A Rust LLM CLI client
Now we have a LLM running locally with an API we build a small CLI client as a proof of concept.
Firstly, thanks to openai-api-rs for adding this feature to allow us to use their crate on local LLM's.
Create a project
Run the following
cargo new llm-cli
then a quick sanity check
$ cargo run --bin llm-cli
Compiling llm-cli v0.1.0 (/workspace/crates/llm-cli)
Finished dev [unoptimized + debuginfo] target(s) in 0.27s
Running `target/debug/llm-cli`
Hello, world!
Add the openai-api-rs
library
$ cd llm-cli
$ cargo add openai-api-rs
Updating crates.io index
Adding openai-api-rs v0.1.12 to dependencies.
Updating crates.io index
OpenSSL
I generally don't install OpenSSL and use RustTLS instead. This is in an effort to keep the size of deployment containers down.
However openai-api-rs
does require OpenSSL so we need the following.
sudo apt-get install -y pkg-config
The Code
use openai_api_rs::v1::api::Client;
use openai_api_rs::v1::chat_completion::{self, ChatCompletionRequest};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = Client::new_with_endpoint("http://llm-api:8080".to_string(), "NOKEY".to_string());
let req = ChatCompletionRequest {
model: "ggml-gpt4all-j".to_string(),
messages: vec![chat_completion::ChatCompletionMessage {
role: chat_completion::MessageRole::user,
content: String::from("What is Bitcoin?"),
name: None,
function_call: None,
}],
functions: None,
function_call: None,
temperature: None,
top_p: None,
n: None,
stream: None,
stop: None,
max_tokens: None,
presence_penalty: None,
frequency_penalty: None,
logit_bias: None,
user: None,
};
let result = client.chat_completion(req).await?;
println!("{:?}", result.choices[0].message.content);
Ok(())
}
TODO
- There's a problem decoding the response. - https://github.com/dongri/openai-api-rs/issues/20