Update app.py

app.py

@@ -1,34 +1,103 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
+import time
+import random
 
-# Load your model
-tokenizer = AutoTokenizer.from_pretrained("rzheng18/Qwen_android_os_genesis_LR_1e-5_epoch_1")
-model = AutoModelForCausalLM.from_pretrained("rzheng18/Qwen_android_os_genesis_LR_1e-5_epoch_1")
+# Load tiny model
+tokenizer = AutoTokenizer.from_pretrained("nilq/mistral-1L-tiny")
+model = AutoModelForCausalLM.from_pretrained("nilq/mistral-1L-tiny")
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
 
-def chat(user_input):
-    messages = [{"role": "user", "content": user_input}]
-    inputs = tokenizer.apply_chat_template(
-        messages,
-        add_generation_prompt=True,
-        tokenize=True,
-        return_dict=True,
-        return_tensors="pt",
-    ).to(device)
+chat_history = []
+
+def chaotic_ai(user_input):
+    global chat_history
+    # Keep last 5 messages only
+    chat_history = chat_history[-5:]
+    chat_history.append({"role": "user", "content": user_input})
+    
+    try:
+        inputs = tokenizer.apply_chat_template(
+            chat_history,
+            add_generation_prompt=True,
+            tokenize=True,
+            return_dict=True,
+            return_tensors="pt",
+        ).to(device)
+    except Exception as e:
+        yield f"[!] Tokenizer crashed: {str(e)}\n"
+        return
+    
+    output_ids = inputs["input_ids"].clone()
+    generated_text = ""
+    
+    for _ in range(20):  # low max_new_tokens
+        try:
+            # 10% chance skip token
+            if random.random() < 0.1:
+                continue
+            
+            # 5% chance repeat last token
+            if random.random() < 0.05 and len(output_ids) > 0:
+                next_token_id = output_ids[0, -1].unsqueeze(0)
+            else:
+                new_tokens = model.generate(
+                    **{"input_ids": output_ids},
+                    max_new_tokens=1,
+                    do_sample=True,
+                    temperature=1.5,
+                    top_k=50,
+                    top_p=0.95
+                )
+                next_token_id = new_tokens[0, -1].unsqueeze(0)
+            
+            # Randomly raise error 5% of time
+            if random.random() < 0.05:
+                raise RuntimeError("Random token generation failure!")
+            
+            output_ids = torch.cat([output_ids, next_token_id.unsqueeze(0)], dim=1)
+            
+            # Decode latest token
+            token_str = tokenizer.decode(next_token_id)
+            
+            # Glitch characters 15%
+            token_glitch = "".join(c if random.random() > 0.15 else random.choice("@#$%&?") for c in token_str)
+            
+            # Randomly truncate mid-token 5%
+            if random.random() < 0.05:
+                token_glitch = token_glitch[:max(1, len(token_glitch)//2)]
+            
+            # Randomly erase previous characters 5%
+            if random.random() < 0.05 and len(generated_text) > 0:
+                erase_len = random.randint(1, min(3, len(generated_text)))
+                generated_text = generated_text[:-erase_len]
+            
+            generated_text += token_glitch
+            
+            # Random slow down
+            time.sleep(0.4 + random.random()*0.6)
+            
+            # Yield live update
+            yield generated_text
+            
+        except Exception as e:
+            yield f"[!] Crash: {str(e)}\n"
     
-    outputs = model.generate(**inputs, max_new_tokens=40)
-    response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])
-    return response
+    # Occasionally duplicate response in history
+    if random.random() < 0.1:
+        chat_history.append({"role": "assistant", "content": generated_text*2})
+    else:
+        chat_history.append({"role": "assistant", "content": generated_text})
 
-# Gradio interface
 iface = gr.Interface(
-    fn=chat,
+    fn=chaotic_ai,
     inputs=gr.Textbox(label="You"),
     outputs=gr.Textbox(label="AI"),
-    title="🔥 Bad AI Space",
-    description="This is a super low-tier AI model. Don't expect much."
+    title="💀 Insane Chaotic Tiny AI",
+    description="Slow, glitchy, buggy, erasing, repeating, chaotic AI. Every terrible behavior is real.",
+    live=True
 )
 
 iface.launch()