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