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# SeekDB Vector Database Integration
This document describes how to use OceanBase SeekDB as the vector database backend for LangBot's knowledge base feature.
## What is SeekDB?
**OceanBase SeekDB** is an AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows. It's developed by OceanBase and released under Apache 2.0 license.
### Key Features
- **Hybrid Search**: Combine vector search, full-text search and relational query in a single statement
- **Multi-Model Support**: Support relational, vector, text, JSON and GIS in a single engine
- **Lightweight**: Requires as little as 1 CPU core and 2 GB of memory
- **Multiple Deployment Modes**: Supports both embedded mode and client/server mode
- **MySQL Compatible**: Powered by OceanBase engine with full ACID compliance and MySQL compatibility
## Installation
SeekDB support is automatically included when you install LangBot. The required dependency `pyseekdb` is listed in `pyproject.toml`.
If you need to install it manually:
```bash
pip install pyseekdb
```
## ⚠️ Platform Compatibility
### Embedded Mode
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full embedded mode support via `pylibseekdb` |
| macOS | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
| Windows | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
**Important**: Embedded mode requires the `pylibseekdb` library, which is only available on Linux. If you're on macOS or Windows, you must use server mode.
### Server Mode (Docker)
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full Docker support |
| macOS | ⚠️ Known Issue | Docker container initialization failure - [See Issue #36](https://github.com/oceanbase/seekdb/issues/36) |
| Windows | ⚠️ Untested | Should work but not yet tested |
**macOS Users**: Currently, SeekDB Docker containers have an initialization issue on macOS ([oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36)). Until this is resolved, we recommend:
- Using ChromaDB or Qdrant as alternatives
- Connecting to a remote SeekDB server on Linux if available
### Server Mode (Remote Connection)
| Platform | Status | Notes |
|----------|--------|-------|
| All Platforms | ✅ Supported | Connect to SeekDB running on a remote Linux server |
**Recommendation for macOS/Windows users**: Deploy SeekDB on a Linux server and connect via server mode configuration.
## Configuration
### Embedded Mode (Recommended for Development)
Embedded mode runs SeekDB directly within the LangBot process, storing data locally. This is the simplest setup and requires no external services.
Edit your `config.yaml`:
```yaml
vdb:
use: seekdb
seekdb:
mode: embedded
path: './data/seekdb' # Path to store SeekDB data
database: 'langbot' # Database name
```
### Server Mode (For Production)
Server mode connects to a remote SeekDB server or OceanBase server. This is recommended for production deployments.
#### SeekDB Server
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
database: 'langbot'
user: 'root'
password: '' # Can also use SEEKDB_PASSWORD env var
```
#### OceanBase Server
If you're using OceanBase with seekdb capabilities:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
tenant: 'sys' # OceanBase tenant name
database: 'langbot'
user: 'root'
password: ''
```
## Configuration Parameters
| Parameter | Required | Default | Description |
|-----------|----------|--------------|-------------|
| `mode` | No | `embedded` | Deployment mode: `embedded` or `server` |
| `path` | No | `./data/seekdb` | Data directory for embedded mode |
| `database` | No | `langbot` | Database name |
| `host` | No | `localhost` | Server host (server mode only) |
| `port` | No | `2881` | Server port (server mode only) |
| `user` | No | `root` | Username (server mode only) |
| `password` | No | `''` | Password (server mode only) |
| `tenant` | No | None | OceanBase tenant (optional, server mode only) |
## Usage
Once configured, SeekDB will be used automatically for all knowledge base operations in LangBot:
1. **Creating Knowledge Bases**: Vectors will be stored in SeekDB collections
2. **Adding Documents**: Document embeddings will be indexed in SeekDB
3. **Searching**: Vector similarity search will use SeekDB's efficient indexing
4. **Deleting**: Document removal will delete vectors from SeekDB
No code changes are required - just update your configuration!
## Architecture Details
### Implementation
The SeekDB adapter is implemented in `src/langbot/pkg/vector/vdbs/seekdb.py` and follows the same `VectorDatabase` interface as Chroma and Qdrant adapters.
Key methods:
- `add_embeddings()`: Add vectors with metadata to a collection
- `search()`: Perform vector similarity search
- `delete_by_file_id()`: Delete vectors by file ID metadata
- `get_or_create_collection()`: Manage collections
- `delete_collection()`: Remove entire collections
### Vector Storage
- Collections are created with HNSW (Hierarchical Navigable Small World) index
- Default distance metric: Cosine similarity
- Default vector dimension: 384 (adjusts automatically based on embeddings)
- Metadata is stored alongside vectors for filtering
## Advantages Over Other Vector Databases
### vs. ChromaDB
- ✅ Better MySQL compatibility
- ✅ Hybrid search capabilities (vector + full-text + SQL)
- ✅ Production-grade distributed mode support
- ✅ Lightweight embedded mode
### vs. Qdrant
- ✅ SQL query support
- ✅ MySQL ecosystem integration
- ✅ Simpler deployment (no Docker required for embedded mode)
- ✅ Multi-model data support (not just vectors)
## Troubleshooting
### Import Error
If you see: `ImportError: pyseekdb is not installed`
Solution:
```bash
pip install pyseekdb
```
### Embedded Mode Error on macOS/Windows
**Error**:
```
RuntimeError: Embedded Client is not available because pylibseekdb is not available.
Please install pylibseekdb (Linux only) or use RemoteServerClient (host/port) instead.
```
**Cause**: `pylibseekdb` is only available on Linux platforms.
**Solution**: Use server mode instead:
1. Deploy SeekDB on a Linux server or VM
2. Configure LangBot to use server mode:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'your-seekdb-server-ip'
port: 2881
database: 'langbot'
user: 'root'
password: ''
```
**Alternative**: Use ChromaDB or Qdrant, which work on all platforms:
```yaml
vdb:
use: chroma # or qdrant
```
### Docker Container Fails on macOS
**Symptoms**:
```bash
docker run -d -p 2881:2881 oceanbase/seekdb:latest
# Container exits immediately with code 30
```
**Error in logs**:
```
[ERROR] Code: Agent.SeekDB.Not.Exists
Message: initialize failed: init agent failed: SeekDB not exists in current directory.
```
**Cause**: This is a known issue with SeekDB Docker containers on macOS. See [oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36).
**Status**: Under investigation by OceanBase team.
**Workaround Options**:
1. **Use alternatives**: ChromaDB or Qdrant work perfectly on macOS
2. **Remote server**: Deploy SeekDB on a Linux server and connect remotely
3. **Wait for fix**: Monitor the GitHub issue for updates
### Connection Error (Server Mode)
If SeekDB server is not reachable, check:
1. Server is running: `ps aux | grep observer`
2. Port is accessible: `nc -zv localhost 2881`
3. Credentials are correct in config
4. Firewall allows connections on port 2881
### Performance Issues
For large datasets:
- Use server mode instead of embedded mode
- Ensure adequate memory allocation
- Consider using OceanBase distributed mode for very large scale
- Adjust HNSW index parameters if needed
## Resources
- SeekDB GitHub: https://github.com/oceanbase/seekdb
- pyseekdb SDK: https://github.com/oceanbase/pyseekdb
- OceanBase Documentation: https://oceanbase.ai
- LangBot Documentation: https://docs.langbot.app
## License
SeekDB is licensed under Apache License 2.0.