lotus/documentation/en/mining-lotus-seal-worker.md

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# Lotus Seal Worker
The **Lotus Seal Worker** is an extra process that can offload heavy processing tasks from your **Lotus Storage Miner**. It can be run on the same machine as your `lotus-storage-miner`, or on another machine communicating over a fast network.
## Note: Using the Lotus Seal Worker from China
If you are trying to use `lotus-seal-worker` from China. You should set this **environment variable** on your machine:
```sh
IPFS_GATEWAY="https://proof-parameters.s3.cn-south-1.jdcloud-oss.com/ipfs/"
```
## Get Started
Make sure that the `lotus-seal-worker` is installed by running:
```sh
make lotus-seal-worker
```
## Running Alongside Storage Miner
You may wish to run the **Lotus Seal Worker** on the same computer as the **Lotus Storage Miner**. This allows you to easily set the process priority of the sealing tasks to be lower than the priority of your more important storage miner process.
To do this, simply run `lotus-seal-worker run`, and the seal worker will automatically pick up the correct authentication tokens from the `LOTUS_STORAGE_PATH` miner repository.
To check that the **Lotus Seal Worker** is properly connected to your storage miner, run `lotus-storage-miner info` and check that the remote worker count has increased.
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```sh
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why@computer ~/lotus> lotus-storage-miner workers list
Worker 0, host computer
CPU: [ ] 0 core(s) in use
RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
GPU: GeForce RTX 2080, not used
Worker 1, host computer
CPU: [ ] 0 core(s) in use
RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
GPU: GeForce RTX 2080, not used
```
## Running Over the Network
Warning: This setup is a little more complex than running it locally.
To use an entirely separate computer for sealing tasks, you will want to run the `lotus-seal-worker` on a separate machine, connected to your **Lotus Storage Miner** via the local area network.
First, you will need to ensure your `lotus-storage-miner`'s API is accessible over the network.
To do this, open up `~/.lotusstorage/config.toml` (Or if you manually set `LOTUS_STORAGE_PATH`, look under that directory) and look for the API field.
Default config:
```toml
[API]
ListenAddress = "/ip4/127.0.0.1/tcp/2345/http"
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RemoteListenAddress = "127.0.0.1:2345"
```
To make your node accessible over the local area network, you will need to determine your machines IP on the LAN, and change the `127.0.0.1` in the file to that address.
A more permissive and less secure option is to change it to `0.0.0.0`. This will allow anyone who can connect to your computer on that port to access the [API](https://docs.lotu.sh/en+api). They will still need an auth token.
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`RemoteListenAddress` must be set to an address which other nodes on your network will be able to reach
Next, you will need to [create an authentication token](https://docs.lotu.sh/en+api-scripting-support#generate-a-jwt-46). All Lotus APIs require authentication tokens to ensure your processes are as secure against attackers attempting to make unauthenticated requests to them.
### Connect the Lotus Seal Worker
On the machine that will run `lotus-seal-worker`, set the `STORAGE_API_INFO` environment variable to `TOKEN:STORAGE_NODE_MULTIADDR`. Where `TOKEN` is the token we created above, and `STORAGE_NODE_MULTIADDR` is the `multiaddr` of the **Lotus Storage Miner** API that was set in `config.toml`.
Once this is set, run:
```sh
lotus-seal-worker run
```
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To check that the **Lotus Seal Worker** is connected to your **Lotus Storage Miner**, run `lotus-storage-miner workers list` and check that the remote worker count has increased.
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```sh
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why@computer ~/lotus> lotus-storage-miner workers list
Worker 0, host computer
CPU: [ ] 0 core(s) in use
RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
GPU: GeForce RTX 2080, not used
Worker 1, host othercomputer
CPU: [ ] 0 core(s) in use
RAM: [|||||||||||||| ] 23% 14 GiB/62.7 GiB
VMEM: [|||||||||||||| ] 23% 14 GiB/62.7 GiB
GPU: GeForce RTX 2080, not used
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```