Robust for abnormal response from LLMs. (#4747)

### What problem does this PR solve?


### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

graphrag/general/community_reports_extractor.py

                 ent_df["entity"] = ent_df["entity_name"]
                 del ent_df["entity_name"]
                 rela_df = pd.DataFrame(self._get_relation_(list(ent_df["entity"]), list(ent_df["entity"]), 10000))
+                if rela_df.empty:
+                    continue
                 rela_df["source"] = rela_df["src_id"]
                 rela_df["target"] = rela_df["tgt_id"]
                 del rela_df["src_id"]

graphrag/search.py

             tenant_ids = tenant_ids.split(",")
         idxnms = [index_name(tid) for tid in tenant_ids]
         ty_kwds = []
-        ents = []
         try:
             ty_kwds, ents = self.query_rewrite(llm, qst, [index_name(tid) for tid in tenant_ids], kb_ids)
             logging.info(f"Q: {qst}, Types: {ty_kwds}, Entities: {ents}")
         nhop_pathes = defaultdict(dict)
         for _, ent in ents_from_query.items():
             nhops = ent.get("n_hop_ents", [])
+            if not isinstance(nhops, list):
+                logging.warning(f"Abnormal n_hop_ents: {nhops}")
+                continue
             for nbr in nhops:
                 path = nbr["path"]
                 wts = nbr["weights"]
                 "From Entity": f,
                 "To Entity": t,
                 "Score": "%.2f" % (rel["sim"] * rel["pagerank"]),
-                "Description": json.loads(ent["description"]).get("description", "")
+                "Description": json.loads(rel["description"]).get("description", "")
             })
             max_token -= num_tokens_from_string(str(relas[-1]))
             if max_token <= 0:

rag/nlp/search.py

                 break
             id = sres.ids[i]
             chunk = sres.field[id]
-            dnm = chunk["docnm_kwd"]
-            did = chunk["doc_id"]
+            dnm = chunk.get("docnm_kwd", "")
+            did = chunk.get("doc_id", "")
             position_int = chunk.get("position_int", [])
             d = {
                 "chunk_id": id,
                 "content_ltks": chunk["content_ltks"],
                 "content_with_weight": chunk["content_with_weight"],
-                "doc_id": chunk["doc_id"],
+                "doc_id": did,
                 "docnm_kwd": dnm,
                 "kb_id": chunk["kb_id"],
                 "important_kwd": chunk.get("important_kwd", []),