Skip to main content

DevMemory is a long‑term memory for AI coding agents. Make AI knowledge searchable.

Project description

DevMemory 🧠🚀

CI PyPI License: MIT

AI code attribution that answers "why?" — for developers and AI agents.

Built on Git AI for capture and Redis Agent Memory Server for semantic search and recall.

For local mode we use sqlite

Status: currently in Beta.

AI code attribution that answers "why?" — for developers and AI agents.

DevMemory tracks which AI tool wrote which line of code, then makes that knowledge searchable. Ask "why did we use this pattern?" and get answers backed by commits, prompts, and context.


Quick Install

# One-line install (local mode)
curl -sSL https://raw.githubusercontent.com/AI-Provenance/ai-dev-memory/main/scripts/install-simple.sh | bash

Then in your project:

devmemory install --mode local

Choose Your Setup

Option 1: Local (SQLite) — Free, No Infrastructure

For tracking AI code attributions locally without external services.

# 1. Install
pip install devmemory

# 2. Set up in your repo
cd your-project
devmemory install --mode local

# 3. Start coding — commits auto-sync
git commit -m "feat: new login"  # AI attribution tracked automatically
devmemory attribution lookup path/to/file.py  # See who wrote what

What's included:

  • AI code line attribution (SQLite)
  • Git hooks for auto-sync
  • devmemory attribution commands
  • Sentry error tracking with AI attributions

Sentry Integration

When an error hits Sentry, see which AI tool and model wrote the code that caused it.

Python:

import sentry_sdk
from devmemory.sentry import create_before_send

sentry_sdk.init(
    dsn="YOUR_SENTRY_DSN",
    before_send=create_before_send(),
)

Node.js / Next.js:

npm install @aiprovenance/sentry
import { createDevMemoryBeforeSend } from "@aiprovenance/sentry";

Sentry.init({
  dsn: process.env.NEXT_PUBLIC_SENTRY_DSN,
  beforeSend(event, hint) {
    return createDevMemoryBeforeSend()(event, hint);
  },
});

Auto-detects repoId from git remote or DEVMEMORY_REPO_ID env var.

This adds ai_model, ai_tool, author, commit_sha, and other tags to every Sentry event.


Option 2: Cloud (Redis AMS) — Full Features

Note: Full Cloud mode is coming soon. Some features below require additional setup.

For teams who want semantic search, team stats, and AI agent memory.

# 1. Install
pip install devmemory

# 2. Start Redis AMS
docker compose --profile debug up -d

# 3. Set up in your repo
cd your-project
devmemory install --mode cloud

# Start using
devmemory why src/auth.py          # Ask why a file looks this way
devmemory search "how do we auth?" # Semantic search
devmemory stats                    # AI vs Human code stats

What's included:

  • Everything in Local mode
  • Semantic memory search
  • Team code statistics
  • Cursor/Claude agent integration
  • Context briefings on branch switch

Sentry integration (Cloud): Error tracking with AI attribution is coming soon — requires API call to enrich events.


Why DevMemory?

For Developers For AI Agents
"Why did we choose this pattern?" Start with repo context, not from scratch
"Who wrote this — AI or human?" Remember what previous agents learned
Team AI vs Human code stats Reuse knowledge across sessions

With Sentry Integration: Errors automatically include AI attribution data — see exactly which AI tool and model generated the code that caused the crash.


Commands

Local Mode

Command Description
devmemory attribution lookup <file> See who wrote each line
devmemory attribution history <file> View attribution history
devmemory sync Sync Git AI notes to SQLite
devmemory status Check system health

Cloud Mode

Command Description
devmemory why <file> Explain why a file/function looks this way
devmemory search <query> Semantic search across all memories
devmemory stats AI vs Human code contribution
devmemory attribution lookup <file> See who wrote each line
devmemory attribution history <file> View attribution history
devmemory sync Sync Git AI notes to AMS
devmemory status Check system health

Requirements

  • Python 3.10+
  • Git AI — for capturing AI code attribution
  • (Cloud mode) Docker — for Redis AMS

Learn More


Stop re-explaining your code. Let DevMemory remember.

Project details


Download files

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

Source Distribution

devmemory-0.1.31.tar.gz (9.7 MB view details)

Uploaded Source

Built Distribution

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

devmemory-0.1.31-py3-none-any.whl (98.2 kB view details)

Uploaded Python 3

File details

Details for the file devmemory-0.1.31.tar.gz.

File metadata

  • Download URL: devmemory-0.1.31.tar.gz
  • Upload date:
  • Size: 9.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for devmemory-0.1.31.tar.gz
Algorithm Hash digest
SHA256 a27a67472583278ddcc80228331cb828b8c5d4b6c07fa48c976656ce2e063f43
MD5 9fd25d89970277663ad4479c77336250
BLAKE2b-256 8d52e91f7dcb1d2850b65125cb275ab838995e9610dec3b7338e22f39e6fe606

See more details on using hashes here.

File details

Details for the file devmemory-0.1.31-py3-none-any.whl.

File metadata

  • Download URL: devmemory-0.1.31-py3-none-any.whl
  • Upload date:
  • Size: 98.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for devmemory-0.1.31-py3-none-any.whl
Algorithm Hash digest
SHA256 506a678d926df5a1e433e3474870f67389412d177169d0902fdd01183732fe3e
MD5 94206a60a341a682edde22ab28364f05
BLAKE2b-256 bde4ba5a887647227d2be10455e32fb27da6dcf98aaebe6b512a8284e281b4ef

See more details on using hashes here.

Supported by

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