Integrations

Dakera provides official integration packages for the most popular AI/agent frameworks. Each integration wraps the Dakera REST API into framework-native components — memory backends, vector stores, and session managers.

Supported Frameworks

Framework Package Language Memory VectorStore Sessions Graph
LangChain langchain-dakera Python ✓ ✓ ✓ ✓
LangChain.js @dakera-ai/langchain TypeScript ✓ ✓ ✓ ✓
CrewAI crewai-dakera Python ✓ ✓ ✓
LlamaIndex llamaindex-dakera Python ✓ ✓ ✓ ✓
AutoGen autogen-dakera Python ✓ ✓ ✓

Getting Started

All integrations follow the same pattern:

  1. Run Dakera — start the server with Docker or from source
  2. Install the package — pip install <package> or npm install <package>
  3. Configure — set DAKERA_API_URL and DAKERA_API_KEY environment variables
  4. Use — import the framework-native class and pass it to your chain/agent

Choosing an Integration

Building a conversational chain? Use LangChain or LangChain.js — they provide both BaseMemory and VectorStore implementations.

Multi-agent orchestration? Use CrewAI or AutoGen — they provide per-agent memory isolation with cross-agent recall.

RAG pipeline? Use LlamaIndex — the DakeraIndexStore integrates directly with LlamaIndex's ingestion pipeline.

Common Configuration

All integrations accept these environment variables:

VariableDescriptionDefault
DAKERA_API_URLDakera server URLhttp://localhost:3300
DAKERA_API_KEYAPI key for authentication(none)

All Integrations