The PDF Reader processes PDF 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/pdf_reader_sync.py
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.pdf_reader import PDFReader
from agno.vectordb.pgvector import PgVector

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

# Create a knowledge base with PDF documents
knowledge = Knowledge(
    vector_db=PgVector(
        table_name="pdf_documents",
        db_url=db_url,
    )
)

# Add PDF content synchronously
knowledge.add_content(
    path="cookbook/knowledge/testing_resources/cv_1.pdf",
    reader=PDFReader(),
)

# Create an agent with the knowledge base
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

# Query the knowledge base
agent.print_response(
    "What skills does an applicant require to apply for the Software Engineer position?",
    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 pypdf 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/pdf_reader_sync.py

​
Params

ParameterTypeDefaultDescription
pathPathRequiredPath to PDF file or URL
split_on_pagesboolTrueSplit the PDF into pages
page_start_numbering_formatOptional[str]NoneFormat for page numbering
page_end_numbering_formatOptional[str]NoneFormat for page numbering
passwordOptional[str]NonePassword to unlock the PDF