app.py

# app.py – Prüfungsrechts-Chatbot (RAG + Sprachmodus)
# Version 26.11 – ohne Modi, stabil für Text + Voice

import gradio as gr
from gradio_pdf import PDF
from huggingface_hub import hf_hub_download

from load_documents import load_documents, DATASET, PDF_FILE, HTML_FILE
from split_documents import split_documents
from vectorstore import build_vectorstore
from retriever import get_retriever
from llm import load_llm
from rag_pipeline import answer, PDF_BASE_URL, LAW_URL

from speech_io import transcribe_audio, synthesize_speech

# =====================================================
# INITIALISIERUNG (global)
# =====================================================

print("🔹 Lade Dokumente ...")
_docs = load_documents()

print("🔹 Splitte Dokumente ...")
_chunks = split_documents(_docs)

print("🔹 Baue VectorStore (FAISS) ...")
_vs = build_vectorstore(_chunks)

print("🔹 Erzeuge Retriever ...")
_retriever = get_retriever(_vs)

print("🔹 Lade LLM ...")
_llm = load_llm()

print("🔹 Lade Dateien für Viewer …")
_pdf_path = hf_hub_download(DATASET, PDF_FILE, repo_type="dataset")
_html_path = hf_hub_download(DATASET, HTML_FILE, repo_type="dataset")

# =====================================================
# Quellen formatieren – Markdown für Chat
# =====================================================

def format_sources_markdown(sources):
    if not sources:
        return ""

    lines = ["", "**📚 Quellen (genutzte Dokumentstellen):**"]
    for s in sources:
        sid = s["id"]
        src = s["source"]
        page = s["page"]
        url = s["url"]
        snippet = s["snippet"]

        title = f"Quelle {sid} – {src}"

        if url:
            base = f"- [{title}]({url})"
        else:
            base = f"- {title}"

        if page and "Prüfungsordnung" in src:
            base += f", Seite {page}"

        lines.append(base)

        if snippet:
            lines.append(f"  > {snippet}")

    return "\n".join(lines)

# =====================================================
# TEXT CHATBOT
# =====================================================

def chatbot_text(user_message, history):
    if not user_message:
        return history, ""

    answer_text, sources = answer(
        question=user_message,
        retriever=_retriever,
        chat_model=_llm,
    )

    quellen_block = format_sources_markdown(sources)

    history = history + [
        {"role": "user", "content": user_message},
        {"role": "assistant", "content": answer_text + quellen_block},
    ]

    return history, ""

# =====================================================
# VOICE CHATBOT
# =====================================================

def chatbot_voice(audio_path, history):
    # 1. Speech → Text
    text = transcribe_audio(audio_path)
    if not text:
        return history, None, ""

    # Lưu vào lịch sử chat
    history = history + [{"role": "user", "content": text}]

    # 2. RAG trả lời
    answer_text, sources = answer(
        question=text,
        retriever=_retriever,
        chat_model=_llm,
    )
    quellen_block = format_sources_markdown(sources)

    bot_msg = answer_text + quellen_block
    history = history + [{"role": "assistant", "content": bot_msg}]

    # 3. Text → Speech
    audio = synthesize_speech(bot_msg)

    return history, audio, ""

# =====================================================
# LAST ANSWER → TTS
# =====================================================

def read_last_answer(history):
    if not history:
        return None

    for msg in reversed(history):
        if msg["role"] == "assistant":
            return synthesize_speech(msg["content"])

    return None

# =====================================================
# UI – GRADIO
# =====================================================

with gr.Blocks(title="Prüfungsrechts-Chatbot (RAG + Sprache)") as demo:
    gr.Markdown("# 🧑‍⚖️ Prüfungsrechts-Chatbot")
    gr.Markdown(
        "Dieser Chatbot beantwortet Fragen **ausschließlich** aus der "
        "Prüfungsordnung (PDF) und dem Hochschulgesetz NRW (Website). "
        "Du kannst Text eingeben oder direkt ins Mikrofon sprechen."
    )

    with gr.Row():
        with gr.Column(scale=2):
            chatbot = gr.Chatbot(label="Chat", height=500)

            msg = gr.Textbox(
                label="Frage eingeben",
                placeholder="Stelle deine Frage zum Prüfungsrecht …",
            )

            # TEXT SENDEN
            msg.submit(
                chatbot_text,
                [msg, chatbot],
                [chatbot, msg]
            )

            send_btn = gr.Button("Senden (Text)")
            send_btn.click(
                chatbot_text,
                [msg, chatbot],
                [chatbot, msg]
            )

            # SPRACHEINGABE
            gr.Markdown("### 🎙️ Spracheingabe")
            voice_in = gr.Audio(sources=["microphone"], type="filepath")
            voice_out = gr.Audio(label="Vorgelesene Antwort", type="numpy")

            voice_btn = gr.Button("Sprechen & senden")
            voice_btn.click(
                chatbot_voice,
                [voice_in, chatbot],
                [chatbot, voice_out, msg]
            )

            read_btn = gr.Button("🔁 Antwort erneut vorlesen")
            read_btn.click(
                read_last_answer,
                [chatbot],
                [voice_out]
            )

            clear_btn = gr.Button("Chat zurücksetzen")
            clear_btn.click(lambda: [], None, chatbot)

        # =====================
        # RECHTE SPALTE: Viewer
        # =====================

        with gr.Column(scale=1):
            gr.Markdown("### 📄 Prüfungsordnung (PDF)")
            PDF(_pdf_path, height=350)

            gr.Markdown("### 📘 Hochschulgesetz NRW (Website)")
            gr.HTML(
                f'<iframe src="{LAW_URL}" style="width:100%;height:350px;border:none;"></iframe>'
            )

if __name__ == "__main__":
    demo.launch()