use anyhow::{Context as _, Result, anyhow};use futures::{AsyncBufReadExt, AsyncReadExt, StreamExt, io::BufReader, stream::BoxStream};use http_client::{AsyncBody, HttpClient, Method, Request as HttpRequest};use serde::{Deserialize, Serialize};use serde_json::Value;use std::{convert::TryFrom, future::Future};use strum::EnumIter; pub const OPEN_AI_API_URL: &str = "https://api.openai.com/v1"; fn is_none_or_empty<T: AsRef<[U]>, U>(opt: &Option<T>) -> bool {    opt.as_ref().map_or(true, |v| v.as_ref().is_empty())} #[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),            _ => anyhow::bail!("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, EnumIter)]pub enum Model {    #[serde(rename = "gpt-3.5-turbo")]    ThreePointFiveTurbo,    #[serde(rename = "gpt-4")]    Four,    #[serde(rename = "gpt-4-turbo")]    FourTurbo,    #[serde(rename = "gpt-4o")]    #[default]    FourOmni,    #[serde(rename = "gpt-4o-mini")]    FourOmniMini,    #[serde(rename = "gpt-4.1")]    FourPointOne,    #[serde(rename = "gpt-4.1-mini")]    FourPointOneMini,    #[serde(rename = "gpt-4.1-nano")]    FourPointOneNano,    #[serde(rename = "o1")]    O1,    #[serde(rename = "o3-mini")]    O3Mini,    #[serde(rename = "o3")]    O3,    #[serde(rename = "o4-mini")]    O4Mini,     #[serde(rename = "custom")]    Custom {        name: String,        /// The name displayed in the UI, such as in the assistant panel model dropdown menu.        display_name: Option<String>,        max_tokens: u64,        max_output_tokens: Option<u64>,        max_completion_tokens: Option<u64>,    },} impl Model {    pub fn default_fast() -> Self {        Self::FourPointOneMini    }     pub fn from_id(id: &str) -> Result<Self> {        match id {            "gpt-3.5-turbo" => Ok(Self::ThreePointFiveTurbo),            "gpt-4" => Ok(Self::Four),            "gpt-4-turbo-preview" => Ok(Self::FourTurbo),            "gpt-4o" => Ok(Self::FourOmni),            "gpt-4o-mini" => Ok(Self::FourOmniMini),            "gpt-4.1" => Ok(Self::FourPointOne),            "gpt-4.1-mini" => Ok(Self::FourPointOneMini),            "gpt-4.1-nano" => Ok(Self::FourPointOneNano),            "o1" => Ok(Self::O1),            "o3-mini" => Ok(Self::O3Mini),            "o3" => Ok(Self::O3),            "o4-mini" => Ok(Self::O4Mini),            invalid_id => anyhow::bail!("invalid model id '{invalid_id}'"),        }    }     pub fn id(&self) -> &str {        match self {            Self::ThreePointFiveTurbo => "gpt-3.5-turbo",            Self::Four => "gpt-4",            Self::FourTurbo => "gpt-4-turbo",            Self::FourOmni => "gpt-4o",            Self::FourOmniMini => "gpt-4o-mini",            Self::FourPointOne => "gpt-4.1",            Self::FourPointOneMini => "gpt-4.1-mini",            Self::FourPointOneNano => "gpt-4.1-nano",            Self::O1 => "o1",            Self::O3Mini => "o3-mini",            Self::O3 => "o3",            Self::O4Mini => "o4-mini",            Self::Custom { name, .. } => name,        }    }     pub fn display_name(&self) -> &str {        match self {            Self::ThreePointFiveTurbo => "gpt-3.5-turbo",            Self::Four => "gpt-4",            Self::FourTurbo => "gpt-4-turbo",            Self::FourOmni => "gpt-4o",            Self::FourOmniMini => "gpt-4o-mini",            Self::FourPointOne => "gpt-4.1",            Self::FourPointOneMini => "gpt-4.1-mini",            Self::FourPointOneNano => "gpt-4.1-nano",            Self::O1 => "o1",            Self::O3Mini => "o3-mini",            Self::O3 => "o3",            Self::O4Mini => "o4-mini",            Self::Custom {                name, display_name, ..            } => display_name.as_ref().unwrap_or(name),        }    }     pub fn max_token_count(&self) -> u64 {        match self {            Self::ThreePointFiveTurbo => 16_385,            Self::Four => 8_192,            Self::FourTurbo => 128_000,            Self::FourOmni => 128_000,            Self::FourOmniMini => 128_000,            Self::FourPointOne => 1_047_576,            Self::FourPointOneMini => 1_047_576,            Self::FourPointOneNano => 1_047_576,            Self::O1 => 200_000,            Self::O3Mini => 200_000,            Self::O3 => 200_000,            Self::O4Mini => 200_000,            Self::Custom { max_tokens, .. } => *max_tokens,        }    }     pub fn max_output_tokens(&self) -> Option<u64> {        match self {            Self::Custom {                max_output_tokens, ..            } => *max_output_tokens,            Self::ThreePointFiveTurbo => Some(4_096),            Self::Four => Some(8_192),            Self::FourTurbo => Some(4_096),            Self::FourOmni => Some(16_384),            Self::FourOmniMini => Some(16_384),            Self::FourPointOne => Some(32_768),            Self::FourPointOneMini => Some(32_768),            Self::FourPointOneNano => Some(32_768),            Self::O1 => Some(100_000),            Self::O3Mini => Some(100_000),            Self::O3 => Some(100_000),            Self::O4Mini => Some(100_000),        }    }     /// Returns whether the given model supports the `parallel_tool_calls` parameter.    ///    /// If the model does not support the parameter, do not pass it up, or the API will return an error.    pub fn supports_parallel_tool_calls(&self) -> bool {        match self {            Self::ThreePointFiveTurbo            | Self::Four            | Self::FourTurbo            | Self::FourOmni            | Self::FourOmniMini            | Self::FourPointOne            | Self::FourPointOneMini            | Self::FourPointOneNano => true,            Self::O1 | Self::O3 | Self::O3Mini | Self::O4Mini | Model::Custom { .. } => false,        }    }} #[derive(Debug, Serialize, Deserialize)]pub struct Request {    pub model: String,    pub messages: Vec<RequestMessage>,    pub stream: bool,    #[serde(default, skip_serializing_if = "Option::is_none")]    pub max_completion_tokens: Option<u64>,    #[serde(default, skip_serializing_if = "Vec::is_empty")]    pub stop: Vec<String>,    pub temperature: f32,    #[serde(default, skip_serializing_if = "Option::is_none")]    pub tool_choice: Option<ToolChoice>,    /// Whether to enable parallel function calling during tool use.    #[serde(default, skip_serializing_if = "Option::is_none")]    pub parallel_tool_calls: Option<bool>,    #[serde(default, skip_serializing_if = "Vec::is_empty")]    pub tools: Vec<ToolDefinition>,} #[derive(Debug, Serialize, Deserialize)]#[serde(untagged)]pub enum ToolChoice {    Auto,    Required,    None,    Other(ToolDefinition),} #[derive(Clone, Deserialize, Serialize, Debug)]#[serde(tag = "type", rename_all = "snake_case")]pub enum ToolDefinition {    #[allow(dead_code)]    Function { function: FunctionDefinition },} #[derive(Clone, Debug, Serialize, Deserialize)]pub struct FunctionDefinition {    pub name: String,    pub description: Option<String>,    pub parameters: Option<Value>,} #[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]#[serde(tag = "role", rename_all = "lowercase")]pub enum RequestMessage {    Assistant {        content: Option<MessageContent>,        #[serde(default, skip_serializing_if = "Vec::is_empty")]        tool_calls: Vec<ToolCall>,    },    User {        content: MessageContent,    },    System {        content: MessageContent,    },    Tool {        content: MessageContent,        tool_call_id: String,    },} #[derive(Serialize, Deserialize, Clone, Debug, Eq, PartialEq)]#[serde(untagged)]pub enum MessageContent {    Plain(String),    Multipart(Vec<MessagePart>),} impl MessageContent {    pub fn empty() -> Self {        MessageContent::Multipart(vec![])    }     pub fn push_part(&mut self, part: MessagePart) {        match self {            MessageContent::Plain(text) => {                *self =                    MessageContent::Multipart(vec![MessagePart::Text { text: text.clone() }, part]);            }            MessageContent::Multipart(parts) if parts.is_empty() => match part {                MessagePart::Text { text } => *self = MessageContent::Plain(text),                MessagePart::Image { .. } => *self = MessageContent::Multipart(vec![part]),            },            MessageContent::Multipart(parts) => parts.push(part),        }    }} impl From<Vec<MessagePart>> for MessageContent {    fn from(mut parts: Vec<MessagePart>) -> Self {        if let [MessagePart::Text { text }] = parts.as_mut_slice() {            MessageContent::Plain(std::mem::take(text))        } else {            MessageContent::Multipart(parts)        }    }} #[derive(Serialize, Deserialize, Clone, Debug, Eq, PartialEq)]#[serde(tag = "type")]pub enum MessagePart {    #[serde(rename = "text")]    Text { text: String },    #[serde(rename = "image_url")]    Image { image_url: ImageUrl },} #[derive(Serialize, Deserialize, Clone, Debug, Eq, PartialEq)]pub struct ImageUrl {    pub url: String,    #[serde(skip_serializing_if = "Option::is_none")]    pub detail: Option<String>,} #[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]pub struct ToolCall {    pub id: String,    #[serde(flatten)]    pub content: ToolCallContent,} #[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]#[serde(tag = "type", rename_all = "lowercase")]pub enum ToolCallContent {    Function { function: FunctionContent },} #[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]pub struct FunctionContent {    pub name: String,    pub arguments: String,} #[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]pub struct ResponseMessageDelta {    pub role: Option<Role>,    pub content: Option<String>,    #[serde(default, skip_serializing_if = "is_none_or_empty")]    pub tool_calls: Option<Vec<ToolCallChunk>>,} #[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: u64,    pub completion_tokens: u64,    pub total_tokens: u64,} #[derive(Serialize, Deserialize, Debug)]pub struct ChoiceDelta {    pub index: u32,    pub delta: ResponseMessageDelta,    pub finish_reason: Option<String>,} #[derive(Serialize, Deserialize, Debug)]#[serde(untagged)]pub enum ResponseStreamResult {    Ok(ResponseStreamEvent),    Err { error: String },} #[derive(Serialize, Deserialize, Debug)]pub struct ResponseStreamEvent {    pub model: String,    pub choices: Vec<ChoiceDelta>,    pub usage: Option<Usage>,} pub async fn stream_completion(    client: &dyn HttpClient,    api_url: &str,    api_key: &str,    request: Request,) -> Result<BoxStream<'static, Result<ResponseStreamEvent>>> {    let uri = format!("{api_url}/chat/completions");    let request_builder = HttpRequest::builder()        .method(Method::POST)        .uri(uri)        .header("Content-Type", "application/json")        .header("Authorization", format!("Bearer {}", api_key));     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 {                            match serde_json::from_str(line) {                                Ok(ResponseStreamResult::Ok(response)) => Some(Ok(response)),                                Ok(ResponseStreamResult::Err { error }) => {                                    Some(Err(anyhow!(error)))                                }                                Err(error) => Some(Err(anyhow!(error))),                            }                        }                    }                    Err(error) => Some(Err(anyhow!(error))),                }            })            .boxed())    } else {        let mut body = String::new();        response.body_mut().read_to_string(&mut body).await?;         #[derive(Deserialize)]        struct OpenAiResponse {            error: OpenAiError,        }         #[derive(Deserialize)]        struct OpenAiError {            message: String,        }         match serde_json::from_str::<OpenAiResponse>(&body) {            Ok(response) if !response.error.message.is_empty() => Err(anyhow!(                "Failed to connect to OpenAI API: {}",                response.error.message,            )),             _ => anyhow::bail!(                "Failed to connect to OpenAI API: {} {}",                response.status(),                body,            ),        }    }} #[derive(Copy, Clone, Serialize, Deserialize)]pub enum OpenAiEmbeddingModel {    #[serde(rename = "text-embedding-3-small")]    TextEmbedding3Small,    #[serde(rename = "text-embedding-3-large")]    TextEmbedding3Large,} #[derive(Serialize)]struct OpenAiEmbeddingRequest<'a> {    model: OpenAiEmbeddingModel,    input: Vec<&'a str>,} #[derive(Deserialize)]pub struct OpenAiEmbeddingResponse {    pub data: Vec<OpenAiEmbedding>,} #[derive(Deserialize)]pub struct OpenAiEmbedding {    pub embedding: Vec<f32>,} pub fn embed<'a>(    client: &dyn HttpClient,    api_url: &str,    api_key: &str,    model: OpenAiEmbeddingModel,    texts: impl IntoIterator<Item = &'a str>,) -> impl 'static + Future<Output = Result<OpenAiEmbeddingResponse>> {    let uri = format!("{api_url}/embeddings");     let request = OpenAiEmbeddingRequest {        model,        input: texts.into_iter().collect(),    };    let body = AsyncBody::from(serde_json::to_string(&request).unwrap());    let request = HttpRequest::builder()        .method(Method::POST)

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