import json
import infinity
import infinity.index as index
from infinity.common import REMOTE_HOST
import pandas as pds

def main():
    try:
        

        
        infinity_obj = infinity.connect(REMOTE_HOST)
        db = infinity_obj.get_database("default")   
        
        
        db.drop_table("fnclass_table", if_exists=True)
        # Create "fnclass_table"
        class_table = db.create_table("fnclass_table", {"id": "varchar","vec": "vector, 4, float", "body": "varchar", "req": "varchar", "keyid": "varchar"}, None)
        
        

        class_table.insert([{"id": 4, "vec": [-0.014, 0.008, 0.021, -0.003], 
                             "body": "Zumba", "keyid": "202308080000721",
                             "req": ""}])
        class_table.insert([{"id": 82, "vec": [-0.007, -0.007, -0.024, 0.031], 
                             "body": "yoga", "keyid": "202309020000121",
                             "req": ""}])
        class_table.insert([{"id": 17, "vec": [0.023, 0.064, -0.030, 0.107], 
                             "body": "aerobics", "keyid": "202308080000721",
                             "req": ""}])
        # `create_index()` is required before match() or fusion()
        tblidx = class_table.create_index("cls_index",
                                 [index.IndexInfo("body",
                                                  index.IndexType.FullText,
                                                  [index.InitParameter("ANALYZER", "segmentation")]),
                                  ], None)
        
       
        #test text search - got result
        qb_result = class_table.match(
            "body", "zumba", "topn=1").fusion("rrf").output(["body","req"]).to_pl()
        
        
        print("------tabular - full txt search-------") 
        print(qb_result) 


	 #test text search - empty result
        qb_result = class_table.match(
            "id", "17", "topn=1").fusion("rrf").output(["body","req"]).to_pl()
        
        
        print("------tabular - full txt search-------") 
        print(qb_result) 
        
        

        #created new table and tried text search but did not get result as expected.
        db.drop_table("t_class_intents", if_exists=True)
        # Create   "t_class_intents"
        intent_tble =  db.create_table("t_class_intents", {"intent_id": "varchar",
                                                               "intent_name":"varchar",
                                                               "body":"varchar",
                                                               "int_vec": "vector, 4, float", 
                                                               "neuron_id": "varchar", 
                                                               "neuron_name": "varchar",                                                               
                                                               "data_txt": "varchar"}, None)
        # index creation
        residxs = intent_tble.create_index("class_intent_index",
                                 [index.IndexInfo("body",
                                                  index.IndexType.FullText,
                                                  [index.InitParameter("ANALYZER", "segmentation")]),
                                  ], None)
        
        residx1s = intent_tble.create_index("class_neuron_index",
                                 [index.IndexInfo("neuron_name",
                                                  index.IndexType.FullText,
                                                  []),
                                  ], None)
        
        intent_tble.insert([{"intent_id": 1, 
                             "int_vec": [-0.056, 0.018, -0.064, 0.010], 
                             "intent_name": "add_class", 
                             "body":"add_class",
                             "neuron_id": "111",
                             "neuron_name": "add_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 2, 
                             "int_vec": [-0.076, 0.067, -0.055, 0.060], 
                             "intent_name": "edit_class", 
                             "body":"edit_class",
                             "neuron_id": "112",
                             "neuron_name": "edit_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 2, 
                             "int_vec": [-0.076, 0.067, -0.055, 0.060], 
                             "intent_name": "edit_class", 
                             "body":"edit_class",
                             "neuron_id": "113",
                             "neuron_name": "modify_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 2, 
                             "int_vec": [-0.076, 0.067, -0.055, 0.060], 
                             "intent_name": "edit_class", 
                             "body":"edit_class",
                             "neuron_id": "114",
                             "neuron_name": "change_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 3, 
                             "int_vec": [-0.051, -0.004, -0.085, -0.020], 
                             "intent_name": "view_class", 
                             "body":"view_class",
                             "neuron_id": "115",
                             "neuron_name": "view_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 3, 
                             "int_vec": [-0.051, -0.004, -0.085, -0.020], 
                             "intent_name": "view_class", 
                             "body":"view_class",
                             "neuron_id": "116",
                             "neuron_name": "list_class",                              
                             "data_txt":""}])
        intent_tble.insert([{"intent_id": 4, 
                             "int_vec": [-0.051, 0.082, -0.054, -0.026], 
                             "intent_name": "delete_class", 
                             "body":"delete_class",
                             "neuron_id": "223",
                             "neuron_name": "delete_class",                              
                             "data_txt":""}])  
        temp_result = intent_tble.match("body","add_class", "topn=1").fusion("rrf").output(["neuron_name"]).to_pl()  
        print(temp_result) #no result
        intent_qb = intent_tble.query_builder
        qb_output = intent_qb.match("body","add_class","topn=1").output(["*"]).to_pl()
        print(qb_output) #no result
        
        intent_name_val = 'add_class'
        qb_output = intent_qb.filter(f"intent_name='{intent_name_val}'").output(["*"]).to_pl()
        print(qb_output) #got result  
        
    except Exception as e:
        print(str(e))   

if __name__ == '__main__':
    main()