The Markdown Reader processes Markdown files synchronously and converts them into documents that can be used with Agno’s knowledge system.

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Code

examples/concepts/knowledge/readers/markdown_reader_sync.py
from pathlib import Path

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.markdown_reader import MarkdownReader
from agno.vectordb.pgvector import PgVector

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

knowledge = Knowledge(
    vector_db=PgVector(
        table_name="markdown_documents",
        db_url=db_url,
    ),
)

# Add Markdown content to knowledge base
knowledge.add_content(
    path=Path("README.md"),
    reader=MarkdownReader(),
)

agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

# Query the knowledge base
agent.print_response(
    "What can you tell me about this project?",
    markdown=True,
)

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install libraries

pip install -U markdown sqlalchemy psycopg pgvector agno openai
3

Set environment variables

export OPENAI_API_KEY=xxx
4

Run 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 \
  agno/pgvector:16
5

Run Agent

python examples/concepts/knowledge/readers/markdown_reader_sync.py