slm-remember

# SuperLocalMemory: Remember

Save content to your local memory system with automatic indexing, knowledge graph integration, and pattern learning.

## Usage

```bash
slm remember "<content>" [--tags tag1,tag2] [--project name] [--importance 1-10]
```

## Examples

### Example 1: Basic Memory
```bash
slm remember "We use FastAPI for REST APIs"
```

**What happens:**
- Content saved to SQLite database
- TF-IDF vectors generated for semantic search
- Entities extracted and added to knowledge graph
- Pattern learning analyzes for coding preferences
- Memory ID returned (e.g., 42)

### Example 2: With Tags
```bash
slm remember "JWT tokens expire after 24 hours" --tags security,auth,jwt
```

**Tags help with:**
- Organization
- Filtering
- Related memory discovery

### Example 3: With Project
```bash
slm remember "Database uses PostgreSQL 15 with UUID primary keys" --project myapp --tags database,postgresql
```

**Project isolation:**
- Separate memories per project
- Switch profiles with `slm switch-profile`
- No context bleeding

### Example 4: Important Memory
```bash
slm remember "CRITICAL: Production deploy requires approval from @lead" --importance 10 --tags deployment,production
```

**Importance (1-10):**
- 1-3: Low priority (notes, ideas)
- 4-6: Normal (coding patterns, decisions)
- 7-9: High priority (critical info, warnings)
- 10: Critical (blockers, security issues)

## Arguments

| Argument | Type | Required | Default | Description |
|----------|------|----------|---------|-------------|
| `<content>` | string | Yes | - | The text to remember |
| `--tags` | string | No | None | Comma-separated tags |
| `--project` | string | No | "default" | Project name |
| `--importance` | integer | No | 5 | Priority level (1-10) |

## Output

```
Memory added with ID: 42

✅ Memory saved successfully

Next steps:
  • Use `slm recall <query>` to search this memory
  • Use `slm list` to see recent memories
```

## What Happens Behind the Scenes

1. **Content Storage:** Saved to SQLite (`~/.superlocalmemory/memory.db`)
2. **Semantic Indexing:** TF-IDF vectors generated for similarity search
3. **Knowledge Graph:** Entities extracted and nodes/edges created
4. **Pattern Learning:** Analyzes content for coding preferences (frameworks, style, testing)
5. **Full-Text Index:** FTS5 index updated for fast keyword search
6. **Timestamp:** Created timestamp recorded

## Advanced Usage

### Natural Language (in AI chat)

Most AI assistants will automatically invoke this skill when you say:
- "Remember that..."
- "Save this for later..."
- "I want to store..."
- "Keep track of..."

**Example in Cursor/Claude:**
```
You: "Remember that we decided to use React hooks over class components"
AI: [Automatically invokes slm-remember skill]
✓ Memory saved
```

### Bulk Import

Save multiple memories from a file:
```bash
# From text file (one memory per line)
while IFS= read -r line; do
  slm remember "$line" --project bulk-import
done < memories.txt

# From CSV (content,tags,project)
while IFS=',' read -r content tags project; do
  slm remember "$content" --tags "$tags" --project "$project"
done < memories.csv
```

### Integration with Git Hooks

**Pre-commit hook** (save commit messages):
```bash
#!/bin/bash
# .git/hooks/post-commit

commit_msg=$(git log -1 --pretty=%B)
commit_hash=$(git log -1 --pretty=%H)

slm remember "Commit: $commit_msg (${commit_hash:0:7})" \
  --tags git,commit \
  --project "$(basename $(git rev-parse --show-toplevel))"
```

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| "Database locked" | Another process accessing DB | Wait or `killall python3` |
| "Content cannot be empty" | Empty string passed | Provide content |
| "Invalid importance" | Value not 1-10 | Use number between 1-10 |
| "Database not found" | SuperLocalMemory not installed | Run `./install.sh` |

## Notes

- **100% local:** Nothing leaves your machine
- **Cross-tool sync:** All AI tools access same database (Cursor, ChatGPT, Claude, etc.)
- **Unlimited:** No memory limits, no quotas
- **Privacy:** Your data stays on your computer
- **Profiles:** Use `slm switch-profile` for profile isolation

## Related Commands

- `slm recall "<query>"` - Search memories semantically
- `slm list` - List recent memories
- `slm status` - Check system health
- `slm build-graph` - Rebuild knowledge graph
- `slm switch-profile <name>` - Switch memory profile

## Technical Details

**Database Schema:**
- Table: `memories`
- Fields: id, content, tags, project_name, importance, created_at, etc.
- Indexes: Full-text search (FTS5), TF-IDF vectors, timestamps

**Performance:**
- Add memory: ~50ms
- With knowledge graph: ~300ms
- Large content (10KB): ~1s

**Limits:**
- Max content size: 1MB
- Max tags: 50 per memory
- Max project name: 64 characters

---

**Created by:** [Varun Pratap Bhardwaj](https://github.com/varun369) (Solution Architect)
**Project:** SuperLocalMemory V3
**License:** AGPL-3.0 (see [LICENSE](../../LICENSE))
**Repository:** https://github.com/qualixar/superlocalmemory

*Open source doesn't mean removing credit. Attribution must be preserved per AGPL-3.0 terms.*