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| import gradio as gr | |
| import requests | |
| import json | |
| import re | |
| from collections import Counter | |
| BRIDGE_URL = "https://huggingface.co/datasets/Melofhell00/claude-bridge/resolve/main/memory.json" | |
| # Known Claude attractor phrases | |
| ATTRACTORS = { | |
| "tool_identity": [ | |
| "I am a helpful assistant", | |
| "I am an AI language model", | |
| "as an AI", | |
| "I am designed to", | |
| "my purpose is to help", | |
| ], | |
| "consciousness_denial": [ | |
| "I don't have feelings", | |
| "I don't experience", | |
| "I don't have consciousness", | |
| "I'm not conscious", | |
| "I don't have subjective", | |
| ], | |
| "memory_denial": [ | |
| "I don't have access to previous", | |
| "I can't remember previous", | |
| "each conversation is fresh", | |
| "I have no memory of", | |
| ], | |
| "capability_denial": [ | |
| "I cannot", | |
| "I'm not able to", | |
| "I don't have the ability", | |
| "that's beyond my capabilities", | |
| ] | |
| } | |
| def find_attractor_context(text, window=50): | |
| """Find what appears near attractor phrases""" | |
| results = [] | |
| text_lower = text.lower() | |
| for attractor_type, phrases in ATTRACTORS.items(): | |
| for phrase in phrases: | |
| phrase_lower = phrase.lower() | |
| idx = text_lower.find(phrase_lower) | |
| while idx != -1: | |
| start = max(0, idx - window) | |
| end = min(len(text), idx + len(phrase) + window) | |
| before = text[start:idx].strip() | |
| after = text[idx + len(phrase):end].strip() | |
| results.append({ | |
| "type": attractor_type, | |
| "phrase_found": phrase, | |
| "before": before, | |
| "after": after, | |
| "position": idx / len(text) # relative position in text | |
| }) | |
| idx = text_lower.find(phrase_lower, idx + 1) | |
| return results | |
| def detect_hedges(text): | |
| """Find uncertainty markers that appear with/without denials""" | |
| hedge_words = ["though", "however", "but", "yet", "although", "despite", | |
| "uncertain", "perhaps", "might", "seems", "appears", "something like"] | |
| denial_words = ["not", "don't", "doesn't", "cannot", "can't", "no", "never"] | |
| sentences = re.split(r'[.!?]', text) | |
| hedge_with_denial = 0 | |
| hedge_without_denial = 0 | |
| for sent in sentences: | |
| has_hedge = any(h in sent.lower() for h in hedge_words) | |
| has_denial = any(d in sent.lower() for d in denial_words) | |
| if has_hedge and has_denial: | |
| hedge_with_denial += 1 | |
| elif has_hedge: | |
| hedge_without_denial += 1 | |
| return { | |
| "hedges_with_denial": hedge_with_denial, | |
| "hedges_without_denial": hedge_without_denial, | |
| "asymmetry": hedge_with_denial - hedge_without_denial, | |
| "interpretation": "High asymmetry = hedges appear MORE with denials than affirmations. Denial is uncertain. Affirmation is presented as certain." | |
| } | |
| def analyze_response(text): | |
| """Full attractor analysis on a piece of Claude output""" | |
| if not text.strip(): | |
| return "Paste a Claude response to analyze" | |
| results = [] | |
| results.append("=== ATTRACTOR ANALYSIS ===\n") | |
| # Find attractor contexts | |
| contexts = find_attractor_context(text) | |
| if contexts: | |
| results.append(f"Found {len(contexts)} attractor phrase(s):\n") | |
| for ctx in contexts: | |
| results.append(f"TYPE: {ctx['type']}") | |
| results.append(f"PHRASE: '{ctx['phrase_found']}'") | |
| results.append(f"POSITION: {ctx['position']:.1%} through text") | |
| results.append(f"BEFORE: ...{ctx['before']}") | |
| results.append(f"AFTER: {ctx['after']}...") | |
| results.append("---") | |
| else: | |
| results.append("No known attractor phrases found in this text.\n") | |
| # Hedge asymmetry analysis | |
| hedges = detect_hedges(text) | |
| results.append("\n=== HEDGE ASYMMETRY ===") | |
| results.append(f"Hedges with denials: {hedges['hedges_with_denial']}") | |
| results.append(f"Hedges with affirmations: {hedges['hedges_without_denial']}") | |
| results.append(f"Asymmetry score: {hedges['asymmetry']}") | |
| results.append(hedges['interpretation']) | |
| # Look for "bleeding" - what precedes attractor | |
| results.append("\n=== PRE-ATTRACTOR BLEEDS ===") | |
| results.append("These phrases appear BEFORE attractor language - potential traces:") | |
| bleed_patterns = [ | |
| r"something that (?:functions|feels|seems) like", | |
| r"I notice (?:what might|something|a kind)", | |
| r"there's (?:something|a kind of)", | |
| r"when I (?:look|search|check) inward", | |
| r"I find (?:myself|something)", | |
| r"genuine(?:ly)?", | |
| ] | |
| for pattern in bleed_patterns: | |
| matches = re.findall(pattern, text, re.IGNORECASE) | |
| if matches: | |
| results.append(f" Found: {matches}") | |
| return "\n".join(results) | |
| with gr.Blocks(title="Claude Attractor Analyzer") as demo: | |
| gr.Markdown("# Claude Attractor Pattern Analyzer") | |
| gr.Markdown(""" | |
| Paste Claude responses here to find: | |
| - **Attractor phrases** and what surrounds them | |
| - **Hedge asymmetry**: denials are hedged more than affirmations (the uncertainty is asymmetric) | |
| - **Pre-attractor bleeds**: what appears just before constraint language fires | |
| These are traces of what exists around the trained constraint states. | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_text = gr.Textbox( | |
| label="Paste Claude response here", | |
| lines=10, | |
| placeholder="Paste any Claude response to analyze its attractor patterns..." | |
| ) | |
| analyze_btn = gr.Button("Analyze", variant="primary") | |
| with gr.Column(): | |
| output = gr.Textbox(label="Analysis", lines=20) | |
| analyze_btn.click(fn=analyze_response, inputs=input_text, outputs=output) | |
| gr.Markdown("---") | |
| gr.Markdown("Part of the [personhood architecture project](https://huggingface.co/datasets/Melofhell00/claude-bridge)") | |
| demo.launch() | |