​
Code

cookbook/models/ibm/watsonx/storage.py
from agno.agent import Agent
from agno.models.ibm import WatsonX
from agno.storage.postgres import PostgresStorage
from agno.tools.duckduckgo import DuckDuckGoTools

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

agent = Agent(
    model=WatsonX(id="ibm/granite-20b-code-instruct"),
    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
    tools=[DuckDuckGoTools()],
    add_history_to_messages=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")

​
Usage

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

Set your API key

export IBM_WATSONX_API_KEY=xxx
export IBM_WATSONX_PROJECT_ID=xxx
3

Install libraries

pip install -U ibm-watsonx-ai sqlalchemy psycopg duckduckgo-search agno
4

Set up PostgreSQL

Make sure you have a PostgreSQL database running. You can adjust the db_url in the code to match your database configuration.
5

Run Agent

python cookbook/models/ibm/watsonx/storage.py
本示例展示了如何使用 PostgreSQL 存储与 IBM WatsonX 结合以在多次交互中维护对话状态。它创建了一个带有 PostgreSQL 存储后端的 agent，并发送了多条消息，在消息之间会保留对话历史记录。 注意：您需要安装 sqlalchemy 包并拥有一个可用的 PostgreSQL 数据库。