import os import torch import torch.nn as nn from torch.nn import functional as F import customtkinter as ctk from tkinter import filedialog, messagebox import re import threading import time MODEL_DIR = "modele" MODEL_PATH = os.path.join(MODEL_DIR, "genius_ultimate_brain.pt") device = 'cuda' if torch.cuda.is_available() else 'cpu' HEBREW_CHARS = " אבגדהוזחטיכלמנסעפצקרשתםןץףך\n.,?!:-" chars = sorted(list(set(HEBREW_CHARS))) vocab_size = len(chars) stoi = { ch:i for i,ch in enumerate(chars) } itos = { i:ch for i,ch in enumerate(chars) } BLOCK_SIZE = 128 N_EMBD = 256 N_HEAD = 8 N_LAYER = 8 if not os.path.exists(MODEL_DIR): os.makedirs(MODEL_DIR) def super_clean_text(text): text = re.sub(r'\d+', ' ', text) # הסרת מספרים text = re.sub(r'([.,?!])\1+', r'\1', text) # פיסוק כפול לאחד allowed = set(HEBREW_CHARS) cleaned = "".join([c for c in text if c in allowed]) cleaned = re.sub(r' +', ' ', cleaned) return cleaned.strip() class GeniusModel(nn.Module): def __init__(self): super().__init__() self.token_embedding_table = nn.Embedding(vocab_size, N_EMBD) self.position_embedding_table = nn.Embedding(BLOCK_SIZE, N_EMBD) self.blocks = nn.Sequential(*[Block(N_EMBD, n_head=N_HEAD) for _ in range(N_LAYER)]) self.ln_f = nn.LayerNorm(N_EMBD) self.lm_head = nn.Linear(N_EMBD, vocab_size) def forward(self, idx, targets=None): B, T = idx.shape x = self.token_embedding_table(idx) + self.position_embedding_table(torch.arange(T, device=device)) x = self.ln_f(self.blocks(x)) logits = self.lm_head(x) loss = F.cross_entropy(logits.view(-1, vocab_size), targets.view(-1)) if targets is not None else None return logits, loss def generate_smart(self, idx, max_new_tokens, temperature=0.8): self.eval() for _ in range(max_new_tokens): idx_cond = idx[:, -BLOCK_SIZE:] with torch.no_grad(): logits, _ = self(idx_cond) logits = logits[:, -1, :] / temperature for char_idx in set(idx[0].tolist()): logits[0, char_idx] /= 1.4 probs = F.softmax(logits, dim=-1) top_probs, top_indices = torch.topk(probs, 5) # בחירת אות אחת מהטופ rel_idx = torch.multinomial(top_probs[0], 1) idx_next = top_indices[0, rel_idx].view(1, 1) # מוודא מימד 2D (1,1) idx = torch.cat((idx, idx_next), dim=1) if itos[idx_next.item()] == '\n': break return idx class Block(nn.Module): def __init__(self, n_embd, n_head): super().__init__() head_size = n_embd // n_head self.sa = MultiHeadAttention(n_head, head_size) self.ffwd = nn.Sequential(nn.Linear(n_embd, 4 * n_embd), nn.ReLU(), nn.Linear(4 * n_embd, n_embd)) self.ln1, self.ln2 = nn.LayerNorm(n_embd), nn.LayerNorm(n_embd) def forward(self, x): x = x + self.sa(self.ln1(x)) return x + self.ffwd(self.ln2(x)) class MultiHeadAttention(nn.Module): def __init__(self, num_heads, head_size): super().__init__() self.heads = nn.ModuleList([Head(head_size) for _ in range(num_heads)]) self.proj = nn.Linear(N_EMBD, N_EMBD) def forward(self, x): return self.proj(torch.cat([h(x) for h in self.heads], dim=-1)) class Head(nn.Module): def __init__(self, head_size): super().__init__() self.key = nn.Linear(N_EMBD, head_size, bias=False) self.query = nn.Linear(N_EMBD, head_size, bias=False) self.value = nn.Linear(N_EMBD, head_size, bias=False) self.register_buffer('tril', torch.tril(torch.ones(BLOCK_SIZE, BLOCK_SIZE))) def forward(self, x): B,T,C = x.shape k, q, v = self.key(x), self.query(x), self.value(x) wei = q @ k.transpose(-2,-1) * C**-0.5 wei = wei.masked_fill(self.tril[:T, :T] == 0, float('-inf')) return F.softmax(wei, dim=-1) @ v class GeniusApp(ctk.CTk): def __init__(self): super().__init__() self.title("הגאון העברי - גרסה יציבה") self.geometry("1100x900") ctk.set_appearance_mode("dark") self.model = GeniusModel().to(device) if os.path.exists(MODEL_PATH): try: self.model.load_state_dict(torch.load(MODEL_PATH, map_location=device)) except: pass self.setup_ui() def setup_ui(self): self.grid_columnconfigure(1, weight=1) self.grid_rowconfigure(0, weight=1) self.sidebar = ctk.CTkFrame(self, width=280) self.sidebar.grid(row=0, column=0, sticky="nsew", padx=10, pady=10) ctk.CTkLabel(self.sidebar, text="מרכז בקרה", font=("Arial", 20, "bold")).pack(pady=20) ctk.CTkButton(self.sidebar, text="העלה קובץ לתיבה", command=self.upload_file, fg_color="#1f538d").pack(pady=10, padx=20) self.loss_label = ctk.CTkLabel(self.sidebar, text="Loss: 0.0000", font=("Consolas", 16), text_color="orange") self.loss_label.pack(pady=20) self.status_label = ctk.CTkLabel(self.sidebar, text="סטטוס: מוכן", text_color="gray") self.status_label.pack(pady=5) self.progress_bar = ctk.CTkProgressBar(self.sidebar) self.progress_bar.set(0) self.progress_bar.pack(pady=10, padx=20) self.main_frame = ctk.CTkFrame(self) self.main_frame.grid(row=0, column=1, sticky="nsew", padx=10, pady=10) ctk.CTkLabel(self.main_frame, text="תיבת אימון ידנית / הדבקה:", font=("Arial", 14)).pack(pady=(15, 5), padx=20, anchor="e") self.train_input_box = ctk.CTkTextbox(self.main_frame, height=180, font=("Arial", 14)) self.train_input_box.pack(fill="x", padx=20, pady=5) self.train_btn = ctk.CTkButton(self.main_frame, text="אמן מודל", height=45, fg_color="green", command=self.start_training) self.train_btn.pack(pady=10, padx=20, fill="x") self.chat_display = ctk.CTkTextbox(self.main_frame, state="disabled", font=("Arial", 16)) self.chat_display.pack(fill="both", expand=True, padx=20, pady=10) self.chat_entry = ctk.CTkEntry(self.main_frame, placeholder_text="כתוב כאן...", height=50) self.chat_entry.pack(side="left", fill="x", expand=True, padx=(20, 5), pady=20) self.chat_entry.bind("", lambda e: self.send_chat()) ctk.CTkButton(self.main_frame, text="שלח", width=120, height=50, command=self.send_chat).pack(side="right", padx=(5, 20), pady=20) def upload_file(self): path = filedialog.askopenfilename() if path: with open(path, "r", encoding="utf-8", errors="ignore") as f: self.train_input_box.delete("1.0", "end") self.train_input_box.insert("end", f.read()) def start_training(self): text = self.train_input_box.get("1.0", "end").strip() if len(text) < 10: return self.train_btn.configure(state="disabled") threading.Thread(target=self.run_training, args=(text,), daemon=True).start() def run_training(self, raw_text): clean_text = super_clean_text(raw_text) data = torch.tensor([stoi[c] for c in clean_text], dtype=torch.long, device=device) optimizer = torch.optim.AdamW(self.model.parameters(), lr=1e-4) self.model.train() steps = 400 for i in range(steps): if len(data) <= BLOCK_SIZE: break ix = torch.randint(len(data) - BLOCK_SIZE, (16,)) x = torch.stack([data[j:j+BLOCK_SIZE] for j in ix]) y = torch.stack([data[j+1:j+BLOCK_SIZE+1] for j in ix]) logits, loss = self.model(x, y) optimizer.zero_grad(set_to_none=True); loss.backward(); optimizer.step() if i % 10 == 0: self.after(0, lambda l=loss.item(), p=i/steps: self.update_ui(l, p)) torch.save(self.model.state_dict(), MODEL_PATH) self.after(0, self.finish_training) def update_ui(self, l, p): self.loss_label.configure(text=f"Loss: {l:.4f}") self.progress_bar.set(p) def finish_training(self): self.train_btn.configure(state="normal") self.status_label.configure(text="האימון הושלם!", text_color="cyan") messagebox.showinfo("הצלחה", "המודל למד את החומר!") def send_chat(self): msg = self.chat_entry.get().strip() if not msg: return self.add_chat(f"אתה: {msg}", "white") self.chat_entry.delete(0, "end") threading.Thread(target=self.think_and_answer, args=(msg,), daemon=True).start() def think_and_answer(self, msg): self.after(0, lambda: self.status_label.configure(text="הגאון חושב...", text_color="orange")) # זמן חשיבה פנימי for i in range(1, 11): time.sleep(0.1) self.after(0, lambda v=i/10: self.progress_bar.set(v)) context = torch.tensor([[stoi.get(c, stoi[' ']) for c in msg]], dtype=torch.long, device=device) gen = self.model.generate_smart(context, max_new_tokens=80) response = "".join([itos[i] for i in gen[0].tolist()])[len(msg):].strip().split('\n')[0] self.after(0, lambda: self.add_chat(f"הגאון: {response}", "#3a86ff")) self.after(0, lambda: self.status_label.configure(text="מוכן", text_color="gray")) self.after(0, lambda: self.progress_bar.set(0)) def add_chat(self, t, color): self.chat_display.configure(state="normal") self.chat_display.insert("end", t + "\n\n") self.chat_display.configure(state="disabled") self.chat_display.see("end") if __name__ == "__main__": app = GeniusApp() app.mainloop()