The S3PDFKnowledgeBase reads PDF files from an S3 bucket, converts them into vector embeddings and loads them to a vector databse.

​
Usage

We are using a local PgVector database for this example. Make sure it’s running

from phi.knowledge.s3.pdf import S3PDFKnowledgeBase
from phi.vectordb.pgvector import PgVector

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

knowledge_base = S3PDFKnowledgeBase(
    bucket_name="phi-public",
    key="recipes/ThaiRecipes.pdf",
    vector_db=PgVector(table_name="recipes", db_url=db_url),
)

Then use the knowledge_base with an Agent:

from phi.agent import Agent
from knowledge_base import knowledge_base

agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)
agent.knowledge.load(recreate=False)

agent.print_response("How to make Thai curry?")

​
Params

ParameterTypeDefaultDescription
readerS3PDFReaderS3PDFReader()A S3PDFReader that converts the PDFs into Documents for the vector database.
vector_dbVectorDb-Vector Database for the Knowledge Base.
num_documentsint5Number of documents to return on search.
optimize_onint-Number of documents to optimize the vector db on.
chunking_strategyChunkingStrategyFixedSizeChunkingThe chunking strategy to use.

Was this page helpful?

PDF URLsS3 Text