Update example_02_self_reflection.py

example_02_self_reflection.py

@@ -1,37 +1,14 @@
-# example_02_self_reflection.py
-
+import argparse
 from wfgy_core import WFGYRunner
-from default_config import DEFAULT_CONFIG
-from transformers import pipeline
 
-prompt = "Why don't AIs like to take showers?"
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--reflect", action="store_true", help="Enable self-reflection")
+    parser.add_argument("--ascii", action="store_true", help="Show ASCII banner")
+    parser.add_argument("--style", type=str, default="default", help="Choose style: default/scientific/meme")
 
-runner = WFGYRunner(config=DEFAULT_CONFIG)
-results = runner.run(prompt)
+    args = parser.parse_args()
 
-reflection_input = (
-    f"You are a linguistic critic AI.\n"
-    f"Here is a prompt before transformation:\n{prompt}\n\n"
-    f"Here is the transformed response:\n{results['output']}\n\n"
-    "In exactly one sentence, explain how the tone or style has changed."
-)
-
-reflector = pipeline("text-generation", model="gpt2")
-generated = reflector(reflection_input, max_length=60, do_sample=True, temperature=0.8)[0]["generated_text"]
-reflection_output = generated.strip()
-
-print("=== Prompt ===")
-print(prompt)
-print("=== Output ===")
-print(results["output"])
-print("=== BBMC Residue ===")
-print(results["BBMC_residue"])
-print("=== BBPF Paths ===")
-print(results["BBPF_paths"])
-print("=== BBCR Reset State ===")
-print(results["BBCR_reset_state"])
-print("=== BBAM Modulated ===")
-print(results["BBAM_modulated"])
-print("=== Self-Reflection ===")
-print(reflection_input)
-print(reflection_output)
+    prompt = "Why don't AIs like to take showers?"
+    runner = WFGYRunner()
+    runner.run(prompt, reflect=args.reflect, style=args.style, show_ascii=args.ascii)