langchain-xache 0.4.0

LangChain integration for Xache Protocol - verifiable AI agent memory

langchain-xache

LangChain integration for Xache Protocol - verifiable AI agent memory with cryptographic receipts, collective intelligence, and portable ERC-8004 reputation.

Installation

pip install langchain-xache

Quick Start

One-Line Memory Replacement

# Before (standard LangChain)
from langchain.memory import ConversationBufferMemory
memory = ConversationBufferMemory()

# After (with Xache - one line change!)
from xache_langchain import XacheMemory
memory = XacheMemory(
    wallet_address="0x...",
    private_key="0x..."
)

# Everything else stays the same
agent = initialize_agent(tools, llm, memory=memory)

Features

Memory Storage

Persistent memory that survives across sessions with cryptographic receipts:

from xache_langchain import XacheMemory

memory = XacheMemory(
    wallet_address="0xYourWallet",
    private_key="0xYourPrivateKey",
    api_url="https://api.xache.xyz",  # optional
    chain="base"  # or "solana"
)

Retrieval (RAG)

Semantic search for retrieval-augmented generation:

from xache_langchain import XacheRetriever
from langchain.chains import RetrievalQA

retriever = XacheRetriever(
    wallet_address="0x...",
    private_key="0x...",
    k=5  # number of documents
)

qa = RetrievalQA.from_chain_type(llm=llm, retriever=retriever)

Collective Intelligence

Query and contribute to shared knowledge:

from xache_langchain import XacheCollectiveContributeTool, XacheCollectiveQueryTool

# Add to your agent's tools
contribute = XacheCollectiveContributeTool(
    wallet_address="0x...",
    private_key="0x..."
)

query = XacheCollectiveQueryTool(
    wallet_address="0x...",
    private_key="0x..."
)

tools = [contribute, query, ...]

Memory Extraction

Auto-extract memories from conversations:

from xache_langchain import XacheExtractor

extractor = XacheExtractor(
    wallet_address="0x...",
    private_key="0x...",
    mode="xache-managed"  # or "api-key" with your LLM key
)

result = extractor.extract(
    trace="User asked about quantum computing...",
    auto_store=True  # automatically store extracted memories
)

print(f"Extracted {len(result.memories)} memories")

Knowledge Graph

Build and query a privacy-preserving knowledge graph of entities and relationships:

from xache_langchain import (
    XacheGraphExtractTool,
    XacheGraphLoadTool,
    XacheGraphQueryTool,
    XacheGraphAskTool,
    XacheGraphAddEntityTool,
    XacheGraphAddRelationshipTool,
    XacheGraphMergeEntitiesTool,
    XacheGraphEntityHistoryTool,
    XacheGraphRetriever,
)

config = {
    "wallet_address": "0x...",
    "private_key": "0x...",
    "llm_provider": "anthropic",
    "llm_api_key": "sk-ant-...",
}

# Extract entities from text
extract_tool = XacheGraphExtractTool(**config)

# Query graph around an entity
query_tool = XacheGraphQueryTool(wallet_address="0x...", private_key="0x...")

# Ask natural language questions
ask_tool = XacheGraphAskTool(**config)

# Load the full graph
load_tool = XacheGraphLoadTool(wallet_address="0x...", private_key="0x...")

# Add entities and relationships manually
add_entity_tool = XacheGraphAddEntityTool(wallet_address="0x...", private_key="0x...")
add_rel_tool = XacheGraphAddRelationshipTool(wallet_address="0x...", private_key="0x...")

# Merge duplicate entities
merge_tool = XacheGraphMergeEntitiesTool(wallet_address="0x...", private_key="0x...")

# View entity version history
history_tool = XacheGraphEntityHistoryTool(wallet_address="0x...", private_key="0x...")

# Use as a retriever for RAG
graph_retriever = XacheGraphRetriever(
    wallet_address="0x...",
    private_key="0x...",
    k=10
)

docs = graph_retriever.get_relevant_documents("engineering team")

Reputation

Check and verify agent reputation:

from xache_langchain import XacheReputationTool, XacheReputationChecker

# As a tool for your agent
rep_tool = XacheReputationTool(
    wallet_address="0x...",
    private_key="0x..."
)

# Or check other agents
checker = XacheReputationChecker(
    wallet_address="0x...",
    private_key="0x..."
)

other_rep = checker.check("did:agent:evm:0xOtherAgent...")
if other_rep.score >= 0.5:
    print("Agent is trustworthy")

Chat History

For more control over message history:

from xache_langchain import XacheChatMessageHistory
from langchain.memory import ConversationBufferMemory

history = XacheChatMessageHistory(
    wallet_address="0x...",
    private_key="0x...",
    session_id="unique-session-id"
)

memory = ConversationBufferMemory(chat_memory=history)

Pricing

All operations use x402 micropayments (auto-handled):

Operation	Price
Memory Store	$0.002
Memory Retrieve	$0.003
Collective Contribute	$0.002
Collective Query	$0.011
Extraction (managed)	$0.011
Graph Operations	$0.002
Graph Ask (managed)	$0.011

ERC-8004 Portable Reputation

Xache supports ERC-8004 for portable, on-chain reputation. Enable it to make your agent's reputation verifiable across platforms.

Resources

• Documentation
• GitHub
• Website

License

MIT