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use crate::agent::tools::{get_tool_definitions, ToolCall};
use crate::apis::api_client::{
CompletionOptions, DynApiClient, Message, ToolDefinition, ToolResult,
};
use anyhow::{Context, Result};
use serde_json::{self, Value};
use tokio::sync::mpsc;
// We'll implement token usage tracking directly in the app without
// a separate structure for now
pub struct AgentExecutor {
api_client: DynApiClient,
conversation: Vec<Message>,
tool_definitions: Vec<ToolDefinition>,
progress_sender: Option<mpsc::Sender<String>>,
}
impl AgentExecutor {
pub fn new(api_client: DynApiClient) -> Self {
let tool_defs = get_tool_definitions()
.into_iter()
.map(|def| ToolDefinition {
name: def["name"].as_str().unwrap_or("").to_string(),
description: def["description"].as_str().unwrap_or("").to_string(),
parameters: def["parameters"].clone(),
})
.collect();
Self {
api_client,
conversation: Vec::new(),
tool_definitions: tool_defs,
progress_sender: None,
}
}
pub fn set_conversation_history(&mut self, history: Vec<Message>) {
self.conversation = history;
}
pub fn get_conversation_history(&self) -> Vec<Message> {
self.conversation.clone()
}
/// Analyze conversation to determine if code parsing might be needed
/// Uses the LLM directly to make this determination rather than keyword matching
async fn might_need_codebase_parsing(&self) -> Result<bool> {
// Get the latest user message
if let Some(last_user_msg) = self
.conversation
.iter()
.rev()
.find(|msg| msg.role == "user")
{
let content = &last_user_msg.content;
// Create a system message explaining the task
let system_message = Message::system(
"You are an assistant that analyzes user queries to determine if they require \
code structure understanding. Respond with only 'yes' or 'no'. Answer 'yes' if \
the query involves understanding, modifying, or implementing code structures like \
functions, classes, modules, etc. Answer 'no' for general information queries, tool \
usage questions, or non-code tasks.".to_string()
);
// Create a user message with the query
let query_message = Message::user(format!(
"Based solely on this query, would understanding the code structure be helpful? \
Query: '{}'",
content
));
// Create a mini-conversation for this specific task
let mini_conversation = vec![system_message, query_message];
// Create LLM options with minimal settings
let options = CompletionOptions {
temperature: Some(0.1), // Low temperature for deterministic response
top_p: Some(0.95),
max_tokens: Some(10), // Very small response needed
tools: None, // No tools needed
require_tool_use: false,
json_schema: None,
};
// Call the API to get the determination - using a separate client call
// that doesn't affect our main conversation history
let (response, _) = self
.api_client
.complete_with_tools(mini_conversation, options, None)
.await?;
// Check the response - looking for a "yes" answer
let response_lower = response.to_lowercase();
Ok(response_lower.contains("yes") || response_lower.contains("true"))
} else {
// No user message found
Ok(false)
}
}
pub fn with_progress_sender(mut self, sender: mpsc::Sender<String>) -> Self {
self.progress_sender = Some(sender);
self
}
pub fn add_system_message(&mut self, content: String) {
self.conversation.push(Message::system(content));
}
pub fn add_user_message(&mut self, content: String) {
self.conversation.push(Message::user(content));
}
pub async fn execute(&mut self) -> Result<String> {
// Create options with tools enabled and optimized parameters for Claude 3.7
let options = CompletionOptions {
temperature: Some(0.5), // Lower temperature for more precise outputs
top_p: Some(0.95), // Slightly higher top_p for better quality
max_tokens: Some(4096), // Generous token limit
tools: Some(self.tool_definitions.clone()),
require_tool_use: false, // Let the model decide when to use tools
json_schema: None, // No structured format for initial response
};
// Check if the query might need codebase parsing using the LLM
// This initial check helps determine if we should suggest code parsing to the model
let needs_parsing = self.might_need_codebase_parsing().await?;
// If this query potentially needs code parsing, suggest it to the model
// by adding a system hint for better context understanding
if needs_parsing {
// Add a temporary system message suggesting code parsing
self.conversation.push(Message::system(
"The user's query appears to be related to code. Consider using the ParseCode tool \
to understand the codebase structure before responding, if you need to understand \
the code to provide a solution. The ParseCode tool will generate an AST \
(Abstract Syntax Tree) that helps you understand the code structure.".to_string()
));
}
// Execute the first completion with tools
let (content, tool_calls) = self
.api_client
.complete_with_tools(self.conversation.clone(), options.clone(), None)
.await?;
// Remove the temporary system message if it was added
if needs_parsing {
if let Some(last) = self.conversation.last() {
if last.role == "system" && last.content.contains("ParseCode tool") {
self.conversation.pop();
}
}
}
// If there are no tool calls, add the content to conversation and return
if tool_calls.is_none() {
self.conversation.push(Message::assistant(content.clone()));
return Ok(content);
}
// Add the assistant's message with tool calls to the conversation - important for OpenAI API
// We need to preserve all the context including tool calls for proper API behavior
// For OpenAI compatibility, store the tool calls in the message content as structured JSON
// This allows for proper serialization/deserialization of tool calls in the message history
if let Some(calls) = &tool_calls {
// Create a JSON object with both content and tool calls
let message_with_tools = serde_json::json!({
"content": content,
"tool_calls": calls.iter().map(|call| {
serde_json::json!({
"id": call.id.clone().unwrap_or_default(),
"name": call.name,
"arguments": call.arguments
})
}).collect::<Vec<_>>()
});
// Store as JSON string in the message
self.conversation.push(Message::assistant(
serde_json::to_string(&message_with_tools).unwrap_or_else(|_| content.clone()),
));
} else {
// No tool calls, just store the content directly
self.conversation.push(Message::assistant(content.clone()));
}
// Process tool calls in a loop until no more tools are called
let mut current_content = content;
let mut current_tool_calls = tool_calls;
let mut tool_results = Vec::new();
let mut loop_count = 0;
const MAX_LOOPS: usize = 10; // Safety limit for tool call loops
while let Some(ref calls) = current_tool_calls {
// Safety check to prevent infinite loops
loop_count += 1;
if loop_count > MAX_LOOPS {
if let Some(sender) = &self.progress_sender {
let _ = sender
.send("Reached maximum number of tool call loops. Stopping.".to_string())
.await;
}
break;
}
// We don't need this summary since each tool call will have its own message
// This improves the async nature of the tool execution
// Execute each tool call and collect results
for (i, call) in calls.iter().enumerate() {
// Format tool call details for better UI display before execution
let formatted_tool_details = match call.name.as_str() {
"View" => {
if let (Some(path), Some(offset), Some(limit)) = (
call.arguments.get("file_path").and_then(|v| v.as_str()),
call.arguments.get("offset").and_then(|v| v.as_u64()),
call.arguments.get("limit").and_then(|v| v.as_u64()),
) {
format!(
"View(file_path: \"{}\", offset: {}, limit: {})…",
path, offset, limit
)
} else if let Some(path) =
call.arguments.get("file_path").and_then(|v| v.as_str())
{
format!("View(file_path: \"{}\")…", path)
} else {
format!("View({:?})…", call.arguments)
}
}
"GlobTool" => {
if let (Some(pattern), Some(path)) = (
call.arguments.get("pattern").and_then(|v| v.as_str()),
call.arguments.get("path").and_then(|v| v.as_str()),
) {
format!("GlobTool(pattern: \"{}\", path: \"{}\")…", pattern, path)
} else if let Some(pattern) =
call.arguments.get("pattern").and_then(|v| v.as_str())
{
format!("GlobTool(pattern: \"{}\")…", pattern)
} else {
format!("GlobTool({:?})…", call.arguments)
}
}
"GrepTool" => {
if let Some(pattern) =
call.arguments.get("pattern").and_then(|v| v.as_str())
{
format!("GrepTool(pattern: \"{}\")…", pattern)
} else {
format!("GrepTool({:?})…", call.arguments)
}
}
"LS" => {
if let Some(path) = call.arguments.get("path").and_then(|v| v.as_str()) {
format!("LS(path: \"{}\")…", path)
} else {
format!("LS({:?})…", call.arguments)
}
}
"Edit" | "Replace" => {
if let Some(path) = call.arguments.get("file_path").and_then(|v| v.as_str())
{
format!("{} file: \"{}\"…", call.name, path)
} else {
format!("{} {:?}…", call.name, call.arguments)
}
}
"Bash" => {
if let Some(cmd) = call.arguments.get("command").and_then(|v| v.as_str()) {
if cmd.len() > 40 {
format!("Bash(command: \"{}...\")…", &cmd[..40])
} else {
format!("Bash(command: \"{}\")…", cmd)
}
} else {
format!("Bash({:?})…", call.arguments)
}
}
_ => format!("{} {:?}…", call.name, call.arguments),
};
// Send the formatted tool details to UI before execution
if let Some(sender) = &self.progress_sender {
let _ = sender
// Use orange color for tool execution in progress
.send(format!("⏺ {}", formatted_tool_details))
.await;
}
// Use the previously formatted tool details for showing execution
// Parse the tool call into our enum
let tool_call: ToolCall = match parse_tool_call(&call.name, &call.arguments) {
Ok(tc) => tc,
Err(e) => {
let error_msg = format!("Failed to parse tool call: {}", e);
if let Some(sender) = &self.progress_sender {
let _ = sender.send(format!("[error] {}", error_msg)).await;
}
// Instead of returning error, provide helpful error message to the model
// Use the ID from the tool call if available (ensuring it's valid for Anthropic API)
tool_results.push(ToolResult {
tool_call_id: call.id.clone().unwrap_or_else(|| format!("tool_{}", i)),
output: format!("ERROR PARSING TOOL CALL: {}. Please check the format of your arguments and try again.", e),
});
continue;
}
};
// No need for additional tool selection message since we already show it above
// This prevents redundant messages about tool usage
// For Edit and Replace tools, show diff preview before executing
let needs_diff_preview = matches!(call.name.as_str(), "Edit" | "Replace");
// Execute the tool
let result = match if needs_diff_preview {
// For file modifications, preview the diff first, then request permission and execute
match &tool_call {
ToolCall::Edit(params) => {
use crate::tools::fs::file_ops::FileOps;
use std::path::PathBuf;
// Generate the diff without making changes yet
let path = PathBuf::from(¶ms.file_path);
match FileOps::generate_edit_diff(
&path,
¶ms.old_string,
¶ms.new_string,
) {
Ok((_, diff)) => {
// Send the diff as a progress message for the permission system to pick up
if let Some(sender) = &self.progress_sender {
let _ = sender.send(diff.clone()).await;
}
// Now execute the actual tool to make the changes
tool_call.execute()
}
Err(e) => Err(e),
}
}
ToolCall::Replace(params) => {
use crate::tools::fs::file_ops::FileOps;
use std::path::PathBuf;
// Generate the diff without making changes yet
let path = PathBuf::from(¶ms.file_path);
match FileOps::generate_write_diff(&path, ¶ms.content) {
Ok((diff, _)) => {
// Send the diff as a progress message for the permission system to pick up
if let Some(sender) = &self.progress_sender {
let _ = sender.send(diff.clone()).await;
}
// Now execute the actual tool to make the changes
tool_call.execute()
}
Err(e) => Err(e),
}
}
_ => tool_call.execute(), // Shouldn't happen, but fallback
}
} else {
// For non-file operations, execute normally
tool_call.execute()
} {
Ok(output) => {
// Send a special marker for tool counting that's easy to detect
if let Some(sender) = &self.progress_sender {
let _ = sender.send("[TOOL_EXECUTED]".to_string()).await;
}
// Format successful tool result with detailed output
if let Some(sender) = &self.progress_sender {
// Send a separate explicit success status notification
let _ = sender
.send(format!(
"[completed] Tool {} executed successfully",
call.name
))
.await;
// Create a preview of the output
let preview = if output.len() > 200 {
format!(
"{}... [+{} more chars]",
&output[..200],
output.len() - 200
)
} else {
output.clone()
};
// For file outputs, prepare a structured display for the UI
let formatted_result = match call.name.as_str() {
"View" => {
if let Some(path) =
call.arguments.get("file_path").and_then(|v| v.as_str())
{
// Display path and first few content lines
let output_lines: Vec<&str> = output.lines().collect();
let header =
format!("View(file_path: \"{}\") → Result:", path);
// Format first few lines with line numbers
if output_lines.len() <= 2 {
format!("{}\n ⎿ {}", header, output)
} else {
let mut formatted = header.to_string();
for (i, line) in output_lines.iter().take(3).enumerate()
{
formatted.push_str(&format!("\n ⎿ {}", line));
if i == 2 && output_lines.len() > 3 {
formatted.push_str(&format!(
"\n ... [{} more lines]",
output_lines.len() - 3
));
}
}
formatted
}
} else {
format!("Tool result: {}", preview)
}
}
"GlobTool" => {
let pattern = call
.arguments
.get("pattern")
.and_then(|v| v.as_str())
.unwrap_or("unknown");
// Tool name for display
let name = "Glob";
// Get the file paths from the output, skipping the header
let file_paths: Vec<String> = output
.lines()
.filter(|line| line.contains(". "))
.map(|line| {
// Extract just the path part after the numbering
line.split_once(". ")
.map(|(_, path)| path.trim().to_string())
.unwrap_or_else(|| line.trim().to_string())
})
.collect();
let file_count = file_paths.len();
// Create a cleaner format that works better with TUI rendering
if file_count == 0 {
format!(
"{}(pattern: \"{}\") → No files found",
name, pattern
)
} else {
let mut formatted = format!(
"{}(pattern: \"{}\") → Found {} files",
name, pattern, file_count
);
// Show first 3 files at most
for path in file_paths.iter().take(3) {
formatted.push_str(&format!("\n ⎿ {}", path));
}
// Add count of remaining files if needed
if file_count > 3 {
formatted.push_str(&format!(
"\n ... [+{} more files]",
file_count - 3
));
}
formatted
}
}
"GrepTool" => {
let pattern = call
.arguments
.get("pattern")
.and_then(|v| v.as_str())
.unwrap_or("unknown");
// First line contains count of matches
let first_line = output.lines().next().unwrap_or("");
let match_count = if first_line.starts_with("Found ") {
first_line
.split_whitespace()
.nth(1)
.and_then(|s| s.parse::<usize>().ok())
.unwrap_or(0)
} else {
output.lines().filter(|l| l.contains(":")).count()
};
// Format the grep matches for better display
if match_count == 0 {
format!("Grep(pattern: \"{}\") → No matches found", pattern)
} else {
let mut formatted = format!(
"Grep(pattern: \"{}\") → Found {} matches",
pattern, match_count
);
// Extract and format the grep matches (path:line:content)
let matches: Vec<&str> = output
.lines()
.filter(|line| line.contains(":"))
.take(3)
.collect();
for grep_match in matches {
formatted.push_str(&format!("\n ⎿ {}", grep_match));
}
// Add count of remaining matches if needed
if match_count > 3 {
formatted.push_str(&format!(
"\n ... [+{} more matches]",
match_count - 3
));
}
formatted
}
}
"LS" => {
if let Some(path) =
call.arguments.get("path").and_then(|v| v.as_str())
{
let file_count =
output.lines().filter(|l| l.contains("FILE")).count();
let dir_count =
output.lines().filter(|l| l.contains("DIR")).count();
format!("LS(path: \"{}\") → Listed {} items ({} files, {} dirs)",
path, file_count + dir_count, file_count, dir_count)
} else {
format!("Tool result: {}", preview)
}
}
"Edit" | "Replace" => {
if let Some(_path) =
call.arguments.get("file_path").and_then(|v| v.as_str())
{
// The output is now already formatted as a diff, directly pass it through
// We return multiple lines that show colored diff output
output.clone()
} else {
format!("Tool result: {}", preview)
}
}
"Bash" => {
if let Some(cmd) =
call.arguments.get("command").and_then(|v| v.as_str())
{
let cmd_preview = if cmd.len() > 30 {
format!("{}...", &cmd[..30])
} else {
cmd.to_string()
};
// Format command output with line counts
let output_lines = output.lines().count();
if output_lines > 5 {
let mut formatted = format!(
"Bash(command: \"{}\") → {} lines of output:",
cmd_preview, output_lines
);
for line in output.lines().take(3) {
formatted.push_str(&format!("\n ⎿ {}", line));
}
formatted.push_str(&format!(
"\n ... [{} more lines]",
output_lines - 3
));
formatted
} else if output_lines > 0 {
let mut formatted = format!(
"Bash(command: \"{}\") → Output:",
cmd_preview
);
for line in output.lines() {
formatted.push_str(&format!("\n ⎿ {}", line));
}
formatted
} else {
format!(
"Bash(command: \"{}\") → No output",
cmd_preview
)
}
} else {
format!("Tool result: {}", preview)
}
}
_ => format!("Tool result: {}", preview),
};
// Replace newlines with proper message breaks to ensure they display properly in TUI
let formatted_lines: Vec<&str> = formatted_result.split('\n').collect();
if formatted_lines.len() <= 1 {
// Single line - just send it directly
let _ = sender
.send(format!("⏺ [completed] {}", formatted_result))
.await;
} else {
// For multiline output, break into separate messages for better display
// Send first line with the [completed] prefix
let _ = sender
.send(format!("⏺ [completed] {}", formatted_lines[0]))
.await;
// Send remaining lines with proper indentation
for line in &formatted_lines[1..] {
let _ = sender.send(format!(" {}", line)).await;
}
}
// Small delay to allow UI update
tokio::time::sleep(tokio::time::Duration::from_millis(100)).await;
}
output
}
Err(e) => {
let error_msg = format!("Tool execution failed: {}", e);
if let Some(sender) = &self.progress_sender {
// Send an explicit error notification that the UI can detect
let _ = sender
.send("[error] Tool execution failed".to_string())
.await;
// Then send the detailed error message
let _ = sender.send(format!("⏺ [error] {}", error_msg)).await;
}
// Return error message as tool result
format!("ERROR EXECUTING TOOL: {}", e)
}
};
// Create a valid tool result ID (for Anthropic API: only alphanumeric, underscore, hyphen)
let tool_call_id = call.id.clone().unwrap_or_else(|| format!("tool_{}", i));
// Add tool result with proper ID for API compatibility
tool_results.push(ToolResult {
tool_call_id: tool_call_id.clone(),
output: result.clone(),
});
// Also add a user message with the tool result to maintain history properly
self.conversation.push(Message {
role: "user".to_string(),
content: format!("Tool result for call {}: {}", tool_call_id, result),
});
}
// Don't show "processing" message to reduce UI noise
// For subsequent calls, add the tool results and use JSON schema to get more reliable output
let next_options = if loop_count >= MAX_LOOPS - 1 {
// On the last loop, request a final summary with no further tool calls
CompletionOptions {
require_tool_use: false,
json_schema: Some(
r#"
{
"type": "object",
"properties": {
"finalSummary": {
"type": "string",
"description": "Final comprehensive summary of findings and results"
}
},
"required": ["finalSummary"]
}
"#
.to_string(),
),
..options.clone()
}
} else {
// For intermediate calls, continue with normal options
options.clone()
};
// Request another completion with the tool results
let (next_content, next_tool_calls) = self
.api_client
.complete_with_tools(
self.conversation.clone(),
next_options,
Some(tool_results.clone()),
)
.await?;
// Extract JSON content if present
current_content = if next_content.trim().starts_with('{')
&& next_content.trim().ends_with('}')
{
// Try to parse as JSON to extract the finalSummary if available
match serde_json::from_str::<serde_json::Value>(&next_content) {
Ok(json) => {
if let Some(summary) = json.get("finalSummary").and_then(|s| s.as_str()) {
summary.to_string()
} else {
next_content
}
}
Err(_) => next_content,
}
} else {
next_content
};
current_tool_calls = next_tool_calls;
// If no more tool calls, break the loop
if current_tool_calls.is_none() {
break;
}
// Clear previous tool results
tool_results.clear();
}
// Add final response to conversation
// Handle the case where there might still be tool calls
if let Some(calls) = ¤t_tool_calls {
// Create a JSON object with both content and tool calls
let message_with_tools = serde_json::json!({
"content": current_content,
"tool_calls": calls.iter().map(|call| {
serde_json::json!({
"id": call.id.clone().unwrap_or_default(),
"name": call.name,
"arguments": call.arguments
})
}).collect::<Vec<_>>()
});
// Store as JSON string in the message
self.conversation.push(Message::assistant(
serde_json::to_string(&message_with_tools)
.unwrap_or_else(|_| current_content.clone()),
));
} else {
// No tool calls, just store the content directly
self.conversation
.push(Message::assistant(current_content.clone()));
}
Ok(current_content)
}
}
fn parse_tool_call(name: &str, args: &Value) -> Result<ToolCall> {
match name {
"View" => {
let params =
serde_json::from_value(args.clone()).context("Failed to parse View parameters")?;
Ok(ToolCall::View(params))
}
"GlobTool" => {
let params = serde_json::from_value(args.clone())
.context("Failed to parse GlobTool parameters")?;
Ok(ToolCall::GlobTool(params))
}
"GrepTool" => {
let params = serde_json::from_value(args.clone())
.context("Failed to parse GrepTool parameters")?;
Ok(ToolCall::GrepTool(params))
}
"LS" => {
let params =
serde_json::from_value(args.clone()).context("Failed to parse LS parameters")?;
Ok(ToolCall::LS(params))
}
"Edit" => {
let params =
serde_json::from_value(args.clone()).context("Failed to parse Edit parameters")?;
Ok(ToolCall::Edit(params))
}
"Replace" => {
let params = serde_json::from_value(args.clone())
.context("Failed to parse Replace parameters")?;
Ok(ToolCall::Replace(params))
}
"Bash" => {
let params =
serde_json::from_value(args.clone()).context("Failed to parse Bash parameters")?;
Ok(ToolCall::Bash(params))
}
"ParseCode" => {
let params = serde_json::from_value(args.clone())
.context("Failed to parse ParseCode parameters")?;
Ok(ToolCall::ParseCode(params))
}
_ => Err(anyhow::anyhow!("Unknown tool: {}", name)),
}
}
// Note: For future improvements, we could extract actual token usage from the API responses
// rather than estimating them based on string length. This would involve parsing the
// response JSON to extract token counts from both Anthropic and OpenAI formats.