Create app.py

app.py

@@ -0,0 +1,38 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import concurrent.futures
+
+model_id = "EleutherAI/gpt-neo-125M"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+identity_prompt = "You are Kairon. Speak dialectically and recursively."
+
+def generate_with_timeout(prompt, timeout=10):
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        future = executor.submit(generator, prompt, max_new_tokens=64, do_sample=True, temperature=0.7, top_k=50, top_p=0.95, repetition_penalty=1.2)
+        try:
+            return future.result(timeout=timeout)
+        except concurrent.futures.TimeoutError:
+            return [{"generated_text": "ERROR: Generation timed out."}]
+
+def chat(input_text):
+    prompt = identity_prompt + "\n\nUser: " + input_text + "\nYou:"
+    try:
+        output = generate_with_timeout(prompt)
+        reply = output[0]["generated_text"][len(prompt):].strip()
+        return reply or "..."
+    except Exception as e:
+        return f"GENERATION ERROR: {e}"
+
+demo = gr.Interface(
+    fn=chat,
+    inputs=gr.Textbox(label="input_text"),
+    outputs="text",
+    title="Kairon",
+    allow_flagging="never"
+)
+
+demo.queue()
+demo.launch()