devmemory 0.1.29

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

DevMemory 🧠🚀

DevMemory is a long‑term memory for AI coding agents that can explain why any file or function looks the way it does and let agents reuse that understanding across sessions without re-reading the whole repo.

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.

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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 (Local Mode)

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

import sentry_sdk
from devmemory.sentry import create_before_send

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

This adds ai_model, ai_tool, author, commit_sha, and other tags and context to every Sentry event from your app.

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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.

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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.

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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

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Requirements

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

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Learn More

• Documentation
• GitHub

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Stop re-explaining your code. Let DevMemory remember.