boost highlight performace (#2419)

### What problem does this PR solve?

#2415

### Type of change

- [x] Performance Improvement

rag/nlp/query.py

@@ -50,7 +50,7 @@ class EsQueryer:
         patts = [
             (r"是*(什么样的|哪家|一下|那家|请问|啥样|咋样了|什么时候|何时|何地|何人|是否|是不是|多少|哪里|怎么|哪儿|怎么样|如何|哪些|是啥|啥是|啊|吗|呢|吧|咋|什么|有没有|呀)是*", ""),
             (r"(^| )(what|who|how|which|where|why)('re|'s)? ", " "),
-            (r"(^| )('s|'re|is|are|were|was|do|does|did|don't|doesn't|didn't|has|have|be|there|you|me|your|my|mine|just|please|may|i|should|would|wouldn't|will|won't|done|go|for|with|so|the|a|an|by|i'm|it's|he's|she's|they|they're|you're|as|by|on|in|at|up|out|down) ", " ")
+            (r"(^| )('s|'re|is|are|were|was|do|does|did|don't|doesn't|didn't|has|have|be|there|you|me|your|my|mine|just|please|may|i|should|would|wouldn't|will|won't|done|go|for|with|so|the|a|an|by|i'm|it's|he's|she's|they|they're|you're|as|by|on|in|at|up|out|down|of) ", " ")
         ]
         for r, p in patts:
             txt = re.sub(r, p, txt, flags=re.IGNORECASE)
@@ -80,7 +80,7 @@ class EsQueryer:
                      must=Q("query_string", fields=self.flds,
                             type="best_fields", query=" ".join(q),
                             boost=1)#, minimum_should_match=min_match)
-                     ), tks
+                     ), list(set([t for t in txt.split(" ") if t]))
 
         def need_fine_grained_tokenize(tk):
             if len(tk) < 3:
@@ -93,8 +93,10 @@ class EsQueryer:
         for tt in self.tw.split(txt)[:256]:  # .split(" "):
             if not tt:
                 continue
+            keywords.append(tt)
             twts = self.tw.weights([tt])
             syns = self.syn.lookup(tt)
+            if syns: keywords.extend(syns)
             logging.info(json.dumps(twts, ensure_ascii=False))
             tms = []
             for tk, w in sorted(twts, key=lambda x: x[1] * -1):
@@ -147,7 +149,7 @@ class EsQueryer:
 
         return Q("bool",
                  must=mst,
-                 ), keywords
+                 ), list(set(keywords))
 
     def hybrid_similarity(self, avec, bvecs, atks, btkss, tkweight=0.3,
                           vtweight=0.7):

rag/nlp/search.py

@@ -189,10 +189,9 @@ class Dealer:
             txt = d["_source"][fieldnm]
             txt = re.sub(r"[\r\n]", " ", txt, flags=re.IGNORECASE|re.MULTILINE)
             txts = []
-            for w in keywords:
-                txt = re.sub(r"(^|[ .?/'\"\(\)!,:;-])(%s)([ .?/'\"\(\)!,:;-])"%re.escape(w), r"\1<em>\2</em>\3", txt, flags=re.IGNORECASE|re.MULTILINE)
-
             for t in re.split(r"[.?!;\n]", txt):
+                for w in keywords:
+                    t = re.sub(r"(^|[ .?/'\"\(\)!,:;-])(%s)([ .?/'\"\(\)!,:;-])"%re.escape(w), r"\1<em>\2</em>\3", t, flags=re.IGNORECASE|re.MULTILINE)
                 if not re.search(r"<em>[^<>]+</em>", t, flags=re.IGNORECASE|re.MULTILINE): continue
                 txts.append(t)
             ans[d["_id"]] = "...".join(txts) if txts else "...".join([a for a in list(hlts.items())[0][1]])