neuron/tools/retrieval-eval/fullsim.py

import numpy as np, json, urllib.request, collections, sys
SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
EV="/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/"
np.seterr(all='ignore')
M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
eidx={k:i for i,k in enumerate(eids)}
d=json.load(open('/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json',encoding='utf-8',errors='surrogateescape'))
N={n['id']:n for n in d['nodes']}
STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
adj=collections.defaultdict(list); hasstruct=set()
for e in d['edges']:
    if e.get('relation') not in STRUCT: continue
    w=float(e.get('weight') or 0.0)
    adj[e['from_id']].append((e['to_id'],w)); adj[e['to_id']].append((e['from_id'],w))
    hasstruct.add(e['from_id']); hasstruct.add(e['to_id'])
del d
gold={q['id']:q for q in json.load(open(EV+"gold_set.json"))['queries']}
LEX={r['id']:r['returned'] for r in json.load(open(EV+"results-main.json"))['rows']}
CACHE={}
def emb(t):
    if t in CACHE: return CACHE[t]
    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
    v=v/(np.linalg.norm(v)+1e-9); CACHE[t]=v; return v
FIRE=0.02; DECAY=0.7; DEPTH=2; SEED_MIN=0.60; ASSOC_MAX=64
def assoc(seeds, s):
    act={x:1.0 for x in seeds}; seen={x:2 for x in seeds}
    Q=[(x,0) for x in seeds]; h=0
    while h<len(Q):
        cur,hop=Q[h]; h+=1
        if hop>=DEPTH: continue
        p=act[cur]
        for oid,w in adj.get(cur,()):
            n=N.get(oid)
            if not n or n.get('node_type') in ('Tag','InternalStateEvent'): continue
            na=p*w*DECAY*float(n.get('salience') or 0.0)
            if na<FIRE: continue
            if oid in seen and na<=act.get(oid,0): continue
            act[oid]=na
            if oid not in seen: seen[oid]=1
            Q.append((oid,hop+1))
    out=[]
    for k,v in seen.items():
        if v!=1 or k not in eidx: continue
        c=float(s[eidx[k]])
        if c<=0: continue
        out.append((c,k))
    out.sort(reverse=True)
    return [k for c,k in out[:ASSOC_MAX]]
def inter3(L,S,A,lim=10):
    out=[]; li=si=ai=0
    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
        if li<len(L):
            if L[li] not in out: out.append(L[li])
            li+=1
        if len(out)>=lim: break
        if si<len(S):
            if S[si] not in out: out.append(S[si])
            si+=1
        if len(out)>=lim: break
        if ai<len(A):
            if A[ai] not in out: out.append(A[ai])
            ai+=1
    return out
def run(mode, K=0):
    res={}
    for qid,q in gold.items():
        v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
        L=LEX[qid][:10]
        ordr=np.argsort(-s)
        S=[eids[j] for j in ordr[:10] if s[j]>SEED_MIN]
        A=[]
        if mode!='hybrid':
            seeds=[x for x in L[:3] if x in N]
            if mode=='semseed':
                seeds=seeds+[eids[j] for j in ordr[:K] if eids[j] in N and eids[j] not in seeds]
            A=assoc(seeds,s) if seeds else []
        res[qid]=inter3(L,S,A)
    return res
def score(res,label):
    hits=0; det={}
    for qid,q in gold.items():
        out=res[qid][:5]
        if q['category']=='nonsense': ok = (len(res[qid])==0)
        elif q['category']=='superseded':
            rel=q['relevant']; must=q.get('must_outrank') or {}
            ok=False
            for good,bad in (must.items() if isinstance(must,dict) else []):
                ok = good in res[qid] and (bad not in res[qid] or res[qid].index(good)<res[qid].index(bad))
            if not must: ok = any(r in out for r in rel)
        else: ok = any(r in out for r in q['relevant'])
        det[qid]=ok; hits+=ok
    print("%-22s outcome-true=%d/38" % (label,hits))
    return det
print("gold sample keys:", list(list(gold.values())[0].keys()))
mk=[q for q in gold.values() if q['category']=='superseded'][0]
print("superseded fields:", {k:v for k,v in mk.items() if k!='derivation'})
a=score(run('hybrid'),'sim hybrid(L+S)')
b=score(run('lexseed'),'sim assoc(lex seeds)')
for K in (3,5,10):
    c=score(run('semseed',K),'sim assoc(+sem K=%d)'%K)
    d=[q for q in gold if c[q]!=b[q]]
    print("   vs lexseed: moved=%d  gains=%s  losses=%s"%(len(d),[q for q in d if c[q]],[q for q in d if not c[q]]))
    e=[q for q in gold if c[q]!=a[q]]
    print("   vs hybrid : moved=%d  gains=%s  losses=%s"%(len(e),[q for q in e if c[q]],[q for q in e if not c[q]]))

print("\n=== Will's own constant ENGRAM_EMBED_SEED_K = 8 ===")
c=score(run('semseed',8),'sim assoc(+sem K=8)')
for base,lab in ((b,'lexseed(iter2)'),(a,'hybrid(iter1 KEEP)')):
    dd=[q for q in gold if c[q]!=base[q]]
    print("   vs %-18s moved=%d gains=%s losses=%s"%(lab,len(dd),[q for q in dd if c[q]],[q for q in dd if not c[q]]))
# diagnostic: what is assoc rank-1 for each paraphrase query at K=8
print("\nassoc leg head at K=8 (paraphrase):")
for qid,q in gold.items():
    if q['category'] not in ('paraphrase','nonsense'): continue
    v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
    L=LEX[qid][:10]; ordr=np.argsort(-s)
    seeds=[x for x in L[:3] if x in N]+[eids[j] for j in ordr[:8] if eids[j] in N and eids[j] not in L[:3]]
    A=assoc(seeds,s) if seeds else []
    rel=set(q['relevant']); gr=next((i+1 for i,x in enumerate(A) if x in rel),None)
    print("  %-4s %-11s |A|=%-4d goldAssocRank=%-5s head=%s"%(qid,q['category'],len(A),gr,
        [ (N[x].get('label') or x)[:26] for x in A[:3] ]))