Knowledge Quick Start

Get started with knowledge-based agents in 5 minutes

Knowledge Quick Start

Give your agent access to documents and get answers with citations.

Installation

pip install "praisonaiagents[knowledge]"

1. Simplest Usage (Default)

from praisonaiagents import Agent

agent = Agent(
    name="Research Assistant",
    knowledge=["research.pdf"]  # Just pass files
)

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

2. Multiple Sources (Array)

from praisonaiagents import Agent

agent = Agent(
    name="Research Assistant",
    knowledge=[
        "paper.pdf",
        "notes.txt", 
        "docs/",           # Entire directory
        "https://example.com/article"  # URLs work too
    ]
)

response = agent.start("Summarize all documents")

3. Custom Configuration (Dict)

from praisonaiagents import Agent

agent = Agent(
    name="Research Assistant",
    knowledge={
        "sources": ["research.pdf", "data/"],
        "chunker": {
            "type": "semantic",      # Better topic boundaries
            "chunk_size": 512
        },
        "vector_store": {
            "provider": "chroma",
            "config": {"collection_name": "my_research"}
        }
    }
)

response = agent.start("What methodology was used?")

4. With Retrieval Options

from praisonaiagents import Agent

agent = Agent(
    name="Research Assistant",
    knowledge={
        "sources": ["research.pdf"],
        "retrieval_k": 5,            # Number of chunks
        "rerank": True               # Better relevance
    }
)

result = agent.query("What are the conclusions?")
print(result.answer)
print(result.citations)

5. Shared Knowledge (Instance)

from praisonaiagents import Agent
from praisonaiagents.knowledge import Knowledge

# Create shared knowledge base
kb = Knowledge(config={
    "vector_store": {"provider": "chroma"}
})
kb.add("company_docs/")

# Multiple agents share same knowledge
analyst = Agent(name="Analyst", knowledge=kb)
writer = Agent(name="Writer", knowledge=kb)

Supported File Types

Category	Formats
Documents	PDF, DOC, DOCX, TXT, MD, RTF
Data	CSV, JSON, XML, Excel
Web	URLs, HTML pages
Media	Images (OCR), YouTube

Next Steps

Storage Options

Configure vector stores

Chat with PDFs

Build a PDF chat agent

Chunking Strategies

Optimize document splitting

RAG

Advanced retrieval