Knowledge Overview

Give your agents access to documents and data

Knowledge Overview

Knowledge allows your agents to answer questions using your own documents - PDFs, text files, web pages, and more.

How It Works

1. Add documents → Chunked and indexed
2. Ask questions → Agent retrieves relevant context
3. Get answers → With source citations

Quick Start

from praisonaiagents import Agent

agent = Agent(
    name="Research Assistant",
    knowledge=["research.pdf", "docs/"]
)

response = agent.start("What are the key findings?")

That’s it! The agent can now answer questions using your documents.

When to Use

Approach	Best For	Link
Agent(knowledge=[...])	Most use cases	Quick Start →
Knowledge() class	Custom indexing	Knowledge API →
RAG() class	Custom pipelines	RAG Module →

Knowledge vs Memory vs RAG

Feature	Knowledge	Memory	RAG
Purpose	Answer from documents	Remember conversations	Retrieve + Generate
Data Source	Files, URLs	Conversations	Knowledge base
Updates	Manual (re-index)	Automatic	Uses Knowledge
Best For	Q&A, research	Chat continuity	Citations, search

What Knowledge.search() returns

Knowledge.search() returns a typed SearchResult from praisonaiagents.knowledge.models.

Field	Type	Description
results	list[SearchResultItem]	Ranked items
metadata	dict	Search-level metadata (always dict, never None)
query	str	Original query string
total_count	int	Total available (may exceed len(results) if paginated)

A SearchResult is a dataclass, so it is always truthy — even when empty. Check .results instead of the object.

# ❌ Wrong — SearchResult is a dataclass, always truthy
if not results:
    print("No results")

# ✅ Right — check .results (or .total_count)
if not results.results:
    print("No results")

from praisonaiagents import Agent
from praisonaiagents.knowledge import Knowledge

knowledge = Knowledge()
knowledge.store("Paris is the capital of France.")

results = knowledge.search("capital of France", user_id="alice")

for item in results.results:
    print(f"[{item.score:.2f}] {item.text}  ({item.source or '-'})")

Each SearchResultItem can be passed directly into RAG context utilities like build_context and deduplicate_chunks. See Search Results for the full field reference.

Next Steps

Quick Start

Get started in 5 minutes

Storage Options

Configure vector stores

Chat with PDFs

Build a PDF chat agent

RAG

Advanced retrieval