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language_model: Remove use_any_tool method from LanguageModel (#27930)

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This PR removes the `use_any_tool` method from the `LanguageModel`
trait.

It was not being used anywhere, and doesn't really fit in our new tool
use story.

Release Notes:

- N/A
This commit is contained in:
Marshall Bowers 2025-04-02 11:49:21 -04:00 • committed by GitHub
parent da3383b10e
commit 889bc13b7d
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12 changed files with 8 additions and 541 deletions
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104
crates/language_models/src/provider/cloud.rs
View file

@ -29,7 +29,6 @@ use settings::{Settings, SettingsStore};
use smol::Timer;
use smol::io::{AsyncReadExt, BufReader};
use std::{
future,
sync::{Arc, LazyLock},
time::Duration,
};
@ -743,109 +742,6 @@ impl LanguageModel for CloudLanguageModel {
}
}
}
fn use_any_tool(
&self,
request: LanguageModelRequest,
tool_name: String,
tool_description: String,
input_schema: serde_json::Value,
_cx: &AsyncApp,
) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
let client = self.client.clone();
let llm_api_token = self.llm_api_token.clone();
match &self.model {
CloudModel::Anthropic(model) => {
let mut request = into_anthropic(
request,
model.tool_model_id().into(),
model.default_temperature(),
model.max_output_tokens(),
model.mode(),
);
request.tool_choice = Some(anthropic::ToolChoice::Tool {
name: tool_name.clone(),
});
request.tools = vec![anthropic::Tool {
name: tool_name.clone(),
description: tool_description,
input_schema,
}];
self.request_limiter
.run(async move {
let response = Self::perform_llm_completion(
client.clone(),
llm_api_token,
PerformCompletionParams {
provider: client::LanguageModelProvider::Anthropic,
model: request.model.clone(),
provider_request: RawValue::from_string(serde_json::to_string(
&request,
)?)?,
},
)
.await?;
Ok(anthropic::extract_tool_args_from_events(
tool_name,
Box::pin(response_lines(response)),
)
.await?
.boxed())
})
.boxed()
}
CloudModel::OpenAi(model) => {
let mut request =
into_open_ai(request, model.id().into(), model.max_output_tokens());
request.tool_choice = Some(open_ai::ToolChoice::Other(
open_ai::ToolDefinition::Function {
function: open_ai::FunctionDefinition {
name: tool_name.clone(),
description: None,
parameters: None,
},
},
));
request.tools = vec![open_ai::ToolDefinition::Function {
function: open_ai::FunctionDefinition {
name: tool_name.clone(),
description: Some(tool_description),
parameters: Some(input_schema),
},
}];
self.request_limiter
.run(async move {
let response = Self::perform_llm_completion(
client.clone(),
llm_api_token,
PerformCompletionParams {
provider: client::LanguageModelProvider::OpenAi,
model: request.model.clone(),
provider_request: RawValue::from_string(serde_json::to_string(
&request,
)?)?,
},
)
.await?;
Ok(open_ai::extract_tool_args_from_events(
tool_name,
Box::pin(response_lines(response)),
)
.await?
.boxed())
})
.boxed()
}
CloudModel::Google(_) => {
future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
}
}
}
}
fn response_lines<T: DeserializeOwned>(