Knowledge Overview

from definable.embedder import OpenAIEmbedder
from definable.knowledge import Knowledge
from definable.vectordb import InMemoryVectorDB

# Create a knowledge base
knowledge = Knowledge(
    vector_db=InMemoryVectorDB(),
    embedder=OpenAIEmbedder(),
)

# Add content
knowledge.add("Python is a programming language created by Guido van Rossum.")
knowledge.add("JavaScript is the language of the web.")

# Search
results = knowledge.search("Who created Python?")
for doc in results:
    print(f"[{doc.reranking_score or 'n/a'}] {doc.content}")

from definable.agent import Agent

agent = Agent(model="gpt-4o-mini", knowledge="./docs/")

# Plain text
knowledge.add("Definable is an AI agent framework.")

# From a text file
knowledge.add("/path/to/document.txt")

# From a PDF
knowledge.add("/path/to/report.pdf")

# From a URL
knowledge.add("https://example.com/article")

results = knowledge.search(
    query="What is Definable?",
    top_k=5,         # Number of results
    rerank=True,     # Apply reranking (if reranker is configured)
)

await knowledge.aadd("New content to index.")
results = await knowledge.asearch("Search query")

# Add and get document IDs
doc_ids = knowledge.add("Some content")

# Remove specific documents
knowledge.remove(doc_ids)

# Clear everything
knowledge.clear()

# Count documents
print(len(knowledge))