Update app.py

app.py

@@ -1,111 +1,107 @@
 """
 ZEN-Bot Ultimate — key-free Hugging Face Space (free CPU)
 
-Skills (type these commands – or just ask naturally):
+Skills
   • Normal chat
   • /math <expr>           — safe calculator
   • /summarize <text>      — 2-sentence TL;DR
   • /translate_es <text>   — English → Spanish
   • /ascii <text>          — big FIGlet ASCII art
   • Any question ending with “?”  → live Wikipedia answer
-Dependencies: transformers, torch, gradio, wikipedia, pyfiglet
+Model: facebook/blenderbot-400M-distill  (public,  ~720 MB weights)
 """
 
 import ast, math, re, gc, traceback, torch, wikipedia, pyfiglet
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# ---------------------------------------------------------------------
-# 0 · Tiny helpers
-# ---------------------------------------------------------------------
-def err_msg(e: Exception) -> str:
-    print("=== ZEN-Bot ERROR ===")
+# ──────────────────────────────────────────────────────────────────────────────
+# 0 · helpers
+# ──────────────────────────────────────────────────────────────────────────────
+def err(e: Exception) -> str:
+    print("\n=== ZEN-Bot ERROR ===")
     traceback.print_exc()
-    print("=====================")
+    print("====================\n")
     return f"⚠️ {type(e).__name__}: {e}"
 
-# ---------------------------------------------------------------------
-# 1 · Load a light, coherent open-weights chat model (fits free CPU)
-# ---------------------------------------------------------------------
-MODEL_NAME = "TinyLlama/TinyLlama-1.1B-Chat"   # ≈1 GB  → ~4 GB RAM
+# ──────────────────────────────────────────────────────────────────────────────
+# 1 · model (fits free CPU tier)
+# ──────────────────────────────────────────────────────────────────────────────
+MODEL_NAME = "facebook/blenderbot-400M-distill"      # always public
 
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-model     = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+model     = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
 model.eval();  torch.set_grad_enabled(False)
 
 GEN_KW = dict(
     max_new_tokens = 64,
-    do_sample      = False,            # fast & deterministic
-    pad_token_id   = tokenizer.eos_token_id,
+    do_sample      = False,                       # fast & deterministic
 )
 
 def llm(prompt: str) -> str:
     try:
-        ids_in  = tokenizer(prompt, return_tensors="pt").input_ids[:, -1024:]
+        ids_in   = tokenizer(prompt, return_tensors="pt",
+                              truncation=True, max_length=1024).input_ids
         with torch.no_grad():
             ids_out = model.generate(ids_in, **GEN_KW)
         reply_ids = ids_out[0, ids_in.shape[-1]:]
         return tokenizer.decode(reply_ids, skip_special_tokens=True).strip()
     except Exception as e:
-        return err_msg(e)
+        return err(e)
 
-# ---------------------------------------------------------------------
-# 2 · /math — safe evaluator
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
+# 2 · /math (safe)
+# ──────────────────────────────────────────────────────────────────────────────
 _ALLOWED = {k: getattr(math, k) for k in dir(math) if not k.startswith("__")}
 _ALLOWED.update({"abs": abs, "round": round})
 
 def safe_math(expr: str) -> str:
     try:
         node = ast.parse(expr, mode="eval")
-
         def ok(n):
             if isinstance(n, ast.Num):            return True
             if isinstance(n, ast.UnaryOp):        return ok(n.operand)
             if isinstance(n, ast.BinOp):          return ok(n.left) and ok(n.right)
             if isinstance(n, ast.Call):
-                return (isinstance(n.func, ast.Name) and
-                        n.func.id in _ALLOWED and
-                        all(ok(a) for a in n.args))
+                return (isinstance(n.func, ast.Name)
+                        and n.func.id in _ALLOWED
+                        and all(ok(a) for a in n.args))
             return False
-
         if not ok(node.body):
-            return "⛔️ Only basic math functions are allowed."
+            return "⛔️ Expression not allowed."
         return str(eval(compile(node, "<expr>", "eval"),
                         {"__builtins__": {}}, _ALLOWED))
     except Exception as e:
-        return err_msg(e)
+        return err(e)
 
-# ---------------------------------------------------------------------
-# 3 · Wikipedia live answer
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
+# 3 · Wikipedia Q&A
+# ──────────────────────────────────────────────────────────────────────────────
 def wiki_answer(q: str) -> str | None:
     try:
         wikipedia.set_lang("en")
-        page = wikipedia.page(q, auto_suggest=True, redirect=True)
-        summ = wikipedia.summary(page.title, sentences=3, auto_suggest=False)
+        page  = wikipedia.page(q, auto_suggest=True, redirect=True)
+        summ  = wikipedia.summary(page.title, sentences=3, auto_suggest=False)
         return f"**{page.title}** — {summ}"
     except (wikipedia.DisambiguationError, wikipedia.PageError):
         return None
     except Exception as e:
-        return err_msg(e)
+        return err(e)
 
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
 # 4 · ASCII art
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
 def ascii_art(txt: str) -> str:
-    try:
-        return pyfiglet.figlet_format(txt, width=120)
-    except Exception as e:
-        return err_msg(e)
+    try:    return pyfiglet.figlet_format(txt, width=120)
+    except Exception as e:  return err(e)
 
-# ---------------------------------------------------------------------
-# 5 · Main router
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
+# 5 · main router
+# ──────────────────────────────────────────────────────────────────────────────
 CMD = re.compile(r"^/(math|summarize|translate_es|ascii)\s+(.+)", re.S | re.I)
 
-def respond(msg: str, chat_hist: list[list[str, str]]) -> str:
-    # 5-A · Commands
+def respond(msg: str, hist: list[list[str, str]]) -> str:
+    # 5-A · commands
     m = CMD.match(msg.strip())
     if m:
         cmd, body = m.group(1).lower(), m.group(2).strip()
@@ -114,39 +110,39 @@ def respond(msg: str, chat_hist: list[list[str, str]]) -> str:
         if cmd == "summarize":    return llm(f"Summarize in two concise sentences:\n\n{body}\n\nSummary:")
         if cmd == "translate_es": return llm(f"Translate into Spanish (natural):\n\n{body}\n\nSpanish:")
 
-    # 5-B · “Question about the world?” → Wikipedia first
+    # 5-B · Wikipedia for factual questions
     if msg.strip().endswith("?") and len(msg.split()) > 2:
         wiki = wiki_answer(msg)
         if wiki:  return wiki
 
-    # 5-C · Normal chat with memory of last 6 turns
+    # 5-C · normal chat (keep last 6 turns)
     prompt = "You are ZEN-Bot, a concise, helpful tutor for young AI pioneers.\n\n"
-    for u, b in chat_hist[-6:]:
+    for u, b in hist[-6:]:
         prompt += f"User: {u}\nAssistant: {b}\n"
     prompt += f"User: {msg}\nAssistant:"
     return llm(prompt)
 
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
 # 6 · Gradio UI
-# ---------------------------------------------------------------------
+# ──────────────────────────────────────────────────────────────────────────────
 demo = gr.ChatInterface(
     fn          = respond,
     title       = "🚀 ZEN-Bot Ultimate (Key-Free)",
     description = (
-        "**What I can do**  \n"
-        "• Normal chat  \n"
+        "**Commands**  \n"
+        "• normal chat  \n"
         "• `/math 2**5 / (sin(0.5)+1)`  \n"
         "• `/summarize <text>`  \n"
-        "• `/translate_es Hello world!`  \n"
+        "• `/translate_es Hello!`  \n"
         "• `/ascii ZEN`  \n"
-        "• Ask any fact question (ends with `?`) — I’ll fetch live from Wikipedia"
+        "• Ask any factual question ending with `?` for live Wikipedia answer"
     ),
     theme       = "soft",
     fill_height = True,
     examples    = [
         "Who discovered penicillin?",
         "/ascii AI ROCKS",
-        "/math sqrt(144) + log(100,10)",
+        "/math sqrt(144)+log(100,10)",
         "/summarize The Industrial Revolution began in Britain...",
         "/translate_es Good evening, friends!",
     ],