import os
import requests
from flask import Flask, request, jsonify, send_from_directory
from dotenv import load_dotenv

# --- LangChain Imports ---
from langchain_groq import ChatGroq
from langchain_core.prompts import PromptTemplate
from langchain_core.output_parsers import StrOutputParser

# Load environment variables
load_dotenv()

app = Flask(__name__)

# --- Configuration ---
TAFSIR_OPTIONS = [
    {"slug": "en-tafisr-ibn-kathir", "name": "Tafsir Ibn Kathir", "author": "Hafiz Ibn Kathir", "highlight": "A famous, highly respected classical commentary."},
    {"slug": "en-tafsir-maarif-ul-quran", "name": "Maarif-ul-Quran", "author": "Mufti Muhammad Shafi", "highlight": "A renowned comprehensive modern commentary."},
    {"slug": "en-al-jalalayn", "name": "Tafsir al-Jalalayn", "author": "Jalal al-Din al-Mahalli & al-Suyuti", "highlight": "A famous concise classical commentary."},
    {"slug": "en-tafsir-ibn-abbas", "name": "Tanwîr al-Miqbâs", "author": "Attributed to Ibn 'Abbâs", "highlight": "One of the earliest commentaries."}
]
# We will always fetch from Al-Wahidi for Shan-e-Nazool
SHAN_E_NAZOOL_SLUG = "en-asbab-al-nuzul-by-al-wahidi"

QURAN_API_BASE_URL = "http://api.alquran.cloud/v1/ayah"
TAFSIR_API_BASE_URL = "https://cdn.jsdelivr.net/gh/spa5k/tafsir_api@main/tafsir"
DATA_UNAVAILABLE_MESSAGE = "No specific commentary was found for this verse in this source."

# --- LangChain Setup ---
try:
    llm = ChatGroq(model="llama-3.3-70b-versatile", temperature=0.6)

    # This is our new, sophisticated, all-in-one prompt
    prompt = PromptTemplate(
        template="""
        You are an expert assistant for Quranic studies. Your task is to provide a clear, multi-source explanation for Surah {surah}, Ayah {ayah}.

        **Your response MUST be structured in the following order, using the provided data:**

        1.  **The Verse:**
            - Start with the heading: "### The Verse (Surah {surah}:{ayah})".
            - Quote the English translation: "{ayah_text}".

        2.  **Shan-e-Nazool (Reason for Revelation):**
            - Use the heading: "### Shan-e-Nazool (Reason for Revelation)".
            - Based **only** on the provided text from "Asbab Al-Nuzul by Al-Wahidi", summarize the reason for revelation.
            - If the text from Al-Wahidi is '{data_unavailable}', you MUST state: "No specific reason for revelation for this verse was found in Al-Wahidi's Asbab al-Nuzul."

        3.  **Commentary from {tafsir_name}:**
            - Use the heading: "### Commentary from {tafsir_name}".
            - Provide a comprehensive summary of the commentary from the user's chosen Tafsir ({tafsir_name} by {tafsir_author}).
            - If the text for this commentary is '{data_unavailable}', you MUST state: "The selected source, {tafsir_name}, does not provide a detailed commentary for this specific verse."

        4.  **Answer to Specific Question (If provided):**
            - If a user question is provided, use the heading: "### Answer to Your Question".
            - Answer the user's question: "{question}"
            - **CRITICAL:** Your answer must be based **only** on the combined information from the Al-Wahidi text and the {tafsir_name} text.
            - If the provided texts do not contain enough information to answer the question, state that clearly. For example: "The provided commentaries do not contain specific information to answer the question: '{question}'."
            - If no question is provided (i.e., the question is 'N/A'), DO NOT include this section in your output.

        5.  **Summary:**
            - Use the heading: "### Summary".
            - Provide a brief, final summary synthesizing the key points from the available commentaries.

        ---
        **DATA FOR YOUR TASK:**

        [Verse Translation]:
        {ayah_text}

        [Asbab Al-Nuzul by Al-Wahidi]:
        {shan_e_nazool_text}

        [{tafsir_name} by {tafsir_author}]:
        {tafsir_text}

        [User's Question]:
        {question}
        ---

        Begin your response now.
        """,
        input_variables=["surah", "ayah", "ayah_text", "shan_e_nazool_text", "tafsir_name", "tafsir_author", "tafsir_text", "question", "data_unavailable"]
    )
    
    output_parser = StrOutputParser()
    main_chain = prompt | llm | output_parser

except Exception as e:
    print(f"Error initializing LangChain components: {e}")
    main_chain = None

# --- Helper Functions ---
def get_data(url: str) -> str:
    """Generic function to fetch data and handle errors."""
    try:
        response = requests.get(url, timeout=10)
        response.raise_for_status()
        data = response.json()
        text = data.get("text", "").strip()
        return text if text else DATA_UNAVAILABLE_MESSAGE
    except requests.exceptions.RequestException:
        return DATA_UNAVAILABLE_MESSAGE

def get_ayah_text(surah: int, ayah: int) -> str:
    url = f"{QURAN_API_BASE_URL}/{surah}:{ayah}/en.asad"
    try:
        response = requests.get(url, timeout=10)
        response.raise_for_status()
        data = response.json()
        if data.get('code') == 200 and data.get('data', {}).get('text'):
            return data['data']['text']
        return "Could not retrieve the translation for this verse."
    except requests.exceptions.RequestException:
        return "Could not retrieve the translation due to a network error."

# --- Flask Routes ---
@app.route('/')
def index():
    return send_from_directory('.', 'index.html')

@app.route('/tafsirs', methods=['GET'])
def get_tafsirs():
    return jsonify(TAFSIR_OPTIONS)

@app.route('/explain', methods=['POST'])
def explain_ayah():
    if not main_chain:
        return jsonify({"error": "LangChain services are not initialized."}), 500

    data = request.get_json()
    surah = data.get('surah')
    ayah = data.get('ayah')
    tafsir_slug = data.get('tafsir_slug')
    question = data.get('question', '').strip()

    try:
        selected_tafsir = next((t for t in TAFSIR_OPTIONS if t['slug'] == tafsir_slug), None)
        if not selected_tafsir:
            return jsonify({"error": "Invalid Tafsir slug."}), 400

        # --- Multi-Source Data Retrieval ---
        ayah_text = get_ayah_text(surah, ayah)
        shan_e_nazool_text = get_data(f"{TAFSIR_API_BASE_URL}/{SHAN_E_NAZOOL_SLUG}/{surah}/{ayah}.json")
        tafsir_text = get_data(f"{TAFSIR_API_BASE_URL}/{tafsir_slug}/{surah}/{ayah}.json")
        
        # --- Invoke the LangChain Chain ---
        result = main_chain.invoke({
            "surah": surah,
            "ayah": ayah,
            "ayah_text": ayah_text,
            "shan_e_nazool_text": shan_e_nazool_text,
            "tafsir_name": selected_tafsir['name'],
            "tafsir_author": selected_tafsir['author'],
            "tafsir_text": tafsir_text,
            "question": question if question else "N/A", # Pass 'N/A' if no question
            "data_unavailable": DATA_UNAVAILABLE_MESSAGE
        })
        
        return jsonify({"explanation": result})

    except Exception as e:
        print(f"An error occurred in the /explain route: {e}")
        return jsonify({"error": "An internal server error occurred."}), 500

if __name__ == '__main__':
    app.run(debug=True)


# #llama-3.3-70b-versatile