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cx.background_executor().spawn(...) -> cx.background_spawn(...) (#25103)

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Done automatically with

> ast-grep -p '$A.background_executor().spawn($B)' -r
'$A.background_spawn($B)' --update-all --globs "\!crates/gpui"

Followed by:

* `cargo fmt`
* Unexpected need to remove some trailing whitespace.
* Manually adding imports of `gpui::{AppContext as _}` which provides
`background_spawn`
* Added `AppContext as _` to existing use of `AppContext`

Release Notes:

- N/A
This commit is contained in:
Michael Sloan 2025-02-18 13:30:33 -07:00 • committed by GitHub
parent f606b0641e
commit b1872e3afd
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120 changed files with 1146 additions and 1267 deletions
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81
crates/language_models/src/provider/anthropic.rs
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@ -252,54 +252,53 @@ pub fn count_anthropic_tokens(
request: LanguageModelRequest,
cx: &App,
) -> BoxFuture<'static, Result<usize>> {
cx.background_executor()
.spawn(async move {
let messages = request.messages;
let mut tokens_from_images = 0;
let mut string_messages = Vec::with_capacity(messages.len());
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;
for message in messages {
use language_model::MessageContent;
let mut string_contents = String::new();
let mut string_contents = String::new();
for content in message.content {
match content {
MessageContent::Text(text) => {
string_contents.push_str(&text);
}
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);
}
for content in message.content {
match content {
MessageContent::Text(text) => {
string_contents.push_str(&text);
}
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()
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 {