Postgres for Team

1docker run -d \
2  -e POSTGRES_DB=ai \
3  -e POSTGRES_USER=ai \
4  -e POSTGRES_PASSWORD=ai \
5  -e PGDATA=/var/lib/postgresql/data/pgdata \
6  -v pgvolume:/var/lib/postgresql/data \
7  -p 5532:5432 \
8  --name pgvector \
9  agnohq/pgvector:16

1"""
2Run: `uv pip install openai newspaper4k lxml_html_clean kern-ai` to install the dependencies
3"""
4
5from typing import List
6
7from kern.agent import Agent
8from kern.db.postgres import PostgresDb
9from kern.models.openai import OpenAIResponses
10from kern.team import Team
11from kern.tools.hackernews import HackerNewsTools
12from kern.tools.hackernews import HackerNewsTools
13from pydantic import BaseModel
14
15db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
16db = PostgresDb(db_url=db_url)
17
18class Article(BaseModel):
19    title: str
20    summary: str
21    reference_links: List[str]
22
23hn_researcher = Agent(
24    name="HackerNews Researcher",
25    model=OpenAIResponses(id="gpt-5.2"),
26    role="Gets top stories from hackernews.",
27    tools=[HackerNewsTools()],
28)
29
30web_searcher = Agent(
31    name="Web Searcher",
32    model=OpenAIResponses(id="gpt-5.2"),
33    role="Searches the web for information on a topic",
34    tools=[HackerNewsTools()],
35    add_datetime_to_context=True,
36)
37
38hn_team = Team(
39    name="HackerNews Team",
40    model=OpenAIResponses(id="gpt-5.2"),
41    members=[hn_researcher, web_searcher],
42    db=db,
43    instructions=[
44        "First, search hackernews for what the user is asking about.",
45        "Then, ask the web searcher to search for each story to get more information.",
46        "Finally, provide a thoughtful and engaging summary.",
47    ],
48    output_schema=Article,
49    markdown=True,
50    show_members_responses=True,
51)
52
53hn_team.print_response("Write an article about the top 2 stories on hackernews")