memos-ai 0.2.0

Python SDK for memos — persistent brain framework for AI agents

MEMOS Python SDK

Python SDK for MEMOS — persistent brain framework for AI agents.

Installation

pip install memos-ai

Publish Verification

python3 -m venv verify
source verify/bin/activate
pip install memos-ai
python3

from memos import MemosClient

print(MemosClient)

Expected output:

<class 'memos.client.MemosClient'>

Quick Start

from memos import MemosClient

client = MemosClient(
    api_key="your_api_key",
    agent_id="your_agent_id"
)

# Store a memory
memory = client.store_memory(
    content="User prefers Python over JavaScript",
    type="semantic",
    importance=4
)

# Search memories
results = client.search("language preferences")
for r in results:
    print(f"{r.score:.2f} — {r.content}")

# Ask with memory context
response = client.query("What language does this user prefer?")
print(response.answer)

# Trigger dream consolidation
dream = client.trigger_dream()
print(f"Created {dream.new_memories_created} new memories")

Authentication

Get your API key and agent ID from https://memos.io/dashboard

Methods Reference

Method	Parameters	Returns	Description
store_memory	content (str), type (str="episodic"), importance (int=3), tags (list[str]=None)	Memory	Store a new memory for the agent
list_memories	None	list[Memory]	List all memories for the agent
delete_memory	memory_id (str)	bool	Delete a specific memory by ID
search	query (str), search_type (str="keyword"), limit (int=10)	list[SearchResult]	Search agent memories
query	question (str), include_sources (bool=True), conversation_history (list[dict]=None)	RAGResponse	Ask a question using RAG
trigger_dream	None	DreamResult	Trigger a dream consolidation cycle
list_skills	None	list[Skill]	List all available skills in the marketplace
execute_skill	skill_id (str), input (str)	SkillResult	Execute a skill
run_pipeline	steps (list[dict]), input (str)	dict	Run a multi-step pipeline
get_identity	None	dict	Get the agent's identity and reputation

Error Handling

from memos import MemosError, AuthError, RateLimitError

try:
    client.store_memory("...")
except AuthError:
    print("Check your API key at memos.io/profile")
except RateLimitError:
    print("Rate limit hit — slow down requests")
except MemosError as e:
    print(f"API error {e.status_code}: {e.message}")

Context Manager

with MemosClient(api_key="...", agent_id="...") as client:
    client.store_memory("...")
# HTTP connection closed automatically

Requirements

Python 3.11+ No additional dependencies beyond httpx.

License

MIT