The AOS TEE Operator is a role of EigenAVS in Hetu Protocols.
By registering with AOS on Dispatcher, the operator could service the AI inference verification task.The staker can delegate funds to an operator by Delegation Manager contract.
The Llm-In-TEE is a novelty framworks to run a TEE verification node service. And the AOS TEE Operators are TEE workers and building on Llm-In-TEE framwork.
Run large AI models and verifiable logic clock in TEE environment.
Firstly, the semantic TEE of this repository is mainly refer to aws nitro enclave for now.
Other TEE instances maybe support for later. For examples,
- Mircosoft Azure,
- Intel SGX,
- AMD SEV
- or Nvidia Confidential Computing GPU
The Llm-In-TEE use the llama.cpp as it's large AI models executor.
Second core module verifiable logic clock is an implementation of Chronos's TEE backend.
The Chronos is a novel logical clock system designed for open networks with Byzantine participants, offering improved fault tolerance and performance. Please refer to hetu chronos repository for more details.
git clone https://github.com/hetu-project/aos-tee-operator.git
cd llm-in-tee
git submodule update --init --recursive
cargo build --features nitro-enclaves --release
Now, this repository use the aws nitro enclave as its trust execution environment.
So, please create a cloud virtual instance and notice choose the Amazon-2023 linux
as base image.
Because this base operator system is more friendly for using of the aws nitro enclave.
- Prepare Env & install dependency tools
sudo sudo dnf upgrade
sudo dnf install -y tmux htop openssl-devel perl docker-24.0.5-1.amzn2023.0.3 aws-nitro-enclaves-cli aws-nitro-enclaves-cli-devel
- Configuration
Please cat /etc/nitro_enclaves/allocator.yaml
and set cpu_count & memory_mib. For tee_vlc: just 2 core + 1024 M
is enough, for tee_llm: 4 core + 16384 M
at least. Update the file and save it.
- run
init.sh
cd scripts
sudo chmod +x init_env.sh
./init_env.sh
Remember please re-run the script when you update the /etc/nitro_enclaves/allocator.yaml
.
Please see Run TEE Operator for more detail information.