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add search TAB backend api (#2375)

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### What problem does this PR solve?
 #2247

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Kevin Hu
2024-09-11 19:49:18 +08:00
committed by GitHub
parent 8052cbc70e
commit 333608a1d4
6 changed files with 117 additions and 16 deletions
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12
rag/nlp/search.py
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@ -79,9 +79,9 @@ class Dealer:
Q("bool", must_not=Q("range", available_int={"lt": 1})))
return bqry
def search(self, req, idxnm, emb_mdl=None):
def search(self, req, idxnm, emb_mdl=None, highlight=False):
qst = req.get("question", "")
bqry, keywords = self.qryr.question(qst)
bqry, keywords = self.qryr.question(qst, min_match="30%")
bqry = self._add_filters(bqry, req)
bqry.boost = 0.05
@ -130,7 +130,7 @@ class Dealer:
qst, emb_mdl, req.get(
"similarity", 0.1), topk)
s["knn"]["filter"] = bqry.to_dict()
if "highlight" in s:
if not highlight and "highlight" in s:
del s["highlight"]
q_vec = s["knn"]["query_vector"]
es_logger.info("【Q】: {}".format(json.dumps(s)))
@ -356,7 +356,7 @@ class Dealer:
rag_tokenizer.tokenize(inst).split(" "))
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, rerank_mdl=None):
vector_similarity_weight=0.3, top=1024, doc_ids=None, aggs=True, rerank_mdl=None, highlight=False):
ranks = {"total": 0, "chunks": [], "doc_aggs": {}}
if not question:
return ranks
@ -364,7 +364,7 @@ class Dealer:
"question": question, "vector": True, "topk": top,
"similarity": similarity_threshold,
"available_int": 1}
sres = self.search(req, index_name(tenant_id), embd_mdl)
sres = self.search(req, index_name(tenant_id), embd_mdl, highlight)
if rerank_mdl:
sim, tsim, vsim = self.rerank_by_model(rerank_mdl,
@ -405,6 +405,8 @@ class Dealer:
"vector": self.trans2floats(sres.field[id].get("q_%d_vec" % dim, "\t".join(["0"] * dim))),
"positions": sres.field[id].get("position_int", "").split("\t")
}
if highlight:
d["highlight"] = rmSpace(sres.highlight[id])
if len(d["positions"]) % 5 == 0:
poss = []
for i in range(0, len(d["positions"]), 5):