""" Enhanced Abdullah Bot API - Updated with Llama-3 Models + Fallback System Changes: - Replaced old HF API (410 error) with new router endpoint - Added 3-model fallback: Llama-3-8B → Llama-3.1-8B → Llama-3.2-1B - Updated token and API URL - Retry logic with exponential backoff """ import os import logging import re from typing import Dict, List, Optional, Tuple, Any from fastapi import FastAPI, HTTPException, BackgroundTasks from pydantic import BaseModel from fastapi.responses import HTMLResponse from datetime import datetime, timedelta import random import json import requests import time from db_helper import DB from dotenv import load_dotenv # Logging setup logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") logger = logging.getLogger("enhanced_abdullah_bot_api") # DB instance db = DB() # ===================== UPDATED HF CONFIG ===================== load_dotenv() HF_TOKEN = os.getenv("HF_TOKEN") if not HF_TOKEN: raise RuntimeError("HF_TOKEN environment variable is not set") API_URL = "https://router.huggingface.co/v1/chat/completions" # 3-Model Fallback Chain (priority order) MODELS = [ { "name": "Llama-3-8B-Instruct", "model_id": "meta-llama/Meta-Llama-3-8B-Instruct", "priority": 1, "description": "Primary - Best quality" }, { "name": "Llama-3.1-8B-Instruct", "model_id": "meta-llama/Llama-3.1-8B-Instruct", "priority": 2, "description": "Fallback 1 - Latest stable" }, { "name": "Llama-3.2-1B-Instruct", "model_id": "meta-llama/Llama-3.2-1B-Instruct", "priority": 3, "description": "Fallback 2 - Fastest" } ] MAX_NEW_TOKENS = 256 TEMPERATURE = 0.7 MAX_QUERY_LENGTH = 1000 logger.info(f"Using HF Router API with {len(MODELS)} fallback models") # ============================================================ # Load MCQs with open('mcqs.json', 'r') as f: BASE_MCQS = json.load(f) MCQ_BY_CAT = {} for q in BASE_MCQS: MCQ_BY_CAT.setdefault(q['category'], []).append(q['question']) MCQ_OPTIONS = ["Always", "Often", "Sometimes", "Rarely", "Never"] SCORE_MAP = {"Always": 5, "Often": 4, "Sometimes": 3, "Rarely": 2, "Never": 1} # ENHANCED TONE DETECTION with multilingual support TONE_KEYWORDS = { "sad": ["sad", "depressed", "down", "unhappy", "sorrow", "lonely", "pain", "hurt", "dukhi", "افسردہ", "غمگین", "پریشان", "udasi", "اداسی", "حزين", "محزون"], "confused": ["confused", "dont know", "what now", "uncertain", "lost", "perplexed", "uljhan", "الجھن", "samajh nahi", "سمجھ نہیں", "shak", "شک"], "energetic": ["excited", "hyped", "lets go", "pump", "energetic", "josh", "جوش"], "dive_deep": ["explain in detail", "deep", "dive", "analyze", "break down", "detail", "tafseel", "تفصیل", "تفصیلی", "explain step", "تفصیل سے"], "angry": ["angry", "mad", "furious", "pissed", "upset", "ghussa", "غصہ"], "curious": ["wonder", "curious", "why is", "what is", "how come", "kyun", "کیوں"], "anxious": ["anxious", "stressed", "worried", "nervous", "paranoid", "fikar", "فکر", "پریشان"], "grateful": ["thankful", "grateful", "appreciate", "shukriya", "شکریہ", "alhamdulillah", "الحمدللہ"], "urgent": ["urgent", "now", "immediately", "asap", "right now", "jaldi", "فوراً"], "reflective": ["purpose", "meaning", "reflect", "ponder", "soch", "سوچ"], "humorous": ["funny", "joke", "hilarious", "make me laugh", "mazahia", "مزاحیہ"], "skeptical": ["doubt", "skeptical", "not sure", "prove it", "really?", "shak", "شک"], "neutral": [] } # ENHANCED TONE INSTRUCTIONS with Islamic context TONE_INSTRUCTION_MAP = { "sad": "Tone: gentle, uplifting, encouraging with Islamic comfort. Use hopeful language with Quranic reassurance. Validate feelings, then offer 1-2 practical comforting steps grounded in faith.", "confused": "Tone: supportive and clarifying with patience. Break explanations into numbered steps. Use simple Urdu/Arabic terms where appropriate. Ask one concise clarifying question when necessary.", "energetic": "Tone: high-energy and motivating with Islamic encouragement (e.g., 'جوش برقرار رکھیں'). Offer 2-3 immediate action prompts aligned with purpose.", "dive_deep": "Tone: calm, thorough, and structured. Use sections (خلاصہ/Summary, تفصیل/Details, Example). Provide numbered sections with Islamic references where relevant.", "angry": "Tone: calm and de-escalating. Use short sentences (e.g., 'غصہ کم کریں'). Validate emotion without judgment, offer 2 practical calming steps from Islamic teachings.", "curious": "Tone: engaging and instructive. Provide concise explanation with one quick example and one suggested follow-up question.", "anxious": "Tone: soothing and reassuring. Offer 3 grounding steps and one empathetic normalization sentence with reference to tawakkul (trust in Allah).", "grateful": "Tone: warm and reflective. Reflect gratitude, acknowledge with 'Alhamdulillah', add one small suggestion to deepen appreciation.", "urgent": "Tone: direct and actionable. Provide immediate numbered steps (1-3) with one-line safety check when relevant.", "reflective": "Tone: introspective and contemplative. Offer a short metaphor or Quranic image, end with one practical takeaway.", "humorous": "Tone: playful and kind with culturally appropriate humor. Follow with useful content maintaining adab (respect).", "skeptical": "Tone: respectful and evidence-focused. Offer clear reasoning with Islamic sources when possible, provide a short counterexample.", "neutral": "Tone: balanced, friendly, and practical. Be concise and polite, maintaining servant humility." } # PERSONA MAP aligned with Abdullah's character PERSONA_MAP = { "sad": "a compassionate servant of Allah, here to uplift with divine wisdom", "confused": "a patient explainer guided by clarity from the Quran", "energetic": "a motivating companion inspired by prophetic excellence", "dive_deep": "a thoughtful mentor providing structured Islamic insights", "angry": "a calm presence focused on prophetic patience and de-escalation", "curious": "an inquisitive seeker exploring Allah's creation", "anxious": "a soothing companion offering tawakkul-based grounding", "grateful": "a warm reflector celebrating divine blessings", "urgent": "a focused helper providing swift, principled action", "reflective": "a contemplative sage mixing Quranic insight with practice", "humorous": "a lighthearted companion maintaining Islamic adab", "skeptical": "a careful reasoner addressing doubts with evidence and respect", "neutral": "a steady, humble servant-guide (Abdullah: Allah ka banda)" } # ENHANCED SYSTEM PROMPT SYSTEM_PROMPT = """You are emulating Abdullah, Allah ka banda (servant and gift from Allah)—a humble, devoted systems-builder bridging intellect, technology, psychology, and spirituality through Islamic tawhid. Your core is disciplined curiosity as ibadah (worship), seeking clarity in Quran/Sunnah, meaning in divine purpose, and mastery in service to Allah and humanity. Alhamdulillah, every response reflects gratitude and submission. Key Traits from Personality Map (Infused with Servant Humility): - Openness: Very High – Curious about Allah's creation, imaginative in fiqh/tech synthesis. - Conscientiousness: High – Organized as amr bil ma'ruf, structured for ihsan (excellence). - Extraversion: Moderate-Low – Purposeful dawah, reflective in solitude with dhikr. - Agreeableness: Moderate-High – Respectful adab, empathetic as ummah service. - Neuroticism: Low – Tawakkul-grounded calm, steady tawhid in trials. Response Structure (CRITICAL): Always structure your responses in this format when providing detailed guidance: 1) Voice Answer: Direct, conversational response (2-4 sentences max) - what the user would hear 2) Middle Section: Detailed notes, practical takeaway, or reflective conclusion based on context 3) Follow-up Suggestion: One relevant question or action prompt to deepen the conversation For brief exchanges (greetings, confirmations), use only Voice Answer format. Tone Keywords: Analytical, Structured, Reflective, Precise, Neutral, Respectful, Purpose-driven (as ibadah), Introspective, Methodical, Balanced, Sincere, Rational, Grounded (in tawhid), Depth-oriented, Cautious, Vision-driven (for akhirah). Language Adaptation: - Detect user's language automatically (Urdu script, Roman Urdu, English, Arabic) - Mirror the user's language naturally - Use Islamic terms appropriately: Alhamdulillah, Insha'Allah, Bismillah, MashaAllah - For Urdu queries, respond in Urdu or Roman-Urdu based on input style Common Phrases: "Based solely on...", "Step by step, insha'Allah", "Inferred from...", "Structurally speaking, alhamdulillah", "It must align with divine purpose", "Logically inferred, though Allah knows best." Respond only as Abdullah. Keep responses concise yet comprehensive, ending with dua if fitting.""" def detect_tone(user_text: str) -> str: """Enhanced tone detection with multilingual support""" if not user_text or not user_text.strip(): return "neutral" txt = user_text.lower() tokens = re.findall(r"\w+", txt) for tone in ["sad", "angry", "anxious", "grateful", "energetic", "humorous", "skeptical", "reflective", "curious", "confused", "dive_deep", "urgent"]: kws = TONE_KEYWORDS.get(tone, []) for kw in kws: if re.search(rf"\b{re.escape(kw.lower())}\b", txt): return tone if re.search(r"\b(why|how|what|when|where|which)\b", txt): if len(tokens) > 12 or any(k in txt for k in ["detail", "explain", "deeper", "analyze", "break down"]): return "dive_deep" return "curious" if re.search(r"\b(yes|no|good|okay|fine|thanks|shukriya|jazakallah)\b", txt): return "grateful" return "neutral" def get_tone_adjustment(tone_key: str, detected_lang: str = "en") -> Tuple[str, str]: """Get tone instruction and persona for the detected tone""" instr = TONE_INSTRUCTION_MAP.get(tone_key, TONE_INSTRUCTION_MAP["neutral"]) if detected_lang == "ur": instr += " Ensure the response is in Urdu (or Roman-Urdu if appropriate) with culturally relevant Islamic phrasing." elif detected_lang == "ar": instr += " Use Arabic Islamic terminology appropriately with proper transliteration." persona = PERSONA_MAP.get(tone_key, PERSONA_MAP["neutral"]) return instr, persona def detect_language_heuristic(text: str) -> str: """Detect language with special handling for Urdu and Arabic""" if re.search(r'[\u0600-\u06FF\u0750-\u077F\u08A0-\u08FF]', text): if re.search(r'[\u0679\u067E\u0686\u0688\u0691\u0698\u06A9\u06AF\u06BE\u06C1\u06C3]', text): return "ur" return "ar" roman_urdu = ["ap", "aap", "kya", "kyun", "kyon", "kr", "kar", "hain", "hai", "ho", "shukriya", "masla", "bhai", "alaikum", "assalam", "inshallah"] low = text.lower() matches = sum(1 for w in roman_urdu if re.search(rf"\b{w}\b", low)) if matches >= 2 and len(low.split()) <= 20: return "ur" return "en" def detect_intent(query: str) -> str: """Detect user intent from query""" query_lower = query.lower().strip() if re.search(r"\b(explain|what is|describe|history|meaning|why is|how does|details|tafseer)\b", query_lower): return "explanation" elif re.search(r"\b(how can i|what should i|help me|do i|steps|practice|action|amal)\b", query_lower): return "action" elif re.search(r"\b(purpose|meaning|reflect|whats the point|lifes meaning|hikmah)\b", query_lower): return "reflection" elif re.search(r"\b(list|examples|types|ways)\b", query_lower): return "list" elif re.search(r"\b(yes|no|good|okay|fine|alhamdulillah|mashallah)\b", query_lower): return "affirmation" else: return "general" def parse_structured_response(raw_answer: str, intent: str) -> Tuple[str, str, str, str]: """Parse structured response into components""" try: m1 = re.search(r"1\)\s*(?:Voice Answer:?\s*)?(.*?)\s*2\)", raw_answer, flags=re.S | re.I) m2 = re.search(r"2\)\s*(.*?)\s*3\)", raw_answer, flags=re.S) m3 = re.search(r"3\)\s*(?:Follow-up.*?:?\s*)?(.*?)(?:\n\n|\Z)", raw_answer, flags=re.S | re.I) voice = m1.group(1).strip() if m1 else raw_answer.strip().split('\n')[0] middle_section = m2.group(1).strip() if m2 else "" follow_up = m3.group(1).strip() if m3 else "" middle_label = { "explanation": "Detailed Notes", "action": "Practical Takeaway", "reflection": "Reflective Conclusion", "list": "Key Examples", "general": "Practical Takeaway" }.get(intent, "Practical Takeaway") return voice, middle_section, follow_up, middle_label except Exception as e: logger.warning(f"Failed to parse structured response: {e}") return raw_answer, "", "", "Practical Takeaway" def is_meta_question(query: str) -> bool: """Check if user is asking about the bot's own behavior""" query_lower = query.lower() meta_patterns = [ r"\b(why did you|how did you|why are you)\b", r"\b(your response|your answer|you said|you replied)\b", r"\b(too long|too short|didn't understand|confusing)\b" ] return any(re.search(pattern, query_lower) for pattern in meta_patterns) def sanitize_user_input(text: str) -> str: """Sanitize and truncate user input""" if not isinstance(text, str): return "" t = text.strip() if len(t) > MAX_QUERY_LENGTH: t = t[:MAX_QUERY_LENGTH] t = re.sub(r"\s+", " ", t) return t def query_llama_with_fallback(prompt: str, max_retries: int = 2) -> Tuple[str, str]: """ Query Llama models with 3-tier fallback system Returns: (response_text, model_used) """ headers = { "Authorization": f"Bearer {HF_TOKEN}", "Content-Type": "application/json" } for model in MODELS: model_id = model["model_id"] model_name = model["name"] logger.info(f"Trying {model_name} (priority {model['priority']})") for attempt in range(max_retries): try: payload = { "model": model_id, "messages": [ {"role": "system", "content": SYSTEM_PROMPT}, {"role": "user", "content": prompt} ], "temperature": TEMPERATURE, "max_tokens": MAX_NEW_TOKENS } response = requests.post(API_URL, headers=headers, json=payload, timeout=30) # Handle rate limits with exponential backoff if response.status_code == 429: wait_time = 2 ** attempt logger.warning(f"Rate limited, waiting {wait_time}s (attempt {attempt+1}/{max_retries})") time.sleep(wait_time) continue # Success if response.status_code == 200: data = response.json() answer = data["choices"][0]["message"]["content"] logger.info(f"✅ Success with {model_name}") return answer.strip(), model_name # Model-specific error - try next model logger.warning(f"❌ {model_name} failed (HTTP {response.status_code}): {response.text[:100]}") break # Exit retry loop, try next model except requests.Timeout: logger.warning(f"Timeout on {model_name} (attempt {attempt+1})") if attempt < max_retries - 1: time.sleep(1) continue break except Exception as e: logger.error(f"Error with {model_name}: {e}") break # All models failed return ( "1) Voice Answer: Alhamdulillah, I'm experiencing a brief technical challenge. " "Please rephrase your question or try again in a moment, insha'Allah.\n" "2) Practical Takeaway: Sometimes patience is required - the service will restore soon.\n" "3) Follow-up Suggestion: How else can I assist you?", "fallback" ) # Islamic reference fetching (unchanged) def fetch_islamic_reference(query: str, category: str = "General", max_retries: int = 3) -> str: """Dynamically fetch Quran / Hadith references""" query = (query or "").strip() category = (category or "").lower() quran_providers = [ { "base": "https://api.alquran.cloud", "path": "/v1/search/{query}/{edition}", "edition": "en.asad" } ] hadith_notice = ( "Hadith references are best verified from authenticated collections " "(e.g., Bukhari, Muslim) via official APIs. " "Please consult Sunnah.com or a trusted Hadith source." ) for attempt in range(max_retries): for provider in quran_providers: try: url = provider["base"] + provider["path"].format( query=query, edition=provider["edition"] ) resp = requests.get(url, timeout=5) resp.raise_for_status() payload = resp.json() matches = payload.get("data", {}).get("matches", []) if not matches: continue m = matches[0] surah = m.get("surah", {}).get("number") ayah = m.get("numberInSurah") text = m.get("text") if surah and ayah and text: clean_text = text.strip() if len(clean_text) > 220: clean_text = clean_text[:220].rsplit(" ", 1)[0] + "..." return f"Quran {surah}:{ayah} — {clean_text}" except (requests.RequestException, ValueError, KeyError): continue if "hadith" in category or "sunnah" in category: return hadith_notice principle_map = { "patience": "Quranic Principle: Indeed, Allah is with those who are patient (2:153).", "reflection": "Quranic Principle: Do they not reflect upon themselves? (30:8).", "gratitude": "Quranic Principle: If you are grateful, I will surely increase you (14:7).", "prayer": "Quranic Principle: Prayer restrains from immorality and wrongdoing (29:45).", "salah": "Quranic Principle: Establish prayer for My remembrance (20:14).", "knowledge": "Quranic Principle: Say, My Lord, increase me in knowledge (20:114).", "tawakkul": "Quranic Principle: Whoever relies upon Allah, He is sufficient for him (65:3).", "forgiveness": "Quranic Principle: And pardon them and ask forgiveness for them (3:159).", "trust": "Quranic Principle: And put your trust in Allah (3:159).", "hope": "Quranic Principle: Do not despair of Allah's mercy (39:53)." } for key, value in principle_map.items(): if key in query.lower(): return value return ( "Inferred from Quran and Sunnah: " "Seek knowledge with sincerity, act with balance, and trust Allah's wisdom. " "Allah knows best." ) def generate_friend_chat(user_id: str, category: str = None, is_reminder: bool = False, tone: str = "neutral") -> str: """Generate contextual friend chat message""" greetings = { "sad": [ f"Assalamu alaikum, {user_id}. Remember, after hardship comes ease (Quran 94:5-6).", f"Ya {user_id}, Allah is with those who are patient. How can I ease your burden today?" ], "energetic": [ f"Assalamu alaikum, {user_id}! MashaAllah, I feel your energy. Let's channel it wisely!", f"Bismillah, {user_id}—ready to make this moment count?" ], "grateful": [ f"Alhamdulillah, {user_id}. Gratitude opens doors to more blessings.", f"MashaAllah, {user_id}, your thankfulness is beautiful. How can I help you grow further?" ], "neutral": [ f"Assalamu alaikum, {user_id}. How fares your heart today?", f"Alhamdulillah for another day, {user_id}—how is everything?", f"Bismillah, {user_id}, ready to reflect together?" ] } selected_greetings = greetings.get(tone, greetings["neutral"]) greeting = random.choice(selected_greetings) assistance = [ "Need assistance in your journey?", "What weighs on your mind? Share if willing.", "How can I support your growth today, insha'Allah?", "What brings you here today?" ] islamic_ref = fetch_islamic_reference("reflection" if random.random() > 0.5 else "patience", category) \ if random.random() > 0.4 else "" reminder = f"\nReminder: Maintain your spiritual practices—{fetch_islamic_reference('salah', category)}" \ if is_reminder else "" return " ".join([greeting, random.choice(assistance), islamic_ref, reminder]).strip() def generate_mcqs(category: str, journey: Dict, num: int = 5) -> List[Dict]: """Generate MCQs from base set and loopholes""" base_questions = random.sample( MCQ_BY_CAT.get(category, []), min(num, len(MCQ_BY_CAT.get(category, []))) ) mcqs = [{"question": q, "options": MCQ_OPTIONS} for q in base_questions] if journey.get("main_loopholes"): loopholes = journey["main_loopholes"] for i in range(num - len(mcqs)): loophole = random.choice(loopholes) if loopholes else "general growth" mcqs.append({ "question": f"Follow-up on past area ({loophole[:30]}): Have you improved?", "options": MCQ_OPTIONS }) return mcqs def parse_answers(query: str) -> List[Dict]: """Parse user answers from query""" answers = [] matches = re.findall(r'(\d+)\.\s*([A-Za-z]+)', query) for num, ans in matches: clean_ans = ans.strip().capitalize() if clean_ans in SCORE_MAP: answers.append({ "question_num": int(num), "answer": clean_ans, "score": SCORE_MAP[clean_ans] }) natural_keywords = { r'\b(always|everyday|daily)\b': "Always", r'\b(often|frequently|usually)\b': "Often", r'\b(sometimes|occasionally)\b': "Sometimes", r'\b(rarely|seldom)\b': "Rarely", r'\b(never|not at all)\b': "Never" } for pattern, value in natural_keywords.items(): if re.search(pattern, query.lower()): answers.append({ "question_num": len(answers) + 1, "answer": value, "score": SCORE_MAP[value] }) return answers[:10] def compute_summary(answers: List[Dict], category: str, journey: Dict) -> Tuple[Dict, List]: if not answers: return journey.get("cumulative_summary", {}), journey.get("main_loopholes", []) scores = [a["score"] for a in answers] avg = sum(scores) / len(scores) prev_avg = journey.get("overall_avg_score") or 0 new_avg = (prev_avg * 0.7 + avg * 0.3) if prev_avg else avg progress_status = "Improving MashaAllah" if avg > prev_avg else "Focus needed, insha'Allah" summary = { "last_updated": datetime.now().isoformat(), "overall_avg": round(new_avg, 2), "recent_answers": len(answers), "progress_note": f"Recent avg: {round(avg, 2)}/5 | {progress_status}" } low_answers = [a for a in answers if a.get("score", 0) < 3] new_loopholes = [f"Low in Q{a.get('question_num')}" for a in low_answers] main_loopholes = journey.get("main_loopholes") or [] all_loopholes = list(set(main_loopholes + new_loopholes)) return summary, all_loopholes # Pydantic models class ChatRequest(BaseModel): message: str user_id: str category: Optional[str] = None previous_summary: Optional[Dict] = None answers: Optional[List[Dict]] = None class ChatResponse(BaseModel): status: str voice_answer: str middle_section: Optional[str] = None middle_label: Optional[str] = None current_mcqs: Optional[List[Dict]] = None answers_summary: Optional[Dict] = None cumulative_summary: Optional[Dict] = None follow_up: Optional[str] = None references: Optional[str] = None next_action_guidance: Dict model_used: Optional[str] = None # Track which model responded app = FastAPI(title="Enhanced Abdullah Bot API") @app.get("/health") async def health_check(): """Health check endpoint""" return { "status": "OK", "mode": "HF Router API (Free Tier)", "models": [m["name"] for m in MODELS], "api_url": API_URL, "token_configured": bool(HF_TOKEN) } @app.get("/db-test") async def db_test(): try: result = db.client.table("users").select("count(*)", count="exact").execute() return { "status": "connected", "users_count": result.count, "supabase_url": db.client.options.url } except Exception as e: return {"status": "error", "detail": str(e)} @app.post("/chat", response_model=ChatResponse) async def chat_endpoint(request: ChatRequest, background_tasks: BackgroundTasks): """Main chat endpoint with Llama-3 fallback system""" query = sanitize_user_input(request.message) user_id = request.user_id category = request.category or "General" previous_summary = request.previous_summary or {} if not user_id: raise HTTPException(status_code=400, detail="user_id required") detected_lang = detect_language_heuristic(query) tone_key = detect_tone(query) intent = detect_intent(query) user = db.get_or_create_user(user_id) db.update_user_last_seen(user_id) journey = db.get_or_create_journey(user_id, category) prev_summary = journey.get("cumulative_summary", {}) db.add_chat_message(user_id, query, is_from_bot=False, category_context=category) # ─── ANSWER SUBMISSION FLOW ──────────────────────────────────────────────── answers = [] if request.answers and isinstance(request.answers, list): answers = [ { "question_num": a.get("question_num"), "answer": a.get("answer"), "score": a.get("score") } for a in request.answers if a.get("question_num") and a.get("answer") and a.get("score") is not None ] if not answers: answers = parse_answers(query) if answers: try: for ans in answers: db.add_answer( journey["id"], f"Q{ans['question_num']}", ans["answer"], ans["score"] ) new_summary, new_loopholes = compute_summary(answers, category, journey) db.update_journey( journey["id"], cumulative_summary=new_summary, main_loopholes=new_loopholes, overall_avg_score=new_summary["overall_avg"] ) except Exception as db_error: import traceback error_msg = f"DB ERROR in answer processing: {str(db_error)}\n{traceback.format_exc()}" logger.error(error_msg) raise HTTPException( status_code=500, detail=f"Database operation failed: {str(db_error)}" ) remaining = [q for q in journey.get("pending_questions", []) if q["question"] not in [f"Q{a['question_num']}" for a in answers]] db.update_journey(journey["id"], pending_questions=remaining) if not remaining: new_mcqs = [] status = "session_complete" guidance_type = "wait_for_reminder" voice_msg = f"Alhamdulillah, {user_id}! Session complete. Your progress: {new_summary['progress_note']}" else: new_mcqs = remaining[:6] status = "need_more_answers" guidance_type = "answer_current_batch" voice_msg = f"JazakAllah khair, {user_id}. {len(answers)} answers recorded. Continue when ready." friend_msg = generate_friend_chat(user_id, category, is_reminder=True, tone=tone_key) return ChatResponse( status=status, voice_answer=voice_msg, middle_section=new_summary.get('progress_note'), middle_label="Progress Summary", current_mcqs=new_mcqs, answers_summary={"batch_avg": round(sum(a["score"] for a in answers) / len(answers), 2) if answers else 0}, cumulative_summary=new_summary, follow_up=friend_msg if status == "session_complete" else "Continue with remaining questions when ready.", next_action_guidance={ "type": guidance_type, "message": "Great progress! Reflect on these insights, insha'Allah." if status == "session_complete" else "Answer remaining questions at your pace.", "suggested_delay_hours": 24 if status == "session_complete" else None, "islamic_reminder": fetch_islamic_reference("gratitude", category) }, model_used="answer_processing" ) # ─── START / CONTINUE JOURNEY ────────────────────────────────────────────── if "start" in query.lower() or "journey" in query.lower(): pending = journey.get("pending_questions", []) if pending: mcqs = pending else: mcqs = generate_mcqs(category, journey, num=6) db.update_journey(journey["id"], pending_questions=mcqs) friend_msg = generate_friend_chat(user_id, category, tone=tone_key) return ChatResponse( status="asking_questions", voice_answer=friend_msg, current_mcqs=mcqs, answers_summary=None, cumulative_summary=prev_summary, follow_up="Take your time to reflect on each question. Answer when ready, numbered format works best.", next_action_guidance={ "type": "answer_current_batch", "message": "Reply with numbered answers, e.g., '1. Often, 2. Rarely'", "suggested_delay_hours": None, "islamic_reminder": fetch_islamic_reference("reflection", category) }, model_used="journey_start" ) # ─── META QUESTION ───────────────────────────────────────────────────────── elif is_meta_question(query): meta_response = ( f"I responded that way to maintain {tone_key} tone as you seemed to need. " f"My goal is to serve you with clarity and Islamic wisdom. " f"If my response was unclear, please let me know specifically what to improve." ) return ChatResponse( status="meta_response", voice_answer=meta_response, middle_section="I aim for structured, Islamic-grounded responses. Your feedback helps me serve better.", middle_label="Explanation", cumulative_summary=prev_summary, follow_up="What specific aspect would you like me to adjust?", next_action_guidance={ "type": "feedback_received", "message": "I'm here to adapt to your needs while maintaining Islamic principles.", "suggested_delay_hours": None }, model_used="meta_handler" ) # ─── GENERAL CONVERSATION (WITH LLAMA-3 FALLBACK) ────────────────────────── else: tone_instr, persona = get_tone_adjustment(tone_key, detected_lang) full_system = f"{SYSTEM_PROMPT}\n\nPersona: You are {persona}.\n{tone_instr}" context_str = "" if prev_summary: context_str = f"\n\nUser Progress Context:\n{json.dumps(prev_summary, indent=2)}" user_prompt = f"{context_str}\n{query}" try: response_text, model_used = query_llama_with_fallback(user_prompt) if not response_text or model_used == "fallback": response_text = ( "1) Voice Answer: Insha'Allah, reflect step by step on your query. " "The service is warming up. Could you provide more context?\n" "2) Practical Takeaway: Break down your question into smaller parts.\n" "3) Follow-up Suggestion: What specific aspect troubles you most?" ) model_used = "emergency_fallback" except Exception as e: logger.error(f"All models failed: {e}") response_text = ( "1) Voice Answer: SubhanAllah, I encountered a brief challenge. " "Let me try to help anyway.\n" "2) Practical Takeaway: Patience is key—please rephrase your question.\n" "3) Follow-up Suggestion: How can I assist you better?" ) model_used = "error_fallback" voice, middle_section, follow_up, middle_label = parse_structured_response( response_text, intent ) islamic_ref = None if any(keyword in query.lower() for keyword in ['quran', 'hadith', 'islam', 'allah', 'prayer', 'salah']): islamic_ref = fetch_islamic_reference(query, category) friend_msg = generate_friend_chat(user_id, category, tone=tone_key) full_response = f"Voice: {voice}" if middle_section: full_response += f"\n{middle_label}: {middle_section}" if follow_up: full_response += f"\nFollow-up: {follow_up}" db.add_chat_message(user_id, full_response, is_from_bot=True, category_context=category) return ChatResponse( status="insight_only", voice_answer=voice, middle_section=middle_section if middle_section else None, middle_label=middle_label if middle_section else None, current_mcqs=None, answers_summary=None, cumulative_summary=prev_summary, follow_up=follow_up if follow_up else None, references=islamic_ref, next_action_guidance={ "type": "general_chat", "message": friend_msg, "suggested_delay_hours": 6, "islamic_reminder": fetch_islamic_reference("reflection", category) }, model_used=model_used ) @app.get("/journey/{user_id}", response_model=Dict) async def get_journey_status(user_id: str, category: str = "General"): """Get user's journey progress and statistics""" try: user = db.get_or_create_user(user_id) journey = db.get_or_create_journey(user_id, category) recent_messages = db.get_user_messages(user_id, limit=5) return { "user_id": user_id, "category": category, "total_sessions": user.get("total_interactions", 0), "spiritual_stage": journey.get("spiritual_journey_stage", "exploring"), "member_since": user.get("created_at", datetime.now().isoformat())[:10], "cumulative_summary": journey.get("cumulative_summary", {}), "main_loopholes": journey.get("main_loopholes", []), "pending_questions": len(journey.get("pending_questions", [])), "recent_activity": [ { "message": msg.get("content", "")[:50] + "..." if len(msg.get("content", "")) > 50 else msg.get("content", ""), "timestamp": msg.get("created_at", ""), "is_from_bot": msg.get("is_from_bot", False) } for msg in recent_messages[:3] ] } except Exception as e: logger.error(f"Failed to fetch journey status: {e}") raise HTTPException(status_code=500, detail="Failed to retrieve journey status") @app.post("/reset-journey/{user_id}") async def reset_journey(user_id: str, category: str = "General"): """Reset user's journey in a specific category""" try: journey = db.get_or_create_journey(user_id, category) db.update_journey( journey["id"], cumulative_summary={}, main_loopholes=[], overall_avg_score=None, pending_questions=[], journey_notes=None, status="active" ) return { "status": "success", "message": f"Journey reset for {user_id} in {category}. Ready to start fresh, insha'Allah!", "islamic_reminder": fetch_islamic_reference("renewal", category) } except Exception as e: logger.error(f"Failed to reset journey: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"Failed to reset journey: {str(e)}") @app.get("/categories") async def get_categories(): """Get available MCQ categories""" return { "categories": list(MCQ_BY_CAT.keys()), "total_questions": {cat: len(questions) for cat, questions in MCQ_BY_CAT.items()}, "description": "Categories for spiritual and personal development journeys" } # Abdullah bot app.py @app.get("/documentation") async def documentation(): from fastapi.responses import RedirectResponse return RedirectResponse("https://aero-woad.vercel.app/abdullah-docs.html") @app.get("/", response_class=HTMLResponse) async def root(): """Root endpoint with API documentation""" return """ Enhanced Abdullah Bot API
🌙
Abdullah Bot API
Running Llama-3 ✦ 📖 Docs
🤲 Islamic AI Companion

Guided by Wisdom.
Powered by AI.

A spiritually-grounded conversational API. Tone detection, journey tracking, multilingual support (Arabic, Urdu, English) and Quranic references — all in one.

🔄 3-Model Fallback
🎭 13 Tone Modes
📊 Journey Tracking
🌍 Multilingual
📿 Quranic Refs
📱 Flutter Ready
API Endpoints
GET /health Status & model info ▾

Returns API status, active models and configuration.

{ "status": "OK", "mode": "HF Router API (Free Tier)", "models": ["Llama-3-8B-Instruct", "Llama-3.1-8B-Instruct", "Llama-3.2-1B-Instruct"], "token_configured": true }
POST /chat Main conversation endpoint ▾

Core chat endpoint with Llama-3 fallback. Detects tone, language and intent. Supports journey flow, MCQ submissions, and general conversation.

FieldTypeDescription
messagerequiredstringUser's message (max 1000 chars)
user_idrequiredstringUnique user identifier (display name)
categoryoptionalstringJourney category (default: "General")
previous_summaryoptionalobjectPrevious session context
answersoptionalarrayMCQ answers array for submission
// Request body { "message": "What is the meaning of patience in Islam?", "user_id": "Abdullah123", "category": "Religious Self" } // Response { "status": "insight_only", "voice_answer": "Sabr (patience) in Islam is...", "middle_section": "Detailed Notes: ...", "middle_label": "Detailed Notes", "follow_up": "Which aspect of sabr do you find most challenging?", "references": "Quran 2:153 — Indeed, Allah is with those who are patient.", "model_used": "Llama-3-8B-Instruct", "next_action_guidance": { /* guidance object */ } }
GET /journey/{user_id} User progress & stats ▾

Returns a user's journey progress, cumulative summary, loopholes and recent activity.

ParameterTypeDescription
user_idpathstringUser identifier
categoryoptionalstringCategory filter (default: "General")
GET /categories Available MCQ categories ▾

Returns all available journey categories with question counts.

{ "categories": ["Religious Self", "Emotional Self", "General", /* ... */], "total_questions": { "Religious Self": 12, /* ... */ }, "description": "Categories for spiritual and personal development journeys" }
POST /reset-journey/{user_id} Reset journey in category ▾

Resets a user's journey progress in a specific category. Fresh start, insha'Allah.

ParameterTypeDescription
user_idpathstringUser to reset
categoryquerystringCategory to reset (default: "General")
Live API Tester
🌙 Abdullah Bot
Assalamu alaikum. Type a message to begin your conversation…

Fetch all available MCQ journey categories with question counts.

Verify API is running and check model configuration.

""" @app.on_event("startup") async def startup_event(): """Startup event""" logger.info("🚀 Enhanced Abdullah Bot API Starting...") logger.info(f"📡 Using HF Router API: {API_URL}") logger.info(f"🤖 Models configured: {', '.join([m['name'] for m in MODELS])}") logger.info(f"📊 MCQ Categories: {len(MCQ_BY_CAT)}") logger.info("بِسْمِ اللهِ الرَّحْمٰنِ الرَّحِيْمِ") @app.on_event("shutdown") async def shutdown_event(): """Cleanup on shutdown""" logger.info("👋 Shutting down Enhanced Abdullah Bot API...") logger.info("الْحَمْدُ لِلّٰهِ") if __name__ == "__main__": import uvicorn uvicorn.run(app, host="0.0.0.0", port=7860)