ZIm/crates/lmstudio/src/lmstudio.rs
Umesh Yadav a743035286
lmstudio: Fix streaming not working in v0.3.15 (#30013)
Closes #29781

Tested this with llama3, gemma3 and qwen3.

This is a breaking change, which means after adding this code changes in
future version zed we will require atleast lmstudio >= 0.3.15. For
context why it's breaking changes check out the issue: #29781.

What this doesn't try to solve is:

* Tool calling, thinking text rendering. Will raise a seperate PR for
these as those are not required in this PR to make it work.


https://github.com/user-attachments/assets/945f9c73-6323-4a88-92e2-2219b760a249

Release Notes:

- lmstudio: Fixed Zed support for LMStudio >= v0.3.15 (breaking change -- older versions are no longer supported).

---------

Co-authored-by: Peter Tripp <peter@zed.dev>
2025-05-06 12:59:36 -04:00

377 lines
10 KiB
Rust

use anyhow::{Context as _, Result, anyhow};
use futures::{AsyncBufReadExt, AsyncReadExt, StreamExt, io::BufReader, stream::BoxStream};
use http_client::{AsyncBody, HttpClient, Method, Request as HttpRequest, http};
use serde::{Deserialize, Serialize};
use serde_json::{Value, value::RawValue};
use std::{convert::TryFrom, sync::Arc, time::Duration};
pub const LMSTUDIO_API_URL: &str = "http://localhost:1234/api/v0";
#[derive(Clone, Copy, Serialize, Deserialize, Debug, Eq, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum Role {
User,
Assistant,
System,
Tool,
}
impl TryFrom<String> for Role {
type Error = anyhow::Error;
fn try_from(value: String) -> Result<Self> {
match value.as_str() {
"user" => Ok(Self::User),
"assistant" => Ok(Self::Assistant),
"system" => Ok(Self::System),
"tool" => Ok(Self::Tool),
_ => Err(anyhow!("invalid role '{value}'")),
}
}
}
impl From<Role> for String {
fn from(val: Role) -> Self {
match val {
Role::User => "user".to_owned(),
Role::Assistant => "assistant".to_owned(),
Role::System => "system".to_owned(),
Role::Tool => "tool".to_owned(),
}
}
}
#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq)]
pub struct Model {
pub name: String,
pub display_name: Option<String>,
pub max_tokens: usize,
}
impl Model {
pub fn new(name: &str, display_name: Option<&str>, max_tokens: Option<usize>) -> Self {
Self {
name: name.to_owned(),
display_name: display_name.map(|s| s.to_owned()),
max_tokens: max_tokens.unwrap_or(2048),
}
}
pub fn id(&self) -> &str {
&self.name
}
pub fn display_name(&self) -> &str {
self.display_name.as_ref().unwrap_or(&self.name)
}
pub fn max_token_count(&self) -> usize {
self.max_tokens
}
}
#[derive(Serialize, Deserialize, Debug)]
#[serde(tag = "role", rename_all = "lowercase")]
pub enum ChatMessage {
Assistant {
#[serde(default)]
content: Option<String>,
#[serde(default)]
tool_calls: Option<Vec<LmStudioToolCall>>,
},
User {
content: String,
},
System {
content: String,
},
}
#[derive(Serialize, Deserialize, Debug)]
#[serde(rename_all = "lowercase")]
pub enum LmStudioToolCall {
Function(LmStudioFunctionCall),
}
#[derive(Serialize, Deserialize, Debug)]
pub struct LmStudioFunctionCall {
pub name: String,
pub arguments: Box<RawValue>,
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct LmStudioFunctionTool {
pub name: String,
pub description: Option<String>,
pub parameters: Option<Value>,
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
#[serde(tag = "type", rename_all = "lowercase")]
pub enum LmStudioTool {
Function { function: LmStudioFunctionTool },
}
#[derive(Serialize, Debug)]
pub struct ChatCompletionRequest {
pub model: String,
pub messages: Vec<ChatMessage>,
pub stream: bool,
pub max_tokens: Option<i32>,
pub stop: Option<Vec<String>>,
pub temperature: Option<f32>,
pub tools: Vec<LmStudioTool>,
}
#[derive(Serialize, Deserialize, Debug)]
pub struct ChatResponse {
pub id: String,
pub object: String,
pub created: u64,
pub model: String,
pub choices: Vec<ChoiceDelta>,
}
#[derive(Serialize, Deserialize, Debug)]
pub struct ChoiceDelta {
pub index: u32,
#[serde(default)]
pub delta: serde_json::Value,
pub finish_reason: Option<String>,
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct ToolCallChunk {
pub index: usize,
pub id: Option<String>,
// There is also an optional `type` field that would determine if a
// function is there. Sometimes this streams in with the `function` before
// it streams in the `type`
pub function: Option<FunctionChunk>,
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct FunctionChunk {
pub name: Option<String>,
pub arguments: Option<String>,
}
#[derive(Serialize, Deserialize, Debug)]
pub struct Usage {
pub prompt_tokens: u32,
pub completion_tokens: u32,
pub total_tokens: u32,
}
#[derive(Serialize, Deserialize, Debug)]
#[serde(untagged)]
pub enum ResponseStreamResult {
Ok(ResponseStreamEvent),
Err { error: String },
}
#[derive(Serialize, Deserialize, Debug)]
pub struct ResponseStreamEvent {
pub created: u32,
pub model: String,
pub choices: Vec<ChoiceDelta>,
pub usage: Option<Usage>,
}
#[derive(Serialize, Deserialize)]
pub struct ListModelsResponse {
pub data: Vec<ModelEntry>,
}
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct ModelEntry {
pub id: String,
pub object: String,
pub r#type: ModelType,
pub publisher: String,
pub arch: Option<String>,
pub compatibility_type: CompatibilityType,
pub quantization: Option<String>,
pub state: ModelState,
pub max_context_length: Option<u32>,
pub loaded_context_length: Option<u32>,
}
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum ModelType {
Llm,
Embeddings,
Vlm,
}
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
#[serde(rename_all = "kebab-case")]
pub enum ModelState {
Loaded,
Loading,
NotLoaded,
}
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
#[serde(rename_all = "lowercase")]
pub enum CompatibilityType {
Gguf,
Mlx,
}
#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
pub struct ResponseMessageDelta {
pub role: Option<Role>,
pub content: Option<String>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub tool_calls: Option<Vec<ToolCallChunk>>,
}
pub async fn complete(
client: &dyn HttpClient,
api_url: &str,
request: ChatCompletionRequest,
) -> Result<ChatResponse> {
let uri = format!("{api_url}/chat/completions");
let request_builder = HttpRequest::builder()
.method(Method::POST)
.uri(uri)
.header("Content-Type", "application/json");
let serialized_request = serde_json::to_string(&request)?;
let request = request_builder.body(AsyncBody::from(serialized_request))?;
let mut response = client.send(request).await?;
if response.status().is_success() {
let mut body = Vec::new();
response.body_mut().read_to_end(&mut body).await?;
let response_message: ChatResponse = serde_json::from_slice(&body)?;
Ok(response_message)
} else {
let mut body = Vec::new();
response.body_mut().read_to_end(&mut body).await?;
let body_str = std::str::from_utf8(&body)?;
Err(anyhow!(
"Failed to connect to API: {} {}",
response.status(),
body_str
))
}
}
pub async fn stream_chat_completion(
client: &dyn HttpClient,
api_url: &str,
request: ChatCompletionRequest,
) -> Result<BoxStream<'static, Result<ChatResponse>>> {
let uri = format!("{api_url}/chat/completions");
let request_builder = http::Request::builder()
.method(Method::POST)
.uri(uri)
.header("Content-Type", "application/json");
let request = request_builder.body(AsyncBody::from(serde_json::to_string(&request)?))?;
let mut response = client.send(request).await?;
if response.status().is_success() {
let reader = BufReader::new(response.into_body());
Ok(reader
.lines()
.filter_map(|line| async move {
match line {
Ok(line) => {
let line = line.strip_prefix("data: ")?;
if line == "[DONE]" {
None
} else {
let result = serde_json::from_str(&line)
.context("Unable to parse chat completions response");
if let Err(ref e) = result {
eprintln!("Error parsing line: {e}\nLine content: '{line}'");
}
Some(result)
}
}
Err(e) => {
eprintln!("Error reading line: {e}");
Some(Err(e.into()))
}
}
})
.boxed())
} else {
let mut body = String::new();
response.body_mut().read_to_string(&mut body).await?;
Err(anyhow!(
"Failed to connect to LM Studio API: {} {}",
response.status(),
body,
))
}
}
pub async fn get_models(
client: &dyn HttpClient,
api_url: &str,
_: Option<Duration>,
) -> Result<Vec<ModelEntry>> {
let uri = format!("{api_url}/models");
let request_builder = HttpRequest::builder()
.method(Method::GET)
.uri(uri)
.header("Accept", "application/json");
let request = request_builder.body(AsyncBody::default())?;
let mut response = client.send(request).await?;
let mut body = String::new();
response.body_mut().read_to_string(&mut body).await?;
if response.status().is_success() {
let response: ListModelsResponse =
serde_json::from_str(&body).context("Unable to parse LM Studio models response")?;
Ok(response.data)
} else {
Err(anyhow!(
"Failed to connect to LM Studio API: {} {}",
response.status(),
body,
))
}
}
/// Sends an empty request to LM Studio to trigger loading the model
pub async fn preload_model(client: Arc<dyn HttpClient>, api_url: &str, model: &str) -> Result<()> {
let uri = format!("{api_url}/completions");
let request = HttpRequest::builder()
.method(Method::POST)
.uri(uri)
.header("Content-Type", "application/json")
.body(AsyncBody::from(serde_json::to_string(
&serde_json::json!({
"model": model,
"messages": [],
"stream": false,
"max_tokens": 0,
}),
)?))?;
let mut response = client.send(request).await?;
if response.status().is_success() {
Ok(())
} else {
let mut body = String::new();
response.body_mut().read_to_string(&mut body).await?;
Err(anyhow!(
"Failed to connect to LM Studio API: {} {}",
response.status(),
body,
))
}
}