Create app.py

app.py

@@ -0,0 +1,131 @@
+import subprocess
+import sys
+import time
+from collections import defaultdict, deque
+
+# Otomatik kurulum
+
+def install_and_import(package):
+    try:
+        __import__(package)
+    except ImportError:
+        print(f"{package} is not installed, installing...")
+        subprocess.check_call([sys.executable, "-m", "pip", "install", package])
+
+install_and_import("gradio")
+install_and_import("transformers")
+install_and_import("torch")
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# === RATE LIMIT ===
+click_logs = defaultdict(lambda: {"minute": deque(), "hour": deque(), "day": deque()})
+LIMITS = {"minute": (13, 60), "hour": (90, 3600), "day": (1350, 86400)}
+
+def check_rate_limit(session_id):
+    now = time.time()
+    logs = click_logs[session_id]
+    remaining, reset_times = {}, {}
+    for key, (limit, interval) in LIMITS.items():
+        # Geçmiş istekleri temizle
+        while logs[key] and now - logs[key][0] > interval:
+            logs[key].popleft()
+        used = len(logs[key])
+        remaining[key] = max(0, limit - used)
+        reset_times[key] = int(interval - (now - logs[key][0]) if logs[key] else interval)
+        if used >= limit:
+            return False, f"⛔ {key.capitalize()} rate limit exceeded ({limit}/{key})", remaining, reset_times
+    # Limit aşılmadıysa log'a şimdi ekle
+    for key in LIMITS:
+        logs[key].append(now)
+    return True, None, remaining, reset_times
+
+# === CHAT ÜRETİM FONKSİYONU ===
+def extract_response_between_tokens(text: str) -> str:
+
+    start = "<|im_start|>assistant<|im_sep|>"
+    end = "<|im_end|>"
+    try:
+        return text.split(start)[1].split(end)[0]
+    except Exception:
+        return text
+
+# Model yükleme
+model_name = "Bertug1911/BrtGPT-1-Pre"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+model.eval()
+
+# Özel token ID
+im_end_id = tokenizer.convert_tokens_to_ids("<|im_end|>")
+
+# Üretim fonksiyonu chat_generate
+def chat_generate(prompt, temperature, top_k, max_new_tokens, session_id):
+    ok, msg, rem, resets = check_rate_limit(session_id)
+    if not ok:
+        return msg, format_status(rem, resets)
+
+    # Jinja chat format
+    messages = [{"role": "user", "content": prompt}]
+    formatted = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer(formatted, return_tensors="pt").to(device)
+    gen = inputs["input_ids"]
+
+    # Döngüsel üretim
+    for _ in range(int(max_new_tokens)):
+        out = model(gen)
+        logits = out.logits[:, -1, :] / float(temperature)
+        if int(top_k) > 0:
+            vals, idxs = torch.topk(logits, int(top_k))
+            filt = torch.full_like(logits, float('-inf'))
+            filt.scatter_(1, idxs, vals)
+            logits = filt
+        probs = torch.softmax(logits, dim=-1)
+        nxt = torch.multinomial(probs, num_samples=1)
+        gen = torch.cat([gen, nxt], dim=1)
+        if nxt.item() == im_end_id:
+            break
+
+    out_text = tokenizer.decode(gen[0], skip_special_tokens=False)
+    # Format düzeltme
+    no_sp = out_text.replace(" ", "").replace("Ġ", " ")
+    formatted_out = no_sp.replace("Ċ", "\n")
+    if not formatted_out.strip().endswith("<|im_end|>"):
+        formatted_out += "<|im_end|>"
+    resp = extract_response_between_tokens(formatted_out)
+    return resp, format_status(rem, resets)
+
+# Durum metni formatlama
+def format_status(rem, resets):
+    return "\n".join([f"🕒 {k.capitalize()}: {rem[k]} left — resets in {resets[k]} sec" for k in ["minute","hour","day"]])
+
+# === UI ===
+with gr.Blocks() as app:
+    session_id = gr.State(str(time.time()))
+    gr.Markdown("""
+    # 🤖 BrtGPT-1-Pre
+    """ )
+
+    with gr.Row():
+        prompt = gr.Textbox(lines=3, placeholder="Enter your message...", label="Prompt")
+        output = gr.Textbox(label="Response")
+
+    with gr.Row():
+        temperature = gr.Slider(0.01,1.0,value=0.5,step=0.01,label="Temperature")
+        top_k = gr.Slider(1,50,value=10,step=1,label="Top-K")
+        max_new_tokens = gr.Slider(1,128,value=15,step=1,label="Max New Tokens")
+
+    generate_button = gr.Button("Generate")
+    status = gr.Markdown()
+
+    generate_button.click(
+        fn=chat_generate,
+        inputs=[prompt, temperature, top_k, max_new_tokens, session_id],
+        outputs=[output, status]
+    )
+
+app.launch()