Update app.py

app.py

@@ -1,44 +1,44 @@
 import os
 import json
 import torch
-import random
 from transformers import pipeline, set_seed
 import gradio as gr
 
 # Model setup
 CACHE_DIR = "./model_cache"
 os.makedirs(CACHE_DIR, exist_ok=True)
+
 generator = pipeline(
     "text-generation",
     model="openai-community/openai-gpt",
     cache_dir=CACHE_DIR,
-    device_map="cpu",
-    torch_dtype=torch.float32
+    device=-1,  # CPU
 )
 
-# State for chat history
-def init_history():
+# Chat history state
+ def init_history():
     return []
 
-def generate_and_record(prompt, max_length, temperature, top_k, top_p, repetition_penalty, seed, num_return_sequences, history):
+def generate_and_record(
+    prompt, max_length, temperature, top_k, top_p, repetition_penalty, seed, num_return_sequences, history
+):
     if seed is not None:
-        set_seed(seed)
+        set_seed(int(seed))
     outputs = generator(
         prompt,
-        max_length=max_length,
-        temperature=temperature,
-        top_k=top_k,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        num_return_sequences=num_return_sequences,
-        do_sample=True
+        max_length=int(max_length),
+        temperature=float(temperature),
+        top_k=int(top_k),
+        top_p=float(top_p),
+        repetition_penalty=float(repetition_penalty),
+        num_return_sequences=int(num_return_sequences),
+        do_sample=True,
     )
     texts = [out["generated_text"] for out in outputs]
-    entry = {"prompt": prompt, "results": texts}
-    history.append(entry)
+    history.append({"prompt": prompt, "results": texts})
     return "\n\n---\n\n".join(texts), history
 
-def export_history(history):
+ def export_history(history):
     path = "chat_history.json"
     with open(path, "w", encoding="utf-8") as f:
         json.dump(history, f, ensure_ascii=False, indent=2)
@@ -71,7 +71,7 @@ with gr.Blocks(title="GPT Text Generation") as demo:
         inputs=[prompt_input, max_length, temperature, top_k, top_p, repetition_penalty, seed_input, num_seq, history_state],
         outputs=[output_text, history_state]
     )
-    clear_btn.click(lambda _: [], inputs=[history_state], outputs=[history_state, output_text], _js="() => {document.querySelectorAll('textarea')[1].value='';}")
+    clear_btn.click(lambda _: ([], ""), inputs=[history_state], outputs=[history_state, output_text])
     export_btn.click(fn=export_history, inputs=[history_state], outputs=[])
 
 demo.queue().launch(server_name="0.0.0.0", server_port=7860)