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Update casing of "OpenAI" in identifiers to match Rust conventions (#6940)
This PR updates the casing of "OpenAI" when used in Rust identifiers to match the [Rust naming guidelines](https://rust-lang.github.io/api-guidelines/naming.html): > In `UpperCamelCase`, acronyms and contractions of compound words count as one word: use `Uuid` rather than `UUID`, `Usize` rather than `USize` or `Stdin` rather than `StdIn`. Release Notes: - N/A
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e8bf06fc42
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9
crates/ai/src/providers/open_ai.rs
Normal file
9
crates/ai/src/providers/open_ai.rs
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@ -0,0 +1,9 @@
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pub mod completion;
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pub mod embedding;
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pub mod model;
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pub use completion::*;
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pub use embedding::*;
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pub use model::OpenAiLanguageModel;
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pub const OPEN_AI_API_URL: &'static str = "https://api.openai.com/v1";
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@ -21,7 +21,7 @@ use crate::{
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models::LanguageModel,
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};
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use crate::providers::open_ai::{OpenAILanguageModel, OPENAI_API_URL};
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use crate::providers::open_ai::{OpenAiLanguageModel, OPEN_AI_API_URL};
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#[derive(Clone, Copy, Serialize, Deserialize, Debug, Eq, PartialEq)]
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#[serde(rename_all = "lowercase")]
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@ -58,7 +58,7 @@ pub struct RequestMessage {
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}
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#[derive(Debug, Default, Serialize)]
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pub struct OpenAIRequest {
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pub struct OpenAiRequest {
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pub model: String,
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pub messages: Vec<RequestMessage>,
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pub stream: bool,
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@ -66,7 +66,7 @@ pub struct OpenAIRequest {
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pub temperature: f32,
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}
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impl CompletionRequest for OpenAIRequest {
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impl CompletionRequest for OpenAiRequest {
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fn data(&self) -> serde_json::Result<String> {
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serde_json::to_string(self)
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}
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@ -79,7 +79,7 @@ pub struct ResponseMessage {
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}
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#[derive(Deserialize, Debug)]
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pub struct OpenAIUsage {
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pub struct OpenAiUsage {
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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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@ -93,20 +93,20 @@ pub struct ChatChoiceDelta {
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}
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#[derive(Deserialize, Debug)]
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pub struct OpenAIResponseStreamEvent {
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pub struct OpenAiResponseStreamEvent {
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pub id: Option<String>,
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pub object: String,
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pub created: u32,
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pub model: String,
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pub choices: Vec<ChatChoiceDelta>,
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pub usage: Option<OpenAIUsage>,
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pub usage: Option<OpenAiUsage>,
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}
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pub async fn stream_completion(
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credential: ProviderCredential,
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executor: BackgroundExecutor,
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request: Box<dyn CompletionRequest>,
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) -> Result<impl Stream<Item = Result<OpenAIResponseStreamEvent>>> {
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) -> Result<impl Stream<Item = Result<OpenAiResponseStreamEvent>>> {
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let api_key = match credential {
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ProviderCredential::Credentials { api_key } => api_key,
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_ => {
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@ -114,10 +114,10 @@ pub async fn stream_completion(
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}
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};
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let (tx, rx) = futures::channel::mpsc::unbounded::<Result<OpenAIResponseStreamEvent>>();
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let (tx, rx) = futures::channel::mpsc::unbounded::<Result<OpenAiResponseStreamEvent>>();
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let json_data = request.data()?;
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let mut response = Request::post(format!("{OPENAI_API_URL}/chat/completions"))
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let mut response = Request::post(format!("{OPEN_AI_API_URL}/chat/completions"))
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.header("Content-Type", "application/json")
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.header("Authorization", format!("Bearer {}", api_key))
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.body(json_data)?
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@ -132,7 +132,7 @@ pub async fn stream_completion(
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fn parse_line(
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line: Result<String, io::Error>,
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) -> Result<Option<OpenAIResponseStreamEvent>> {
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) -> Result<Option<OpenAiResponseStreamEvent>> {
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if let Some(data) = line?.strip_prefix("data: ") {
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let event = serde_json::from_str(data)?;
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Ok(Some(event))
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@ -169,16 +169,16 @@ pub async fn stream_completion(
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response.body_mut().read_to_string(&mut body).await?;
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#[derive(Deserialize)]
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struct OpenAIResponse {
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error: OpenAIError,
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struct OpenAiResponse {
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error: OpenAiError,
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}
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#[derive(Deserialize)]
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struct OpenAIError {
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struct OpenAiError {
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message: String,
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}
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match serde_json::from_str::<OpenAIResponse>(&body) {
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match serde_json::from_str::<OpenAiResponse>(&body) {
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Ok(response) if !response.error.message.is_empty() => Err(anyhow!(
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"Failed to connect to OpenAI API: {}",
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response.error.message,
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@ -194,16 +194,16 @@ pub async fn stream_completion(
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}
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#[derive(Clone)]
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pub struct OpenAICompletionProvider {
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model: OpenAILanguageModel,
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pub struct OpenAiCompletionProvider {
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model: OpenAiLanguageModel,
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credential: Arc<RwLock<ProviderCredential>>,
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executor: BackgroundExecutor,
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}
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impl OpenAICompletionProvider {
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impl OpenAiCompletionProvider {
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pub async fn new(model_name: String, executor: BackgroundExecutor) -> Self {
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let model = executor
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.spawn(async move { OpenAILanguageModel::load(&model_name) })
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.spawn(async move { OpenAiLanguageModel::load(&model_name) })
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.await;
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let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
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Self {
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@ -214,7 +214,7 @@ impl OpenAICompletionProvider {
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}
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}
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impl CredentialProvider for OpenAICompletionProvider {
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impl CredentialProvider for OpenAiCompletionProvider {
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fn has_credentials(&self) -> bool {
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match *self.credential.read() {
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ProviderCredential::Credentials { .. } => true,
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@ -232,7 +232,7 @@ impl CredentialProvider for OpenAICompletionProvider {
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if let Some(api_key) = env::var("OPENAI_API_KEY").log_err() {
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async move { ProviderCredential::Credentials { api_key } }.boxed()
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} else {
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let credentials = cx.read_credentials(OPENAI_API_URL);
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let credentials = cx.read_credentials(OPEN_AI_API_URL);
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async move {
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if let Some(Some((_, api_key))) = credentials.await.log_err() {
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if let Some(api_key) = String::from_utf8(api_key).log_err() {
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@ -266,7 +266,7 @@ impl CredentialProvider for OpenAICompletionProvider {
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let credential = credential.clone();
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let write_credentials = match credential {
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ProviderCredential::Credentials { api_key } => {
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Some(cx.write_credentials(OPENAI_API_URL, "Bearer", api_key.as_bytes()))
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Some(cx.write_credentials(OPEN_AI_API_URL, "Bearer", api_key.as_bytes()))
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}
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_ => None,
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};
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@ -281,7 +281,7 @@ impl CredentialProvider for OpenAICompletionProvider {
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fn delete_credentials(&self, cx: &mut AppContext) -> BoxFuture<()> {
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*self.credential.write() = ProviderCredential::NoCredentials;
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let delete_credentials = cx.delete_credentials(OPENAI_API_URL);
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let delete_credentials = cx.delete_credentials(OPEN_AI_API_URL);
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async move {
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delete_credentials.await.log_err();
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}
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@ -289,7 +289,7 @@ impl CredentialProvider for OpenAICompletionProvider {
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}
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}
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impl CompletionProvider for OpenAICompletionProvider {
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impl CompletionProvider for OpenAiCompletionProvider {
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fn base_model(&self) -> Box<dyn LanguageModel> {
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let model: Box<dyn LanguageModel> = Box::new(self.model.clone());
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model
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@ -25,17 +25,17 @@ use util::ResultExt;
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use crate::auth::{CredentialProvider, ProviderCredential};
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use crate::embedding::{Embedding, EmbeddingProvider};
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use crate::models::LanguageModel;
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use crate::providers::open_ai::OpenAILanguageModel;
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use crate::providers::open_ai::OpenAiLanguageModel;
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use crate::providers::open_ai::OPENAI_API_URL;
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use crate::providers::open_ai::OPEN_AI_API_URL;
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lazy_static! {
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static ref OPENAI_BPE_TOKENIZER: CoreBPE = cl100k_base().unwrap();
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static ref OPEN_AI_BPE_TOKENIZER: CoreBPE = cl100k_base().unwrap();
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}
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#[derive(Clone)]
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pub struct OpenAIEmbeddingProvider {
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model: OpenAILanguageModel,
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pub struct OpenAiEmbeddingProvider {
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model: OpenAiLanguageModel,
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credential: Arc<RwLock<ProviderCredential>>,
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pub client: Arc<dyn HttpClient>,
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pub executor: BackgroundExecutor,
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@ -44,42 +44,42 @@ pub struct OpenAIEmbeddingProvider {
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}
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#[derive(Serialize)]
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struct OpenAIEmbeddingRequest<'a> {
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struct OpenAiEmbeddingRequest<'a> {
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model: &'static str,
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input: Vec<&'a str>,
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}
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#[derive(Deserialize)]
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struct OpenAIEmbeddingResponse {
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data: Vec<OpenAIEmbedding>,
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usage: OpenAIEmbeddingUsage,
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struct OpenAiEmbeddingResponse {
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data: Vec<OpenAiEmbedding>,
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usage: OpenAiEmbeddingUsage,
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}
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#[derive(Debug, Deserialize)]
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struct OpenAIEmbedding {
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struct OpenAiEmbedding {
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embedding: Vec<f32>,
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index: usize,
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object: String,
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}
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#[derive(Deserialize)]
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struct OpenAIEmbeddingUsage {
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struct OpenAiEmbeddingUsage {
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prompt_tokens: usize,
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total_tokens: usize,
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}
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impl OpenAIEmbeddingProvider {
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impl OpenAiEmbeddingProvider {
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pub async fn new(client: Arc<dyn HttpClient>, executor: BackgroundExecutor) -> Self {
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let (rate_limit_count_tx, rate_limit_count_rx) = watch::channel_with(None);
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let rate_limit_count_tx = Arc::new(Mutex::new(rate_limit_count_tx));
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// Loading the model is expensive, so ensure this runs off the main thread.
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let model = executor
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.spawn(async move { OpenAILanguageModel::load("text-embedding-ada-002") })
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.spawn(async move { OpenAiLanguageModel::load("text-embedding-ada-002") })
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.await;
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let credential = Arc::new(RwLock::new(ProviderCredential::NoCredentials));
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OpenAIEmbeddingProvider {
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OpenAiEmbeddingProvider {
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model,
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credential,
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client,
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@ -140,7 +140,7 @@ impl OpenAIEmbeddingProvider {
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.header("Content-Type", "application/json")
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.header("Authorization", format!("Bearer {}", api_key))
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.body(
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serde_json::to_string(&OpenAIEmbeddingRequest {
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serde_json::to_string(&OpenAiEmbeddingRequest {
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input: spans.clone(),
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model: "text-embedding-ada-002",
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})
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@ -152,7 +152,7 @@ impl OpenAIEmbeddingProvider {
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}
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}
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impl CredentialProvider for OpenAIEmbeddingProvider {
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impl CredentialProvider for OpenAiEmbeddingProvider {
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fn has_credentials(&self) -> bool {
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match *self.credential.read() {
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ProviderCredential::Credentials { .. } => true,
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@ -170,7 +170,7 @@ impl CredentialProvider for OpenAIEmbeddingProvider {
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if let Some(api_key) = env::var("OPENAI_API_KEY").log_err() {
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async move { ProviderCredential::Credentials { api_key } }.boxed()
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} else {
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let credentials = cx.read_credentials(OPENAI_API_URL);
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let credentials = cx.read_credentials(OPEN_AI_API_URL);
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async move {
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if let Some(Some((_, api_key))) = credentials.await.log_err() {
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if let Some(api_key) = String::from_utf8(api_key).log_err() {
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@ -204,7 +204,7 @@ impl CredentialProvider for OpenAIEmbeddingProvider {
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let credential = credential.clone();
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let write_credentials = match credential {
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ProviderCredential::Credentials { api_key } => {
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Some(cx.write_credentials(OPENAI_API_URL, "Bearer", api_key.as_bytes()))
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Some(cx.write_credentials(OPEN_AI_API_URL, "Bearer", api_key.as_bytes()))
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}
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_ => None,
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};
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@ -219,7 +219,7 @@ impl CredentialProvider for OpenAIEmbeddingProvider {
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fn delete_credentials(&self, cx: &mut AppContext) -> BoxFuture<()> {
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*self.credential.write() = ProviderCredential::NoCredentials;
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let delete_credentials = cx.delete_credentials(OPENAI_API_URL);
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let delete_credentials = cx.delete_credentials(OPEN_AI_API_URL);
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async move {
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delete_credentials.await.log_err();
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}
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@ -228,7 +228,7 @@ impl CredentialProvider for OpenAIEmbeddingProvider {
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}
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#[async_trait]
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impl EmbeddingProvider for OpenAIEmbeddingProvider {
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impl EmbeddingProvider for OpenAiEmbeddingProvider {
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fn base_model(&self) -> Box<dyn LanguageModel> {
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let model: Box<dyn LanguageModel> = Box::new(self.model.clone());
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model
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@ -270,7 +270,7 @@ impl EmbeddingProvider for OpenAIEmbeddingProvider {
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StatusCode::OK => {
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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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let response: OpenAIEmbeddingResponse = serde_json::from_str(&body)?;
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let response: OpenAiEmbeddingResponse = serde_json::from_str(&body)?;
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log::trace!(
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"openai embedding completed. tokens: {:?}",
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@ -1,9 +0,0 @@
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pub mod completion;
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pub mod embedding;
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pub mod model;
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pub use completion::*;
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pub use embedding::*;
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pub use model::OpenAILanguageModel;
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pub const OPENAI_API_URL: &'static str = "https://api.openai.com/v1";
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@ -5,22 +5,22 @@ use util::ResultExt;
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use crate::models::{LanguageModel, TruncationDirection};
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#[derive(Clone)]
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pub struct OpenAILanguageModel {
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pub struct OpenAiLanguageModel {
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name: String,
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bpe: Option<CoreBPE>,
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}
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impl OpenAILanguageModel {
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impl OpenAiLanguageModel {
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pub fn load(model_name: &str) -> Self {
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let bpe = tiktoken_rs::get_bpe_from_model(model_name).log_err();
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OpenAILanguageModel {
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OpenAiLanguageModel {
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name: model_name.to_string(),
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bpe,
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}
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}
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}
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impl LanguageModel for OpenAILanguageModel {
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impl LanguageModel for OpenAiLanguageModel {
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fn name(&self) -> String {
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self.name.clone()
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}
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|
@ -1,11 +0,0 @@
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pub trait LanguageModel {
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fn name(&self) -> String;
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fn count_tokens(&self, content: &str) -> anyhow::Result<usize>;
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fn truncate(
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&self,
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content: &str,
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length: usize,
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direction: TruncationDirection,
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) -> anyhow::Result<String>;
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fn capacity(&self) -> anyhow::Result<usize>;
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}
|
@ -7,7 +7,7 @@ mod streaming_diff;
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use ai::providers::open_ai::Role;
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use anyhow::Result;
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pub use assistant_panel::AssistantPanel;
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use assistant_settings::OpenAIModel;
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use assistant_settings::OpenAiModel;
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use chrono::{DateTime, Local};
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use collections::HashMap;
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use fs::Fs;
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@ -68,7 +68,7 @@ struct SavedConversation {
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messages: Vec<SavedMessage>,
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message_metadata: HashMap<MessageId, MessageMetadata>,
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summary: String,
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model: OpenAIModel,
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model: OpenAiModel,
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}
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impl SavedConversation {
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|
@ -1,5 +1,5 @@
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use crate::{
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assistant_settings::{AssistantDockPosition, AssistantSettings, OpenAIModel},
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assistant_settings::{AssistantDockPosition, AssistantSettings, OpenAiModel},
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codegen::{self, Codegen, CodegenKind},
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prompts::generate_content_prompt,
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Assist, CycleMessageRole, InlineAssist, MessageId, MessageMetadata, MessageStatus,
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@ -10,7 +10,7 @@ use ai::prompts::repository_context::PromptCodeSnippet;
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use ai::{
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auth::ProviderCredential,
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completion::{CompletionProvider, CompletionRequest},
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providers::open_ai::{OpenAICompletionProvider, OpenAIRequest, RequestMessage},
|
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providers::open_ai::{OpenAiCompletionProvider, OpenAiRequest, RequestMessage},
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};
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use anyhow::{anyhow, Result};
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use chrono::{DateTime, Local};
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@ -123,7 +123,7 @@ impl AssistantPanel {
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.unwrap_or_default();
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// Defaulting currently to GPT4, allow for this to be set via config.
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let completion_provider =
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OpenAICompletionProvider::new("gpt-4".into(), cx.background_executor().clone())
|
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OpenAiCompletionProvider::new("gpt-4".into(), cx.background_executor().clone())
|
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.await;
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|
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// TODO: deserialize state.
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@ -717,7 +717,7 @@ impl AssistantPanel {
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content: prompt,
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});
|
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|
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let request = Box::new(OpenAIRequest {
|
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let request = Box::new(OpenAiRequest {
|
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model: model.full_name().into(),
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messages,
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stream: true,
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@ -1393,7 +1393,7 @@ struct Conversation {
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pending_summary: Task<Option<()>>,
|
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completion_count: usize,
|
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pending_completions: Vec<PendingCompletion>,
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model: OpenAIModel,
|
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model: OpenAiModel,
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token_count: Option<usize>,
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max_token_count: usize,
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pending_token_count: Task<Option<()>>,
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@ -1501,7 +1501,7 @@ impl Conversation {
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||||
};
|
||||
let model = saved_conversation.model;
|
||||
let completion_provider: Arc<dyn CompletionProvider> = Arc::new(
|
||||
OpenAICompletionProvider::new(
|
||||
OpenAiCompletionProvider::new(
|
||||
model.full_name().into(),
|
||||
cx.background_executor().clone(),
|
||||
)
|
||||
@ -1626,7 +1626,7 @@ impl Conversation {
|
||||
Some(self.max_token_count as isize - self.token_count? as isize)
|
||||
}
|
||||
|
||||
fn set_model(&mut self, model: OpenAIModel, cx: &mut ModelContext<Self>) {
|
||||
fn set_model(&mut self, model: OpenAiModel, cx: &mut ModelContext<Self>) {
|
||||
self.model = model;
|
||||
self.count_remaining_tokens(cx);
|
||||
cx.notify();
|
||||
@ -1679,7 +1679,7 @@ impl Conversation {
|
||||
return Default::default();
|
||||
}
|
||||
|
||||
let request: Box<dyn CompletionRequest> = Box::new(OpenAIRequest {
|
||||
let request: Box<dyn CompletionRequest> = Box::new(OpenAiRequest {
|
||||
model: self.model.full_name().to_string(),
|
||||
messages: self
|
||||
.messages(cx)
|
||||
@ -1962,7 +1962,7 @@ impl Conversation {
|
||||
content: "Summarize the conversation into a short title without punctuation"
|
||||
.into(),
|
||||
}));
|
||||
let request: Box<dyn CompletionRequest> = Box::new(OpenAIRequest {
|
||||
let request: Box<dyn CompletionRequest> = Box::new(OpenAiRequest {
|
||||
model: self.model.full_name().to_string(),
|
||||
messages: messages.collect(),
|
||||
stream: true,
|
||||
|
@ -5,7 +5,7 @@ use serde::{Deserialize, Serialize};
|
||||
use settings::Settings;
|
||||
|
||||
#[derive(Clone, Debug, Serialize, Deserialize, JsonSchema, PartialEq)]
|
||||
pub enum OpenAIModel {
|
||||
pub enum OpenAiModel {
|
||||
#[serde(rename = "gpt-3.5-turbo-0613")]
|
||||
ThreePointFiveTurbo,
|
||||
#[serde(rename = "gpt-4-0613")]
|
||||
@ -14,28 +14,28 @@ pub enum OpenAIModel {
|
||||
FourTurbo,
|
||||
}
|
||||
|
||||
impl OpenAIModel {
|
||||
impl OpenAiModel {
|
||||
pub fn full_name(&self) -> &'static str {
|
||||
match self {
|
||||
OpenAIModel::ThreePointFiveTurbo => "gpt-3.5-turbo-0613",
|
||||
OpenAIModel::Four => "gpt-4-0613",
|
||||
OpenAIModel::FourTurbo => "gpt-4-1106-preview",
|
||||
OpenAiModel::ThreePointFiveTurbo => "gpt-3.5-turbo-0613",
|
||||
OpenAiModel::Four => "gpt-4-0613",
|
||||
OpenAiModel::FourTurbo => "gpt-4-1106-preview",
|
||||
}
|
||||
}
|
||||
|
||||
pub fn short_name(&self) -> &'static str {
|
||||
match self {
|
||||
OpenAIModel::ThreePointFiveTurbo => "gpt-3.5-turbo",
|
||||
OpenAIModel::Four => "gpt-4",
|
||||
OpenAIModel::FourTurbo => "gpt-4-turbo",
|
||||
OpenAiModel::ThreePointFiveTurbo => "gpt-3.5-turbo",
|
||||
OpenAiModel::Four => "gpt-4",
|
||||
OpenAiModel::FourTurbo => "gpt-4-turbo",
|
||||
}
|
||||
}
|
||||
|
||||
pub fn cycle(&self) -> Self {
|
||||
match self {
|
||||
OpenAIModel::ThreePointFiveTurbo => OpenAIModel::Four,
|
||||
OpenAIModel::Four => OpenAIModel::FourTurbo,
|
||||
OpenAIModel::FourTurbo => OpenAIModel::ThreePointFiveTurbo,
|
||||
OpenAiModel::ThreePointFiveTurbo => OpenAiModel::Four,
|
||||
OpenAiModel::Four => OpenAiModel::FourTurbo,
|
||||
OpenAiModel::FourTurbo => OpenAiModel::ThreePointFiveTurbo,
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -54,7 +54,7 @@ pub struct AssistantSettings {
|
||||
pub dock: AssistantDockPosition,
|
||||
pub default_width: Pixels,
|
||||
pub default_height: Pixels,
|
||||
pub default_open_ai_model: OpenAIModel,
|
||||
pub default_open_ai_model: OpenAiModel,
|
||||
}
|
||||
|
||||
/// Assistant panel settings
|
||||
@ -79,7 +79,7 @@ pub struct AssistantSettingsContent {
|
||||
/// The default OpenAI model to use when starting new conversations.
|
||||
///
|
||||
/// Default: gpt-4-1106-preview
|
||||
pub default_open_ai_model: Option<OpenAIModel>,
|
||||
pub default_open_ai_model: Option<OpenAiModel>,
|
||||
}
|
||||
|
||||
impl Settings for AssistantSettings {
|
||||
|
@ -4,7 +4,7 @@ use ai::prompts::file_context::FileContext;
|
||||
use ai::prompts::generate::GenerateInlineContent;
|
||||
use ai::prompts::preamble::EngineerPreamble;
|
||||
use ai::prompts::repository_context::{PromptCodeSnippet, RepositoryContext};
|
||||
use ai::providers::open_ai::OpenAILanguageModel;
|
||||
use ai::providers::open_ai::OpenAiLanguageModel;
|
||||
use language::{BufferSnapshot, OffsetRangeExt, ToOffset};
|
||||
use std::cmp::{self, Reverse};
|
||||
use std::ops::Range;
|
||||
@ -131,7 +131,7 @@ pub fn generate_content_prompt(
|
||||
project_name: Option<String>,
|
||||
) -> anyhow::Result<String> {
|
||||
// Using new Prompt Templates
|
||||
let openai_model: Arc<dyn LanguageModel> = Arc::new(OpenAILanguageModel::load(model));
|
||||
let openai_model: Arc<dyn LanguageModel> = Arc::new(OpenAiLanguageModel::load(model));
|
||||
let lang_name = if let Some(language_name) = language_name {
|
||||
Some(language_name.to_string())
|
||||
} else {
|
||||
|
@ -8,7 +8,7 @@ mod semantic_index_tests;
|
||||
|
||||
use crate::semantic_index_settings::SemanticIndexSettings;
|
||||
use ai::embedding::{Embedding, EmbeddingProvider};
|
||||
use ai::providers::open_ai::OpenAIEmbeddingProvider;
|
||||
use ai::providers::open_ai::OpenAiEmbeddingProvider;
|
||||
use anyhow::{anyhow, Context as _, Result};
|
||||
use collections::{BTreeMap, HashMap, HashSet};
|
||||
use db::VectorDatabase;
|
||||
@ -91,7 +91,7 @@ pub fn init(
|
||||
|
||||
cx.spawn(move |cx| async move {
|
||||
let embedding_provider =
|
||||
OpenAIEmbeddingProvider::new(http_client, cx.background_executor().clone()).await;
|
||||
OpenAiEmbeddingProvider::new(http_client, cx.background_executor().clone()).await;
|
||||
let semantic_index = SemanticIndex::new(
|
||||
fs,
|
||||
db_file_path,
|
||||
|
Loading…
Reference in New Issue
Block a user