Delete app.py

app.py

@@ -1,1181 +0,0 @@
-import os
-import re
-import time
-import sqlite3
-import hashlib
-import secrets
-from datetime import date
-
-import gradio as gr
-import torch
-
-from transformers import AutoTokenizer
-from peft import AutoPeftModelForCausalLM
-
-
-# ============================================================
-# CONFIG
-# ============================================================
-
-MODEL_PATH = "."
-
-DB_PATH = "users.db"
-
-FREE_DAILY_LIMIT = 10
-PRO_DAILY_LIMIT = 1000
-
-ADMIN_EMAIL = os.getenv(
-    "ADMIN_EMAIL",
-    "admin@example.com"
-)
-
-ADMIN_PASSWORD = os.getenv(
-    "ADMIN_PASSWORD",
-    "CHANGE_THIS_PASSWORD"
-)
-
-
-# ============================================================
-# DATABASE
-# ============================================================
-
-def db():
-    conn = sqlite3.connect(
-        DB_PATH,
-        check_same_thread=False
-    )
-    conn.row_factory = sqlite3.Row
-    return conn
-
-
-def init_db():
-
-    conn = db()
-
-    conn.execute("""
-        CREATE TABLE IF NOT EXISTS users (
-            id INTEGER PRIMARY KEY AUTOINCREMENT,
-            email TEXT UNIQUE NOT NULL,
-            password_hash TEXT NOT NULL,
-            salt TEXT NOT NULL,
-            plan TEXT DEFAULT 'free',
-            active INTEGER DEFAULT 1,
-            daily_usage INTEGER DEFAULT 0,
-            usage_date TEXT,
-            created_at TEXT DEFAULT CURRENT_TIMESTAMP
-        )
-    """)
-
-    conn.commit()
-
-    existing = conn.execute(
-        "SELECT id FROM users WHERE email = ?",
-        (ADMIN_EMAIL.lower().strip(),)
-    ).fetchone()
-
-    if not existing:
-
-        password_hash, salt = hash_password(
-            ADMIN_PASSWORD
-        )
-
-        conn.execute("""
-            INSERT INTO users
-            (email, password_hash, salt, plan, active)
-            VALUES (?, ?, ?, 'admin', 1)
-        """, (
-            ADMIN_EMAIL.lower().strip(),
-            password_hash,
-            salt
-        ))
-
-        conn.commit()
-
-    conn.close()
-
-
-# ============================================================
-# PASSWORD
-# ============================================================
-
-def hash_password(password, salt=None):
-
-    if salt is None:
-        salt = secrets.token_hex(16)
-
-    password_hash = hashlib.pbkdf2_hmac(
-        "sha256",
-        password.encode("utf-8"),
-        salt.encode("utf-8"),
-        200_000
-    ).hex()
-
-    return password_hash, salt
-
-
-def verify_password(
-    password,
-    stored_hash,
-    salt
-):
-
-    calculated, _ = hash_password(
-        password,
-        salt
-    )
-
-    return secrets.compare_digest(
-        calculated,
-        stored_hash
-    )
-
-
-# ============================================================
-# USERS
-# ============================================================
-
-def get_user(email):
-
-    conn = db()
-
-    user = conn.execute(
-        "SELECT * FROM users WHERE email = ?",
-        (email.lower().strip(),)
-    ).fetchone()
-
-    conn.close()
-
-    return user
-
-
-def create_user(email, password):
-
-    email = email.lower().strip()
-
-    if not re.match(
-        r"^[^@\s]+@[^@\s]+\.[^@\s]+$",
-        email
-    ):
-        return False, "Geçerli bir e-posta adresi gir."
-
-    if len(password) < 8:
-        return False, "Şifre en az 8 karakter olmalı."
-
-    if get_user(email):
-        return False, "Bu e-posta zaten kayıtlı."
-
-    password_hash, salt = hash_password(password)
-
-    conn = db()
-
-    conn.execute("""
-        INSERT INTO users
-        (email, password_hash, salt, plan, active)
-        VALUES (?, ?, ?, 'free', 1)
-    """, (
-        email,
-        password_hash,
-        salt
-    ))
-
-    conn.commit()
-    conn.close()
-
-    return True, "Hesap oluşturuldu."
-
-
-def login_user(email, password):
-
-    user = get_user(email)
-
-    if not user:
-        return None, "E-posta veya şifre hatalı."
-
-    if not verify_password(
-        password,
-        user["password_hash"],
-        user["salt"]
-    ):
-        return None, "E-posta veya şifre hatalı."
-
-    if not user["active"]:
-        return None, "Hesabın pasif durumda."
-
-    today = str(date.today())
-
-    if user["usage_date"] != today:
-
-        conn = db()
-
-        conn.execute("""
-            UPDATE users
-            SET daily_usage = 0,
-                usage_date = ?
-            WHERE id = ?
-        """, (
-            today,
-            user["id"]
-        ))
-
-        conn.commit()
-        conn.close()
-
-        user = get_user(email)
-
-    return user, "Giriş başarılı."
-
-
-# ============================================================
-# LIMIT
-# ============================================================
-
-def get_limit(plan):
-
-    if plan == "admin":
-        return 999999
-
-    if plan == "pro":
-        return PRO_DAILY_LIMIT
-
-    return FREE_DAILY_LIMIT
-
-
-def can_use(user):
-
-    today = str(date.today())
-
-    if user["usage_date"] != today:
-        return True
-
-    return (
-        user["daily_usage"]
-        <
-        get_limit(user["plan"])
-    )
-
-
-def increment_usage(user_id):
-
-    conn = db()
-
-    conn.execute("""
-        UPDATE users
-        SET daily_usage = daily_usage + 1,
-            usage_date = ?
-        WHERE id = ?
-    """, (
-        str(date.today()),
-        user_id
-    ))
-
-    conn.commit()
-    conn.close()
-
-
-# ============================================================
-# MODEL
-# ============================================================
-
-print("Loading model...")
-
-DEVICE = (
-    "cuda"
-    if torch.cuda.is_available()
-    else "cpu"
-)
-
-print("Device:", DEVICE)
-
-adapter_file = os.path.join(
-    MODEL_PATH,
-    "adapter_model.safetensors"
-)
-
-if not os.path.exists(adapter_file):
-
-    raise RuntimeError(
-        "adapter_model.safetensors bulunamadı. "
-        "PEFT adapter ağırlığını Space'e yükle."
-    )
-
-
-tokenizer = AutoTokenizer.from_pretrained(
-    MODEL_PATH
-)
-
-model = AutoPeftModelForCausalLM.from_pretrained(
-    MODEL_PATH,
-    dtype=(
-        torch.float16
-        if DEVICE == "cuda"
-        else torch.float32
-    )
-)
-
-model.to(DEVICE)
-model.eval()
-
-print("Model loaded.")
-
-
-# ============================================================
-# CRYPTO ASSET DETECTION
-# ============================================================
-
-KNOWN_ASSETS = {
-
-    "BTC": [
-        "bitcoin",
-        "btc"
-    ],
-
-    "ETH": [
-        "ethereum",
-        "eth"
-    ],
-
-    "SOL": [
-        "solana",
-        "sol"
-    ],
-
-    "BNB": [
-        "binance coin",
-        "bnb"
-    ],
-
-    "XRP": [
-        "ripple",
-        "xrp"
-    ],
-
-    "ADA": [
-        "cardano",
-        "ada"
-    ],
-
-    "DOGE": [
-        "dogecoin",
-        "doge"
-    ],
-
-    "AVAX": [
-        "avalanche",
-        "avax"
-    ],
-
-    "LINK": [
-        "chainlink",
-        "link"
-    ],
-
-    "DOT": [
-        "polkadot",
-        "dot"
-    ]
-}
-
-
-def detect_assets(text):
-
-    lower = text.lower()
-
-    detected = []
-
-    for symbol, names in KNOWN_ASSETS.items():
-
-        for name in names:
-
-            pattern = (
-                r"(?<![a-z])"
-                + re.escape(name)
-                + r"(?![a-z])"
-            )
-
-            if re.search(pattern, lower):
-
-                detected.append(symbol)
-                break
-
-    return detected
-
-
-# ============================================================
-# SENTIMENT EXTRACTION
-# ============================================================
-
-def extract_sentiment(text):
-
-    lower = text.lower()
-
-    # Strong explicit labels
-    if re.search(
-        r"\bbullish\b|\bpositive\b",
-        lower
-    ):
-        return "Bullish"
-
-    if re.search(
-        r"\bbearish\b|\bnegative\b",
-        lower
-    ):
-        return "Bearish"
-
-    if re.search(
-        r"\bneutral\b|\bsideways\b",
-        lower
-    ):
-        return "Neutral"
-
-    # Keyword fallback
-    bullish_words = [
-        "rise",
-        "rising",
-        "surge",
-        "surging",
-        "gain",
-        "gains",
-        "growth",
-        "breakout",
-        "bull",
-        "buy",
-        "buying",
-        "inflow",
-        "inflows",
-        "adoption",
-        "strong",
-        "record high",
-        "higher"
-    ]
-
-    bearish_words = [
-        "fall",
-        "falling",
-        "drop",
-        "dropping",
-        "crash",
-        "loss",
-        "losses",
-        "sell",
-        "selling",
-        "outflow",
-        "outflows",
-        "bear",
-        "resistance",
-        "hack",
-        "liquidation",
-        "lower",
-        "weak"
-    ]
-
-    bullish_score = sum(
-        word in lower
-        for word in bullish_words
-    )
-
-    bearish_score = sum(
-        word in lower
-        for word in bearish_words
-    )
-
-    if bullish_score > bearish_score:
-        return "Bullish"
-
-    if bearish_score > bullish_score:
-        return "Bearish"
-
-    return "Neutral"
-
-
-# ============================================================
-# SENTIMENT SCORE
-# ============================================================
-
-def sentiment_score(
-    sentiment,
-    text
-):
-
-    lower = text.lower()
-
-    bullish_words = [
-        "surge",
-        "breakout",
-        "bullish",
-        "strong",
-        "inflow",
-        "growth",
-        "rally",
-        "higher",
-        "buy"
-    ]
-
-    bearish_words = [
-        "crash",
-        "bearish",
-        "weak",
-        "outflow",
-        "liquidation",
-        "hack",
-        "lower",
-        "sell"
-    ]
-
-    bull = sum(
-        x in lower
-        for x in bullish_words
-    )
-
-    bear = sum(
-        x in lower
-        for x in bearish_words
-    )
-
-    raw = bull - bear
-
-    if sentiment == "Bullish":
-        raw += 1
-
-    elif sentiment == "Bearish":
-        raw -= 1
-
-    score = max(
-        -1,
-        min(
-            1,
-            raw / 5
-        )
-    )
-
-    return score
-
-
-# ============================================================
-# STRENGTH
-# ============================================================
-
-def get_strength(score):
-
-    absolute = abs(score)
-
-    if absolute >= 0.70:
-        return "STRONG"
-
-    if absolute >= 0.35:
-        return "MODERATE"
-
-    return "WEAK"
-
-
-# ============================================================
-# RISK
-# ============================================================
-
-def get_risk(
-    text,
-    score
-):
-
-    lower = text.lower()
-
-    high_risk_words = [
-        "hack",
-        "exploit",
-        "crash",
-        "liquidation",
-        "lawsuit",
-        "ban",
-        "bankruptcy",
-        "rug"
-    ]
-
-    medium_risk_words = [
-        "volatility",
-        "resistance",
-        "uncertain",
-        "uncertainty",
-        "regulation"
-    ]
-
-    if any(
-        word in lower
-        for word in high_risk_words
-    ):
-        return "HIGH"
-
-    if any(
-        word in lower
-        for word in medium_risk_words
-    ):
-        return "MEDIUM"
-
-    if abs(score) > 0.7:
-        return "MEDIUM"
-
-    return "LOW"
-
-
-# ============================================================
-# MARKET IMPACT
-# ============================================================
-
-def get_market_impact(
-    sentiment,
-    score
-):
-
-    if abs(score) >= 0.70:
-        strength = "High"
-
-    elif abs(score) >= 0.35:
-        strength = "Moderate"
-
-    else:
-        strength = "Low"
-
-    if sentiment == "Bullish":
-        return f"Positive ({strength})"
-
-    if sentiment == "Bearish":
-        return f"Negative ({strength})"
-
-    return f"Neutral ({strength})"
-
-
-# ============================================================
-# SIGNAL BAR
-# ============================================================
-
-def bar(value):
-
-    value = max(
-        0,
-        min(
-            100,
-            int(value)
-        )
-    )
-
-    filled = int(
-        value / 5
-    )
-
-    return (
-        "█" * filled
-        +
-        "░" * (20 - filled)
-    )
-
-
-# ============================================================
-# DETAILED ANALYSIS
-# ============================================================
-
-def analyze_crypto(
-    text,
-    user
-):
-
-    start = time.perf_counter()
-
-    if not text or not text.strip():
-
-        return "Lütfen analiz edilecek metni gir."
-
-    if user is None:
-
-        return "Önce giriş yapmalısın."
-
-    current_user = get_user(
-        user["email"]
-    )
-
-    if not current_user:
-
-        return "Oturum bulunamadı."
-
-    if not current_user["active"]:
-
-        return "Hesabın aktif değil."
-
-    if not can_use(current_user):
-
-        limit = get_limit(
-            current_user["plan"]
-        )
-
-        return (
-            f"## ⚠️ Günlük Limit Doldu\n\n"
-            f"**Plan:** "
-            f"{current_user['plan'].upper()}\n\n"
-            f"**Limit:** {limit} analiz/gün"
-        )
-
-
-    # --------------------------------------------------------
-    # MODEL
-    # --------------------------------------------------------
-
-    prompt = f"""
-You are a cryptocurrency sentiment analysis model.
-
-Analyze the following crypto market text.
-
-Classify the sentiment as exactly one:
-Bullish
-Neutral
-Bearish
-
-Return the sentiment label clearly.
-
-Text:
-{text}
-
-Sentiment:
-"""
-
-
-    inputs = tokenizer(
-        prompt,
-        return_tensors="pt",
-        truncation=True,
-        max_length=512
-    )
-
-    inputs = {
-        k: v.to(DEVICE)
-        for k, v in inputs.items()
-    }
-
-
-    with torch.no_grad():
-
-        output = model.generate(
-            **inputs,
-            max_new_tokens=20,
-            do_sample=False
-        )
-
-
-    generated = output[
-        0
-    ][
-        inputs["input_ids"].shape[1]:
-    ]
-
-
-    raw_result = tokenizer.decode(
-        generated,
-        skip_special_tokens=True
-    ).strip()
-
-
-    # --------------------------------------------------------
-    # ANALYSIS
-    # --------------------------------------------------------
-
-    sentiment = extract_sentiment(
-        raw_result
-        +
-        " "
-        +
-        text
-    )
-
-    score = sentiment_score(
-        sentiment,
-        text
-    )
-
-    strength = get_strength(
-        score
-    )
-
-    risk = get_risk(
-        text,
-        score
-    )
-
-    impact = get_market_impact(
-        sentiment,
-        score
-    )
-
-    assets = detect_assets(
-        text
-    )
-
-
-    # --------------------------------------------------------
-    # DISPLAY SCORES
-    # --------------------------------------------------------
-
-    if sentiment == "Bullish":
-
-        bullish = 70 + abs(score) * 25
-        bearish = 10
-        neutral = 100 - bullish - bearish
-
-    elif sentiment == "Bearish":
-
-        bearish = 70 + abs(score) * 25
-        bullish = 10
-        neutral = 100 - bearish - bullish
-
-    else:
-
-        neutral = 60 + (1 - abs(score)) * 20
-        bullish = (100 - neutral) / 2
-        bearish = bullish
-
-
-    bullish = max(
-        0,
-        min(
-            100,
-            bullish
-        )
-    )
-
-    bearish = max(
-        0,
-        min(
-            100,
-            bearish
-        )
-    )
-
-    neutral = max(
-        0,
-        100 - bullish - bearish
-    )
-
-
-    # --------------------------------------------------------
-    # DIRECTION ICON
-    # --------------------------------------------------------
-
-    if sentiment == "Bullish":
-        icon = "🟢"
-
-    elif sentiment == "Bearish":
-        icon = "🔴"
-
-    else:
-        icon = "🟡"
-
-
-    elapsed = (
-        time.perf_counter()
-        - start
-    )
-
-
-    # --------------------------------------------------------
-    # USAGE
-    # --------------------------------------------------------
-
-    increment_usage(
-        current_user["id"]
-    )
-
-    new_user = get_user(
-        current_user["email"]
-    )
-
-
-    # --------------------------------------------------------
-    # ASSET TEXT
-    # --------------------------------------------------------
-
-    asset_text = (
-        ", ".join(assets)
-        if assets
-        else "Belirlenmedi"
-    )
-
-
-    # --------------------------------------------------------
-    # SCORE TEXT
-    # --------------------------------------------------------
-
-    score_text = (
-        f"{score:+.2f}"
-    )
-
-
-    # --------------------------------------------------------
-    # FINAL REPORT
-    # --------------------------------------------------------
-
-    report = f"""
-# {icon} CRYPTO SENTIMENT ANALYSIS
-
-## Genel Sinyal
-
-### **{sentiment.upper()}**
-
-| Metrik | Sonuç |
-|---|---|
-| **Sentiment** | {sentiment} |
-| **Sentiment Score** | `{score_text}` |
-| **Signal Strength** | **{strength}** |
-| **Market Impact** | **{impact}** |
-| **Risk Level** | **{risk}** |
-| **Detected Asset** | **{asset_text}** |
-
----
-
-## 📊 Sentiment Distribution
-
-### 🟢 Bullish — **{bullish:.1f}%**
-
-`{bar(bullish)}`
-
-### 🟡 Neutral — **{neutral:.1f}%**
-
-`{bar(neutral)}`
-
-### 🔴 Bearish — **{bearish:.1f}%**
-
-`{bar(bearish)}`
-
-> **Not:** Bu yüzdeler mevcut generative modelin gerçek
-> softmax sınıf olasılıkları değildir; model çıktısı ve metin
-> sinyallerinden oluşturulan yaklaşık dağılımdır.
-
----
-
-## 🎯 Signal Interpretation
-
-**Direction:** `{sentiment}`
-
-**Strength:** `{strength}`
-
-**Risk:** `{risk}`
-
-**Market Impact:** `{impact}`
-
----
-
-## 🪙 Asset Detection
-
-Detected assets:
-
-**{asset_text}**
-
----
-
-## 🤖 Model Output
-
-```text
-{raw_result if raw_result else "No explicit label returned."}
-
-``` 
-
-"""
-    # Keep the report as the function result.
-    return report
-
-
-# ============================================================
-# AUTHENTICATION / UI
-# ============================================================
-
-def signup_action(email, password):
-    ok, message = create_user(email, password)
-    return message
-
-
-def login_action(email, password):
-    user, message = login_user(email, password)
-    if user is None:
-        return None, f"❌ {message}"
-    return dict(user), f"✅ {message} — {user['email']} ({user['plan'].upper()})"
-
-
-def logout_action():
-    return None, "Çıkış yapıldı."
-
-
-def user_info(user):
-    if not user:
-        return "Giriş yapılmadı."
-    current = get_user(user["email"])
-    if not current:
-        return "Oturum bulunamadı."
-    limit = get_limit(current["plan"])
-    usage = current["daily_usage"] if current["usage_date"] == str(date.today()) else 0
-    return (
-        f"**{current['email']}**  \\n"
-        f"Plan: **{current['plan'].upper()}**  \\n"
-        f"Günlük kullanım: **{usage}/{limit}**"
-    )
-
-
-def admin_users_action(user):
-    if not user or user.get("plan") != "admin":
-        return "❌ Admin yetkisi gerekli."
-    conn = db()
-    rows = conn.execute(
-        "SELECT id, email, plan, active, daily_usage, usage_date, created_at FROM users ORDER BY id"
-    ).fetchall()
-    conn.close()
-    if not rows:
-        return "Kullanıcı yok."
-    lines = ["| ID | Email | Plan | Active | Usage | Date |", "|---:|---|---|---:|---:|---|"]
-    for r in rows:
-        lines.append(
-            f"| {r['id']} | {r['email']} | {r['plan']} | {r['active']} | {r['daily_usage']} | {r['usage_date'] or '-'} |"
-        )
-    return "\\n".join(lines)
-
-
-def admin_change_plan(user, email, plan):
-    if not user or user.get("plan") != "admin":
-        return "❌ Admin yetkisi gerekli."
-    plan = (plan or "").lower().strip()
-    if plan not in {"free", "pro", "admin"}:
-        return "❌ Plan free, pro veya admin olmalı."
-    target = get_user(email)
-    if not target:
-        return "❌ Kullanıcı bulunamadı."
-    conn = db()
-    conn.execute("UPDATE users SET plan = ? WHERE id = ?", (plan, target["id"]))
-    conn.commit()
-    conn.close()
-    return f"✅ {email} → {plan}"
-
-
-def admin_set_active(user, email, active):
-    if not user or user.get("plan") != "admin":
-        return "❌ Admin yetkisi gerekli."
-    target = get_user(email)
-    if not target:
-        return "❌ Kullanıcı bulunamadı."
-    conn = db()
-    conn.execute("UPDATE users SET active = ? WHERE id = ?", (1 if active else 0, target["id"]))
-    conn.commit()
-    conn.close()
-    return f"✅ {email} → {'aktif' if active else 'pasif'}"
-
-
-def admin_delete(user, email):
-    if not user or user.get("plan") != "admin":
-        return "❌ Admin yetkisi gerekli."
-    email = (email or "").lower().strip()
-    if email == ADMIN_EMAIL.lower().strip():
-        return "❌ Ana admin hesabı silinemez."
-    target = get_user(email)
-    if not target:
-        return "❌ Kullanıcı bulunamadı."
-    conn = db()
-    conn.execute("DELETE FROM users WHERE id = ?", (target["id"],))
-    conn.commit()
-    conn.close()
-    return f"✅ {email} silindi."
-
-
-# Initialize database before serving the UI.
-init_db()
-
-with gr.Blocks(title="Crypto Sentiment AI") as demo:
-    session = gr.State(None)
-
-    gr.Markdown("# 🧠 Crypto Sentiment AI")
-    gr.Markdown("Kripto metinlerini analiz et ve model tabanlı sentiment sinyalini görüntüle.")
-
-    with gr.Tab("🔐 Hesap"):
-        with gr.Row():
-            with gr.Column():
-                gr.Markdown("### Giriş")
-                login_email = gr.Textbox(label="E-posta")
-                login_password = gr.Textbox(label="Şifre", type="password")
-                login_btn = gr.Button("Giriş Yap", variant="primary")
-                logout_btn = gr.Button("Çıkış Yap")
-            with gr.Column():
-                gr.Markdown("### Kayıt")
-                signup_email = gr.Textbox(label="E-posta")
-                signup_password = gr.Textbox(label="Şifre", type="password")
-                signup_btn = gr.Button("Hesap Oluştur")
-
-        auth_status = gr.Markdown("Giriş yapılmadı.")
-        account_info = gr.Markdown("Giriş yapılmadı.")
-
-        login_btn.click(
-            login_action,
-            inputs=[login_email, login_password],
-            outputs=[session, auth_status],
-        ).then(user_info, inputs=session, outputs=account_info)
-
-        logout_btn.click(
-            logout_action,
-            outputs=[session, auth_status],
-        ).then(user_info, inputs=session, outputs=account_info)
-
-        signup_btn.click(
-            signup_action,
-            inputs=[signup_email, signup_password],
-            outputs=auth_status,
-        )
-
-    with gr.Tab("📊 Sentiment Analysis"):
-        analysis_text = gr.Textbox(
-            label="Crypto market text",
-            placeholder="Örn: Bitcoin breaks resistance as institutional inflows increase...",
-            lines=8,
-        )
-        analyze_btn = gr.Button("🔎 Analiz Et", variant="primary")
-        report_output = gr.Markdown()
-        analyze_btn.click(
-            analyze_crypto,
-            inputs=[analysis_text, session],
-            outputs=report_output,
-        )
-
-    with gr.Tab("👑 Admin"):
-        gr.Markdown("Admin işlemleri yalnızca admin planındaki oturumla çalışır.")
-        refresh_btn = gr.Button("Kullanıcıları Yenile")
-        users_output = gr.Markdown()
-        refresh_btn.click(admin_users_action, inputs=session, outputs=users_output)
-
-        with gr.Row():
-            admin_email_input = gr.Textbox(label="Hedef e-posta")
-            admin_plan = gr.Dropdown(["free", "pro", "admin"], value="free", label="Yeni plan")
-        change_plan_btn = gr.Button("Planı Değiştir")
-        activate_btn = gr.Button("Aktif Et")
-        deactivate_btn = gr.Button("Pasif Et")
-        delete_btn = gr.Button("Kullanıcıyı Sil")
-        admin_status = gr.Markdown()
-
-        change_plan_btn.click(
-            admin_change_plan,
-            inputs=[session, admin_email_input, admin_plan],
-            outputs=admin_status,
-        ).then(admin_users_action, inputs=session, outputs=users_output)
-
-        activate_btn.click(
-            admin_set_active,
-            inputs=[session, admin_email_input, gr.State(True)],
-            outputs=admin_status,
-        ).then(admin_users_action, inputs=session, outputs=users_output)
-
-        deactivate_btn.click(
-            admin_set_active,
-            inputs=[session, admin_email_input, gr.State(False)],
-            outputs=admin_status,
-        ).then(admin_users_action, inputs=session, outputs=users_output)
-
-        delete_btn.click(
-            admin_delete,
-            inputs=[session, admin_email_input],
-            outputs=admin_status,
-        ).then(admin_users_action, inputs=session, outputs=users_output)
-
-    gr.Markdown(
-        "⚠️ Sentiment dağılımı mevcut generative PEFT modelinden gerçek softmax sınıf olasılığı değildir."
-    )
-
-
-if __name__ == "__main__":
-    demo.launch()