Framework Integrations

Memvid provides native adapters for the most popular AI frameworks. Each adapter exposes tools, retrievers, and utilities formatted specifically for that framework.

One Memory, Any Framework. The same .mv2 file works with all adapters. Switch frameworks without re-indexing your data.

Quick Comparison

Framework	Language	Best For
LangChain	Python, Node.js	Agents, chains, RAG
LlamaIndex	Python, Node.js	RAG pipelines, indexing
Vercel AI	Node.js	Next.js, streaming
OpenAI	Python, Node.js	Direct API, function calling
Google ADK	Python, Node.js	Gemini, ADK agents
AutoGen	Python, Node.js	Multi-agent systems
CrewAI	Python, Node.js	Agent crews
Semantic Kernel	Python, Node.js	Enterprise AI, Azure
Haystack	Python	Search pipelines

Choosing the Right Adapter

I'm building a RAG application

Recommended: LangChain or LlamaIndexUse the tools to search your knowledge base and build RAG pipelines.

# LangChain with tools
from memvid_sdk import use
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

mem = use('langchain', 'knowledge.mv2')
agent = create_react_agent(ChatOpenAI(model="gpt-4o"), mem.tools)
result = agent.invoke({"messages": [{"role": "user", "content": "What is..."}]})

# Or use find() + ask() directly
results = mem.find("search query", k=5)
answer = mem.ask("What is the main concept?")

I'm building an AI agent

Recommended: LangChain, AutoGen, or CrewAIThese frameworks excel at agent orchestration with tool use.

# LangChain Agent
from langgraph.prebuilt import create_react_agent
mem = use('langchain', 'knowledge.mv2')
agent = create_react_agent(model, mem.tools)

# AutoGen
mem = use('autogen', 'knowledge.mv2')
assistant = AssistantAgent("helper", llm_config={"tools": mem.tools})

I'm using Next.js / Vercel

Recommended: Vercel AI SDKNative streaming support and seamless integration with Next.js.

import { use } from '@memvid/sdk';
import { streamText } from 'ai';

const mem = await use('vercel-ai', 'knowledge.mv2');

export async function POST(req: Request) {
  const result = await streamText({
    model: openai('gpt-4o'),
    tools: mem.tools,
    messages: await req.json(),
  });
  return result.toDataStreamResponse();
}

I want direct OpenAI/Gemini function calling

Recommended: OpenAI or Google ADKUse the native function calling APIs without framework overhead.

# OpenAI
mem = use('openai', 'knowledge.mv2')
response = client.chat.completions.create(
    model="gpt-4o",
    tools=mem.tools,
    messages=[...]
)

# Google Gemini
mem = use('google-adk', 'knowledge.mv2')
chat = client.chats.create(
    model="gemini-2.0-flash",
    config=types.GenerateContentConfig(tools=[mem.tools])
)

I'm building enterprise AI with Azure

Recommended: Semantic KernelMicrosoft’s SDK with enterprise features and Azure integration.

mem = use('semantic-kernel', 'knowledge.mv2')
kernel.add_plugin(mem.tools, "memvid")

Universal Features

All adapters provide these core capabilities:

Tools / Functions

Every adapter exposes three primary tools:

Tool	Description
`memvid_put`	Store documents in memory
`memvid_find`	Search for relevant documents
`memvid_ask`	Ask questions with RAG synthesis

# Access tools (framework-specific format)
tools = mem.tools

Direct API Access

You can always bypass the adapter and use the core API directly:

# These work with any adapter
results = mem.find('search query', k=10)
answer = mem.ask('What is machine learning?')
timeline = mem.timeline(limit=50)
stats = mem.stats()

Installation

Each adapter requires its framework to be installed:

Node.js
Python

# Core SDK
npm install @memvid/sdk

# Framework dependencies (install what you need)
npm install @langchain/core @langchain/openai   # LangChain
npm install llamaindex                          # LlamaIndex
npm install ai @ai-sdk/openai                   # Vercel AI
npm install openai                              # OpenAI
npm install @google/generative-ai              # Google ADK

# Core SDK
pip install memvid-sdk

# Framework dependencies (install what you need)
pip install "memvid-sdk[langchain]"        # LangChain
pip install "memvid-sdk[llamaindex]"       # LlamaIndex
pip install "memvid-sdk[openai]"           # OpenAI
pip install google-genai                   # Google ADK
pip install "memvid-sdk[autogen]"          # AutoGen
pip install "memvid-sdk[crewai]"           # CrewAI
pip install "memvid-sdk[semantic-kernel]"  # Semantic Kernel
pip install "memvid-sdk[haystack]"         # Haystack

# Or install all integrations:
pip install "memvid-sdk[full]"