Agent with Knowledge

Code

1from kern.agent import Agent
2from kern.knowledge.embedder.google import GeminiEmbedder
3from kern.knowledge.knowledge import Knowledge
4from kern.models.google import Gemini
5from kern.vectordb.pgvector import PgVector
6
7db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
8
9knowledge = Knowledge(
10    vector_db=PgVector(
11        table_name="recipes",
12        db_url=db_url,
13        embedder=GeminiEmbedder(),
14    ),
15)
16# Add content to the knowledge
17knowledge.insert(
18    url="https://kern-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"
19)
20
21agent = Agent(model=Gemini(id="gemini-2.0-flash-001"), knowledge=knowledge)
22agent.print_response("How to make Thai curry?", markdown=True)

Usage

Set up your virtual environment

1uv venv --python 3.12
2source .venv/bin/activate

1uv venv --python 3.12
2.venv\Scripts\activate

Set your API key

1export GOOGLE_API_KEY=xxx

Install dependencies

1uv pip install -U google-genai sqlalchemy pgvector pypdf openai kern-ai

Run PgVector

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

Run Agent

1python cookbook/11_models/google/gemini/knowledge.py