SupabaseHybridSearch for Python

Hi, I'm wondering if there is any template/code for SupabseHybridsearch in Python (pref. langchain)?

Got it to work for Typescritp but we are considering switching to Python for our AI framework.

AAndré Hi, I'm wondering if there is any template/code for SupabseHybridsearch in Pytho...

Olyno•1/3/24, 6:26 PM

Hi :vmathi: There isn't a specific SupabaseHybridSearch implementation available for Python at the moment.

You can try the following tho:

import psycopg2
from psycopg2 import sql

def hybrid_search(query, num_results_sim, num_results_ft):
   # Connect to your Supabase database
   conn = psycopg2.connect(database="your_database", user="your_username", password="your_password", host="your_host", port="your_port")
   cur = conn.cursor()
   
   # Perform similarity search
   sim_query = sql.SQL("SELECT * FROM your_table WHERE pgvector_distance(your_column, {}) <= {} ORDER BY pgvector_distance LIMIT {}").format(sql.Identifier(query), sql.Identifier(num_results_sim))
   cur.execute(sim_query)
   sim_results = cur.fetchall()
   
   # Perform full-text search
   ft_query = sql.SQL("SELECT * FROM your_table WHERE to_tsvector(your_column) @@ plainto_tsquery({}) ORDER BY ts_rank_cd(to_tsvector(your_column), plainto_tsquery({})) DESC LIMIT {}").format(sql.Identifier(query), sql.Identifier(query), sql.Identifier(num_results_ft))
   cur.execute(ft_query)
   ft_results = cur.fetchall()
   
   # Combine and return results
   results = sim_results + ft_results
   return results

import psycopg2
from psycopg2 import sql

def hybrid_search(query, num_results_sim, num_results_ft):
   # Connect to your Supabase database
   conn = psycopg2.connect(database="your_database", user="your_username", password="your_password", host="your_host", port="your_port")
   cur = conn.cursor()
   
   # Perform similarity search
   sim_query = sql.SQL("SELECT * FROM your_table WHERE pgvector_distance(your_column, {}) <= {} ORDER BY pgvector_distance LIMIT {}").format(sql.Identifier(query), sql.Identifier(num_results_sim))
   cur.execute(sim_query)
   sim_results = cur.fetchall()
   
   # Perform full-text search
   ft_query = sql.SQL("SELECT * FROM your_table WHERE to_tsvector(your_column) @@ plainto_tsquery({}) ORDER BY ts_rank_cd(to_tsvector(your_column), plainto_tsquery({})) DESC LIMIT {}").format(sql.Identifier(query), sql.Identifier(query), sql.Identifier(num_results_ft))
   cur.execute(ft_query)
   ft_results = cur.fetchall()
   
   # Combine and return results
   results = sim_results + ft_results
   return results

AndréOP•1/3/24, 6:27 PM

Thanks, will try

import psycopg2 from psycopg2 import sql def hybrid_search(query, num_results_sim, num_results_ft): # Connect to your Supabase database conn = psycopg2.connect(database="your_database", user="your_username", password="your_password", host="your_host", port="your_port") cur = conn.cursor() # Perform similarity search sim_query = sql.SQL("SELECT * FROM your_table WHERE pgvector_distance(your_column, {}) <= {} ORDER BY pgvector_distance LIMIT {}").format(sql.Identifier(query), sql.Identifier(num_results_sim)) cur.execute(sim_query) sim_results = cur.fetchall() # Perform full-text search ft_query = sql.SQL("SELECT * FROM your_table WHERE to_tsvector(your_column) @@ plainto_tsquery({}) ORDER BY ts_rank_cd(to_tsvector(your_column), plainto_tsquery({})) DESC LIMIT {}").format(sql.Identifier(query), sql.Identifier(query), sql.Identifier(num_results_ft)) cur.execute(ft_query) ft_results = cur.fetchall() # Combine and return results results = sim_results + ft_results return results

SupabaseHybridSearch for Python

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