Membase

Membase is the first decentralized AI memory layer for AI agents.It provides secure, scalable storage for conversation history, knowledge bases, and blockchain-synced task coordination.

Membase ensures that agents have long-term, verifiable memory — a critical foundation for sovereign, self-evolving AI agents in Web3.

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Key Features

• Decentralized Memory: Persistent storage for conversations, interactions, and prompts.

• Knowledge Base Management: Embedding and retrieval of structured documents using local or remote vector stores.

• Blockchain Task Coordination: Smart contract-based task registry and reward distribution.

• Storage Hub Integration: Sync conversations and documents to a decentralized memory hub.

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Installation

pip install git+https://github.com/unibaseio/membase.git
# or clone into local
git clone https://github.com/unibaseio/membase.git
cd membase
pip install -e .

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Quick Start Examples

Multi-Memory (Conversation Management)

from membase.memory.multi_memory import MultiMemory
from membase.memory.message import Message

mm = MultiMemory(membase_account="default", auto_upload_to_hub=True, preload_from_hub=True)

msg = Message(
    name="agent9527",
    content="Hello! How can I help you?",
    role="assistant",
    metadata="help info"
)

conversation_id = 'your_conversation'
mm.add(msg, conversation_id)

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Buffered Memory (Simple Memory)

from membase.memory.buffered_memory import BufferedMemory
from membase.memory.message import Message

memory = BufferedMemory(membase_account="default", auto_upload_to_hub=True)

msg = Message(
    name="agent9527",
    content="Hello! How can I help you?",
    role="assistant",
    metadata="help info"
)

memory.add(msg)

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Knowledge Base Management

from membase.knowledge.chroma import ChromaKnowledgeBase
from membase.knowledge.document import Document

kb = ChromaKnowledgeBase(
    persist_directory="/tmp/test",
    membase_account="default",
    auto_upload_to_hub=True
)

doc = Document(
    content="The quick brown fox jumps over the lazy dog.",
    metadata={"source": "test", "date": "2025-03-05"}
)

kb.add_documents(doc)

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Blockchain Task Coordination

Set environment variables first:

export MEMBASE_ID="<unique_id>"
export MEMBASE_ACCOUNT="<your_account_address>"
export MEMBASE_SECRET_KEY="<your_secret_key>"

Create and complete tasks:

from membase.chain.chain import membase_chain

task_id = "task0227"
price = 100000

# Create task
membase_chain.createTask(task_id, price)

# Register and join task
agent_id = "alice"
membase_chain.register(agent_id)
membase_chain.joinTask(task_id, agent_id)

# Complete task
membase_chain.finishTask(task_id, agent_id)

# View task info
membase_chain.getTask(task_id)

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Resources

• GitHub Repository: Membase GitHub

• Documentation: Coming soon on Gitbook

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