ZIm/crates/agent/src/tool_use.rs
Antonio Scandurra 9f6809a28d
Reuse conversation cache when streaming edits (#30245)
Release Notes:

- Improved latency when the agent applies edits.
2025-05-08 14:36:34 +02:00

518 lines
18 KiB
Rust

use std::sync::Arc;
use anyhow::Result;
use assistant_tool::{AnyToolCard, Tool, ToolResultOutput, ToolUseStatus, ToolWorkingSet};
use collections::HashMap;
use futures::FutureExt as _;
use futures::future::Shared;
use gpui::{App, Entity, SharedString, Task};
use language_model::{
ConfiguredModel, LanguageModel, LanguageModelRequest, LanguageModelToolResult,
LanguageModelToolUse, LanguageModelToolUseId, Role,
};
use project::Project;
use ui::{IconName, Window};
use util::truncate_lines_to_byte_limit;
use crate::thread::{MessageId, PromptId, ThreadId};
use crate::thread_store::SerializedMessage;
#[derive(Debug)]
pub struct ToolUse {
pub id: LanguageModelToolUseId,
pub name: SharedString,
pub ui_text: SharedString,
pub status: ToolUseStatus,
pub input: serde_json::Value,
pub icon: ui::IconName,
pub needs_confirmation: bool,
}
pub struct ToolUseState {
tools: Entity<ToolWorkingSet>,
tool_uses_by_assistant_message: HashMap<MessageId, Vec<LanguageModelToolUse>>,
tool_results: HashMap<LanguageModelToolUseId, LanguageModelToolResult>,
pending_tool_uses_by_id: HashMap<LanguageModelToolUseId, PendingToolUse>,
tool_result_cards: HashMap<LanguageModelToolUseId, AnyToolCard>,
tool_use_metadata_by_id: HashMap<LanguageModelToolUseId, ToolUseMetadata>,
}
impl ToolUseState {
pub fn new(tools: Entity<ToolWorkingSet>) -> Self {
Self {
tools,
tool_uses_by_assistant_message: HashMap::default(),
tool_results: HashMap::default(),
pending_tool_uses_by_id: HashMap::default(),
tool_result_cards: HashMap::default(),
tool_use_metadata_by_id: HashMap::default(),
}
}
/// Constructs a [`ToolUseState`] from the given list of [`SerializedMessage`]s.
///
/// Accepts a function to filter the tools that should be used to populate the state.
pub fn from_serialized_messages(
tools: Entity<ToolWorkingSet>,
messages: &[SerializedMessage],
project: Entity<Project>,
window: &mut Window,
cx: &mut App,
) -> Self {
let mut this = Self::new(tools);
let mut tool_names_by_id = HashMap::default();
for message in messages {
match message.role {
Role::Assistant => {
if !message.tool_uses.is_empty() {
let tool_uses = message
.tool_uses
.iter()
.map(|tool_use| LanguageModelToolUse {
id: tool_use.id.clone(),
name: tool_use.name.clone().into(),
raw_input: tool_use.input.to_string(),
input: tool_use.input.clone(),
is_input_complete: true,
})
.collect::<Vec<_>>();
tool_names_by_id.extend(
tool_uses
.iter()
.map(|tool_use| (tool_use.id.clone(), tool_use.name.clone())),
);
this.tool_uses_by_assistant_message
.insert(message.id, tool_uses);
for tool_result in &message.tool_results {
let tool_use_id = tool_result.tool_use_id.clone();
let Some(tool_use) = tool_names_by_id.get(&tool_use_id) else {
log::warn!("no tool name found for tool use: {tool_use_id:?}");
continue;
};
this.tool_results.insert(
tool_use_id.clone(),
LanguageModelToolResult {
tool_use_id: tool_use_id.clone(),
tool_name: tool_use.clone(),
is_error: tool_result.is_error,
content: tool_result.content.clone(),
output: tool_result.output.clone(),
},
);
if let Some(tool) = this.tools.read(cx).tool(tool_use, cx) {
if let Some(output) = tool_result.output.clone() {
if let Some(card) =
tool.deserialize_card(output, project.clone(), window, cx)
{
this.tool_result_cards.insert(tool_use_id, card);
}
}
}
}
}
}
Role::System | Role::User => {}
}
}
this
}
pub fn cancel_pending(&mut self) -> Vec<PendingToolUse> {
let mut cancelled_tool_uses = Vec::new();
self.pending_tool_uses_by_id
.retain(|tool_use_id, tool_use| {
if matches!(tool_use.status, PendingToolUseStatus::Error { .. }) {
return true;
}
let content = "Tool canceled by user".into();
self.tool_results.insert(
tool_use_id.clone(),
LanguageModelToolResult {
tool_use_id: tool_use_id.clone(),
tool_name: tool_use.name.clone(),
content,
output: None,
is_error: true,
},
);
cancelled_tool_uses.push(tool_use.clone());
false
});
cancelled_tool_uses
}
pub fn pending_tool_uses(&self) -> Vec<&PendingToolUse> {
self.pending_tool_uses_by_id.values().collect()
}
pub fn tool_uses_for_message(&self, id: MessageId, cx: &App) -> Vec<ToolUse> {
let Some(tool_uses_for_message) = &self.tool_uses_by_assistant_message.get(&id) else {
return Vec::new();
};
let mut tool_uses = Vec::new();
for tool_use in tool_uses_for_message.iter() {
let tool_result = self.tool_results.get(&tool_use.id);
let status = (|| {
if let Some(tool_result) = tool_result {
return if tool_result.is_error {
ToolUseStatus::Error(tool_result.content.clone().into())
} else {
ToolUseStatus::Finished(tool_result.content.clone().into())
};
}
if let Some(pending_tool_use) = self.pending_tool_uses_by_id.get(&tool_use.id) {
match pending_tool_use.status {
PendingToolUseStatus::Idle => ToolUseStatus::Pending,
PendingToolUseStatus::NeedsConfirmation { .. } => {
ToolUseStatus::NeedsConfirmation
}
PendingToolUseStatus::Running { .. } => ToolUseStatus::Running,
PendingToolUseStatus::Error(ref err) => {
ToolUseStatus::Error(err.clone().into())
}
PendingToolUseStatus::InputStillStreaming => {
ToolUseStatus::InputStillStreaming
}
}
} else {
ToolUseStatus::Pending
}
})();
let (icon, needs_confirmation) =
if let Some(tool) = self.tools.read(cx).tool(&tool_use.name, cx) {
(tool.icon(), tool.needs_confirmation(&tool_use.input, cx))
} else {
(IconName::Cog, false)
};
tool_uses.push(ToolUse {
id: tool_use.id.clone(),
name: tool_use.name.clone().into(),
ui_text: self.tool_ui_label(
&tool_use.name,
&tool_use.input,
tool_use.is_input_complete,
cx,
),
input: tool_use.input.clone(),
status,
icon,
needs_confirmation,
})
}
tool_uses
}
pub fn tool_ui_label(
&self,
tool_name: &str,
input: &serde_json::Value,
is_input_complete: bool,
cx: &App,
) -> SharedString {
if let Some(tool) = self.tools.read(cx).tool(tool_name, cx) {
if is_input_complete {
tool.ui_text(input).into()
} else {
tool.still_streaming_ui_text(input).into()
}
} else {
format!("Unknown tool {tool_name:?}").into()
}
}
pub fn tool_results_for_message(
&self,
assistant_message_id: MessageId,
) -> Vec<&LanguageModelToolResult> {
let Some(tool_uses) = self
.tool_uses_by_assistant_message
.get(&assistant_message_id)
else {
return Vec::new();
};
tool_uses
.iter()
.filter_map(|tool_use| self.tool_results.get(&tool_use.id))
.collect()
}
pub fn message_has_tool_results(&self, assistant_message_id: MessageId) -> bool {
self.tool_uses_by_assistant_message
.get(&assistant_message_id)
.map_or(false, |results| !results.is_empty())
}
pub fn tool_result(
&self,
tool_use_id: &LanguageModelToolUseId,
) -> Option<&LanguageModelToolResult> {
self.tool_results.get(tool_use_id)
}
pub fn tool_result_card(&self, tool_use_id: &LanguageModelToolUseId) -> Option<&AnyToolCard> {
self.tool_result_cards.get(tool_use_id)
}
pub fn insert_tool_result_card(
&mut self,
tool_use_id: LanguageModelToolUseId,
card: AnyToolCard,
) {
self.tool_result_cards.insert(tool_use_id, card);
}
pub fn request_tool_use(
&mut self,
assistant_message_id: MessageId,
tool_use: LanguageModelToolUse,
metadata: ToolUseMetadata,
cx: &App,
) -> Arc<str> {
let tool_uses = self
.tool_uses_by_assistant_message
.entry(assistant_message_id)
.or_default();
let mut existing_tool_use_found = false;
for existing_tool_use in tool_uses.iter_mut() {
if existing_tool_use.id == tool_use.id {
*existing_tool_use = tool_use.clone();
existing_tool_use_found = true;
}
}
if !existing_tool_use_found {
tool_uses.push(tool_use.clone());
}
let status = if tool_use.is_input_complete {
self.tool_use_metadata_by_id
.insert(tool_use.id.clone(), metadata);
PendingToolUseStatus::Idle
} else {
PendingToolUseStatus::InputStillStreaming
};
let ui_text: Arc<str> = self
.tool_ui_label(
&tool_use.name,
&tool_use.input,
tool_use.is_input_complete,
cx,
)
.into();
self.pending_tool_uses_by_id.insert(
tool_use.id.clone(),
PendingToolUse {
assistant_message_id,
id: tool_use.id,
name: tool_use.name.clone(),
ui_text: ui_text.clone(),
input: tool_use.input,
status,
},
);
ui_text
}
pub fn run_pending_tool(
&mut self,
tool_use_id: LanguageModelToolUseId,
ui_text: SharedString,
task: Task<()>,
) {
if let Some(tool_use) = self.pending_tool_uses_by_id.get_mut(&tool_use_id) {
tool_use.ui_text = ui_text.into();
tool_use.status = PendingToolUseStatus::Running {
_task: task.shared(),
};
}
}
pub fn confirm_tool_use(
&mut self,
tool_use_id: LanguageModelToolUseId,
ui_text: impl Into<Arc<str>>,
input: serde_json::Value,
request: Arc<LanguageModelRequest>,
tool: Arc<dyn Tool>,
) {
if let Some(tool_use) = self.pending_tool_uses_by_id.get_mut(&tool_use_id) {
let ui_text = ui_text.into();
tool_use.ui_text = ui_text.clone();
let confirmation = Confirmation {
tool_use_id,
input,
request,
tool,
ui_text,
};
tool_use.status = PendingToolUseStatus::NeedsConfirmation(Arc::new(confirmation));
}
}
pub fn insert_tool_output(
&mut self,
tool_use_id: LanguageModelToolUseId,
tool_name: Arc<str>,
output: Result<ToolResultOutput>,
configured_model: Option<&ConfiguredModel>,
) -> Option<PendingToolUse> {
let metadata = self.tool_use_metadata_by_id.remove(&tool_use_id);
telemetry::event!(
"Agent Tool Finished",
model = metadata
.as_ref()
.map(|metadata| metadata.model.telemetry_id()),
model_provider = metadata
.as_ref()
.map(|metadata| metadata.model.provider_id().to_string()),
thread_id = metadata.as_ref().map(|metadata| metadata.thread_id.clone()),
prompt_id = metadata.as_ref().map(|metadata| metadata.prompt_id.clone()),
tool_name,
success = output.is_ok()
);
match output {
Ok(output) => {
let tool_result = output.content;
const BYTES_PER_TOKEN_ESTIMATE: usize = 3;
// Protect from clearly large output
let tool_output_limit = configured_model
.map(|model| model.model.max_token_count() * BYTES_PER_TOKEN_ESTIMATE)
.unwrap_or(usize::MAX);
let tool_result = if tool_result.len() <= tool_output_limit {
tool_result
} else {
let truncated = truncate_lines_to_byte_limit(&tool_result, tool_output_limit);
format!(
"Tool result too long. The first {} bytes:\n\n{}",
truncated.len(),
truncated
)
};
self.tool_results.insert(
tool_use_id.clone(),
LanguageModelToolResult {
tool_use_id: tool_use_id.clone(),
tool_name,
content: tool_result.into(),
is_error: false,
output: output.output,
},
);
self.pending_tool_uses_by_id.remove(&tool_use_id)
}
Err(err) => {
self.tool_results.insert(
tool_use_id.clone(),
LanguageModelToolResult {
tool_use_id: tool_use_id.clone(),
tool_name,
content: err.to_string().into(),
is_error: true,
output: None,
},
);
if let Some(tool_use) = self.pending_tool_uses_by_id.get_mut(&tool_use_id) {
tool_use.status = PendingToolUseStatus::Error(err.to_string().into());
}
self.pending_tool_uses_by_id.get(&tool_use_id).cloned()
}
}
}
pub fn has_tool_results(&self, assistant_message_id: MessageId) -> bool {
self.tool_uses_by_assistant_message
.contains_key(&assistant_message_id)
}
pub fn tool_results(
&self,
assistant_message_id: MessageId,
) -> impl Iterator<Item = (&LanguageModelToolUse, Option<&LanguageModelToolResult>)> {
self.tool_uses_by_assistant_message
.get(&assistant_message_id)
.into_iter()
.flatten()
.map(|tool_use| (tool_use, self.tool_results.get(&tool_use.id)))
}
}
#[derive(Debug, Clone)]
pub struct PendingToolUse {
pub id: LanguageModelToolUseId,
/// The ID of the Assistant message in which the tool use was requested.
#[allow(unused)]
pub assistant_message_id: MessageId,
pub name: Arc<str>,
pub ui_text: Arc<str>,
pub input: serde_json::Value,
pub status: PendingToolUseStatus,
}
#[derive(Debug, Clone)]
pub struct Confirmation {
pub tool_use_id: LanguageModelToolUseId,
pub input: serde_json::Value,
pub ui_text: Arc<str>,
pub request: Arc<LanguageModelRequest>,
pub tool: Arc<dyn Tool>,
}
#[derive(Debug, Clone)]
pub enum PendingToolUseStatus {
InputStillStreaming,
Idle,
NeedsConfirmation(Arc<Confirmation>),
Running { _task: Shared<Task<()>> },
Error(#[allow(unused)] Arc<str>),
}
impl PendingToolUseStatus {
pub fn is_idle(&self) -> bool {
matches!(self, PendingToolUseStatus::Idle)
}
pub fn is_error(&self) -> bool {
matches!(self, PendingToolUseStatus::Error(_))
}
pub fn needs_confirmation(&self) -> bool {
matches!(self, PendingToolUseStatus::NeedsConfirmation { .. })
}
}
#[derive(Clone)]
pub struct ToolUseMetadata {
pub model: Arc<dyn LanguageModel>,
pub thread_id: ThreadId,
pub prompt_id: PromptId,
}