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Implement Anthropic prompt caching (#16274)

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Release Notes:

- Adds support for Prompt Caching in Anthropic. For models that support
it this can dramatically lower cost while improving performance.
This commit is contained in:
Roy Williams 2024-08-15 23:21:06 -04:00 committed by GitHub
parent 09b6e3f2a6
commit 46fb917e02
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GPG Key ID: B5690EEEBB952194
11 changed files with 338 additions and 70 deletions
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67
crates/anthropic/src/anthropic.rs
View File

@ -14,6 +14,14 @@ pub use supported_countries::*;
pub const ANTHROPIC_API_URL: &'static str = "https://api.anthropic.com";
#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq)]
pub struct AnthropicModelCacheConfiguration {
pub min_total_token: usize,
pub should_speculate: bool,
pub max_cache_anchors: usize,
}
#[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))]
#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq, EnumIter)]
pub enum Model {
@ -32,6 +40,8 @@ pub enum Model {
max_tokens: usize,
/// Override this model with a different Anthropic model for tool calls.
tool_override: Option<String>,
/// Indicates whether this custom model supports caching.
cache_configuration: Option<AnthropicModelCacheConfiguration>,
},
}
@ -70,6 +80,21 @@ impl Model {
}
}
pub fn cache_configuration(&self) -> Option<AnthropicModelCacheConfiguration> {
match self {
Self::Claude3_5Sonnet | Self::Claude3Haiku => Some(AnthropicModelCacheConfiguration {
min_total_token: 2_048,
should_speculate: true,
max_cache_anchors: 4,
}),
Self::Custom {
cache_configuration,
..
} => cache_configuration.clone(),
_ => None,
}
}
pub fn max_token_count(&self) -> usize {
match self {
Self::Claude3_5Sonnet
@ -104,7 +129,10 @@ pub async fn complete(
.method(Method::POST)
.uri(uri)
.header("Anthropic-Version", "2023-06-01")
.header("Anthropic-Beta", "tools-2024-04-04")
.header(
"Anthropic-Beta",
"tools-2024-04-04,prompt-caching-2024-07-31",
)
.header("X-Api-Key", api_key)
.header("Content-Type", "application/json");
@ -161,7 +189,10 @@ pub async fn stream_completion(
.method(Method::POST)
.uri(uri)
.header("Anthropic-Version", "2023-06-01")
.header("Anthropic-Beta", "tools-2024-04-04")
.header(
"Anthropic-Beta",
"tools-2024-04-04,prompt-caching-2024-07-31",
)
.header("X-Api-Key", api_key)
.header("Content-Type", "application/json");
if let Some(low_speed_timeout) = low_speed_timeout {
@ -226,7 +257,7 @@ pub fn extract_text_from_events(
match response {
Ok(response) => match response {
Event::ContentBlockStart { content_block, .. } => match content_block {
Content::Text { text } => Some(Ok(text)),
Content::Text { text, .. } => Some(Ok(text)),
_ => None,
},
Event::ContentBlockDelta { delta, .. } => match delta {
@ -285,13 +316,25 @@ pub async fn extract_tool_args_from_events(
}))
}
#[derive(Debug, Serialize, Deserialize, Copy, Clone)]
#[serde(rename_all = "lowercase")]
pub enum CacheControlType {
Ephemeral,
}
#[derive(Debug, Serialize, Deserialize, Copy, Clone)]
pub struct CacheControl {
#[serde(rename = "type")]
pub cache_type: CacheControlType,
}
#[derive(Debug, Serialize, Deserialize)]
pub struct Message {
pub role: Role,
pub content: Vec<Content>,
}
#[derive(Debug, Serialize, Deserialize)]
#[derive(Debug, Serialize, Deserialize, Eq, PartialEq, Hash)]
#[serde(rename_all = "lowercase")]
pub enum Role {
User,
@ -302,19 +345,31 @@ pub enum Role {
#[serde(tag = "type")]
pub enum Content {
#[serde(rename = "text")]
Text { text: String },
Text {
text: String,
#[serde(skip_serializing_if = "Option::is_none")]
cache_control: Option<CacheControl>,
},
#[serde(rename = "image")]
Image { source: ImageSource },
Image {
source: ImageSource,
#[serde(skip_serializing_if = "Option::is_none")]
cache_control: Option<CacheControl>,
},
#[serde(rename = "tool_use")]
ToolUse {
id: String,
name: String,
input: serde_json::Value,
#[serde(skip_serializing_if = "Option::is_none")]
cache_control: Option<CacheControl>,
},
#[serde(rename = "tool_result")]
ToolResult {
tool_use_id: String,
content: String,
#[serde(skip_serializing_if = "Option::is_none")]
cache_control: Option<CacheControl>,
},
}

176
crates/assistant/src/context.rs
View File

@ -21,8 +21,8 @@ use gpui::{
use language::{AnchorRangeExt, Bias, Buffer, LanguageRegistry, OffsetRangeExt, Point, ToOffset};
use language_model::{
LanguageModelImage, LanguageModelRegistry, LanguageModelRequest, LanguageModelRequestMessage,
Role,
LanguageModel, LanguageModelCacheConfiguration, LanguageModelImage, LanguageModelRegistry,
LanguageModelRequest, LanguageModelRequestMessage, Role,
};
use open_ai::Model as OpenAiModel;
use paths::{context_images_dir, contexts_dir};
@ -30,7 +30,7 @@ use project::Project;
use serde::{Deserialize, Serialize};
use smallvec::SmallVec;
use std::{
cmp::Ordering,
cmp::{max, Ordering},
collections::hash_map,
fmt::Debug,
iter, mem,
@ -107,6 +107,8 @@ impl ContextOperation {
message.status.context("invalid status")?,
),
timestamp: id.0,
should_cache: false,
is_cache_anchor: false,
},
version: language::proto::deserialize_version(&insert.version),
})
@ -121,6 +123,8 @@ impl ContextOperation {
timestamp: language::proto::deserialize_timestamp(
update.timestamp.context("invalid timestamp")?,
),
should_cache: false,
is_cache_anchor: false,
},
version: language::proto::deserialize_version(&update.version),
}),
@ -313,6 +317,8 @@ pub struct MessageMetadata {
pub role: Role,
pub status: MessageStatus,
timestamp: clock::Lamport,
should_cache: bool,
is_cache_anchor: bool,
}
#[derive(Clone, Debug)]
@ -338,6 +344,7 @@ pub struct Message {
pub anchor: language::Anchor,
pub role: Role,
pub status: MessageStatus,
pub cache: bool,
}
impl Message {
@ -373,6 +380,7 @@ impl Message {
LanguageModelRequestMessage {
role: self.role,
content,
cache: self.cache,
}
}
}
@ -421,6 +429,7 @@ pub struct Context {
token_count: Option<usize>,
pending_token_count: Task<Option<()>>,
pending_save: Task<Result<()>>,
pending_cache_warming_task: Task<Option<()>>,
path: Option<PathBuf>,
_subscriptions: Vec<Subscription>,
telemetry: Option<Arc<Telemetry>>,
@ -498,6 +507,7 @@ impl Context {
pending_completions: Default::default(),
token_count: None,
pending_token_count: Task::ready(None),
pending_cache_warming_task: Task::ready(None),
_subscriptions: vec![cx.subscribe(&buffer, Self::handle_buffer_event)],
pending_save: Task::ready(Ok(())),
path: None,
@ -524,6 +534,8 @@ impl Context {
role: Role::User,
status: MessageStatus::Done,
timestamp: first_message_id.0,
should_cache: false,
is_cache_anchor: false,
},
);
this.message_anchors.push(message);
@ -948,6 +960,7 @@ impl Context {
let token_count = cx.update(|cx| model.count_tokens(request, cx))?.await?;
this.update(&mut cx, |this, cx| {
this.token_count = Some(token_count);
this.start_cache_warming(&model, cx);
cx.notify()
})
}
@ -955,6 +968,121 @@ impl Context {
});
}
pub fn mark_longest_messages_for_cache(
&mut self,
cache_configuration: &Option<LanguageModelCacheConfiguration>,
speculative: bool,
cx: &mut ModelContext<Self>,
) -> bool {
let cache_configuration =
cache_configuration
.as_ref()
.unwrap_or(&LanguageModelCacheConfiguration {
max_cache_anchors: 0,
should_speculate: false,
min_total_token: 0,
});
let messages: Vec<Message> = self
.messages_from_anchors(
self.message_anchors.iter().take(if speculative {
self.message_anchors.len().saturating_sub(1)
} else {
self.message_anchors.len()
}),
cx,
)
.filter(|message| message.offset_range.len() >= 5_000)
.collect();
let mut sorted_messages = messages.clone();
sorted_messages.sort_by(|a, b| b.offset_range.len().cmp(&a.offset_range.len()));
if cache_configuration.max_cache_anchors == 0 && cache_configuration.should_speculate {
// Some models support caching, but don't support anchors. In that case we want to
// mark the largest message as needing to be cached, but we will not mark it as an
// anchor.
sorted_messages.truncate(1);
} else {
// Save 1 anchor for the inline assistant.
sorted_messages.truncate(max(cache_configuration.max_cache_anchors, 1) - 1);
}
let longest_message_ids: HashSet<MessageId> = sorted_messages
.into_iter()
.map(|message| message.id)
.collect();
let cache_deltas: HashSet<MessageId> = self
.messages_metadata
.iter()
.filter_map(|(id, metadata)| {
let should_cache = longest_message_ids.contains(id);
let should_be_anchor = should_cache && cache_configuration.max_cache_anchors > 0;
if metadata.should_cache != should_cache
|| metadata.is_cache_anchor != should_be_anchor
{
Some(*id)
} else {
None
}
})
.collect();
let mut newly_cached_item = false;
for id in cache_deltas {
newly_cached_item = newly_cached_item || longest_message_ids.contains(&id);
self.update_metadata(id, cx, |metadata| {
metadata.should_cache = longest_message_ids.contains(&id);
metadata.is_cache_anchor =
metadata.should_cache && (cache_configuration.max_cache_anchors > 0);
});
}
newly_cached_item
}
fn start_cache_warming(&mut self, model: &Arc<dyn LanguageModel>, cx: &mut ModelContext<Self>) {
let cache_configuration = model.cache_configuration();
if !self.mark_longest_messages_for_cache(&cache_configuration, true, cx) {
return;
}
if let Some(cache_configuration) = cache_configuration {
if !cache_configuration.should_speculate {
return;
}
}
let request = {
let mut req = self.to_completion_request(cx);
// Skip the last message because it's likely to change and
// therefore would be a waste to cache.
req.messages.pop();
req.messages.push(LanguageModelRequestMessage {
role: Role::User,
content: vec!["Respond only with OK, nothing else.".into()],
cache: false,
});
req
};
let model = Arc::clone(model);
self.pending_cache_warming_task = cx.spawn(|_, cx| {
async move {
match model.stream_completion(request, &cx).await {
Ok(mut stream) => {
stream.next().await;
log::info!("Cache warming completed successfully");
}
Err(e) => {
log::warn!("Cache warming failed: {}", e);
}
};
anyhow::Ok(())
}
.log_err()
});
}
pub fn reparse_slash_commands(&mut self, cx: &mut ModelContext<Self>) {
let buffer = self.buffer.read(cx);
let mut row_ranges = self
@ -1352,20 +1480,26 @@ impl Context {
self.count_remaining_tokens(cx);
}
pub fn assist(&mut self, cx: &mut ModelContext<Self>) -> Option<MessageAnchor> {
let provider = LanguageModelRegistry::read_global(cx).active_provider()?;
let model = LanguageModelRegistry::read_global(cx).active_model()?;
let last_message_id = self.message_anchors.iter().rev().find_map(|message| {
fn get_last_valid_message_id(&self, cx: &ModelContext<Self>) -> Option<MessageId> {
self.message_anchors.iter().rev().find_map(|message| {
message
.start
.is_valid(self.buffer.read(cx))
.then_some(message.id)
})?;
})
}
pub fn assist(&mut self, cx: &mut ModelContext<Self>) -> Option<MessageAnchor> {
let provider = LanguageModelRegistry::read_global(cx).active_provider()?;
let model = LanguageModelRegistry::read_global(cx).active_model()?;
let last_message_id = self.get_last_valid_message_id(cx)?;
if !provider.is_authenticated(cx) {
log::info!("completion provider has no credentials");
return None;
}
// Compute which messages to cache, including the last one.
self.mark_longest_messages_for_cache(&model.cache_configuration(), false, cx);
let request = self.to_completion_request(cx);
let assistant_message = self
@ -1580,6 +1714,8 @@ impl Context {
role,
status,
timestamp: anchor.id.0,
should_cache: false,
is_cache_anchor: false,
};
self.insert_message(anchor.clone(), metadata.clone(), cx);
self.push_op(
@ -1696,6 +1832,8 @@ impl Context {
role,
status: MessageStatus::Done,
timestamp: suffix.id.0,
should_cache: false,
is_cache_anchor: false,
};
self.insert_message(suffix.clone(), suffix_metadata.clone(), cx);
self.push_op(
@ -1745,6 +1883,8 @@ impl Context {
role,
status: MessageStatus::Done,
timestamp: selection.id.0,
should_cache: false,
is_cache_anchor: false,
};
self.insert_message(selection.clone(), selection_metadata.clone(), cx);
self.push_op(
@ -1811,6 +1951,7 @@ impl Context {
content: vec![
"Summarize the context into a short title without punctuation.".into(),
],
cache: false,
}));
let request = LanguageModelRequest {
messages: messages.collect(),
@ -1910,14 +2051,22 @@ impl Context {
result
}
pub fn messages<'a>(&'a self, cx: &'a AppContext) -> impl 'a + Iterator<Item = Message> {
fn messages_from_anchors<'a>(
&'a self,
message_anchors: impl Iterator<Item = &'a MessageAnchor> + 'a,
cx: &'a AppContext,
) -> impl 'a + Iterator<Item = Message> {
let buffer = self.buffer.read(cx);
let messages = self.message_anchors.iter().enumerate();
let messages = message_anchors.enumerate();
let images = self.image_anchors.iter();
Self::messages_from_iters(buffer, &self.messages_metadata, messages, images)
}
pub fn messages<'a>(&'a self, cx: &'a AppContext) -> impl 'a + Iterator<Item = Message> {
self.messages_from_anchors(self.message_anchors.iter(), cx)
}
pub fn messages_from_iters<'a>(
buffer: &'a Buffer,
metadata: &'a HashMap<MessageId, MessageMetadata>,
@ -1969,6 +2118,7 @@ impl Context {
anchor: message_anchor.start,
role: metadata.role,
status: metadata.status.clone(),
cache: metadata.is_cache_anchor,
image_offsets,
});
}
@ -2215,6 +2365,8 @@ impl SavedContext {
role: message.metadata.role,
status: message.metadata.status,
timestamp: message.metadata.timestamp,
should_cache: false,
is_cache_anchor: false,
},
version: version.clone(),
});
@ -2231,6 +2383,8 @@ impl SavedContext {
role: metadata.role,
status: metadata.status,
timestamp,
should_cache: false,
is_cache_anchor: false,
},
version: version.clone(),
});
@ -2325,6 +2479,8 @@ impl SavedContextV0_3_0 {
role: metadata.role,
status: metadata.status.clone(),
timestamp,
should_cache: false,
is_cache_anchor: false,
},
image_offsets: Vec::new(),
})

1
crates/assistant/src/inline_assistant.rs
View File

@ -2387,6 +2387,7 @@ impl Codegen {
messages.push(LanguageModelRequestMessage {
role: Role::User,
content: vec![prompt.into()],
cache: false,
});
Ok(LanguageModelRequest {

1
crates/assistant/src/prompt_library.rs
View File

@ -784,6 +784,7 @@ impl PromptLibrary {
messages: vec![LanguageModelRequestMessage {
role: Role::System,
content: vec![body.to_string().into()],
cache: false,
}],
stop: Vec::new(),
temperature: 1.,

1
crates/assistant/src/terminal_inline_assistant.rs
View File

@ -277,6 +277,7 @@ impl TerminalInlineAssistant {
messages.push(LanguageModelRequestMessage {
role: Role::User,
content: vec![prompt.into()],
cache: false,
});
Ok(LanguageModelRequest {

1
crates/assistant/src/workflow.rs
View File

@ -136,6 +136,7 @@ impl WorkflowStep {
request.messages.push(LanguageModelRequestMessage {
role: Role::User,
content: vec![prompt.into()],
cache: false,
});
// Invoke the model to get its edit suggestions for this workflow step.

14
crates/language_model/src/language_model.rs
View File

@ -20,7 +20,7 @@ pub use registry::*;
pub use request::*;
pub use role::*;
use schemars::JsonSchema;
use serde::de::DeserializeOwned;
use serde::{de::DeserializeOwned, Deserialize, Serialize};
use std::{future::Future, sync::Arc};
use ui::IconName;
@ -43,6 +43,14 @@ pub enum LanguageModelAvailability {
RequiresPlan(Plan),
}
/// Configuration for caching language model messages.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
pub struct LanguageModelCacheConfiguration {
pub max_cache_anchors: usize,
pub should_speculate: bool,
pub min_total_token: usize,
}
pub trait LanguageModel: Send + Sync {
fn id(&self) -> LanguageModelId;
fn name(&self) -> LanguageModelName;
@ -78,6 +86,10 @@ pub trait LanguageModel: Send + Sync {
cx: &AsyncAppContext,
) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>>;
fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
None
}
#[cfg(any(test, feature = "test-support"))]
fn as_fake(&self) -> &provider::fake::FakeLanguageModel {
unimplemented!()

24
crates/language_model/src/provider/anthropic.rs
View File

@ -1,7 +1,7 @@
use crate::{
settings::AllLanguageModelSettings, LanguageModel, LanguageModelId, LanguageModelName,
LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
LanguageModelProviderState, LanguageModelRequest, RateLimiter, Role,
settings::AllLanguageModelSettings, LanguageModel, LanguageModelCacheConfiguration,
LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest, RateLimiter, Role,
};
use anthropic::AnthropicError;
use anyhow::{anyhow, Context as _, Result};
@ -38,6 +38,7 @@ pub struct AvailableModel {
pub name: String,
pub max_tokens: usize,
pub tool_override: Option<String>,
pub cache_configuration: Option<LanguageModelCacheConfiguration>,
}
pub struct AnthropicLanguageModelProvider {
@ -171,6 +172,13 @@ impl LanguageModelProvider for AnthropicLanguageModelProvider {
name: model.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,
}
}),
},
);
}
@ -351,6 +359,16 @@ impl LanguageModel for AnthropicModel {
.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,
})
}
fn use_any_tool(
&self,
request: LanguageModelRequest,

12
crates/language_model/src/provider/cloud.rs
View File

@ -1,7 +1,7 @@
use super::open_ai::count_open_ai_tokens;
use crate::{
settings::AllLanguageModelSettings, CloudModel, LanguageModel, LanguageModelId,
LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,
settings::AllLanguageModelSettings, CloudModel, LanguageModel, LanguageModelCacheConfiguration,
LanguageModelId, LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,
LanguageModelProviderState, LanguageModelRequest, RateLimiter, ZedModel,
};
use anthropic::AnthropicError;
@ -56,6 +56,7 @@ pub struct AvailableModel {
name: String,
max_tokens: usize,
tool_override: Option<String>,
cache_configuration: Option<LanguageModelCacheConfiguration>,
}
pub struct CloudLanguageModelProvider {
@ -202,6 +203,13 @@ impl LanguageModelProvider for CloudLanguageModelProvider {
name: model.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,
}
}),
})
}
AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {

84
crates/language_model/src/request.rs
View File

@ -193,6 +193,7 @@ impl From<&str> for MessageContent {
pub struct LanguageModelRequestMessage {
pub role: Role,
pub content: Vec<MessageContent>,
pub cache: bool,
}
impl LanguageModelRequestMessage {
@ -213,7 +214,7 @@ impl LanguageModelRequestMessage {
.content
.get(0)
.map(|content| match content {
MessageContent::Text(s) => s.is_empty(),
MessageContent::Text(s) => s.trim().is_empty(),
MessageContent::Image(_) => true,
})
.unwrap_or(false)
@ -286,7 +287,7 @@ impl LanguageModelRequest {
}
pub fn into_anthropic(self, model: String) -> anthropic::Request {
let mut new_messages: Vec<LanguageModelRequestMessage> = Vec::new();
let mut new_messages: Vec<anthropic::Message> = Vec::new();
let mut system_message = String::new();
for message in self.messages {
@ -296,18 +297,50 @@ impl LanguageModelRequest {
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::Content> = message
.content
.into_iter()
// TODO: filter out the empty messages in the message construction step
.filter_map(|content| match content {
MessageContent::Text(t) if !t.is_empty() => {
Some(anthropic::Content::Text {
text: t,
cache_control,
})
}
MessageContent::Image(i) => Some(anthropic::Content::Image {
source: anthropic::ImageSource {
source_type: "base64".to_string(),
media_type: "image/png".to_string(),
data: i.source.to_string(),
},
cache_control,
}),
_ => None,
})
.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 == message.role {
// TODO: is this append done properly?
last_message.content.push(MessageContent::Text(format!(
"\n\n{}",
message.string_contents()
)));
if last_message.role == anthropic_role {
last_message.content.extend(anthropic_message_content);
continue;
}
}
new_messages.push(message);
new_messages.push(anthropic::Message {
role: anthropic_role,
content: anthropic_message_content,
});
}
Role::System => {
if !system_message.is_empty() {
@ -320,36 +353,7 @@ impl LanguageModelRequest {
anthropic::Request {
model,
messages: new_messages
.into_iter()
.filter_map(|message| {
Some(anthropic::Message {
role: match message.role {
Role::User => anthropic::Role::User,
Role::Assistant => anthropic::Role::Assistant,
Role::System => return None,
},
content: message
.content
.into_iter()
// TODO: filter out the empty messages in the message construction step
.filter_map(|content| match content {
MessageContent::Text(t) if !t.is_empty() => {
Some(anthropic::Content::Text { text: t })
}
MessageContent::Image(i) => Some(anthropic::Content::Image {
source: anthropic::ImageSource {
source_type: "base64".to_string(),
media_type: "image/png".to_string(),
data: i.source.to_string(),
},
}),
_ => None,
})
.collect(),
})
})
.collect(),
messages: new_messages,
max_tokens: 4092,
system: Some(system_message),
tools: Vec::new(),

27
crates/language_model/src/settings.rs
View File

@ -7,14 +7,17 @@ use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use settings::{update_settings_file, Settings, SettingsSources};
use crate::provider::{
self,
anthropic::AnthropicSettings,
cloud::{self, ZedDotDevSettings},
copilot_chat::CopilotChatSettings,
google::GoogleSettings,
ollama::OllamaSettings,
open_ai::OpenAiSettings,
use crate::{
provider::{
self,
anthropic::AnthropicSettings,
cloud::{self, ZedDotDevSettings},
copilot_chat::CopilotChatSettings,
google::GoogleSettings,
ollama::OllamaSettings,
open_ai::OpenAiSettings,
},
LanguageModelCacheConfiguration,
};
/// Initializes the language model settings.
@ -93,10 +96,18 @@ impl AnthropicSettingsContent {
name,
max_tokens,
tool_override,
cache_configuration,
} => Some(provider::anthropic::AvailableModel {
name,
max_tokens,
tool_override,
cache_configuration: cache_configuration.as_ref().map(
|config| LanguageModelCacheConfiguration {
max_cache_anchors: config.max_cache_anchors,
should_speculate: config.should_speculate,
min_total_token: config.min_total_token,
},
),
}),
_ => None,
})