axiom-memory

pip install axiom-memory

from axiom import MemoryStore

store = MemoryStore()

# Store a memory
store.remember("Brian prefers dark mode", tags=["preference", "user-brian"])

# Search later
results = store.search("dark mode", limit=5)

# See what you know
print(store.stats())
# → Total: 42 memories, Avg importance: 0.67

$ axiom chat
Axiom Chat — I remember everything you tell me.
Type 'exit' to quit, 'stats' for memory stats.

You> I'm Brian, I'm building an AI startup in Nairobi
  → Remembered (id=f5db1eff, importance=0.55)

You> I love Python and dark mode
  → Remembered (id=878939c2, importance=0.55)

You> stats
Total memories: 8
Avg importance: 0.550

You> exit
Goodbye!

$ axiom chat
Welcome back! I remember 8 things about you.

You> What do you know about me?
  → Remembered (id=a1b2c3d4, importance=0.66)
  💡 Related: Brian prefers dark mode

{
  "mcpServers": {
    "axiom-memory": {
      "command": "axiom",
      "args": ["serve", "--port", "8765"]
    }
  }
}

axiom remember "Brian likes Python" --tags preference,user-brian
axiom search "Python"
axiom stats
axiom chat            # Interactive persistent chatbot
axiom export backup.json
axiom import backup.json
axiom serve           # Start MCP server

from axiom import MemoryStore

store = MemoryStore("memories.db")

# Core operations
store.remember("content", tags=["tag"], importance=0.8)
store.recall("memory-id")
store.search("query", limit=10, tags=["python"], min_importance=0.5)
store.update("memory-id", content="new content", importance=0.95)
store.forget("memory-id")
store.stats()

# Import / Export
store.export_json("backup.json")
store.import_json("backup.json")

# LLM-powered extraction (requires OpenAI key)
store.extract_from_conversation("I love building AI agents in Python")

axiom/
├── core/
│   ├── memory.py          # Memory model (Pydantic)
│   ├── store.py           # MemoryStore — main API
│   ├── storage/           # Pluggable storage backends
│   │   ├── base.py        # StorageBackend ABC
│   │   └── sqlite.py      # SQLite implementation
│   ├── search/            # Pluggable search engines
│   │   ├── base.py        # SearchEngine ABC
│   │   └── keyword.py     # FTS5 keyword search
│   ├── scoring/           # Pluggable scoring engines
│   │   ├── base.py        # ScoringEngine ABC
│   │   └── simple.py      # Recency + usage + importance
│   └── dream.py           # DreamEngine interface (future)
├── llm/extractor.py       # Optional LLM extraction
├── mcp/server.py          # MCP server
├── cli.py                 # CLI tool
├── io.py                  # JSON import/export
└── config.py              # Settings

from axiom.core.storage.base import StorageBackend

class MyStorage(StorageBackend):
    def store(self, memory): ...
    def retrieve(self, memory_id): ...
    def update(self, memory): ...
    def delete(self, memory_id): ...
    def search(self, query, limit, offset): ...
    def list_all(self, limit, offset): ...
    def count(self): ...
    def count_by_type(self): ...
    def all_tags(self): ...
    def increment_usage(self, memory_id): ...
    def get_all(self): ...

store = MemoryStore(storage=MyStorage())

git clone https://github.com/mungaibriankariuki-collab/axiom-memory
cd axiom-memory
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pre-commit install
pytest --cov=axiom