"""
AI Agent for text chat mode.
Handles routing, GPT responses, Mistral streaming,
voice transcription, and image analysis.
"""

import json
import requests
from datetime import datetime, timezone
from config import GPT_URL, MISTRAL_COOKIE, TRANSCRIPT_URL, CLOUDINARY_URL, CLOUDINARY_PRESET
from chat.history import ChatHistory
from subjects.loader import subject_loader
from database.chat_history import save_user_chat_to_db, load_user_chat_from_db


class AIAgent:
    def __init__(self):
        self.gpt_url = GPT_URL
        self.mistral_cookie = MISTRAL_COOKIE
        self.transcript_base_url = TRANSCRIPT_URL
        self.cloudinary_url = CLOUDINARY_URL
        self.cloudinary_preset = CLOUDINARY_PRESET

        self.chat_history = ChatHistory()

        # Exam sessions (in-memory)
        self.exam_sessions = {}
        self.exam_lock = __import__('threading').Lock()

        print("✅ AIAgent initialized")

    # ─── GPT call ───

    def _call_gpt5(self, user_message, system_prompt, temperature=0.7):
        payload = {
            "user_input": user_message,
            "chat_history": [{"role": "system", "content": system_prompt}],
            "temperature": temperature,
            "top_p": 0.95,
            "max_completion_tokens": 4000
        }
        try:
            response = requests.post(self.gpt_url, json=payload, timeout=120)
            response.raise_for_status()
            return response.json().get("assistant_response", "")
        except Exception as e:
            print(f"❌ GPT-5 Error: {e}")
            return None

    def _call_gpt5_multipart(self, image_url, text_prompt, system_prompt, temperature=0.7):
        payload = {
            "user_input": None,
            "chat_history": [
                {"role": "system", "content": system_prompt},
                {
                    "role": "user",
                    "type": "multipart",
                    "content": [
                        {"type": "image", "url": image_url},
                        {"type": "text", "text": text_prompt}
                    ]
                }
            ],
            "temperature": temperature,
            "top_p": 0.95,
            "max_completion_tokens": 4000
        }
        try:
            response = requests.post(self.gpt_url, json=payload, timeout=120)
            response.raise_for_status()
            return response.json().get("assistant_response", "")
        except Exception as e:
            print(f"❌ GPT-5 Multipart Error: {e}")
            return None

    # ─── Mistral streaming ───

    def _call_mistral_stream(self, user_message, file_content, session_id):
        chat_context = self.chat_history.get_full_context(session_id)

        full_prompt = f"""{file_content}

=== سياق المحادثة ===
{chat_context if chat_context else "هذه بداية المحادثة مع الطالب."}
=== نهاية السياق ===

سؤال الطالب الحالي: {user_message}

إجابتك:"""

        headers = {
            "Content-Type": "application/json",
            "Cookie": self.mistral_cookie,
            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
        }

        payload = {
            "inputs": [{
                "object": "entry",
                "type": "message.input",
                "created_at": datetime.now(timezone.utc).isoformat(),
                "role": "user",
                "content": full_prompt,
                "prefix": False
            }],
            "stream": True,
            "instructions": "",
            "tools": [],
            "completion_args": {
                "temperature": 0.7,
                "top_p": 0.95,
                "max_tokens": 4096
            },
            "model": "mistral-medium-latest"
        }

        try:
            response = requests.post(
                "https://console.mistral.ai/api-ui/bora/v1/conversations",
                headers=headers,
                json=payload,
                stream=True,
                timeout=120
            )

            if response.status_code not in [200, 201]:
                error_msg = f"Mistral Error: {response.status_code} - {response.text[:500]}"
                yield json.dumps({"error": error_msg}) + "\n"
                return

            full_response = ""
            for line in response.iter_lines():
                if line:
                    line = line.decode('utf-8')
                    if line.startswith('data: '):
                        try:
                            data = json.loads(line[6:])
                            if data.get('type') == 'message.output.delta':
                                content = data.get('content', '')
                                if content:
                                    full_response += content
                                    yield json.dumps({"chunk": content}) + "\n"
                        except json.JSONDecodeError:
                            continue

            if full_response:
                self.chat_history.add_message(session_id, "assistant", full_response)

            yield json.dumps({"done": True, "full_response": full_response}) + "\n"

        except requests.exceptions.Timeout:
            yield json.dumps({"error": "انتهت مهلة الاتصال بالخادم. حاول مرة أخرى."}) + "\n"
        except requests.exceptions.ConnectionError:
            yield json.dumps({"error": "خطأ في الاتصال بالخادم."}) + "\n"
        except Exception as e:
            yield json.dumps({"error": str(e)}) + "\n"

    # ─── Routing ───

    def route_message(self, user_message, session_id):
        subject_id = self.chat_history.get_subject(session_id)
        subject_data = subject_loader.load(subject_id) if subject_id else None
        if not subject_data:
            return "main.txt"

        structure_content = subject_data.get("structure.txt", "")
        chat_context = self.chat_history.get_full_context(session_id)
        last_file = self.chat_history.get_last_file(session_id)
        p_files = subject_data.get("_p_files", [])
        p_files_list = "\n".join([f"- {f}" for f in p_files])

        routing_prompt = f"""{structure_content}

**الملفات المتاحة:**
- main.txt: للتحيات والأسئلة العامة
{p_files_list}

**سياق المحادثة:**
{chat_context if chat_context else "لا يوجد سياق سابق"}

**الملف الأخير المستخدم:** {last_file if last_file else "لا يوجد"}

**تعليمات:**
- إذا كانت الرسالة متابعة لموضوع سابق → استخدم نفس الملف الأخير: {last_file if last_file else "main.txt"}
- إذا قال الطالب "استمر" أو "أكمل" → استخدم نفس الملف الأخير
- أجب **فقط** باسم الملف (مثال: p1.txt أو main.txt)

رسالة الطالب: {user_message}

الملف المناسب:"""

        chosen_file = self._call_gpt5(user_message, routing_prompt, temperature=0.2)

        if not chosen_file:
            return last_file if last_file else "main.txt"

        chosen_file = chosen_file.strip().lower()
        valid_files = ["main.txt"] + p_files

        for vf in valid_files:
            if vf in chosen_file:
                return vf

        return last_file if last_file else "main.txt"

    # ─── GPT response ───

    def respond_gpt(self, user_message, chosen_file, session_id):
        subject_id = self.chat_history.get_subject(session_id)
        subject_data = subject_loader.load(subject_id) if subject_id else None
        if not subject_data:
            return "عذراً، لم يتم تحديد المادة. يرجى اختيار المادة أولاً."

        main_content = subject_data.get("main.txt", "")
        chat_context = self.chat_history.get_full_context(session_id)

        system_prompt = f"""{main_content}

=== سياق المحادثة السابقة ===
{chat_context if chat_context else "هذه بداية المحادثة."}
=== نهاية السياق ==="""

        self.chat_history.add_message(session_id, "user", user_message)
        response = self._call_gpt5(user_message, system_prompt, temperature=0.8)

        if response:
            self.chat_history.add_message(session_id, "assistant", response)
            return response
        else:
            err = "عذراً، حدث خطأ في النظام. حاول مرة أخرى."
            self.chat_history.add_message(session_id, "assistant", err)
            return err

    # ─── Mistral response ───

    def respond_mistral_stream(self, user_message, chosen_file, session_id):
        subject_id = self.chat_history.get_subject(session_id)
        subject_data = subject_loader.load(subject_id) if subject_id else None
        if not subject_data:
            def error_gen():
                yield json.dumps({"error": "عذراً، لم يتم تحديد المادة."}) + "\n"
            return error_gen()

        file_content = subject_data.get(chosen_file, "")
        self.chat_history.add_message(session_id, "user", user_message)
        return self._call_mistral_stream(user_message, file_content, session_id)

    # ─── Process message (route + decide) ───

    def process_message(self, user_message, session_id):
        subject = self.chat_history.get_subject(session_id)
        if not subject:
            return None, "no_subject"

        subject_data = subject_loader.load(subject)
        if not subject_data:
            return None, "subject_not_found"

        chosen_file = self.route_message(user_message, session_id)
        self.chat_history.set_last_file(session_id, chosen_file)

        print(f"📀 Subject: {subject} | Routed to: {chosen_file} | Session: {session_id}")
        return chosen_file, "ok"

    # ─── Subject session management ───

    def select_subject(self, username, session_id, subject_id):
        """Select a subject and load/restore chat history."""
        current_subject = self.chat_history.get_subject(session_id)

        # Save current subject chat before switching
        if current_subject and current_subject != subject_id:
            raw = self.chat_history.get_raw_session(session_id)
            save_user_chat_to_db(username, current_subject, raw)

        # Clear and set new subject
        self.chat_history.clear_session(session_id)
        self.chat_history.set_subject(session_id, subject_id)

        # Try to restore saved chat
        saved = load_user_chat_from_db(username, subject_id)
        if saved:
            self.chat_history.restore_session(session_id, saved)

        # Save immediately
        raw = self.chat_history.get_raw_session(session_id)
        save_user_chat_to_db(username, subject_id, raw)

    def save_current_chat(self, username, session_id):
        """Save current session to DB."""
        subject_id = self.chat_history.get_subject(session_id)
        if subject_id:
            raw = self.chat_history.get_raw_session(session_id)
            save_user_chat_to_db(username, subject_id, raw)

    # ─── Audio ───

    def upload_audio(self, audio_file_path, original_filename):
        try:
            with open(audio_file_path, 'rb') as f:
                files = {'audio': (original_filename, f, 'audio/webm')}
                response = requests.post(
                    f"{self.transcript_base_url}/upload",
                    files=files,
                    timeout=60
                )
                response.raise_for_status()
                data = response.json()
                if 'file_url' in data:
                    return data['file_url'], None
                else:
                    return None, data.get('error', 'Upload failed')
        except Exception as e:
            print(f"❌ Audio upload error: {e}")
            return None, str(e)

    def transcribe_audio(self, file_url):
        try:
            payload = {
                "file_url": file_url,
                "prompt": "هذا تسجيل صوتي لطالب يسأل سؤالاً دراسياً"
            }
            response = requests.post(
                f"{self.transcript_base_url}/transcribe",
                json=payload,
                timeout=120
            )
            response.raise_for_status()
            data = response.json()
            if 'transcription' in data:
                return data['transcription'], None
            else:
                return None, data.get('error', 'Transcription failed')
        except Exception as e:
            print(f"❌ Transcription error: {e}")
            return None, str(e)

    # ─── Image ───

    def upload_image_to_cloudinary(self, image_path):
        try:
            with open(image_path, 'rb') as image_file:
                files = {'file': image_file}
                data = {'upload_preset': self.cloudinary_preset}
                response = requests.post(
                    self.cloudinary_url,
                    files=files,
                    data=data,
                    timeout=60
                )
                if response.status_code == 200:
                    result = response.json()
                    image_url = result.get('url') or result.get('secure_url')
                    return image_url, None
                else:
                    return None, f"Cloudinary error: {response.status_code}"
        except Exception as e:
            return None, str(e)

    def analyze_image(self, image_url, session_id):
        system_prompt = """أنت مساعد تعليمي ذكي متخصص في تحليل الصور الدراسية.

مهمتك:
1. إذا كانت الصورة تحتوي على محتوى دراسي (معادلات، نصوص، مسائل، رسوم بيانية، جداول، شروحات، كتب، أوراق امتحانات):
   - استخرج كل المحتوى من الصورة بدقة تامة
   - اكتب المعادلات بصيغة LaTeX
   - اكتب النصوص كما هي
   - اشرح الرسوم البيانية إن وجدت
   - قدم المحتوى بشكل منظم ومفيد

2. إذا كانت الصورة لا تحتوي على محتوى دراسي:
   - أجب فقط بالكلمة: <unsupported>

لا تضف أي تعليق إضافي."""

        result = self._call_gpt5_multipart(
            image_url=image_url,
            text_prompt="حلل هذه الصورة واستخرج محتواها الدراسي",
            system_prompt=system_prompt,
            temperature=0.3
        )
        return result

    # ─── Exam session management ───

    def create_exam_session(self, username, subject_id, door_file, question_count, difficulty):
        with self.exam_lock:
            self.exam_sessions[username] = {
                "subject_id": subject_id,
                "door_file": door_file,
                "question_count": question_count,
                "difficulty": difficulty,
                "questions": [],
                "current_index": 0,
                "score": 0,
                "answers": [],
                "started_at": datetime.now().isoformat(),
                "status": "generating",
            }
        return self.exam_sessions[username]

    def get_exam_session(self, username):
        with self.exam_lock:
            return self.exam_sessions.get(username, None)

    def clear_exam_session(self, username):
        with self.exam_lock:
            if username in self.exam_sessions:
                del self.exam_sessions[username]
                print(f"🗑️ Cleared exam session for {username}")