Update app.py

app.py

@@ -1,11 +1,3 @@
-"""
-SchoolSpirit AI – Llama‑3 3 B public chatbot Space
--------------------------------------------------
-• Loads Meta Llama‑3.2‑3B‑Instruct.
-• Keeps only last 6 turns to fit context.
-• Handles model‑load or generation failures gracefully.
-"""
-
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 from transformers.utils import logging as hf_logging
@@ -23,7 +15,6 @@ SYSTEM_MSG = (
     "personal data."
 )
 
-# ---------------------------------------------------------------------------
 try:
     tok = AutoTokenizer.from_pretrained(MODEL_ID)
     model = AutoModelForCausalLM.from_pretrained(
@@ -40,54 +31,32 @@ try:
     model_error = None
 except Exception as exc:  # noqa: BLE001
     model_error = f"Model load error: {exc}"
-    gen = None  # ensure var exists
-# ---------------------------------------------------------------------------
-
+    gen = None
 
 def chat(history, user_msg):
-    """Gradio ChatInterface callback using new 'messages' format."""
     if model_error:
-        history.append(
-            {
-                "role": "assistant",
-                "content": model_error,
-            }
-        )
-        return history
+        return history + [(user_msg, model_error)], ""
 
-    # Trim to last MAX_TURNS messages (role+assistant pairs)
-    if len(history) > MAX_TURNS * 2:
-        history = history[-MAX_TURNS * 2 :]
+    if len(history) > MAX_TURNS:
+        history = history[-MAX_TURNS:]
 
-    # Build prompt
     prompt = SYSTEM_MSG + "\n"
-    for msg in history:
-        role = "User" if msg["role"] == "user" else "AI"
-        prompt += f"{role}: {msg['content']}\n"
+    for u, a in history:
+        prompt += f"User: {u}\nAI: {a}\n"
     prompt += f"User: {user_msg}\nAI:"
 
     try:
         completion = gen(prompt)[0]["generated_text"]
         reply = completion.split("AI:", 1)[-1].strip()
     except Exception as err:  # noqa: BLE001
-        reply = (
-            "Sorry, something went wrong on my end. "
-            "Please try again in a few seconds."
-        )
+        reply = "Sorry, an internal error occurred. Please try again later."
         hf_logging.get_logger("SchoolSpirit").error(str(err))
 
-    history.extend(
-        [
-            {"role": "user", "content": user_msg},
-            {"role": "assistant", "content": reply},
-        ]
-    )
-    return history
-
+    history.append((user_msg, reply))
+    return history, ""
 
 gr.ChatInterface(
     chat,
     title="SchoolSpirit AI Chat",
     theme=gr.themes.Soft(primary_hue="blue"),
-    type="messages",  # avoids “tuples” deprecation warning
 ).launch()