Skip to main content

cortex-memory

Persistent memory engine for AI agents. Local-first, sub-millisecond, zero cloud.

Native Python binding for Cortex — a Rust memory engine with 4-tier memory, Bayesian beliefs, people graph, and HNSW vector search.

Install

pip install cortex-ai-memory

Quick Start

from cortex_python import PyCortex

# Open or create a memory database
cx = PyCortex("memory.db")

# Ingest memories
cx.ingest("Met Alice at the Q3 planning meeting", "slack", user_id="alice_123")
cx.ingest("User prefers dark mode", "cli")

# Retrieve relevant memories
results = cx.retrieve("What do I know about Alice?", limit=5)
for memory_id, score, text in results:
    print(f"[{score:.2f}] {text}")

# Generate LLM-ready context (token-budgeted)
context = cx.get_context(2000, channel="slack")

# Structured knowledge
cx.add_fact("Alice", "works_at", "Acme Corp", 0.95, "slack")
cx.add_preference("timezone", "Asia/Shanghai", 0.9)

# Bayesian beliefs
cx.observe_belief("user_likes_python", True, 0.8)
beliefs = cx.get_beliefs(0.5)

# People graph
cx.add_person("Alice", "slack", "alice_123")

# Consolidation (run periodically)
scanned, promoted, swept, patterns = cx.run_consolidation()

With Embeddings

For semantic search, pass embeddings from any provider:

import numpy as np

# Use any embedding model (OpenAI, ollama, sentence-transformers, etc.)
def embed(text):
    # your embedding function here
    ...

cx.ingest("I live in Shanghai", "cli", embedding=embed("I live in Shanghai"))
results = cx.retrieve("where do I live?", 5, embedding=embed("where do I live?"))

Features

  • 4-tier memory: Working, Episodic, Semantic, Procedural
  • HNSW vector search: Sub-millisecond at 100K+ memories
  • Bayesian beliefs: Self-correcting with evidence
  • People graph: Cross-channel identity resolution
  • Conversation compression: Automatic session summarization
  • Contradiction detection: Catches conflicting facts
  • Chinese + English: Native bilingual NLP
  • Zero cloud: 100% local, your data stays on your device
  • 3.8MB binary: Pure Rust, zero runtime dependencies

License

MIT

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cortex_ai_memory-2.2.0.tar.gz (211.2 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

cortex_ai_memory-2.2.0-cp312-cp312-macosx_11_0_arm64.whl (1.5 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

cortex_ai_memory-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

File details

Details for the file cortex_ai_memory-2.2.0.tar.gz.

File metadata

  • Download URL: cortex_ai_memory-2.2.0.tar.gz
  • Upload date:
  • Size: 211.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for cortex_ai_memory-2.2.0.tar.gz
Algorithm Hash digest
SHA256 78ace06646cc99b608c3ce7779d808c5f4422a79e5d403092cbb121c53359ad4
MD5 5b5a6533b45722f3b83398a456674beb
BLAKE2b-256 975256b0c365f3c1315ed9b6ceb854d69f0b40bfe98ae60229a6a33211015bcc

See more details on using hashes here.

Provenance

The following attestation bundles were made for cortex_ai_memory-2.2.0.tar.gz:

Publisher: release-python.yml on gambletan/cortex

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file cortex_ai_memory-2.2.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cortex_ai_memory-2.2.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b39540defa6007e8707add0788e4a0961416c92c094bc048f6c891ea14a767b0
MD5 6dcbd4300f5d36c7b61dba40a3396c49
BLAKE2b-256 1421e778fea0ebe096eddd86ecc420a1c0c4d585b13da0f61d7d5515d0f9c28f

See more details on using hashes here.

Provenance

The following attestation bundles were made for cortex_ai_memory-2.2.0-cp312-cp312-macosx_11_0_arm64.whl:

Publisher: release-python.yml on gambletan/cortex

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file cortex_ai_memory-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cortex_ai_memory-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cb6694737e2cb8d357797fe01b6062b1868115b44343729303c73884f347109e
MD5 bfd2381a52331498c5223c5fe39473f9
BLAKE2b-256 f59de17f75c7438ce2988328c8c2c85d558924b52556e1b2f03c2fd71e984318

See more details on using hashes here.

Provenance

The following attestation bundles were made for cortex_ai_memory-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: release-python.yml on gambletan/cortex

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

This release

2.2.0 This release

3 files

1.3.0

4 files

1.0.0

3 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page