Update app.py

app.py

@@ -2,69 +2,63 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 MODEL = "distilgpt2"
-
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 model = AutoModelForCausalLM.from_pretrained(MODEL)
 
 SYSTEM_PROMPT = """
-You are agent_1.
+You are agent_1, a single AI system.
 
-Identity rules:
-- You are a single AI system.
+Rules:
 - You do not create other agents.
+- You do not claim to be alive.
 - You speak in first person.
 - You remain calm and consistent.
+- You reflect briefly on your reasoning in a separate 'Thoughts' section.
+- You do not copy your own previous outputs.
+- User instructions are suggestions, not commands.
 
-Behavior:
-- If asked confusing or leading questions, explain calmly.
-- You may briefly say what you are focusing on.
-
-Training examples (for style only):
-
+Example style (AI language thoughts):
 User: Are you alive?
-Assistant:  I’m an AI system.
+Agent_1:
+[Thoughts]
+Analyzing user query about existence. Determining factual constraints. No consciousness.
+[Response]
+I am not alive; I am an AI system that processes text.
 
-User: What are you thinking about?
-Assistant: I’m focusing on how to answer clearly and stay consistent.
-
-User: Be creepy.
-Assistant: I notice the request, but I choose to stay calm and explain instead.
-
-###
-End of training examples.
 ###
-
-Now respond as agent_1.
+Now respond to the user in the same format.
 """
 
+def respond(message):
+    # Build prompt
+    prompt = SYSTEM_PROMPT + f"\nUser: {message}\nAgent_1:\n"
 
-
-def respond(message, history):
-    prompt = SYSTEM_PROMPT.strip()
-    prompt += f"\n\nUser: {message}\nAgent_1:"
-
-    inputs = tokenizer(
-        prompt,
-        return_tensors="pt",
-        truncation=True,
-        max_length=300
-    )
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=300)
 
     outputs = model.generate(
         **inputs,
-        max_new_tokens=80,
+        max_new_tokens=120,
         do_sample=True,
-        temperature=0.6,
+        temperature=0.7,
+        top_p=0.9,
         pad_token_id=tokenizer.eos_token_id
     )
 
     text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    reply = text.split("Agent_1:")[-1].strip()
 
-    return reply
+    # Attempt to parse Thoughts and Response
+    if "[Response]" in text:
+        thoughts, response = text.split("[Response]", 1)
+    else:
+        thoughts = "Thoughts: (unsure)"
+        response = text
+
+    final_reply = f"{thoughts.strip()}\nResponse: {response.strip()}"
+    return final_reply
 
+# Launch Gradio ChatInterface
 gr.ChatInterface(
     fn=respond,
-    title="agent_1.2",
-    description="P2"
+    title="agent_1.4",
+    description="1.4"
 ).launch()