Praison AI

RAG Agent CLI

Command-line interface for RAG agents

Build and run RAG agents from the command line.

Diagram

User

RAG Agent

Knowledge Base

Quick Start

  1. Simple Usage
    bash
    praisonai-ts run --knowledge my-kb --prompt "What is PraisonAI?"
  2. With Configuration
    bash
    praisonai-ts chat --knowledge my-kb --instructions "Answer from docs" --model gpt-4o

Commands

Create Knowledge Base

bash
# Create a new knowledge base
praisonai-ts knowledge create my-kb

# Add documents
praisonai-ts knowledge add my-kb ./documents/

# Add from URL
praisonai-ts knowledge add my-kb https://example.com/doc.pdf

Query Knowledge Base

bash
# Query the knowledge base
praisonai-ts knowledge query my-kb "What is PraisonAI?"

# Query with options
praisonai-ts knowledge query my-kb "question" --top-k 5 --min-score 0.7

Run RAG Agent

bash
# Run agent with knowledge base
praisonai-ts run \
  --instructions "Answer questions using the knowledge base" \
  --knowledge my-kb \
  --prompt "What is PraisonAI?"

# Interactive mode
praisonai-ts chat \
  --knowledge my-kb \
  --instructions "You are a helpful assistant"

Options

OptionTypeDefaultDescription
--knowledgestring–Knowledge base name or path
--top-knumber5Number of results to retrieve
--min-scorenumber0.7Minimum similarity score
--rerankbooleanfalseEnable reranking
--citationsstringinlineCitation format

Examples

Build Knowledge Base from Directory

bash
# Add all PDFs from a directory
praisonai-ts knowledge add docs-kb ./docs/ --pattern "*.pdf"

# Add with metadata
praisonai-ts knowledge add docs-kb ./docs/ \
  --metadata '{"source": "documentation", "version": "1.0"}'

RAG Chat Session

bash
# Start interactive RAG chat
praisonai-ts chat \
  --knowledge docs-kb \
  --instructions "Answer questions about the documentation" \
  --model gpt-4o

Export Knowledge Base

bash
# Export to JSON
praisonai-ts knowledge export docs-kb --output kb-export.json

# Import from JSON
praisonai-ts knowledge import new-kb --input kb-export.json

Environment Variables

VariableRequiredDescription
OPENAI_API_KEYYesFor embeddings
PINECONE_API_KEYFor PineconePinecone API key

Related

RAG Agent SDK

Build RAG agents in code

 Knowledge Base

Manage knowledge bases