import gradio as gr
import json
import logging
import argparse
import sys
import os
import math
import pickle
from deep_translator import GoogleTranslator
from gematria import calculate_gematria
from collections import defaultdict
from typing import Dict, List, Any, Optional

# --- Configuration ---
# Logging is kept for file-based or production logging, but we'll use print() for immediate console debug
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
BOOK_RANGE = range(1, 40)
CACHE_FILE = "tanakh_phrasedict.cache"

# --- Core Logic Functions ---

def get_power_result(total_sum: int, query_value: int) -> int:
    """Calculates the power or root result."""
    if query_value <= 1:
        return 1
    if query_value < total_sum:
        try:
            exponent = int(math.floor(math.log(total_sum, query_value)))
            return query_value ** exponent
        except (ValueError, OverflowError):
            return 1

def find_all_matching_phrases(target_sum: int, phrase_dictionary: Dict[int, List[Dict]]) -> List[Dict]:
    """Finds all phrases matching a target Gematria."""
    return phrase_dictionary.get(int(target_sum), [])

# --- Global State: Load dictionary once at startup ---
try:
    if not os.path.exists(CACHE_FILE):
        raise FileNotFoundError(f"ERROR: Cache file '{CACHE_FILE}' not found. Please run 'build_indices.py' first.")
    logging.info(f"Loading phrase dictionary from cache: {CACHE_FILE}")
    with open(CACHE_FILE, 'rb') as f:
        phrase_dictionary: Optional[Dict[int, List[Dict]]] = pickle.load(f)
    logging.info("Phrase dictionary loaded successfully for the Gradio app.")
except (FileNotFoundError, IOError, pickle.UnpicklingError) as e:
    logging.error(str(e))
    phrase_dictionary = None

# --- Main Analysis Function for Gradio ---

def run_analysis(query: str, translate: bool, process_verses: int, results_per_verse: int, xor_depth: int, progress=gr.Progress(track_tqdm=True)):
    """The main analysis function called by the Gradio interface."""
    if phrase_dictionary is None:
        return "## Fatal Error\nCould not start analysis. The phrase dictionary cache file (`tanakh_phrasedict.cache`) is missing or corrupt. Please run `build_indices.py` and restart the app."

    print("\n--- NEW ANALYSIS RUN ---") # Console Debug
    output_lines = []

    try:
        query_value = calculate_gematria(query)
        if query_value <= 1 and query:
            return f"## Error\nQuery '{query}' has an invalid Gematria value ({query_value}). Please enter a valid query."
    except Exception as e:
        return f"## Error\nCould not calculate Gematria for query '{query}'. Details: {e}"

    progress(0, desc="Initializing...")
    translator = None
    if translate:
        try:
            translator = GoogleTranslator(source='iw', target='en')
        except Exception as e:
            logging.error(f"Could not initialize translator: {e}")
            output_lines.append(f"**Warning:** Could not initialize translator: {e}")

    output_lines.append(f"## XOR Gematria Resonance Analysis for: `{query}`")

    verses_processed = 0
    resonance_count = 0

    # Using a generator to handle the nested loops cleanly and break out
    def get_verses():
        for book_num in BOOK_RANGE:
            filepath = f"texts/torah/{book_num:02}.json"
            if not os.path.exists(filepath): continue
            with open(filepath, 'r', encoding='utf-8') as f:
                data = json.load(f)
                for chap_idx, chapter in enumerate(data.get("text", []), start=1):
                    for verse_idx, verse_text in enumerate(chapter, start=1):
                        yield (book_num, chap_idx, verse_idx, verse_text)

    for book_num, chap_idx, verse_idx, verse_text in get_verses():
        # Correctly handle the processing limit
        if process_verses and verses_processed >= process_verses:
            print(f"DEBUG: Processing limit of {process_verses} verses reached. Stopping analysis.")
            break
        verses_processed += 1
        progress(verses_processed / process_verses, desc=f"Analyzing Verse {verses_processed}/{process_verses}")

        verse_sum = calculate_gematria(verse_text)
        if verse_sum <= 1: continue

        if query_value < verse_sum:
            power_result = get_power_result(verse_sum, query_value)
            main_target_sum = verse_sum ^ power_result
        elif query_value > verse_sum:
            main_target_sum = query_value ^ verse_sum
            power_result= 0
        elif query_value == verse_sum:
            main_target_sum = verse_sum
            power_result=0
        main_matches = find_all_matching_phrases(main_target_sum, phrase_dictionary)

        verse_ref = f"B{book_num:02d}, C{chap_idx}, V{verse_idx}"
        if power_result == 0:
            print(f"DEBUG: Analyzing [{verse_ref}] | Verse Sum: {verse_sum}, Main Target: {main_target_sum}") # Console Debug
        print(f"DEBUG: Analyzing [{verse_ref}] | Verse Sum: {verse_sum}, Power/Root: {power_result}, Main Target: {main_target_sum}") # Console Debug

        if not main_matches:
            print("DEBUG: No main resonance found. Skipping.") # Console Debug
            continue

        resonance_count += 1
        print(f"DEBUG: Found Resonance #{resonance_count}!") # Console Debug

        output_lines.append("\n---\n")
        output_lines.append(f"### Resonance #{resonance_count} in [{verse_ref}]")
        output_lines.append(f"> {verse_text.strip()}\n")

        output_lines.append("```")
        output_lines.append(f"Verse Sum (X) : {verse_sum} | Query: \"{query}\" (G: {query_value}) | Power/Root (Y): {power_result}")
        output_lines.append("```\n")

        def format_matches(matches: List[Dict], title: str, calculation_str: str):
            if not matches: return

            matches.sort(key=lambda p: (p.get('freq', 0) / p.get('words', 99)), reverse=True)
            matches_to_show = matches[:results_per_verse]

            output_lines.append(f"**{title}:** `{calculation_str}`")

            for match in matches_to_show:
                translation_str = ""
                if translator:
                    try:
                        translation_str = translator.translate(match['text'])
                    except Exception:
                        translation_str = "[Translation failed]"

                score = (p.get('freq', 0) / p.get('words', 99)) if (p:=match).get('words') else 0
                gematria_val = calculate_gematria(match['text'])

                output_lines.append(f"  * **{match['text']}**")
                output_lines.append(f"    `G: {gematria_val}, Words: {match.get('words', 'N/A')}, Freq: {match.get('freq', 'N/A')}, Score: {score:.2f}`")
                if translation_str:
                    output_lines.append(f"\n*Translation: \"{translation_str}\"*")
            output_lines.append("")

        if power_result!=0:
            calc_str = f"[{verse_sum}] ^ [{power_result}] → [G_target:{main_target_sum}]"
        elif power_result==0:
            calc_str = f"[{verse_sum}] ^ [{query_value}] → [G_target:{main_target_sum}]"
        format_matches(main_matches, "Main Resonance", calc_str)

        if xor_depth > 0:
            output_lines.append(f"**Bitplane Variations of the Result ({main_target_sum}):**")
            for depth in range(xor_depth):
                bit_flip = 1 << depth
                target_sum = main_target_sum ^ bit_flip
                bitplane_matches = find_all_matching_phrases(target_sum, phrase_dictionary)

                if bitplane_matches:
                    bitplane_calc_str = f"[{main_target_sum}] ^ [Bit {depth+1}] → [G_target:{target_sum}]"
                    format_matches(bitplane_matches, f"Variation (Depth {depth + 1})", bitplane_calc_str)

    if resonance_count == 0:
        output_lines.append("\n**No resonances found. Consider increasing 'Verses to Process' or trying a different query.**")

    print("--- ANALYSIS COMPLETE ---") # Console Debug
    return "\n".join(output_lines)

# --- Gradio UI Definition ---
# Custom CSS fse:or a professional dark theme inspired by the screenshot
custom_css = """
#output_markdown h3 {
    color: #f97316; /* Vibrant orange for main resonance headers */
    border-bottom: 2px solid #374151;
    padding-bottom: 8px;
    margin-top: 24px;
}
#output_markdown blockquote {
    background-color: #1f2937;
    border-left: 5px solid #f97316;
    padding: 12px;
    font-style: italic;
    color: #d1d5db;
}
#output_markdown code {
    background-color: #374151;
    color: #e5e7eb;
    padding: 3px 6px;
    border-radius: 5px;
    font-size: 0.9em;
}
"""

# Using the robust Default theme and customizing it for the desired dark look
dark_theme = gr.themes.Default(
    primary_hue=gr.themes.colors.orange,
    secondary_hue=gr.themes.colors.blue,
    neutral_hue=gr.themes.colors.slate
).set(
    body_background_fill="#0f172a",
    background_fill_primary="#1e293b",
    background_fill_secondary="#334155",
    body_text_color="#e2e8f0",
    color_accent_soft="#1e293b",
    border_color_accent="#334155",
    border_color_primary="#334155",
    button_primary_background_fill="#f97316",
    button_primary_text_color="#ffffff",
    button_secondary_background_fill="#334155",
    button_secondary_text_color="#e2e8f0",
)

with gr.Blocks(theme=dark_theme, css=custom_css, title="Tanakh XOR Gematria Resonance") as demo:
    gr.Markdown("# 📜 Tanakh XOR Gematria Resonance")

    with gr.Tabs():
        with gr.TabItem("XOR Gematria Resonance"):
            with gr.Row():
                with gr.Column(scale=1):
                    query = gr.Textbox(
                        label="Query Phrase",
                        placeholder="e.g., יהוה, אלהים, light...",
                    )
                    run_button = gr.Button("🔮 Divine Resonance", variant="primary")

                    with gr.Accordion("Advanced Parameters", open=False):
                        process_verses = gr.Slider(
                            label="Verses to Process", minimum=1, maximum=35000, step=1, value=10,
                            info="How many verses to analyze from the start of the Tanakh."
                        )
                        results_per_verse = gr.Slider(
                            label="Results per Resonance", minimum=1, maximum=10, step=1, value=1,
                            info="How many top phrases to show for each found resonance type."
                        )
                        xor_depth = gr.Slider(
                            label="Bitplane Variation Depth", minimum=0, maximum=16, step=1, value=2,
                            info="How many bit-levels of the main result to vary and analyze."
                        )
                        translate = gr.Checkbox(label="Translate to English", value=True)

                    gr.Examples(
                        examples=[
                            ["יהוה"], ["אלהים"], ["שכינה"],
                            ["משיח ישמעאל"], ["מאה שלושים ושבע"], ["צדק ומשפט"]
                        ],
                        inputs=[query]
                    )

                with gr.Column(scale=3):
                    output_markdown = gr.Markdown(label="Resonances", elem_id="output_markdown")

        with gr.TabItem("About & Help"):
            gr.Markdown(
                """
                ### How It Works
                This tool explores the numerological and structural connections within the Tanakh based on Gematria and bitwise XOR operations. It is an instrument for textual exploration, not a historical or theological authority.

                1.  **Gematria Calculation:** The Gematria (numerical value) of your **Query Phrase** and each **Verse** in the Tanakh is calculated.
                2.  **Power/Root Operator (Y):** To create a non-obvious link, the Query's Gematria is transformed. If it's smaller than the Verse's Gematria, its highest possible power is taken. If larger, its n-th root is taken. This becomes the "Operator" (Y).
                3.  **Main Resonance:** The core operation is `Verse_Gematria (X) ^ Operator (Y)`. The result is a **Target Gematria**. The app then finds all phrases in the Tanakh with this exact numerical value. This is the "Main Resonance".
                4.  **Bitplane Variations:** To explore the "fractal neighborhood" of the Main Resonance, the app then "flips" each bit of the result, one by one. For each flipped bit (`depth`), it calculates a new Target Gematria (`Main_Result ^ 2^depth`) and finds corresponding phrases. This reveals concepts that are numerologically "close" to the main result.
                5.  **Scoring:** Results are sorted by a relevance score calculated as `Frequency / Word_Count` to prioritize short, common phrases.

                ### Parameters
                - **Verses to Process:** Limits how many verses the script analyzes. Higher numbers take longer.
                - **Results per Resonance:** Limits how many phrases are shown for the main resonance and each variation.
                - **Bitplane Variation Depth:** Controls how many "bit-flips" are tested. A depth of 5 will test flipping Bit 1, Bit 2, Bit 3, Bit 4, and Bit 5.
                """
            )

    run_button.click(
        fn=run_analysis,
        inputs=[query, translate, process_verses, results_per_verse, xor_depth],
        outputs=[output_markdown]
    )

if __name__ == "__main__":
    if phrase_dictionary is None:
        print("CRITICAL: Phrase dictionary could not be loaded. The application cannot start.")
        print("Please ensure 'tanakh_phrasedict.cache' exists and is valid. Run 'build_indices.py' if necessary.")
    else:
        # The share=True argument creates a public link for easy sharing. Remove it if you only want local access.
        demo.launch()