From 2fb3523ba3b1f0fa4e55990a3ab179ffe70964f2 Mon Sep 17 00:00:00 2001 From: Deril Raju <47169600+deril2605@users.noreply.github.com> Date: Fri, 13 Mar 2026 19:35:24 +0530 Subject: [PATCH 1/2] Use Vector class for query embedding in search --- examples/agent_knowledge_postgres.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/examples/agent_knowledge_postgres.py b/examples/agent_knowledge_postgres.py index 1f84fa9..835eb10 100644 --- a/examples/agent_knowledge_postgres.py +++ b/examples/agent_knowledge_postgres.py @@ -34,6 +34,7 @@ import psycopg from openai import OpenAI from pgvector.psycopg import register_vector +from pgvector import Vector from agent_framework import Agent, AgentSession, BaseContextProvider, Message, SessionContext, SupportsAgentRun from agent_framework.openai import OpenAIChatClient @@ -257,7 +258,7 @@ def __init__(self, conn: psycopg.Connection, max_results: int = 3): def _search(self, query: str) -> list[dict]: """Run hybrid search (vector + full-text) and return matching products.""" - query_embedding = get_embedding(query) + query_embedding = Vector(get_embedding(query)) cursor = self.conn.execute( HYBRID_SEARCH_SQL, From c6607f67a9be3c99a2ba7dde4c235932107c52d0 Mon Sep 17 00:00:00 2001 From: Deril Raju <47169600+deril2605@users.noreply.github.com> Date: Sat, 14 Mar 2026 13:13:46 +0530 Subject: [PATCH 2/2] Refactor query_embedding to use Vector class Updated query_embedding to use Vector for hybrid search. --- examples/agent_knowledge_pg_rewrite.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/examples/agent_knowledge_pg_rewrite.py b/examples/agent_knowledge_pg_rewrite.py index 47b5f5a..35fcf40 100644 --- a/examples/agent_knowledge_pg_rewrite.py +++ b/examples/agent_knowledge_pg_rewrite.py @@ -38,6 +38,7 @@ import psycopg from openai import OpenAI from pgvector.psycopg import register_vector +from pgvector import Vector from agent_framework import Agent, AgentSession, BaseContextProvider, Message, SessionContext, SupportsAgentRun from agent_framework.openai import OpenAIChatClient @@ -305,7 +306,7 @@ async def _rewrite_query(self, conversation_messages: list[Message]) -> str: def _search(self, query: str) -> list[dict]: """Run hybrid search (vector + full-text) and return matching products.""" - query_embedding = get_embedding(query) + query_embedding = Vector(get_embedding(query)) cursor = self.conn.execute( HYBRID_SEARCH_SQL,