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modeling_twentyq.py

@@ -273,54 +273,31 @@ class TwentyQForCausalLM(PreTrainedModel, GenerationMixin):
     def play(self):
         """Interactive CLI mode — play 20Q in the terminal."""
         self._ensure_strings()
-        self._rng = random.Random()
-        print(f"\n  Think of something and I'll try to guess it in 20 questions.\n")
+        print("\n  Think of something and I'll try to guess it in 20 questions.\n")
         input("  Press Enter when ready... ")
-        print()
 
-        answers = []
-        qnum = 0
-
-        qnum += 1
-        print(f"  {qnum}. Is it Animal, Vegetable, Mineral, or Other?")
+        # Use the same generate() path as the pipeline
+        conversation = "Think of something and I'll try to guess it in 20 questions.\n"
         while True:
-            r = input("  > ").strip().lower()
-            avm = AVM_WORDS.get(r) or AVM_WORDS.get(r[:1] if r else "", 0)
-            if avm:
-                answers.append((0, avm, False))
-                break
-        print()
-
-        while qnum < 30:
-            nc, best_t, best_s, cidx, cscores = self._rank_targets(answers)
-            if nc == 0:
-                print("  I'm stumped!")
+            # Generate next response
+            conversation += "[A] "
+            ids = torch.tensor([list(conversation.encode("utf-8"))])
+            out = self.generate(ids)
+            response = bytes(out[0, ids.shape[1]:].tolist()).decode("utf-8", errors="replace")
+            conversation += response + "\n"
+
+            print(f"\n  20Q: {response}")
+            if "I win" in response or "stumped" in response:
                 return
 
-            if nc == 1 or qnum == 20 or qnum == 24 or qnum == 30 or (qnum >= 18 and nc <= 2):
-                qnum += 1
-                print(f"  {qnum}. I'm guessing... {self.targets_str[best_t]}?")
-                r = input("  (Y/N/Close) > ").strip().lower()
-                if r.startswith("y"):
-                    print(f"\n  I win! Got it in {qnum} questions.")
-                    return
-                answers.append((best_t, 0, True))
-                if qnum >= 25:
-                    break
-                print()
-                continue
-
-            q = self._select_question(answers, nc, cidx)
-            if q < 0:
-                break
-            qnum += 1
-            print(f"  {qnum}. {self.questions_str[q]}?")
-            while True:
-                r = input("  > ").strip().lower()
-                ac = ANSWER_WORDS.get(r) or ANSWER_WORDS.get(r[:1] if r else "", 0)
-                if ac and ac > 0:
-                    answers.append((q, ac, False))
-                    break
-            print()
+            if "Animal, Vegetable, Mineral" in response:
+                hint = "(Animal/Vegetable/Mineral/Other)"
+            elif "guessing" in response.lower():
+                hint = "(Yes/No/Close)"
+            else:
+                hint = "(Yes/No/Probably/Doubtful/Maybe/Unknown)"
 
-        print(f"\n  I give up after {qnum} questions!")
+            reply = input(f"  You {hint}: ").strip()
+            if not reply:
+                return
+            conversation += f"[U] {reply}\n"