4f2f9ff762
https://github.com/user-attachments/assets/7854a737-ef83-414c-b397-45122e4f32e8 Release Notes: - Create file and edit file tools now stream their tool descriptions, so you can see what they're doing sooner. --------- Co-authored-by: Marshall Bowers <git@maxdeviant.com>
1053 lines
41 KiB
Rust
1053 lines
41 KiB
Rust
use crate::AllLanguageModelSettings;
|
|
use crate::ui::InstructionListItem;
|
|
use anthropic::{AnthropicError, AnthropicModelMode, ContentDelta, Event, ResponseContent, Usage};
|
|
use anyhow::{Context as _, Result, anyhow};
|
|
use collections::{BTreeMap, HashMap};
|
|
use credentials_provider::CredentialsProvider;
|
|
use editor::{Editor, EditorElement, EditorStyle};
|
|
use futures::Stream;
|
|
use futures::{FutureExt, StreamExt, future::BoxFuture, stream::BoxStream};
|
|
use gpui::{
|
|
AnyView, App, AsyncApp, Context, Entity, FontStyle, Subscription, Task, TextStyle, WhiteSpace,
|
|
};
|
|
use http_client::HttpClient;
|
|
use language_model::{
|
|
AuthenticateError, LanguageModel, LanguageModelCacheConfiguration, LanguageModelId,
|
|
LanguageModelKnownError, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
|
|
LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest, MessageContent,
|
|
RateLimiter, Role,
|
|
};
|
|
use language_model::{LanguageModelCompletionEvent, LanguageModelToolUse, StopReason};
|
|
use schemars::JsonSchema;
|
|
use serde::{Deserialize, Serialize};
|
|
use settings::{Settings, SettingsStore};
|
|
use std::pin::Pin;
|
|
use std::str::FromStr;
|
|
use std::sync::Arc;
|
|
use strum::IntoEnumIterator;
|
|
use theme::ThemeSettings;
|
|
use ui::{Icon, IconName, List, Tooltip, prelude::*};
|
|
use util::{ResultExt, maybe};
|
|
|
|
const PROVIDER_ID: &str = language_model::ANTHROPIC_PROVIDER_ID;
|
|
const PROVIDER_NAME: &str = "Anthropic";
|
|
|
|
#[derive(Default, Clone, Debug, PartialEq)]
|
|
pub struct AnthropicSettings {
|
|
pub api_url: String,
|
|
/// Extend Zed's list of Anthropic models.
|
|
pub available_models: Vec<AvailableModel>,
|
|
pub needs_setting_migration: bool,
|
|
}
|
|
|
|
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
|
|
pub struct AvailableModel {
|
|
/// The model's name in the Anthropic API. e.g. claude-3-5-sonnet-latest, claude-3-opus-20240229, etc
|
|
pub name: String,
|
|
/// The model's name in Zed's UI, such as in the model selector dropdown menu in the assistant panel.
|
|
pub display_name: Option<String>,
|
|
/// The model's context window size.
|
|
pub max_tokens: usize,
|
|
/// A model `name` to substitute when calling tools, in case the primary model doesn't support tool calling.
|
|
pub tool_override: Option<String>,
|
|
/// Configuration of Anthropic's caching API.
|
|
pub cache_configuration: Option<LanguageModelCacheConfiguration>,
|
|
pub max_output_tokens: Option<u32>,
|
|
pub default_temperature: Option<f32>,
|
|
#[serde(default)]
|
|
pub extra_beta_headers: Vec<String>,
|
|
/// The model's mode (e.g. thinking)
|
|
pub mode: Option<ModelMode>,
|
|
}
|
|
|
|
#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize, JsonSchema)]
|
|
#[serde(tag = "type", rename_all = "lowercase")]
|
|
pub enum ModelMode {
|
|
#[default]
|
|
Default,
|
|
Thinking {
|
|
/// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
|
|
budget_tokens: Option<u32>,
|
|
},
|
|
}
|
|
|
|
impl From<ModelMode> for AnthropicModelMode {
|
|
fn from(value: ModelMode) -> Self {
|
|
match value {
|
|
ModelMode::Default => AnthropicModelMode::Default,
|
|
ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
|
|
}
|
|
}
|
|
}
|
|
|
|
impl From<AnthropicModelMode> for ModelMode {
|
|
fn from(value: AnthropicModelMode) -> Self {
|
|
match value {
|
|
AnthropicModelMode::Default => ModelMode::Default,
|
|
AnthropicModelMode::Thinking { budget_tokens } => ModelMode::Thinking { budget_tokens },
|
|
}
|
|
}
|
|
}
|
|
|
|
pub struct AnthropicLanguageModelProvider {
|
|
http_client: Arc<dyn HttpClient>,
|
|
state: gpui::Entity<State>,
|
|
}
|
|
|
|
const ANTHROPIC_API_KEY_VAR: &str = "ANTHROPIC_API_KEY";
|
|
|
|
pub struct State {
|
|
api_key: Option<String>,
|
|
api_key_from_env: bool,
|
|
_subscription: Subscription,
|
|
}
|
|
|
|
impl State {
|
|
fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
|
|
let credentials_provider = <dyn CredentialsProvider>::global(cx);
|
|
let api_url = AllLanguageModelSettings::get_global(cx)
|
|
.anthropic
|
|
.api_url
|
|
.clone();
|
|
cx.spawn(async move |this, cx| {
|
|
credentials_provider
|
|
.delete_credentials(&api_url, &cx)
|
|
.await
|
|
.ok();
|
|
this.update(cx, |this, cx| {
|
|
this.api_key = None;
|
|
this.api_key_from_env = false;
|
|
cx.notify();
|
|
})
|
|
})
|
|
}
|
|
|
|
fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
|
|
let credentials_provider = <dyn CredentialsProvider>::global(cx);
|
|
let api_url = AllLanguageModelSettings::get_global(cx)
|
|
.anthropic
|
|
.api_url
|
|
.clone();
|
|
cx.spawn(async move |this, cx| {
|
|
credentials_provider
|
|
.write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)
|
|
.await
|
|
.ok();
|
|
|
|
this.update(cx, |this, cx| {
|
|
this.api_key = Some(api_key);
|
|
cx.notify();
|
|
})
|
|
})
|
|
}
|
|
|
|
fn is_authenticated(&self) -> bool {
|
|
self.api_key.is_some()
|
|
}
|
|
|
|
fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
|
|
if self.is_authenticated() {
|
|
return Task::ready(Ok(()));
|
|
}
|
|
|
|
let credentials_provider = <dyn CredentialsProvider>::global(cx);
|
|
let api_url = AllLanguageModelSettings::get_global(cx)
|
|
.anthropic
|
|
.api_url
|
|
.clone();
|
|
|
|
cx.spawn(async move |this, cx| {
|
|
let (api_key, from_env) = if let Ok(api_key) = std::env::var(ANTHROPIC_API_KEY_VAR) {
|
|
(api_key, true)
|
|
} else {
|
|
let (_, api_key) = credentials_provider
|
|
.read_credentials(&api_url, &cx)
|
|
.await?
|
|
.ok_or(AuthenticateError::CredentialsNotFound)?;
|
|
(
|
|
String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
|
|
false,
|
|
)
|
|
};
|
|
|
|
this.update(cx, |this, cx| {
|
|
this.api_key = Some(api_key);
|
|
this.api_key_from_env = from_env;
|
|
cx.notify();
|
|
})?;
|
|
|
|
Ok(())
|
|
})
|
|
}
|
|
}
|
|
|
|
impl AnthropicLanguageModelProvider {
|
|
pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
|
|
let state = cx.new(|cx| State {
|
|
api_key: None,
|
|
api_key_from_env: false,
|
|
_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
|
|
cx.notify();
|
|
}),
|
|
});
|
|
|
|
Self { http_client, state }
|
|
}
|
|
|
|
fn create_language_model(&self, model: anthropic::Model) -> Arc<dyn LanguageModel> {
|
|
Arc::new(AnthropicModel {
|
|
id: LanguageModelId::from(model.id().to_string()),
|
|
model,
|
|
state: self.state.clone(),
|
|
http_client: self.http_client.clone(),
|
|
request_limiter: RateLimiter::new(4),
|
|
})
|
|
}
|
|
}
|
|
|
|
impl LanguageModelProviderState for AnthropicLanguageModelProvider {
|
|
type ObservableEntity = State;
|
|
|
|
fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
|
|
Some(self.state.clone())
|
|
}
|
|
}
|
|
|
|
impl LanguageModelProvider for AnthropicLanguageModelProvider {
|
|
fn id(&self) -> LanguageModelProviderId {
|
|
LanguageModelProviderId(PROVIDER_ID.into())
|
|
}
|
|
|
|
fn name(&self) -> LanguageModelProviderName {
|
|
LanguageModelProviderName(PROVIDER_NAME.into())
|
|
}
|
|
|
|
fn icon(&self) -> IconName {
|
|
IconName::AiAnthropic
|
|
}
|
|
|
|
fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
|
|
Some(self.create_language_model(anthropic::Model::default()))
|
|
}
|
|
|
|
fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
|
|
Some(self.create_language_model(anthropic::Model::default_fast()))
|
|
}
|
|
|
|
fn recommended_models(&self, _cx: &App) -> Vec<Arc<dyn LanguageModel>> {
|
|
[
|
|
anthropic::Model::Claude3_7Sonnet,
|
|
anthropic::Model::Claude3_7SonnetThinking,
|
|
]
|
|
.into_iter()
|
|
.map(|model| self.create_language_model(model))
|
|
.collect()
|
|
}
|
|
|
|
fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
|
|
let mut models = BTreeMap::default();
|
|
|
|
// Add base models from anthropic::Model::iter()
|
|
for model in anthropic::Model::iter() {
|
|
if !matches!(model, anthropic::Model::Custom { .. }) {
|
|
models.insert(model.id().to_string(), model);
|
|
}
|
|
}
|
|
|
|
// Override with available models from settings
|
|
for model in AllLanguageModelSettings::get_global(cx)
|
|
.anthropic
|
|
.available_models
|
|
.iter()
|
|
{
|
|
models.insert(
|
|
model.name.clone(),
|
|
anthropic::Model::Custom {
|
|
name: model.name.clone(),
|
|
display_name: model.display_name.clone(),
|
|
max_tokens: model.max_tokens,
|
|
tool_override: model.tool_override.clone(),
|
|
cache_configuration: model.cache_configuration.as_ref().map(|config| {
|
|
anthropic::AnthropicModelCacheConfiguration {
|
|
max_cache_anchors: config.max_cache_anchors,
|
|
should_speculate: config.should_speculate,
|
|
min_total_token: config.min_total_token,
|
|
}
|
|
}),
|
|
max_output_tokens: model.max_output_tokens,
|
|
default_temperature: model.default_temperature,
|
|
extra_beta_headers: model.extra_beta_headers.clone(),
|
|
mode: model.mode.clone().unwrap_or_default().into(),
|
|
},
|
|
);
|
|
}
|
|
|
|
models
|
|
.into_values()
|
|
.map(|model| self.create_language_model(model))
|
|
.collect()
|
|
}
|
|
|
|
fn is_authenticated(&self, cx: &App) -> bool {
|
|
self.state.read(cx).is_authenticated()
|
|
}
|
|
|
|
fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
|
|
self.state.update(cx, |state, cx| state.authenticate(cx))
|
|
}
|
|
|
|
fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {
|
|
cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
|
|
.into()
|
|
}
|
|
|
|
fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
|
|
self.state.update(cx, |state, cx| state.reset_api_key(cx))
|
|
}
|
|
}
|
|
|
|
pub struct AnthropicModel {
|
|
id: LanguageModelId,
|
|
model: anthropic::Model,
|
|
state: gpui::Entity<State>,
|
|
http_client: Arc<dyn HttpClient>,
|
|
request_limiter: RateLimiter,
|
|
}
|
|
|
|
pub fn count_anthropic_tokens(
|
|
request: LanguageModelRequest,
|
|
cx: &App,
|
|
) -> BoxFuture<'static, Result<usize>> {
|
|
cx.background_spawn(async move {
|
|
let messages = request.messages;
|
|
let mut tokens_from_images = 0;
|
|
let mut string_messages = Vec::with_capacity(messages.len());
|
|
|
|
for message in messages {
|
|
use language_model::MessageContent;
|
|
|
|
let mut string_contents = String::new();
|
|
|
|
for content in message.content {
|
|
match content {
|
|
MessageContent::Text(text) => {
|
|
string_contents.push_str(&text);
|
|
}
|
|
MessageContent::Thinking { .. } => {
|
|
// Thinking blocks are not included in the input token count.
|
|
}
|
|
MessageContent::RedactedThinking(_) => {
|
|
// Thinking blocks are not included in the input token count.
|
|
}
|
|
MessageContent::Image(image) => {
|
|
tokens_from_images += image.estimate_tokens();
|
|
}
|
|
MessageContent::ToolUse(_tool_use) => {
|
|
// TODO: Estimate token usage from tool uses.
|
|
}
|
|
MessageContent::ToolResult(tool_result) => {
|
|
string_contents.push_str(&tool_result.content);
|
|
}
|
|
}
|
|
}
|
|
|
|
if !string_contents.is_empty() {
|
|
string_messages.push(tiktoken_rs::ChatCompletionRequestMessage {
|
|
role: match message.role {
|
|
Role::User => "user".into(),
|
|
Role::Assistant => "assistant".into(),
|
|
Role::System => "system".into(),
|
|
},
|
|
content: Some(string_contents),
|
|
name: None,
|
|
function_call: None,
|
|
});
|
|
}
|
|
}
|
|
|
|
// Tiktoken doesn't yet support these models, so we manually use the
|
|
// same tokenizer as GPT-4.
|
|
tiktoken_rs::num_tokens_from_messages("gpt-4", &string_messages)
|
|
.map(|tokens| tokens + tokens_from_images)
|
|
})
|
|
.boxed()
|
|
}
|
|
|
|
impl AnthropicModel {
|
|
fn stream_completion(
|
|
&self,
|
|
request: anthropic::Request,
|
|
cx: &AsyncApp,
|
|
) -> BoxFuture<'static, Result<BoxStream<'static, Result<anthropic::Event, AnthropicError>>>>
|
|
{
|
|
let http_client = self.http_client.clone();
|
|
|
|
let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
|
|
let settings = &AllLanguageModelSettings::get_global(cx).anthropic;
|
|
(state.api_key.clone(), settings.api_url.clone())
|
|
}) else {
|
|
return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
|
|
};
|
|
|
|
async move {
|
|
let api_key = api_key.ok_or_else(|| anyhow!("Missing Anthropic API Key"))?;
|
|
let request =
|
|
anthropic::stream_completion(http_client.as_ref(), &api_url, &api_key, request);
|
|
request.await.context("failed to stream completion")
|
|
}
|
|
.boxed()
|
|
}
|
|
}
|
|
|
|
impl LanguageModel for AnthropicModel {
|
|
fn id(&self) -> LanguageModelId {
|
|
self.id.clone()
|
|
}
|
|
|
|
fn name(&self) -> LanguageModelName {
|
|
LanguageModelName::from(self.model.display_name().to_string())
|
|
}
|
|
|
|
fn provider_id(&self) -> LanguageModelProviderId {
|
|
LanguageModelProviderId(PROVIDER_ID.into())
|
|
}
|
|
|
|
fn provider_name(&self) -> LanguageModelProviderName {
|
|
LanguageModelProviderName(PROVIDER_NAME.into())
|
|
}
|
|
|
|
fn supports_tools(&self) -> bool {
|
|
true
|
|
}
|
|
|
|
fn telemetry_id(&self) -> String {
|
|
format!("anthropic/{}", self.model.id())
|
|
}
|
|
|
|
fn api_key(&self, cx: &App) -> Option<String> {
|
|
self.state.read(cx).api_key.clone()
|
|
}
|
|
|
|
fn max_token_count(&self) -> usize {
|
|
self.model.max_token_count()
|
|
}
|
|
|
|
fn max_output_tokens(&self) -> Option<u32> {
|
|
Some(self.model.max_output_tokens())
|
|
}
|
|
|
|
fn count_tokens(
|
|
&self,
|
|
request: LanguageModelRequest,
|
|
cx: &App,
|
|
) -> BoxFuture<'static, Result<usize>> {
|
|
count_anthropic_tokens(request, cx)
|
|
}
|
|
|
|
fn stream_completion(
|
|
&self,
|
|
request: LanguageModelRequest,
|
|
cx: &AsyncApp,
|
|
) -> BoxFuture<'static, Result<BoxStream<'static, Result<LanguageModelCompletionEvent>>>> {
|
|
let request = into_anthropic(
|
|
request,
|
|
self.model.request_id().into(),
|
|
self.model.default_temperature(),
|
|
self.model.max_output_tokens(),
|
|
self.model.mode(),
|
|
);
|
|
let request = self.stream_completion(request, cx);
|
|
let future = self.request_limiter.stream(async move {
|
|
let response = request
|
|
.await
|
|
.map_err(|err| match err.downcast::<AnthropicError>() {
|
|
Ok(anthropic_err) => anthropic_err_to_anyhow(anthropic_err),
|
|
Err(err) => anyhow!(err),
|
|
})?;
|
|
Ok(map_to_language_model_completion_events(response))
|
|
});
|
|
async move { Ok(future.await?.boxed()) }.boxed()
|
|
}
|
|
|
|
fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
|
|
self.model
|
|
.cache_configuration()
|
|
.map(|config| LanguageModelCacheConfiguration {
|
|
max_cache_anchors: config.max_cache_anchors,
|
|
should_speculate: config.should_speculate,
|
|
min_total_token: config.min_total_token,
|
|
})
|
|
}
|
|
}
|
|
|
|
pub fn into_anthropic(
|
|
request: LanguageModelRequest,
|
|
model: String,
|
|
default_temperature: f32,
|
|
max_output_tokens: u32,
|
|
mode: AnthropicModelMode,
|
|
) -> anthropic::Request {
|
|
let mut new_messages: Vec<anthropic::Message> = Vec::new();
|
|
let mut system_message = String::new();
|
|
|
|
for message in request.messages {
|
|
if message.contents_empty() {
|
|
continue;
|
|
}
|
|
|
|
match message.role {
|
|
Role::User | Role::Assistant => {
|
|
let cache_control = if message.cache {
|
|
Some(anthropic::CacheControl {
|
|
cache_type: anthropic::CacheControlType::Ephemeral,
|
|
})
|
|
} else {
|
|
None
|
|
};
|
|
let anthropic_message_content: Vec<anthropic::RequestContent> = message
|
|
.content
|
|
.into_iter()
|
|
.filter_map(|content| match content {
|
|
MessageContent::Text(text) => {
|
|
if !text.is_empty() {
|
|
Some(anthropic::RequestContent::Text {
|
|
text,
|
|
cache_control,
|
|
})
|
|
} else {
|
|
None
|
|
}
|
|
}
|
|
MessageContent::Thinking {
|
|
text: thinking,
|
|
signature,
|
|
} => {
|
|
if !thinking.is_empty() {
|
|
Some(anthropic::RequestContent::Thinking {
|
|
thinking,
|
|
signature: signature.unwrap_or_default(),
|
|
cache_control,
|
|
})
|
|
} else {
|
|
None
|
|
}
|
|
}
|
|
MessageContent::RedactedThinking(data) => {
|
|
if !data.is_empty() {
|
|
Some(anthropic::RequestContent::RedactedThinking {
|
|
data: String::from_utf8(data).ok()?,
|
|
})
|
|
} else {
|
|
None
|
|
}
|
|
}
|
|
MessageContent::Image(image) => Some(anthropic::RequestContent::Image {
|
|
source: anthropic::ImageSource {
|
|
source_type: "base64".to_string(),
|
|
media_type: "image/png".to_string(),
|
|
data: image.source.to_string(),
|
|
},
|
|
cache_control,
|
|
}),
|
|
MessageContent::ToolUse(tool_use) => {
|
|
Some(anthropic::RequestContent::ToolUse {
|
|
id: tool_use.id.to_string(),
|
|
name: tool_use.name.to_string(),
|
|
input: tool_use.input,
|
|
cache_control,
|
|
})
|
|
}
|
|
MessageContent::ToolResult(tool_result) => {
|
|
Some(anthropic::RequestContent::ToolResult {
|
|
tool_use_id: tool_result.tool_use_id.to_string(),
|
|
is_error: tool_result.is_error,
|
|
content: tool_result.content.to_string(),
|
|
cache_control,
|
|
})
|
|
}
|
|
})
|
|
.collect();
|
|
let anthropic_role = match message.role {
|
|
Role::User => anthropic::Role::User,
|
|
Role::Assistant => anthropic::Role::Assistant,
|
|
Role::System => unreachable!("System role should never occur here"),
|
|
};
|
|
if let Some(last_message) = new_messages.last_mut() {
|
|
if last_message.role == anthropic_role {
|
|
last_message.content.extend(anthropic_message_content);
|
|
continue;
|
|
}
|
|
}
|
|
new_messages.push(anthropic::Message {
|
|
role: anthropic_role,
|
|
content: anthropic_message_content,
|
|
});
|
|
}
|
|
Role::System => {
|
|
if !system_message.is_empty() {
|
|
system_message.push_str("\n\n");
|
|
}
|
|
system_message.push_str(&message.string_contents());
|
|
}
|
|
}
|
|
}
|
|
|
|
anthropic::Request {
|
|
model,
|
|
messages: new_messages,
|
|
max_tokens: max_output_tokens,
|
|
system: if system_message.is_empty() {
|
|
None
|
|
} else {
|
|
Some(anthropic::StringOrContents::String(system_message))
|
|
},
|
|
thinking: if let AnthropicModelMode::Thinking { budget_tokens } = mode {
|
|
Some(anthropic::Thinking::Enabled { budget_tokens })
|
|
} else {
|
|
None
|
|
},
|
|
tools: request
|
|
.tools
|
|
.into_iter()
|
|
.map(|tool| anthropic::Tool {
|
|
name: tool.name,
|
|
description: tool.description,
|
|
input_schema: tool.input_schema,
|
|
})
|
|
.collect(),
|
|
tool_choice: None,
|
|
metadata: None,
|
|
stop_sequences: Vec::new(),
|
|
temperature: request.temperature.or(Some(default_temperature)),
|
|
top_k: None,
|
|
top_p: None,
|
|
}
|
|
}
|
|
|
|
pub fn map_to_language_model_completion_events(
|
|
events: Pin<Box<dyn Send + Stream<Item = Result<Event, AnthropicError>>>>,
|
|
) -> impl Stream<Item = Result<LanguageModelCompletionEvent>> {
|
|
struct RawToolUse {
|
|
id: String,
|
|
name: String,
|
|
input_json: String,
|
|
}
|
|
|
|
struct State {
|
|
events: Pin<Box<dyn Send + Stream<Item = Result<Event, AnthropicError>>>>,
|
|
tool_uses_by_index: HashMap<usize, RawToolUse>,
|
|
usage: Usage,
|
|
stop_reason: StopReason,
|
|
}
|
|
|
|
futures::stream::unfold(
|
|
State {
|
|
events,
|
|
tool_uses_by_index: HashMap::default(),
|
|
usage: Usage::default(),
|
|
stop_reason: StopReason::EndTurn,
|
|
},
|
|
|mut state| async move {
|
|
while let Some(event) = state.events.next().await {
|
|
match event {
|
|
Ok(event) => match event {
|
|
Event::ContentBlockStart {
|
|
index,
|
|
content_block,
|
|
} => match content_block {
|
|
ResponseContent::Text { text } => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Text(text))],
|
|
state,
|
|
));
|
|
}
|
|
ResponseContent::Thinking { thinking } => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Thinking {
|
|
text: thinking,
|
|
signature: None,
|
|
})],
|
|
state,
|
|
));
|
|
}
|
|
ResponseContent::RedactedThinking { .. } => {
|
|
// Redacted thinking is encrypted and not accessible to the user, see:
|
|
// https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking#suggestions-for-handling-redacted-thinking-in-production
|
|
}
|
|
ResponseContent::ToolUse { id, name, .. } => {
|
|
state.tool_uses_by_index.insert(
|
|
index,
|
|
RawToolUse {
|
|
id,
|
|
name,
|
|
input_json: String::new(),
|
|
},
|
|
);
|
|
}
|
|
},
|
|
Event::ContentBlockDelta { index, delta } => match delta {
|
|
ContentDelta::TextDelta { text } => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Text(text))],
|
|
state,
|
|
));
|
|
}
|
|
ContentDelta::ThinkingDelta { thinking } => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Thinking {
|
|
text: thinking,
|
|
signature: None,
|
|
})],
|
|
state,
|
|
));
|
|
}
|
|
ContentDelta::SignatureDelta { signature } => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Thinking {
|
|
text: "".to_string(),
|
|
signature: Some(signature),
|
|
})],
|
|
state,
|
|
));
|
|
}
|
|
ContentDelta::InputJsonDelta { partial_json } => {
|
|
if let Some(tool_use) = state.tool_uses_by_index.get_mut(&index) {
|
|
tool_use.input_json.push_str(&partial_json);
|
|
|
|
return Some((
|
|
vec![maybe!({
|
|
Ok(LanguageModelCompletionEvent::ToolUse(
|
|
LanguageModelToolUse {
|
|
id: tool_use.id.clone().into(),
|
|
name: tool_use.name.clone().into(),
|
|
is_input_complete: false,
|
|
input: if tool_use.input_json.is_empty() {
|
|
serde_json::Value::Object(
|
|
serde_json::Map::default(),
|
|
)
|
|
} else {
|
|
serde_json::Value::from_str(
|
|
// Convert invalid (incomplete) JSON into
|
|
// JSON that serde will accept, e.g. by closing
|
|
// unclosed delimiters. This way, we can update
|
|
// the UI with whatever has been streamed back so far.
|
|
&partial_json_fixer::fix_json(
|
|
&tool_use.input_json,
|
|
),
|
|
)
|
|
.map_err(|err| anyhow!(err))?
|
|
},
|
|
},
|
|
))
|
|
})],
|
|
state,
|
|
));
|
|
}
|
|
}
|
|
},
|
|
Event::ContentBlockStop { index } => {
|
|
if let Some(tool_use) = state.tool_uses_by_index.remove(&index) {
|
|
return Some((
|
|
vec![maybe!({
|
|
Ok(LanguageModelCompletionEvent::ToolUse(
|
|
LanguageModelToolUse {
|
|
id: tool_use.id.into(),
|
|
name: tool_use.name.into(),
|
|
is_input_complete: true,
|
|
input: if tool_use.input_json.is_empty() {
|
|
serde_json::Value::Object(
|
|
serde_json::Map::default(),
|
|
)
|
|
} else {
|
|
serde_json::Value::from_str(
|
|
&tool_use.input_json,
|
|
)
|
|
.map_err(|err| anyhow!(err))?
|
|
},
|
|
},
|
|
))
|
|
})],
|
|
state,
|
|
));
|
|
}
|
|
}
|
|
Event::MessageStart { message } => {
|
|
update_usage(&mut state.usage, &message.usage);
|
|
return Some((
|
|
vec![
|
|
Ok(LanguageModelCompletionEvent::UsageUpdate(convert_usage(
|
|
&state.usage,
|
|
))),
|
|
Ok(LanguageModelCompletionEvent::StartMessage {
|
|
message_id: message.id,
|
|
}),
|
|
],
|
|
state,
|
|
));
|
|
}
|
|
Event::MessageDelta { delta, usage } => {
|
|
update_usage(&mut state.usage, &usage);
|
|
if let Some(stop_reason) = delta.stop_reason.as_deref() {
|
|
state.stop_reason = match stop_reason {
|
|
"end_turn" => StopReason::EndTurn,
|
|
"max_tokens" => StopReason::MaxTokens,
|
|
"tool_use" => StopReason::ToolUse,
|
|
_ => {
|
|
log::error!(
|
|
"Unexpected anthropic stop_reason: {stop_reason}"
|
|
);
|
|
StopReason::EndTurn
|
|
}
|
|
};
|
|
}
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::UsageUpdate(
|
|
convert_usage(&state.usage),
|
|
))],
|
|
state,
|
|
));
|
|
}
|
|
Event::MessageStop => {
|
|
return Some((
|
|
vec![Ok(LanguageModelCompletionEvent::Stop(state.stop_reason))],
|
|
state,
|
|
));
|
|
}
|
|
Event::Error { error } => {
|
|
return Some((
|
|
vec![Err(anyhow!(AnthropicError::ApiError(error)))],
|
|
state,
|
|
));
|
|
}
|
|
_ => {}
|
|
},
|
|
Err(err) => {
|
|
return Some((vec![Err(anthropic_err_to_anyhow(err))], state));
|
|
}
|
|
}
|
|
}
|
|
|
|
None
|
|
},
|
|
)
|
|
.flat_map(futures::stream::iter)
|
|
}
|
|
|
|
pub fn anthropic_err_to_anyhow(err: AnthropicError) -> anyhow::Error {
|
|
if let AnthropicError::ApiError(api_err) = &err {
|
|
if let Some(tokens) = api_err.match_window_exceeded() {
|
|
return anyhow!(LanguageModelKnownError::ContextWindowLimitExceeded { tokens });
|
|
}
|
|
}
|
|
|
|
anyhow!(err)
|
|
}
|
|
|
|
/// Updates usage data by preferring counts from `new`.
|
|
fn update_usage(usage: &mut Usage, new: &Usage) {
|
|
if let Some(input_tokens) = new.input_tokens {
|
|
usage.input_tokens = Some(input_tokens);
|
|
}
|
|
if let Some(output_tokens) = new.output_tokens {
|
|
usage.output_tokens = Some(output_tokens);
|
|
}
|
|
if let Some(cache_creation_input_tokens) = new.cache_creation_input_tokens {
|
|
usage.cache_creation_input_tokens = Some(cache_creation_input_tokens);
|
|
}
|
|
if let Some(cache_read_input_tokens) = new.cache_read_input_tokens {
|
|
usage.cache_read_input_tokens = Some(cache_read_input_tokens);
|
|
}
|
|
}
|
|
|
|
fn convert_usage(usage: &Usage) -> language_model::TokenUsage {
|
|
language_model::TokenUsage {
|
|
input_tokens: usage.input_tokens.unwrap_or(0),
|
|
output_tokens: usage.output_tokens.unwrap_or(0),
|
|
cache_creation_input_tokens: usage.cache_creation_input_tokens.unwrap_or(0),
|
|
cache_read_input_tokens: usage.cache_read_input_tokens.unwrap_or(0),
|
|
}
|
|
}
|
|
|
|
struct ConfigurationView {
|
|
api_key_editor: Entity<Editor>,
|
|
state: gpui::Entity<State>,
|
|
load_credentials_task: Option<Task<()>>,
|
|
}
|
|
|
|
impl ConfigurationView {
|
|
const PLACEHOLDER_TEXT: &'static str = "sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
|
|
|
|
fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
|
|
cx.observe(&state, |_, _, cx| {
|
|
cx.notify();
|
|
})
|
|
.detach();
|
|
|
|
let load_credentials_task = Some(cx.spawn({
|
|
let state = state.clone();
|
|
async move |this, cx| {
|
|
if let Some(task) = state
|
|
.update(cx, |state, cx| state.authenticate(cx))
|
|
.log_err()
|
|
{
|
|
// We don't log an error, because "not signed in" is also an error.
|
|
let _ = task.await;
|
|
}
|
|
this.update(cx, |this, cx| {
|
|
this.load_credentials_task = None;
|
|
cx.notify();
|
|
})
|
|
.log_err();
|
|
}
|
|
}));
|
|
|
|
Self {
|
|
api_key_editor: cx.new(|cx| {
|
|
let mut editor = Editor::single_line(window, cx);
|
|
editor.set_placeholder_text(Self::PLACEHOLDER_TEXT, cx);
|
|
editor
|
|
}),
|
|
state,
|
|
load_credentials_task,
|
|
}
|
|
}
|
|
|
|
fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
|
|
let api_key = self.api_key_editor.read(cx).text(cx);
|
|
if api_key.is_empty() {
|
|
return;
|
|
}
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn_in(window, async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(api_key, cx))?
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
|
|
cx.notify();
|
|
}
|
|
|
|
fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
|
|
self.api_key_editor
|
|
.update(cx, |editor, cx| editor.set_text("", window, cx));
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn_in(window, async move |_, cx| {
|
|
state.update(cx, |state, cx| state.reset_api_key(cx))?.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
|
|
cx.notify();
|
|
}
|
|
|
|
fn render_api_key_editor(&self, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let settings = ThemeSettings::get_global(cx);
|
|
let text_style = TextStyle {
|
|
color: cx.theme().colors().text,
|
|
font_family: settings.ui_font.family.clone(),
|
|
font_features: settings.ui_font.features.clone(),
|
|
font_fallbacks: settings.ui_font.fallbacks.clone(),
|
|
font_size: rems(0.875).into(),
|
|
font_weight: settings.ui_font.weight,
|
|
font_style: FontStyle::Normal,
|
|
line_height: relative(1.3),
|
|
white_space: WhiteSpace::Normal,
|
|
..Default::default()
|
|
};
|
|
EditorElement::new(
|
|
&self.api_key_editor,
|
|
EditorStyle {
|
|
background: cx.theme().colors().editor_background,
|
|
local_player: cx.theme().players().local(),
|
|
text: text_style,
|
|
..Default::default()
|
|
},
|
|
)
|
|
}
|
|
|
|
fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
|
|
!self.state.read(cx).is_authenticated()
|
|
}
|
|
}
|
|
|
|
impl Render for ConfigurationView {
|
|
fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let env_var_set = self.state.read(cx).api_key_from_env;
|
|
|
|
if self.load_credentials_task.is_some() {
|
|
div().child(Label::new("Loading credentials...")).into_any()
|
|
} else if self.should_render_editor(cx) {
|
|
v_flex()
|
|
.size_full()
|
|
.on_action(cx.listener(Self::save_api_key))
|
|
.child(Label::new("To use Zed's assistant with Anthropic, you need to add an API key. Follow these steps:"))
|
|
.child(
|
|
List::new()
|
|
.child(
|
|
InstructionListItem::new(
|
|
"Create one by visiting",
|
|
Some("Anthropic's settings"),
|
|
Some("https://console.anthropic.com/settings/keys")
|
|
)
|
|
)
|
|
.child(
|
|
InstructionListItem::text_only("Paste your API key below and hit enter to start using the assistant")
|
|
)
|
|
)
|
|
.child(
|
|
h_flex()
|
|
.w_full()
|
|
.my_2()
|
|
.px_2()
|
|
.py_1()
|
|
.bg(cx.theme().colors().editor_background)
|
|
.border_1()
|
|
.border_color(cx.theme().colors().border)
|
|
.rounded_sm()
|
|
.child(self.render_api_key_editor(cx)),
|
|
)
|
|
.child(
|
|
Label::new(
|
|
format!("You can also assign the {ANTHROPIC_API_KEY_VAR} environment variable and restart Zed."),
|
|
)
|
|
.size(LabelSize::Small)
|
|
.color(Color::Muted),
|
|
)
|
|
.into_any()
|
|
} else {
|
|
h_flex()
|
|
.mt_1()
|
|
.p_1()
|
|
.justify_between()
|
|
.rounded_md()
|
|
.border_1()
|
|
.border_color(cx.theme().colors().border)
|
|
.bg(cx.theme().colors().background)
|
|
.child(
|
|
h_flex()
|
|
.gap_1()
|
|
.child(Icon::new(IconName::Check).color(Color::Success))
|
|
.child(Label::new(if env_var_set {
|
|
format!("API key set in {ANTHROPIC_API_KEY_VAR} environment variable.")
|
|
} else {
|
|
"API key configured.".to_string()
|
|
})),
|
|
)
|
|
.child(
|
|
Button::new("reset-key", "Reset Key")
|
|
.label_size(LabelSize::Small)
|
|
.icon(Some(IconName::Trash))
|
|
.icon_size(IconSize::Small)
|
|
.icon_position(IconPosition::Start)
|
|
.disabled(env_var_set)
|
|
.when(env_var_set, |this| {
|
|
this.tooltip(Tooltip::text(format!("To reset your API key, unset the {ANTHROPIC_API_KEY_VAR} environment variable.")))
|
|
})
|
|
.on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
|
|
)
|
|
.into_any()
|
|
}
|
|
}
|
|
}
|