Improving CAPTCHA Accessibility in DeepSeek v3

app.py

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+from flask import Flask, render_template, request, redirect, url_for, flash
+import hcaptcha
+
+app = Flask(__name__)
+app.secret_key = 'your_secret_key'
+
+# Configure hCaptcha
+hcaptcha_site_key = 'your_hcaptcha_site_key'
+hcaptcha_secret_key = 'your_hcaptcha_secret_key'
+
+@app.route('/signup', methods=['GET', 'POST'])
+def signup():
+    if request.method == 'POST':
+        hcaptcha_response = request.form['h-captcha-response']
+        if hcaptcha.verify(hcaptcha_secret_key, hcaptcha_response):
+            # Process the sign-up form
+            flash('Sign-up successful!', 'success')
+            return redirect(url_for('login'))
+        else:
+            flash('hCaptcha verification failed. Please try again.', 'danger')
+    return render_template('signup.html', hcaptcha_site_key=hcaptcha_site_key)
+
+@app.route('/login', methods=['GET', 'POST'])
+def login():
+    if request.method == 'POST':
+        hcaptcha_response = request.form['h-captcha-response']
+        if hcaptcha.verify(hcaptcha_secret_key, hcaptcha_response):
+            # Process the login form
+            flash('Login successful!', 'success')
+            return redirect(url_for('dashboard'))
+        else:
+            flash('hCaptcha verification failed. Please try again.', 'danger')
+    return render_template('login.html', hcaptcha_site_key=hcaptcha_site_key)
+
+@app.route('/dashboard')
+def dashboard():
+    return 'Welcome to the dashboard!'
+
+if __name__ == '__main__':
+    app.run(debug=True)

inference/models/__init__.py

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+from .config import ModelArgs
+from .attention import MLA
+from .moe import Gate, Expert, MoE
+from .linear import Linear, ColumnParallelLinear, RowParallelLinear
+
+__all__ = [
+    'ModelArgs',
+    'MLA',
+    'Gate',
+    'Expert', 
+    'MoE',
+    'Linear',
+    'ColumnParallelLinear',
+    'RowParallelLinear'
+]

inference/models/attention.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torch.distributed as dist
+from .config import ModelArgs
+from ..kernel import act_quant, weight_dequant, fp8_gemm
+
+class MLA(nn.Module):
+    def __init__(self, args: ModelArgs):
+        super().__init__()
+        self.dim = args.dim
+        self.n_heads = args.n_heads
+        self.n_local_heads = args.n_heads // dist.get_world_size() if dist.is_initialized() else args.n_heads
+        self.q_lora_rank = args.q_lora_rank
+        self.kv_lora_rank = args.kv_lora_rank
+        self.qk_nope_head_dim = args.qk_nope_head_dim
+        self.qk_rope_head_dim = args.qk_rope_head_dim
+        self.qk_head_dim = args.qk_nope_head_dim + args.qk_rope_head_dim
+        self.v_head_dim = args.v_head_dim
+
+        # Initialize components (implementation from original MLA class)
+        # ... (rest of the MLA implementation)
+
+    def forward(self, x: torch.Tensor, start_pos: int, freqs_cis: torch.Tensor, mask: Optional[torch.Tensor]):
+        # ... (MLA forward implementation)

inference/models/config.py

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+from dataclasses import dataclass
+from typing import Literal
+
+@dataclass
+class ModelArgs:
+    max_batch_size: int = 8
+    max_seq_len: int = 4096 * 4
+    dtype: Literal["bf16", "fp8"] = "bf16"
+    vocab_size: int = 102400
+    dim: int = 2048
+    inter_dim: int = 10944
+    moe_inter_dim: int = 1408
+    n_layers: int = 27
+    n_dense_layers: int = 1
+    n_heads: int = 16
+    # moe
+    n_routed_experts: int = 64
+    n_shared_experts: int = 2
+    n_activated_experts: int = 6
+    n_expert_groups: int = 1
+    n_limited_groups: int = 1
+    score_func: Literal["softmax", "sigmoid"] = "softmax"
+    route_scale: float = 1.
+    # mla
+    q_lora_rank: int = 0
+    kv_lora_rank: int = 512
+    qk_nope_head_dim: int = 128
+    qk_rope_head_dim: int = 64
+    v_head_dim: int = 128
+    # yarn
+    original_seq_len: int = 4096
+    rope_theta: float = 10000.0
+    rope_factor: float = 40
+    beta_fast: int = 32
+    beta_slow: int = 1
+    mscale: float = 1.

inference/models/linear.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torch.distributed as dist
+from ..kernel import act_quant, weight_dequant, fp8_gemm
+
+class Linear(nn.Module):
+    dtype = torch.bfloat16
+
+    def __init__(self, in_features: int, out_features: int, bias: bool = False, dtype = None):
+        # ... (Linear implementation)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # ... (Linear forward implementation)
+
+class ColumnParallelLinear(Linear):
+    def __init__(self, in_features: int, out_features: int, bias: bool = False, dtype = None):
+        # ... (ColumnParallelLinear implementation)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # ... (ColumnParallelLinear forward implementation)
+
+class RowParallelLinear(Linear):
+    def __init__(self, in_features: int, out_features: int, bias: bool = False, dtype = None):
+        # ... (RowParallelLinear implementation)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # ... (RowParallelLinear forward implementation)

inference/models/moe.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torch.distributed as dist
+from .config import ModelArgs
+from .linear import Linear, ColumnParallelLinear, RowParallelLinear
+
+class Gate(nn.Module):
+    def __init__(self, args: ModelArgs):
+        super().__init__()
+        # ... (Gate implementation)
+
+    def forward(self, x: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
+        # ... (Gate forward implementation)
+
+class Expert(nn.Module):
+    def __init__(self, dim: int, inter_dim: int):
+        super().__init__()
+        # ... (Expert implementation)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # ... (Expert forward implementation)
+
+class MoE(nn.Module):
+    def __init__(self, args: ModelArgs):
+        super().__init__()
+        # ... (MoE implementation)
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # ... (MoE forward implementation)

requirements.txt

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+hcaptcha
+flask

static/css/styles.css

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+/* General styles for the form elements */
+body {
+    font-family: Arial, sans-serif;
+    background-color: #f4f4f4;
+    color: #333;
+    margin: 0;
+    padding: 0;
+}
+
+.container {
+    max-width: 500px;
+    margin: 50px auto;
+    padding: 20px;
+    background-color: #fff;
+    box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
+    border-radius: 8px;
+}
+
+h1 {
+    text-align: center;
+    color: #333;
+}
+
+.form-group {
+    margin-bottom: 15px;
+}
+
+label {
+    display: block;
+    margin-bottom: 5px;
+    font-weight: bold;
+}
+
+input[type="text"],
+input[type="email"],
+input[type="password"] {
+    width: 100%;
+    padding: 10px;
+    border: 1px solid #ccc;
+    border-radius: 4px;
+    box-sizing: border-box;
+}
+
+button {
+    width: 100%;
+    padding: 10px;
+    background-color: #007bff;
+    color: #fff;
+    border: none;
+    border-radius: 4px;
+    cursor: pointer;
+    font-size: 16px;
+}
+
+button:hover {
+    background-color: #0056b3;
+}
+
+/* Styles for hCaptcha widget */
+.h-captcha {
+    margin: 20px 0;
+}
+
+/* High contrast and readability for visually impaired users */
+body {
+    background-color: #000;
+    color: #fff;
+}
+
+input[type="text"],
+input[type="email"],
+input[type="password"] {
+    background-color: #333;
+    color: #fff;
+    border: 1px solid #555;
+}
+
+button {
+    background-color: #ffcc00;
+    color: #000;
+}
+
+button:hover {
+    background-color: #e6b800;
+}

templates/login.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Login</title>
+    <link rel="stylesheet" href="{{ url_for('static', filename='css/styles.css') }}">
+</head>
+<body>
+    <div class="container">
+        <h1>Login</h1>
+        <form action="{{ url_for('login') }}" method="POST">
+            <div class="form-group">
+                <label for="username" aria-label="Username">Username</label>
+                <input type="text" id="username" name="username" required aria-required="true">
+            </div>
+            <div class="form-group">
+                <label for="password" aria-label="Password">Password</label>
+                <input type="password" id="password" name="password" required aria-required="true">
+            </div>
+            <div class="form-group">
+                <div class="h-captcha" data-sitekey="{{ hcaptcha_site_key }}" role="presentation" aria-hidden="true"></div>
+            </div>
+            <button type="submit" aria-label="Login">Login</button>
+        </form>
+    </div>
+    <script src="https://hcaptcha.com/1/api.js" async defer></script>
+</body>
+</html>

templates/signup.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Sign Up</title>
+    <link rel="stylesheet" href="{{ url_for('static', filename='css/styles.css') }}">
+</head>
+<body>
+    <div class="container">
+        <h1>Sign Up</h1>
+        <form action="{{ url_for('signup') }}" method="POST">
+            <div class="form-group">
+                <label for="username" aria-label="Username">Username</label>
+                <input type="text" id="username" name="username" required aria-required="true">
+            </div>
+            <div class="form-group">
+                <label for="email" aria-label="Email">Email</label>
+                <input type="email" id="email" name="email" required aria-required="true">
+            </div>
+            <div class="form-group">
+                <label for="password" aria-label="Password">Password</label>
+                <input type="password" id="password" name="password" required aria-required="true">
+            </div>
+            <div class="form-group">
+                <div class="h-captcha" data-sitekey="{{ hcaptcha_site_key }}" role="presentation" aria-hidden="true"></div>
+            </div>
+            <button type="submit" aria-label="Sign Up">Sign Up</button>
+        </form>
+    </div>
+    <script src="https://hcaptcha.com/1/api.js" async defer></script>
+</body>
+</html>