Documentation Index
Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
Use this file to discover all available pages before exploring further.
ChromaDB
Embedded vector database for local development.
Setup
Quick Start (Agent with Knowledge)
Use ChromaDB as a knowledge store with an agent:
from praisonaiagents import Agent
# Agent with knowledge from files (uses ChromaDB by default)
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant with access to documents.",
knowledge=["./docs/guide.pdf", "./docs/faq.md"]
)
agent.chat("What does the guide say about getting started?")
Advanced Usage (Direct Store)
from praisonai.persistence.factory import create_knowledge_store
# Local file storage
store = create_knowledge_store("chroma", path="./chroma_data")
# Create collection
store.create_collection("documents", dimension=384)
# Insert documents
from praisonai.persistence.knowledge.base import KnowledgeDocument
doc = KnowledgeDocument(
content="PraisonAI is an AI agent framework",
embedding=[0.1] * 384,
metadata={"source": "docs"}
)
store.insert("documents", [doc])
# Search
results = store.search("documents", query_embedding, limit=5)
Configuration
| Option | Description |
|---|
path | Data directory path |
collection_metadata | Default collection metadata |