import gradio as gr
import cohere
import os
from dotenv import load_dotenv
from email.mime.text import MIMEText
import json
from huggingface_hub import list_models

from qdrant_client.models import Distance, VectorParams
from qdrant_client import QdrantClient, models
import uuid
import base64
import requests

load_dotenv(verbose=True)

# Initialize Qdrant and Cohere clients
client = QdrantClient(url=os.environ.get("QDRANT_URL"), api_key=os.environ.get("QDRANT_API_KEY"))
cohere_client = cohere.Client(api_key=os.environ.get("COHERE_API_KEY"))
co = cohere.ClientV2(api_key=os.environ.get("COHERE_API_KEY"))


'''# OAuthProfile example
class OAuthProfile:
    def __init__(self, name, username, profile, picture):
        self.name = name
        self.username = username
        self.profile = profile
        self.picture = picture

oauth_profile = OAuthProfile(
    name="",
    username="",
    profile="",
    picture=""
)'''


def greeting(profile: gr.OAuthProfile | None) -> str:
    if profile is None:
        return "⛔️"
    else:
        print("profile:",profile)
        state.value["loginuser"] = profile.name
        return f"ようこそ！ {profile.name}さん"
    #if profile is None:
        #return "⛔️"
    #return f"ようこそ！ {profile.name}さん"



def list_private_models(profile: gr.OAuthProfile | None, oauth_token: gr.OAuthToken | None) -> tuple[str, gr.update, gr.update]:
    gr.Textbox(oauth_token)
    if oauth_token is None:
        state.value["loginuser"] = "HuggingFaceにログインしてください。"
        state.value["picture"] = ""
        return "HuggingFaceにログインしてください。", gr.update(visible=False), gr.update(visible=False)   #, gr.update(visible=False)
    #models = [
        #f"{model.id} ({'private' if model.private else 'public'})"
        #for model in list_models(author=profile.username, token=oauth_token.token)
    #]
    userinfo = f"""名前: {profile.name}さん\nID: {profile.username}\nプロファイル: {profile.profile}"""
    print("userinfo:",userinfo)
    state.value["loginuser"] = userinfo
    state.value["picture"] = profile.picture

    print("pic:",state.value["picture"],profile.picture)
    print("login-user:",state.value["loginuser"],userinfo)

    '''global oauth_profile
    oauth_profile = OAuthProfile(
    name=profile.name,
    username=profile.username,
    profile=profile.profile,
    picture=profile.picture
    )'''
    
    #return profile.username, gr.update(visible=True), gr.update(visible=True) #, gr.update(visible=True)
    return userinfo, gr.update(visible=True), gr.update(visible=True) #, gr.update(visible=True)

def user_info(state):
    print("state:", state)
    uinfo = f"""情報: {state["loginuser"]}"""
    gr.Info(uinfo)
    #gr.Info("情報: Created by RYH International.")
    
    return gr.update(visible=True)

def auth(user_name, password):
    encoded = base64.b64encode(password.encode("utf-8"))

    # APIエンドポイントのURL
    url = "https://www.ryhintl.com/dbjson/getjson?sqlcmd=select userid from ku_credential where password = '" + encoded.decode("utf-8") + "'"

    # GETリクエストの例
    response = requests.get(url)
    if response.status_code == 200:
        credential_id = response.content.decode('utf-8')
        parsed_data = json.loads(credential_id)

        # useridを取得
        taken_userid = parsed_data[0]["userid"]
        if (taken_userid == user_name):
            state.value["loginuser"] = user_name
            return True # 認証成功
        else:
            return False

def process_invitees(state,input_json):
    try:
        # Parse the JSON input
        invitees = json.loads(input_json)

        # Generate embeddings using Cohere
        response = cohere_client.embed(
            texts=[
                f"{note.get('kx_subject', '')}, {note.get('kx_creator', '')}, {note.get('kx_content', '')}, {note.get('kx_industry', '')}, {note.get('kx_kind', '')}, {note.get('kx_category', '')}, {note.get('kx_date', '')}"
                for note in invitees
            ],
            model="embed-multilingual-v3.0",
            input_type="search_document",
        )

        # Upload points to Qdrant
        client.upload_points(
            collection_name="knowledge_utility",
            points=[
                models.PointStruct(
                    id=uuid.uuid4().hex,
                    vector=embedding,
                    payload=note,
                )
                for note, embedding in zip(invitees, response.embeddings)
            ]
        )

        return "Data uploaded successfully!"

    except Exception as e:
        return f"Error: {str(e)}"

# Function to send Gmail
def send_gmail(mail_from, mail_to, mail_subject, mail_body):
    try:
        sent_mails = f"From: {mail_from}\nTo: {mail_to}\nSubject: {mail_subject}\nBody:\n{mail_body}\n"
    except Exception as e:
        sent_mails = f"Error sending mail: {str(e)}"
    return sent_mails

# Function to handle search query
def search(state,query: str):
    #state["userid"] = "kuuser"
    
    global sent_mails
    # Embed query using Cohere
    response = cohere_client.embed(
        texts=[query],
        model="embed-multilingual-v3.0",
        input_type="search_query",
    )
    
    # Query Qdrant collection for relevant points
    results = client.query_points(
        collection_name="knowledge_utility",
        query=response.embeddings[0],
        limit=1,
    ).points

    for result in results:
        state["score"] = result.score
        
    # Filter points based on similarity threshold
    similarity_threshold = 0.1  # Example threshold for filtering
    filtered_points = [point for point in results if point.score >= similarity_threshold]

    #print("filtered_points:",filtered_points)

    # Apply limit to the filtered points
    final_limit = len(filtered_points)  # Example limit
    limited_points = filtered_points[:final_limit]
    #print("finals:",final_limit,limited_points)

    # Assuming `results` is a list of ScoredPoint objects
    payload_list = []

    # Iterate through the limited results and extract payloads
    for point in limited_points:
        # Access the payload attribute and append it to the list
        #print("point:",point)
        payload_list.append(point.payload)
    
    #print("payload_list:",payload_list)

    # Template for the invitation letter
    template = ""

    # Prepare results in a user-friendly format
    formatted_results = [
        f"kx_subject: {point.payload['kx_subject']}\nkx_content: {point.payload['kx_content']}\nkx_creator: {point.payload['kx_creator']}\nkx_industry: {point.payload['kx_industry']}\nkx_kind: {point.payload['kx_kind']}\nkx_category: {point.payload['kx_category']}\nkx_date: {point.payload['kx_date']}"
        for point in results
    ]

    #print("formatted_results",formatted_results)
    final_result = "\n\n".join(formatted_results)

    res = co.chat(
    model="command-a-03-2025",
    messages=[
        {
            "role": "user",
            "content": final_result+"を要約してください。 必ず、日本語で答えてください。",
        }
    ],
    )
    final = res.message.content[0].text

    # Extract content between "---"
    start_marker = "---"
    end_marker = "---"
    start_index = final.find(start_marker) + len(start_marker)
    end_index = final.rfind(end_marker)

    return final,state["score"]

# Gradio Blocks Interface
with gr.Blocks(css="footer {visibility: hidden;} .custom-image {width: 64px; height: 64px;} .custom-btn {width: 150px; height: 30px; background-color: lightblue; border-radius: 10px; font-size: 12px; color: #3C82F6;} #header {display: flex; justify-content: space-between; align-items: center; font-size: 24px; font-weight: bold;} #logo {width: 50px; height: 50px;}",title="Knowledge Utility",theme=gr.themes.Glass()) as ku:
    state = gr.State({
        "userid": "",
        "loginuser": "",
        "picture": "",
        "score": 0
    })
    
    gr.LoginButton()
    # ^ add a login button to the Space
    m1 = gr.Markdown()
    m2 = gr.Markdown()
    ku.load(greeting, inputs=None, outputs=m1)

    with gr.Column():
        gr.HTML('<div id="header"><span>🛡️ Knowledge Utility</span><img id="logo" src="https://www.ryhintl.com/images/ryhlogo/ryhlogo.png" width="64" height="64" alt="Logo"></div>')
        gr.Markdown("# ナレッジ・エージェント")
        gr.Markdown("📧 ベクターDBに保存されている知識ベースのインベントリを使用して知識共有します。")
        

    with gr.Sidebar(open=False):
        #gr.Image(value=oauth_profile.picture, elem_classes=["custom-image"])
        
        gr.HTML("""
        <!DOCTYPE html>
        <html lang="ja">
        <head>
        <meta charset="UTF-8">
        <meta name="viewport" content="width=device-width, initial-scale=1.0">
        <title>Knowledge Utility</title>
        <style>
        body {
            font-family: Arial, sans-serif;
            line-height: 1.6;
            background-color: #f4f4f9;
            color: #333;
            margin: 0;
            padding: 0;
        }
        header {
            background: #0078d7;
            color: #fff;
            padding: 1rem 0;
            text-align: center;
        }
        section {
            max-width: 800px;
            margin: 2rem auto;
            padding: 1rem;
            background: #fff;
            border-radius: 5px;
            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
        }
        h1, h2, h3 {
            color: #0078d7;
        }
        ul {
            padding-left: 1.5rem;
        }
        footer {
            text-align: center;
            padding: 1rem 0;
            margin-top: 2rem;
            background: #0078d7;
            color: white;
        }
        </style>
        </head>
        <body>
        <header>
            <h1 style="color: white;">Knowledge Utility</h1>
            <p style="color: white;">知識をシェアし、成長を加速させる。</p>
        </header>
        <section>
            <h2>Knowledge Utilityとは？</h2>
            <p>
                Knowledge Utilityは、企業や個人が知識を効果的に共有し、成長を促進するためのプラットフォームです。
                データ、アイデア、専門知識をシームレスに交換し、新たな価値を生み出します。
            </p>
        <h2>主な機能</h2>
        <ul>
            <li><strong>情報の検索:</strong> 高速かつ正確なクエリによる知識の取得。</li>
            <li><strong>データの登録:</strong> 個人または企業の資産をデータベースに統合。</li>
            <li><strong>コラボレーション:</strong> チームやコミュニティ間の知識交換を促進。</li>
        </ul>
        <h2>メリット</h2>
        <p>
            Knowledge Utilityを活用することで、効率の向上、意思決定のスピードアップ、そして
            組織の成長が期待できます。
        </p>
        </section>
        <footer>
            <p>&copy; 2025 Knowledge Utility Platform. All rights reserved.</p>
        </footer>
        </body>
        </html>
    """)

        with gr.Blocks(css=".custom-btn-container { display: flex; justify-content: center; } .custom-btn { width: 150px; height: 30px; background-color: lightblue; border-radius: 10px; font-size: 12px; color: #3C82F6; }") as ubutton:
            with gr.Row(elem_classes=["custom-btn-container"]): # 中央揃え用のクラス
                user_btn = gr.Button("情報", elem_classes=["custom-btn"])
                user_btn.click(fn=user_info, inputs=[state], outputs=user_btn)

        #user_btn = gr.Button("情報", elem_classes=["custom-btn"])

    #user_btn.click(fn=user_info, inputs=[state], outputs=None)
        

    with gr.Tab("KU 検索") as tab_find:
        with gr.Row():
            query_input = gr.Textbox(
                label="クエリ",
                placeholder="例）物流・流通業界向けの提案書を内容を教えてください。",
                info="例）物流・流通業界向けの提案書を内容を教えてください。AI市場の動向を調べています。参考できる事例を教えてください。", 
                value="経営デジタル・トランスフォーメーション関連のプロジェクトの提案書を書こうと思っています。参考できる事例を教えてください。",
                lines=2,
            )
            with gr.Column():
                search_button = gr.Button("実行", elem_classes=["custom-btn"])
                clear_button = gr.Button("クリア", elem_classes=["custom-btn"])
    
        result_output = [gr.Textbox(label="結果", show_copy_button=True),gr.Textbox(label="スコア")]

        # Button click events
        search_button.click(fn=search, inputs=[state,query_input], outputs=result_output)
        clear_button.click(lambda: "", None, result_output)

    with gr.Tab("KU インベントリ登録") as tab_reg:
        with gr.Row():
            input_text = gr.Textbox(label="KU JSON Payroll", lines=10, placeholder="Paste your JSON Payroll here...", info="""[{"kx_subject": "中古車販売における現状と問題点", "kx_creator": "username", "kx_content": "事前情報の収集: 顧客動向、問題・課題の想定、3C分析を通じて仮説を策定する。企業動向、顧客動向、競合動向を分析し、仮説を立案する。仮説提案営業の商談フロー: あいさつ、自社紹介、詳細ヒアリング、仮説検証、解決策の提案、ディスカッション、宿題の出し合い、あいさつのステップを踏む。効果的な商談の進め方: 訪問の趣旨を伝え、基本的な質問をし、相手に話させる。仮説をぶつけ、次回の日付と宿題を決める。ヒアリングの技術: 荷主担当者と営業担当者の知識の差を理解し、必要に応じて役割を分担する。ロジスティクスフローを描き、詳細な設問項目を作成する。", "kx_industry": "物流・流通", "kx_kind": "小売", "kx_category": "提案書", "kx_date": "2025/06/02"}]""")
            output_text = gr.Textbox(label="Result")
        with gr.Row():
            submit_button = gr.Button("実行", elem_classes=["custom-btn"])

        submit_button.click(process_invitees, inputs=[state,input_text], outputs=output_text)

# Launch the app
    ku.load(list_private_models, inputs=None, outputs=[m2, tab_find, tab_reg])
ku.launch(favicon_path="favicon.ico",share=True)