import os
import re
import json
import uuid
import random
from pathlib import Path
from datetime import datetime, timezone

import gradio as gr
from huggingface_hub import HfApi


# -----------------------------------------------------------------------------
# Configuration
# -----------------------------------------------------------------------------

STUDY_ROOT = Path("avg_study")
PROMPT_JSON = "prompts_mapping.json"

HF_TOKEN = os.getenv("HF_TOKEN")
RESULTS_REPO_ID = os.getenv("RESULTS_REPO_ID")

api = HfApi(token=HF_TOKEN) if HF_TOKEN else None

LOCAL_RESULTS_DIR = Path("local_results")
LOCAL_RESULTS_DIR.mkdir(exist_ok=True)


# -----------------------------------------------------------------------------
# Load prompt mapping and build pairs
# -----------------------------------------------------------------------------

def clean_prompt(prompt: str) -> str:
    if not prompt:
        return ""
    prompt = re.sub(r"\s*idx\d+\s+r\d+\s*$", "", prompt).strip()
    return prompt


def format_prompt_html(prompt: str) -> str:
    safe_prompt = prompt.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
    return f"<div id='prompt_box'><strong>{safe_prompt}</strong></div>"


def load_prompt_mapping(mapping_file: str):
    mapping_path = Path(mapping_file)
    if not mapping_path.exists():
        raise FileNotFoundError(
            f"Mapping file '{mapping_file}' not found. "
            "Ensure that 'prompts_mapping.json' exists in the repository."
        )
    with open(mapping_path, "r", encoding="utf-8") as f:
        return json.load(f)


def build_pairs_from_mapping(prompt_map):
    pairs = []
    for idx, entry in prompt_map.items():
        prompt = clean_prompt(entry.get("prompt", ""))
        category = entry.get("category", "")
        good_rel = entry.get("good_file")
        bad_rel = entry.get("bad_file")

        if not good_rel or not bad_rel:
            continue

        good_path = STUDY_ROOT / good_rel
        bad_path = STUDY_ROOT / bad_rel

        pairs.append(
            {
                "pair_id": idx,
                "category": category,
                "prompt": prompt,
                "good_path": str(good_path.resolve()),
                "bad_path": str(bad_path.resolve()),
            }
        )
    return pairs


prompt_map = load_prompt_mapping(PROMPT_JSON)
PAIRS = build_pairs_from_mapping(prompt_map)

print(f"Loaded {len(PAIRS)} pairs.")
if PAIRS:
    print("First pair:", PAIRS[0])

if not PAIRS:
    raise RuntimeError(
        "No matched good/bad pairs found in mapping. "
        "Check that 'avg_study' contains matching files and that the mapping file lists them."
    )


# -----------------------------------------------------------------------------
# Helper functions
# -----------------------------------------------------------------------------

def video_value(path_str: str) -> str:
    path = Path(path_str)
    print(f"Loading video: {path}")
    print(f"Exists: {path.exists()}")
    if not path.exists():
        raise FileNotFoundError(f"Video file not found: {path}")
    return str(path.resolve())


def sample_pair(pair):
    good_on_A = random.choice([True, False])

    if good_on_A:
        A_path = pair["good_path"]
        B_path = pair["bad_path"]
        A_label = "good"
        B_label = "bad"
    else:
        A_path = pair["bad_path"]
        B_path = pair["good_path"]
        A_label = "bad"
        B_label = "good"

    current = pair.copy()
    current.update(
        {
            "A_path": A_path,
            "B_path": B_path,
            "A_label": A_label,
            "B_label": B_label,
            "good_on_A": good_on_A,
        }
    )
    return current


def local_save(record: dict) -> str:
    local_name = LOCAL_RESULTS_DIR / f"{record['response_id']}.json"
    with open(local_name, "w", encoding="utf-8") as f:
        json.dump(record, f, ensure_ascii=False, indent=2)
    return str(local_name)


def save_response(record: dict) -> dict:
    local_path = local_save(record)

    if not (RESULTS_REPO_ID and HF_TOKEN and api):
        return {
            "ok": True,
            "saved_local": True,
            "saved_hub": False,
            "message": f"Saved locally to {local_path}. Hub upload is not configured.",
        }

    tmp_name = f"/tmp/{record['response_id']}.json"
    with open(tmp_name, "w", encoding="utf-8") as f:
        json.dump(record, f, ensure_ascii=False, indent=2)

    remote_path = f"responses/{record['timestamp'][:10]}/{record['response_id']}.json"

    try:
        api.upload_file(
            path_or_fileobj=tmp_name,
            path_in_repo=remote_path,
            repo_id=RESULTS_REPO_ID,
            repo_type="dataset",
        )
        return {
            "ok": True,
            "saved_local": True,
            "saved_hub": True,
            "message": f"Saved to dataset repo: {remote_path}",
        }
    except Exception as e:
        return {
            "ok": False,
            "saved_local": True,
            "saved_hub": False,
            "message": f"Saved locally to {local_path}, but Hub upload failed: {e}",
        }


# -----------------------------------------------------------------------------
# Gradio callback functions
# -----------------------------------------------------------------------------

def start_session():
    try:
        participant_id = str(uuid.uuid4())
        remaining_pairs = PAIRS.copy()

        pair = random.choice(remaining_pairs)
        remaining_pairs.remove(pair)
        current = sample_pair(pair)

        status_msg = "Study loaded. Read the prompt, watch both videos, and answer the questions below."

        return (
            format_prompt_html(current["prompt"]),
            video_value(current["A_path"]),
            video_value(current["B_path"]),
            f"Participant ID: {participant_id}",
            participant_id,
            remaining_pairs,
            current,
            None,
            None,
            None,
            status_msg,
            gr.update(visible=False),
            gr.update(visible=True),
        )
    except Exception as e:
        print(f"start_session error: {type(e).__name__}: {e}")
        return (
            format_prompt_html(f"Error loading study: {type(e).__name__}: {e}"),
            None,
            None,
            "",
            None,
            [],
            None,
            None,
            None,
            None,
            f"Start failed: {type(e).__name__}: {e}",
            gr.update(visible=True),
            gr.update(visible=False),
        )


def submit_and_next(ans_prompt, ans_logic, ans_visual, participant_id, remaining_pairs, current):
    try:
        if current is None:
            return (
                format_prompt_html("No current pair loaded."),
                None,
                None,
                remaining_pairs,
                current,
                "No current pair loaded."
            )

        if ans_prompt is None or ans_logic is None or ans_visual is None:
            return (
                format_prompt_html(current["prompt"]),
                video_value(current["A_path"]),
                video_value(current["B_path"]),
                remaining_pairs,
                current,
                "Please answer all questions before continuing."
            )

        timestamp = datetime.now(timezone.utc).isoformat()

        record = {
            "response_id": str(uuid.uuid4()),
            "timestamp": timestamp,
            "participant_id": participant_id,
            "category": current["category"],
            "prompt": current["prompt"],
            "pair_id": current["pair_id"],
            "A_video": current["A_path"],
            "B_video": current["B_path"],
            "good_video": current["good_path"],
            "bad_video": current["bad_path"],
            "good_on_A": current["good_on_A"],
            "A_label": current["A_label"],
            "B_label": current["B_label"],
            "adherence_answer": ans_prompt,
            "logic_answer": ans_logic,
            "visual_quality_answer": ans_visual,
        }

        save_result = save_response(record)

        if not remaining_pairs:
            finish_msg = save_result["message"] + "\n\nYou have completed all pairs. Thank you!"
            return (
                format_prompt_html("Study complete."),
                None,
                None,
                remaining_pairs,
                None,
                finish_msg
            )

        pair = random.choice(remaining_pairs)
        remaining_pairs.remove(pair)
        next_pair = sample_pair(pair)

        status_msg = save_result["message"]
        if not save_result["saved_hub"]:
            status_msg += "\n\nYour response was still saved locally."

        return (
            format_prompt_html(next_pair["prompt"]),
            video_value(next_pair["A_path"]),
            video_value(next_pair["B_path"]),
            remaining_pairs,
            next_pair,
            status_msg
        )
    except Exception as e:
        print(f"submit_and_next error: {type(e).__name__}: {e}")
        return (
            format_prompt_html(current["prompt"] if current else "Error"),
            None,
            None,
            remaining_pairs,
            current,
            f"Submit failed: {type(e).__name__}: {e}"
        )


# -----------------------------------------------------------------------------
# Build Gradio UI
# -----------------------------------------------------------------------------

with gr.Blocks(
    title="Human Study",
    css="""
    #prompt_box {
        width: 100%;
        text-align: center !important;
        font-size: 30px !important;
        font-weight: 900 !important;
        line-height: 1.35 !important;
        margin-top: 16px !important;
        margin-bottom: 22px !important;
    }
    """
) as demo:
    gr.Markdown(
        """
        # Human Study

        Read the prompt, watch both videos, and answer the questions below. Each response is saved
        automatically when you click **Submit and continue**. The study ends once you have gone through
        all available pairs. Thank you for your participation!
        """
    )

    participant_label = gr.Markdown()
    status = gr.Markdown()

    start_btn = gr.Button("Start Study", visible=True)

    prompt_md = gr.HTML("<div id='prompt_box'><strong>Prompt will appear here.</strong></div>")

    with gr.Row():
        video_A = gr.Video(label="A", interactive=False, format="mp4")
        video_B = gr.Video(label="B", interactive=False, format="mp4")

    q_adherence = gr.Radio(
        choices=["A", "B", "No preference"],
        label="Which video has better adherence to the prompt?"
    )
    q_logic = gr.Radio(
        choices=["A", "B", "No preference"],
        label="Which video has a more logical change of events?"
    )
    q_visual = gr.Radio(
        choices=["A", "B", "No preference"],
        label="Which video has better visual quality?"
    )

    next_btn = gr.Button("Submit and continue", visible=False)

    participant_id_state = gr.State()
    remaining_pairs_state = gr.State([])
    current_pair_state = gr.State()

    start_btn.click(
        fn=start_session,
        outputs=[
            prompt_md,
            video_A,
            video_B,
            participant_label,
            participant_id_state,
            remaining_pairs_state,
            current_pair_state,
            q_adherence,
            q_logic,
            q_visual,
            status,
            start_btn,
            next_btn,
        ]
    )

    next_btn.click(
        fn=submit_and_next,
        inputs=[
            q_adherence,
            q_logic,
            q_visual,
            participant_id_state,
            remaining_pairs_state,
            current_pair_state,
        ],
        outputs=[
            prompt_md,
            video_A,
            video_B,
            remaining_pairs_state,
            current_pair_state,
            status,
        ]
    ).then(
        lambda: (None, None, None),
        outputs=[q_adherence, q_logic, q_visual]
    )

demo.launch()