Create api/router_rerank.py

api/router_rerank.py

@@ -3,22 +3,24 @@ from fastapi import APIRouter
 import numpy as np
 from consensus.topo import TopologicalConsciousness
 from api.schemas import RerankRequest
+from adapters.hf_sentence_tfm_adapter import SentenceTransformerAdapter
 
 router = APIRouter(prefix="/rerank", tags=["rag"])
 
 @router.post("")
 def rerank(req: RerankRequest):
-    from adapters.openai_adapter import OpenAIAdapter
-    model = OpenAIAdapter()
+    model = SentenceTransformerAdapter()
     q = np.array(model.embed_text(req.query))
     doc_embs = [np.array(model.embed_text(d)) for d in req.docs]
     tc = TopologicalConsciousness(n_anyons=len(doc_embs), central_charge=627)
     pc = tc.calculate_coherence(doc_embs)
     alpha, beta, lamb = 1.0, 0.3, 0.2
     scores = []
+    qn = q / (np.linalg.norm(q) + 1e-12)
     for e in doc_embs:
-        sim = float(q @ e / ((np.linalg.norm(q)+1e-12)*(np.linalg.norm(e)+1e-12)))
+        en = e / (np.linalg.norm(e) + 1e-12)
+        sim = float(qn @ en)
         energy = tc.cardy_boundary_energy(e)
         scores.append(alpha*sim + beta*pc - lamb*energy)
     order = np.argsort(scores)[::-1].tolist()
-    return {"order": order, "scores": [float(s) for s in scores]}
+    return {"order": order, "scores": [float(s) for s in scores], "coherence": pc}