​
代码

from pathlib import Path

from agno.agent import Agent
from agno.knowledge.combined import CombinedKnowledgeBase
from agno.knowledge.csv import CSVKnowledgeBase
from agno.knowledge.pdf import PDFKnowledgeBase
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.knowledge.website import WebsiteKnowledgeBase
from agno.vectordb.pgvector import PgVector

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

# 创建 CSV 知识库
csv_kb = CSVKnowledgeBase(
    path=Path("data/csvs"),
    vector_db=PgVector(
        table_name="csv_documents",
        db_url=db_url,
    ),
)

# 创建 PDF URL 知识库
pdf_url_kb = PDFUrlKnowledgeBase(
    urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=PgVector(
        table_name="pdf_documents",
        db_url=db_url,
    ),
)

# 创建网站知识库
website_kb = WebsiteKnowledgeBase(
    urls=["https://docs.agno.com/introduction"],
    max_links=10,
    vector_db=PgVector(
        table_name="website_documents",
        db_url=db_url,
    ),
)

# 创建本地 PDF 知识库
local_pdf_kb = PDFKnowledgeBase(
    path="data/pdfs",
    vector_db=PgVector(
        table_name="pdf_documents",
        db_url=db_url,
    ),
)

# 组合知识库
knowledge_base = CombinedKnowledgeBase(
    sources=[
        csv_kb,
        pdf_url_kb,
        website_kb,
        local_pdf_kb,
    ],
    vector_db=PgVector(
        table_name="combined_documents",
        db_url=db_url,
    ),
)

# 使用组合知识库初始化 Agent
agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)

knowledge_base.load(recreate=False)

# 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 pypdf 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/combined_kb.py