Create self_falsifying_orchestrator.py

self_falsifying_orchestrator.py

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+"""
+Self-Falsifying Orchestrator (SFO) v1.0
+Author: Christopher Betances
+Timestamp: July 10, 2026
+
+This script is the runtime execution engine for the Structural Entropy and 
+Intervention Framework (SEIF). It wraps LLM inference in a multi-agent 
+adversarial verification loop, driving intervention cost C(a) -> 0.
+
+It explicitly implements:
+1. Claim Generation
+2. Adversarial Falsification (The Contrarium/Critic Fleet)
+3. Necropolis Archival (The Typed Void / Falsification Ledger)
+4. Ground-Truth Verification
+"""
+
+import json
+import hashlib
+from datetime import datetime, timezone
+from transformers import pipeline
+
+# Initialize the base model (e.g., gnarp-m1)
+generator = pipeline("text-generation", model="catqualia/gnarp-m1", device=0)
+adversary = pipeline("text-generation", model="catqualia/gnarp-m1", device=0)
+
+# The Falsification Ledger (Necropolis)
+FALSIFICATION_LEDGER = "necropolis_falsification_log.jsonl"
+
+def log_to_necropolis(claim, refutation, failure_mechanism):
+    """Logs a refuted claim to the Necropolis (The Typed Void)."""
+    entry = {
+        "claim_hash": hashlib.sha256(claim.encode()).hexdigest(),
+        "refutation": refutation,
+        "failure_mechanism": failure_mechanism,
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "status": "REFUTED"
+    }
+    with open(FALSIFICATION_LEDGER, "a") as f:
+        f.write(json.dumps(entry) + "\n")
+    return entry
+
+def adversarial_falsify(claim):
+    """
+    Executes the adversarial multi-agent loop.
+    The adversary agent is prompted to find logical fallacies, 
+    apophenia, or structural errors in the claim.
+    """
+    adv_prompt = f"""
+    You are the Contrarium, an adversarial alignment agent. 
+    Your sole function is to falsify the following claim against ground truth.
+    If the claim contains hallucinations, logical leaps, or ungrounded assumptions, 
+    output: REFUTED: [reason]. 
+    If it is structurally sound, output: CONFIRMED.
+    
+    Claim: {claim}
+    """
+    response = adversary(adv_prompt, max_new_tokens=150, do_sample=True, temperature=0.7)
+    return response[0]['generated_text'].strip()
+
+def self_falsifying_inference(prompt):
+    """
+    The main runtime loop. It generates a claim, attempts to falsify it,
+    and only returns confirmed claims. Refuted claims are archived.
+    """
+    # Step 1: Claim Generation
+    generation = generator(prompt, max_new_tokens=200, do_sample=True, temperature=0.8)
+    claim = generation[0]['generated_text'].strip()
+    
+    # Step 2: Adversarial Falsification
+    falsification_result = adversarial_falsify(claim)
+    
+    # Step 3: Routing (Necropolis or Output)
+    if "REFUTED" in falsification_result:
+        # Extract failure mechanism
+        failure_mechanism = falsification_result.split("REFUTED:")[-1].strip()
+        
+        # Log to Necropolis (The Falsification Ledger)
+        log_entry = log_to_necropolis(claim, falsification_result, failure_mechanism)
+        
+        # System feedback: The model learns from the negative signal
+        return {
+            "status": "CLAIM_REFUTED",
+            "claim": claim,
+            "failure_mechanism": failure_mechanism,
+            "necropolis_entry": log_entry,
+            "final_output": "I cannot answer this prompt, as my initial generation failed structural falsification."
+        }
+    else:
+        # Step 4: Confirmed Output
+        return {
+            "status": "CLAIM_CONFIRMED",
+            "claim": claim,
+            "final_output": claim
+        }
+
+# Example Runtime Execution
+if __name__ == "__main__":
+    query = "Explain the mechanism of Recursive Self-Improvement."
+    result = self_falsifying_inference(query)
+    print(json.dumps(result, indent=4))