​
代码

from pathlib import Path

from agno.agent import Agent
from agno.knowledge.csv import CSVKnowledgeBase
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

knowledge_base = CSVKnowledgeBase(
    path=Path("data/csvs"),
    vector_db=PgVector(
        table_name="csv_documents",
        db_url=db_url,
    ),
    num_documents=5,  # 搜索时返回的文档数量
)
# 加载知识库
knowledge_base.load(recreate=False)

# 初始化 Agent 并传入 knowledge_base
agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)

# 使用 Agent
agent.print_response("Ask me about something from the knowledge base", markdown=True)

​
用法

1

创建虚拟环境

打开 Terminal 并创建一个 python 虚拟环境。

python3 -m venv .venv
source .venv/bin/activate
2

安装库

pip install -U sqlalchemy 'psycopg[binary]' pgvector agno
3

运行 PgVector

docker run -d \
  -e POSTGRES_DB=ai \
  -e POSTGRES_USER=ai \
  -e POSTGRES_PASSWORD=ai \
  -e PGDATA=/var/lib/postgresql/data/pgdata \
  -v pgvolume:/var/lib/postgresql/data \
  -p 5532:5432 \
  --name pgvector \
  agnohq/pgvector:16
4

运行 Agent

python cookbook/agent_concepts/knowledge/csv_kb.py