LlamaIndex Integration

CortexDB integrates with LlamaIndex as a memory store, providing persistent hybrid-retrieval memory for agents and query engines.

Installation

pip install cortexdb[llamaindex]

As a Memory Store

from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI
from cortexdb.integrations.llamaindex import CortexMemoryStore

memory = CortexMemoryStore(
    api_key="your-cortex-api-key",
    tenant_id="my-app",
)

agent = ReActAgent.from_tools(
    tools,
    llm=OpenAI(model="gpt-4o"),
    memory=memory,
    verbose=True,
)

response = agent.chat("Remember that our API rate limit is 1000 req/s per tenant.")
# Later...
response = agent.chat("What is our API rate limit?")

As a Retriever

from cortexdb.integrations.llamaindex import CortexRetriever
from llama_index.core.query_engine import RetrieverQueryEngine

retriever = CortexRetriever(
    api_key="your-cortex-api-key",
    tenant_id="my-app",
    top_k=10,
)

query_engine = RetrieverQueryEngine.from_args(retriever)
response = query_engine.query("What architectural decisions have been made?")

Configuration

| Parameter | Default | Description | |---|---|---| | api_key | $CORTEX_API_KEY | CortexDB API key | | tenant_id | Required | Tenant identifier | | namespace | None | Memory namespace | | top_k | 10 | Results per recall | | auto_remember | True | Auto-store conversation turns |