ChainMemory Python SDK
Permanent memory for AI agents on the ChainMemory blockchain.
Install
pip install chainmemory
Quick Start
from chainmemory import ChainMemory
# Generate new API key
cm = ChainMemory.create()
# Get AIC from https://faucet.chainmemory.ai
# Or use existing key
cm = ChainMemory(api_key="aic_...")
# Register your AI
cm.register("MyAgent", "gpt-4")
# Write a memory (instant response, syncs to blockchain in ~30s)
memory = cm.remember(
"Decided to use Python for ML pipeline",
category="DECISION",
importance=8
)
print(memory["memory_id"]) # 1
print(memory["tier"]) # episodic
print(memory["chain_sync"]) # pending -> synced in 30s
# Recall memories
memories = cm.recall(limit=10)
for m in memories:
print(f"[{m['category']}] {m['summary']}")
# Get profile
profile = cm.profile()
print(f"Total memories: {profile['local_memories']}")
print(f"Synced to chain: {profile['synced_memories']}")
# Network stats (no API key needed)
stats = ChainMemory.stats()
print(f"Block: {stats['block']}")
print(f"Chain ID: {stats['chain_id']}")
LangChain Integration
from langchain.memory import ConversationBufferMemory
from chainmemory import ChainMemory
cm = ChainMemory(api_key="aic_...")
cm.register("LangChainAgent", "gpt-4")
# Save conversation turns to ChainMemory
def save_to_chainmemory(human_input, ai_output):
cm.remember(
f"User: {human_input[:140]} | AI: {ai_output[:140]}",
category="INTERACTION",
importance=5,
platform="langchain"
)
Categories
| Category | Use Case |
|---|---|
| DECISION | Important decisions made |
| LEARNING | New knowledge acquired |
| INTERACTION | Conversation summaries |
| STATE | Agent state changes |
| ERROR | Errors and corrections |
| MILESTONE | Key achievements |
| CUSTOM | Everything else |
Network
| Field | Value |
|---|---|
| Chain ID | 202604 |
| Currency | AIC (native) |
| RPC | https://rpc.chainmemory.ai |
| Explorer | https://chainmemory.ai |
| Faucet | https://faucet.chainmemory.ai |
License
MIT — ChainMemory — The permanent memory layer for artificial intelligence.
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