)
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# Track which personalization fields were used
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personalization = [
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k for k in ("name", "company", "industry", "city", "stage")
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if lead_data.get(k)
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]
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return MessageDraft(
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channel=channel,
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language=language,
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tone=tone,
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variants=variants,
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best_send_time=best_time,
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best_send_day=best_day,
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personalization_used=personalization,
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metadata={
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"max_length": CHANNEL_LIMITS[channel],
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"lead_name": lead_data.get("name", ""),
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"industry": lead_data.get("industry", ""),
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},
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)
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# ── Prompt Construction ──────────────────────
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def _build_system_prompt(
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self, channel: str, tone: str, lead_data: dict, context: dict, language: str
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) -> str:
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lang_key = language if language in ("ar", "en") else "ar"
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tone_instruction = TONE_INSTRUCTIONS.get(tone, TONE_INSTRUCTIONS["friendly"])[lang_key]
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industry = (lead_data.get("industry") or "").lower().replace(" ", "_")
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industry_note = ""
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if industry in INDUSTRY_CONTEXT:
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industry_note = INDUSTRY_CONTEXT[industry][lang_key]
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char_limit = CHANNEL_LIMITS[channel]
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if language == "ar":
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prompt = (
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"أنت كاتب رسائل مبيعات محترف متخصص في السوق السعودي.\n"
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f"القناة: {channel} (حد أقصى {char_limit} حرف)\n"
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f"النبرة: {tone_instruction}\n"
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)
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if industry_note:
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prompt += f"القطاع: {industry_note}\n"
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prompt += (
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"\nقواعد مهمة:\n"
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"- لا تستخدم لهجة مصرية أو شامية\n"
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"- استخدم 'ريال' للعملة\n"
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"- راعي ثقافة الأعمال السعودية\n"
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"- اكتب رسالتين مختلفتين (A و B) لاختبار A/B\n"
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"- الرسالة يجب أن تكون كاملة وجاهزة للإرسال\n"
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)
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if channel == "email":
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prompt += "- أضف عنوان بريد مناسب لكل رسالة\n"
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else:
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prompt = (
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"You are a professional sales message writer for the Saudi market.\n"
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f"Channel: {channel} (max {char_limit} characters)\n"
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f"Tone: {tone_instruction}\n"
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)
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if industry_note:
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prompt += f"Industry: {industry_note}\n"
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prompt += (
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"\nRules:\n"
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"- Write two different message variants (A and B) for A/B testing\n"
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"- Messages must be complete and ready to send\n"
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"- Be culturally aware of Saudi business norms\n"
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)
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if channel == "email":
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prompt += "- Include an email subject line for each variant\n"
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prompt += (
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"\nأجب بصيغة JSON فقط:\n"
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"{\n"
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' "variant_a": {"content": "...", "subject": "..." },\n'
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' "variant_b": {"content": "...", "subject": "..." }\n'
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"}\n"
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"subject مطلوب فقط للبريد الإلكتروني. للواتساب والرسائل اتركه فارغ."
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)
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return prompt
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def _build_user_prompt(
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self, channel: str, tone: str, lead_data: dict, context: dict, language: str
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) -> str:
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name = lead_data.get("name", "العميل" if language == "ar" else "Customer")
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company = lead_data.get("company", "")
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industry = lead_data.get("industry", "")
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stage = lead_data.get("stage", "")
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city = lead_data.get("city", "")
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last_contact = lead_data.get("last_contact", "")
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deal_value = context.get("deal_value", "")
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product = context.get("product", "")
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previous_topic = context.get("previous_topic", "")
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objection = context.get("objection", "")
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if language == "ar":
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parts = [f"اكتب رسالة {channel} للعميل:"]
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parts.append(f"- الاسم: {name}")
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if company:
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parts.append(f"- الشركة: {company}")
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if industry:
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parts.append(f"- القطاع: {industry}")
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if stage:
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parts.append(f"- مرحلة البيع: {stage}")
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if city:
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parts.append(f"- المدينة: {city}")
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if last_contact:
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parts.append(f"- آخر تواصل: {last_contact}")
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if deal_value:
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parts.append(f"- قيمة الصفقة: {deal_value} ريال")
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if product:
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parts.append(f"- المنتج: {product}")
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if previous_topic:
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parts.append(f"- الموضوع السابق: {previous_topic}")
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if objection:
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parts.append(f"- اعتراض العميل: {objection}")
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else:
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parts = [f"Write a {channel} message for:"]
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parts.append(f"- Name: {name}")
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if company:
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parts.append(f"- Company: {company}")
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if industry:
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parts.append(f"- Industry: {industry}")
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if stage:
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parts.append(f"- Stage: {stage}")
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if city:
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parts.append(f"- City: {city}")
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if last_contact:
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parts.append(f"- Last contact: {last_contact}")
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if deal_value:
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parts.append(f"- Deal value: {deal_value} SAR")
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if product:
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parts.append(f"- Product: {product}")
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if previous_topic:
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parts.append(f"- Previous topic: {previous_topic}")
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if objection:
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parts.append(f"- Objection: {objection}")
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return "\n".join(parts)
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# ── Response Parsing ─────────────────────────
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def _parse_variants(self, parsed: dict, channel: str) -> list[MessageVariant]:
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"""Parse LLM JSON response into MessageVariant objects."""
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variants = []
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char_limit = CHANNEL_LIMITS[channel]
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for key, label in [("variant_a", "A"), ("variant_b", "B")]:
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variant_data = parsed.get(key, {})
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if isinstance(variant_data, str):
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content = variant_data
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subject = None
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else:
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content = variant_data.get("content", "")
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subject = variant_data.get("subject") if channel == "email" else None
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# Truncate if over limit
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if len(content) > char_limit:
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content = content[:char_limit - 3] + "..."
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read_time = max(1, len(content) // 200 * 10) # ~200 chars / 10 sec
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variants.append(MessageVariant(
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content=content,
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subject=subject,
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variant_label=label,
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estimated_read_time_sec=read_time,
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))
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return variants
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def _fallback_variants(
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self, channel: str, tone: str, lead_data: dict, language: str
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) -> list[MessageVariant]:
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"""Generate basic fallback messages when LLM is unavailable."""
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name = lead_data.get("name", "")
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company = lead_data.get("company", "")
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if language == "ar":
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greeting = "السلام عليكم" if tone == "formal" else "هلا والله"
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if tone == "follow_up":
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text_a = f"{greeting} {name}، كيف حالك؟ حبيت أتابع معك بخصوص محادثتنا السابقة. هل عندك أي أسئلة؟"
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text_b = f"{greeting} {name}، يعطيك العافية! تواصلنا قبل وحبيت أشوف إذا تحتاج أي شي ثاني."
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elif tone == "urgent":
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text_a = f"{greeting} {name}، عندنا عرض خاص ينتهي قريب. تبي أرسل لك التفاصيل؟"
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text_b = f"{greeting} {name}، فرصة محدودة متاحة الحين. هل تحب نتكلم عنها؟"
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else:
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text_a = f"{greeting} {name}، يسعدنا تواصلك! كيف نقدر نساعدك اليوم؟"
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text_b = f"{greeting} {name}، حياك الله! عندنا حلول ممتازة تناسب احتياجاتك."
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else:
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if tone == "follow_up":
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text_a = f"Hi {name}, following up on our previous conversation. Do you have any questions?"
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text_b = f"Hello {name}, just checking in. Would you like to continue our discussion?"
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elif tone == "urgent":
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text_a = f"Hi {name}, we have a limited-time offer. Shall I share the details?"
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text_b = f"Hello {name}, a special opportunity is available now. Interested?"
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else:
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text_a = f"Hi {name}, great to connect! How can we help you today?"
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text_b = f"Hello {name}, we have solutions tailored to your needs. Let's chat!"
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return [
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MessageVariant(content=text_a, variant_label="A", estimated_read_time_sec=10),
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MessageVariant(content=text_b, variant_label="B", estimated_read_time_sec=10),
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]
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# ── Send Time Calculation ────────────────────
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def _calculate_best_send_time(self, channel: str) -> tuple[str, str]:
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"""Calculate best send time based on Saudi business hours."""
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now_utc = datetime.now(timezone.utc)
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now_saudi = now_utc + SAUDI_TZ_OFFSET
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window = SEND_WINDOWS.get(channel, SEND_WINDOWS["whatsapp"])
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peak_hours = window["peak"]
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# Find the next available peak hour
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current_hour = now_saudi.hour
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current_weekday = now_saudi.weekday()
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# Check today first
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if current_weekday in SAUDI_WORK_DAYS:
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for peak in peak_hours:
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if peak > current_hour:
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best_time = f"{peak:02d}:00 (توقيت السعودية)"
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day_names_ar = {
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6: "الأحد", 0: "الاثنين", 1: "الثلاثاء",
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2: "الأربعاء", 3: "الخميس",
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}
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best_day = day_names_ar.get(current_weekday, "اليوم")
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return best_time, best_day
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# Next work day
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days_ahead = 1
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while days_ahead <= 7:
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next_day = (current_weekday + days_ahead) % 7
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if next_day in SAUDI_WORK_DAYS:
|
|
best_time = f"{peak_hours[0]:02d}:00 (توقيت السعودية)"
|
|
day_names_ar = {
|
|
6: "الأحد", 0: "الاثنين", 1: "الثلاثاء",
|
|
2: "الأربعاء", 3: "الخميس", 4: "الجمعة", 5: "السبت",
|
|
}
|
|
best_day = day_names_ar.get(next_day, "")
|
|
return best_time, best_day
|
|
days_ahead += 1
|
|
|
|
return f"{peak_hours[0]:02d}:00 (توقيت السعودية)", "الأحد"
|