Knowledge Source Types

Agent(knowledge=...) accepts local file paths and plain text — URLs are not ingested and are skipped with a warning.

from praisonaiagents import Agent

agent = Agent(
    name="Reader",
    instructions="Answer from the provided notes.",
    knowledge=["notes.pdf", "Key fact: launch is in March."],
)
agent.start("When is the launch?")

What Each Source Does

_process_knowledge inspects every item and routes it by type.

Source	Example	Behaviour
Local file path	`"notes.pdf"`	`Knowledge.add(path)` — read and indexed
Plain string	`"Key fact: ..."`	`Knowledge.store(text)` — stored as text
URL	`"https://example.com"`	Warns and skips — not ingested

Agent(knowledge=["https://..."]) does not fetch the URL. It logs:

Knowledge source 'https://example.com...' is a URL; URL knowledge ingestion is not yet implemented in the core SDK. This source will be skipped. Fetch and pass the content as text, or a local file path, instead.

Only the scheme and host are logged — credentials and query strings are redacted.

Fetch, Then Pass Text

Fetch the page yourself and pass the text as a knowledge source.

import requests
from praisonaiagents import Agent

text = requests.get("https://example.com/article").text
agent = Agent(name="Reader", instructions="Summarise the article.", knowledge=[text])
agent.start("Summarise it.")

Knowledge.add(url) used directly also does not fetch URLs — it raises NotImplementedError("URL processing not yet implemented"). Use the fetch-then-text recipe above for both the Agent and direct-Knowledge paths.

Best Practices

Convert web content to text before ingesting

Fetch pages with requests, httpx, or a scraper, then pass the extracted text as a knowledge string.

Prefer local files for documents

Save PDFs and docs locally and pass the path — Knowledge.add(path) reads and chunks them for you.

Check logs if a source seems missing

A skipped URL logs a warning; if answers lack a source you expected, confirm it was a file or text, not a URL.

Knowledge Base

Chunking, embedding, and search options.

RAG

Retrieval-augmented generation patterns.

Getting Started

Install

Core Concepts

Guides

Features

Models

Databases

Observability

Memory

Telemetry & Analytics

Knowledge

RAG

Persistence

Tools

Other Features

Developers

Configuration

Best Practices

Getting Started (No Code)

Knowledge Source Types

What Each Source Does

Fetch, Then Pass Text

Best Practices

Knowledge Base

RAG

​What Each Source Does

​Fetch, Then Pass Text

​Best Practices

​Related

Knowledge Base

RAG

What Each Source Does

Fetch, Then Pass Text

Best Practices

Related