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Test APIs and fix bugs (#41)

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KevinHuSh
2024-01-22 19:51:38 +08:00
committed by GitHub
parent 484e5abc1f
commit 34b2ab3b2f
11 changed files with 46 additions and 27 deletions
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9
rag/nlp/search.py
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@ -187,9 +187,10 @@ class Dealer:
if len(t) < 5: continue
idx.append(i)
pieces_.append(t)
es_logger.info("{} => {}".format(answer, pieces_))
if not pieces_: return answer
ans_v = embd_mdl.encode(pieces_)
ans_v, c = embd_mdl.encode(pieces_)
assert len(ans_v[0]) == len(chunk_v[0]), "The dimension of query and chunk do not match: {} vs. {}".format(
len(ans_v[0]), len(chunk_v[0]))
@ -219,7 +220,7 @@ class Dealer:
Dealer.trans2floats(
sres.field[i]["q_%d_vec" % len(sres.query_vector)]) for i in sres.ids]
if not ins_embd:
return []
return [], [], []
ins_tw = [huqie.qie(sres.field[i][cfield]).split(" ") for i in sres.ids]
sim, tksim, vtsim = self.qryr.hybrid_similarity(sres.query_vector,
ins_embd,
@ -235,6 +236,8 @@ class Dealer:
def retrieval(self, question, embd_mdl, tenant_id, kb_ids, page, page_size, similarity_threshold=0.2,
vector_similarity_weight=0.3, top=1024, doc_ids=None, aggs=True):
ranks = {"total": 0, "chunks": [], "doc_aggs": {}}
if not question: return ranks
req = {"kb_ids": kb_ids, "doc_ids": doc_ids, "size": top,
"question": question, "vector": True,
"similarity": similarity_threshold}
@ -243,7 +246,7 @@ class Dealer:
sim, tsim, vsim = self.rerank(
sres, question, 1 - vector_similarity_weight, vector_similarity_weight)
idx = np.argsort(sim * -1)
ranks = {"total": 0, "chunks": [], "doc_aggs": {}}
dim = len(sres.query_vector)
start_idx = (page - 1) * page_size
for i in idx: