- Backend: Added OllamaProvider::chat_stream() with newline-delimited JSON parsing - Backend: Emit chat:token events for each token received from Ollama - Backend: Added futures dependency and stream feature for reqwest - Frontend: Added streamingContent state and chat:token event listener - Frontend: Real-time token display with auto-scroll - Frontend: Markdown and syntax highlighting support for streaming content - Fixed all TypeScript errors (tsc --noEmit) - Fixed all Biome warnings and errors - Fixed all Clippy warnings - Added comprehensive code quality documentation - Added tsc --noEmit to verification checklist Tested and verified: - Tokens stream in real-time - Auto-scroll works during streaming - Tool calls interrupt streaming correctly - Multi-turn conversations work - Smooth performance with no lag
292 lines
11 KiB
Rust
292 lines
11 KiB
Rust
use crate::commands::{fs, search, shell};
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use crate::llm::ollama::OllamaProvider;
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use crate::llm::prompts::SYSTEM_PROMPT;
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use crate::llm::types::{Message, Role, ToolCall, ToolDefinition, ToolFunctionDefinition};
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use crate::state::SessionState;
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use serde::Deserialize;
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use serde_json::json;
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use tauri::{AppHandle, Emitter, State};
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#[derive(Deserialize)]
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pub struct ProviderConfig {
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pub provider: String, // "ollama"
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pub model: String,
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pub base_url: Option<String>,
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pub enable_tools: Option<bool>,
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}
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const MAX_TURNS: usize = 30;
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#[tauri::command]
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pub async fn get_ollama_models(base_url: Option<String>) -> Result<Vec<String>, String> {
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let url = base_url.unwrap_or_else(|| "http://localhost:11434".to_string());
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OllamaProvider::get_models(&url).await
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}
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#[tauri::command]
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pub async fn chat(
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app: AppHandle,
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messages: Vec<Message>,
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config: ProviderConfig,
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state: State<'_, SessionState>,
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) -> Result<Vec<Message>, String> {
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// 1. Setup Provider
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let base_url = config
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.base_url
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.clone()
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.unwrap_or_else(|| "http://localhost:11434".to_string());
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if config.provider.as_str() != "ollama" {
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return Err(format!("Unsupported provider: {}", config.provider));
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}
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let provider = OllamaProvider::new(base_url);
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// 2. Define Tools
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let tool_defs = get_tool_definitions();
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let tools = if config.enable_tools.unwrap_or(true) {
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tool_defs.as_slice()
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} else {
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&[]
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};
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// 3. Agent Loop
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let mut current_history = messages.clone();
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// Inject System Prompt
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current_history.insert(
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0,
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Message {
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role: Role::System,
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content: SYSTEM_PROMPT.to_string(),
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tool_calls: None,
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tool_call_id: None,
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},
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);
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// Inject reminder as a second system message
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current_history.insert(
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1,
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Message {
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role: Role::System,
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content: "REMINDER: Distinguish between showing examples (use code blocks in chat) vs implementing changes (use write_file tool). Keywords like 'show me', 'example', 'how does' = chat response. Keywords like 'create', 'add', 'implement', 'fix' = use tools.".to_string(),
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tool_calls: None,
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tool_call_id: None,
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},
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);
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let mut new_messages: Vec<Message> = Vec::new();
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let mut turn_count = 0;
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loop {
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if turn_count >= MAX_TURNS {
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return Err("Max conversation turns reached.".to_string());
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}
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turn_count += 1;
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// Call LLM with streaming
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let response = provider
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.chat_stream(&app, &config.model, ¤t_history, tools)
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.await
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.map_err(|e| format!("LLM Error: {}", e))?;
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// Process Response
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if let Some(tool_calls) = response.tool_calls {
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// The Assistant wants to run tools
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let assistant_msg = Message {
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role: Role::Assistant,
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content: response.content.unwrap_or_default(),
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tool_calls: Some(tool_calls.clone()),
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tool_call_id: None,
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};
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current_history.push(assistant_msg.clone());
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new_messages.push(assistant_msg);
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// Emit history excluding system prompts (indices 0 and 1)
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app.emit("chat:update", ¤t_history[2..])
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.map_err(|e| e.to_string())?;
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// Execute Tools
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for call in tool_calls {
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let output = execute_tool(&call, &state).await;
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let tool_msg = Message {
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role: Role::Tool,
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content: output,
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tool_calls: None,
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// For Ollama/Simple flow, we just append.
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// For OpenAI strict, this needs to match call.id.
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tool_call_id: call.id,
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};
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current_history.push(tool_msg.clone());
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new_messages.push(tool_msg);
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// Emit history excluding system prompts (indices 0 and 1)
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app.emit("chat:update", ¤t_history[2..])
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.map_err(|e| e.to_string())?;
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}
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} else {
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// Final text response
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let assistant_msg = Message {
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role: Role::Assistant,
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content: response.content.unwrap_or_default(),
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tool_calls: None,
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tool_call_id: None,
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};
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// We don't push to current_history needed for next loop, because we are done.
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new_messages.push(assistant_msg.clone());
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current_history.push(assistant_msg);
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// Emit history excluding system prompts (indices 0 and 1)
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app.emit("chat:update", ¤t_history[2..])
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.map_err(|e| e.to_string())?;
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break;
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}
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}
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Ok(new_messages)
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}
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async fn execute_tool(call: &ToolCall, state: &State<'_, SessionState>) -> String {
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let name = call.function.name.as_str();
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// Parse arguments. They come as a JSON string from the LLM abstraction.
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let args: serde_json::Value = match serde_json::from_str(&call.function.arguments) {
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Ok(v) => v,
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Err(e) => return format!("Error parsing arguments: {}", e),
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};
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match name {
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"read_file" => {
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let path = args["path"].as_str().unwrap_or("").to_string();
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match fs::read_file(path, state.clone()).await {
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Ok(content) => content,
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Err(e) => format!("Error: {}", e),
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}
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}
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"write_file" => {
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let path = args["path"].as_str().unwrap_or("").to_string();
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let content = args["content"].as_str().unwrap_or("").to_string();
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match fs::write_file(path, content, state.clone()).await {
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Ok(_) => "File written successfully.".to_string(),
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Err(e) => format!("Error: {}", e),
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}
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}
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"list_directory" => {
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let path = args["path"].as_str().unwrap_or("").to_string();
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match fs::list_directory(path, state.clone()).await {
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Ok(entries) => serde_json::to_string(&entries).unwrap_or_default(),
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Err(e) => format!("Error: {}", e),
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}
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}
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"search_files" => {
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let query = args["query"].as_str().unwrap_or("").to_string();
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match search::search_files(query, state.clone()).await {
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Ok(results) => serde_json::to_string(&results).unwrap_or_default(),
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Err(e) => format!("Error: {}", e),
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}
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}
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"exec_shell" => {
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let command = args["command"].as_str().unwrap_or("").to_string();
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let args_vec: Vec<String> = args["args"]
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.as_array()
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.map(|arr| {
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arr.iter()
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.map(|v| v.as_str().unwrap_or("").to_string())
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.collect()
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})
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.unwrap_or_default();
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match shell::exec_shell(command, args_vec, state.clone()).await {
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Ok(output) => serde_json::to_string(&output).unwrap_or_default(),
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Err(e) => format!("Error: {}", e),
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}
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}
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_ => format!("Unknown tool: {}", name),
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}
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}
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fn get_tool_definitions() -> Vec<ToolDefinition> {
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vec![
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ToolDefinition {
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kind: "function".to_string(),
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function: ToolFunctionDefinition {
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name: "read_file".to_string(),
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description: "Reads the complete content of a file from the project. Use this to understand existing code before making changes.".to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
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"path": { "type": "string", "description": "Relative path to the file from project root" }
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},
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"required": ["path"]
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}),
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},
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},
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ToolDefinition {
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kind: "function".to_string(),
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function: ToolFunctionDefinition {
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name: "write_file".to_string(),
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description: "Creates or completely overwrites a file with new content. YOU MUST USE THIS to implement code changes - do not suggest code to the user. The content parameter must contain the COMPLETE file including all imports, functions, and unchanged code.".to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
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"path": { "type": "string", "description": "Relative path to the file from project root" },
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"content": { "type": "string", "description": "The complete file content to write (not a diff or partial code)" }
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},
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"required": ["path", "content"]
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}),
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},
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},
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ToolDefinition {
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kind: "function".to_string(),
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function: ToolFunctionDefinition {
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name: "list_directory".to_string(),
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description: "Lists all files and directories at a given path. Use this to explore the project structure.".to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
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"path": { "type": "string", "description": "Relative path to list (use '.' for project root)" }
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},
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"required": ["path"]
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}),
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},
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},
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ToolDefinition {
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kind: "function".to_string(),
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function: ToolFunctionDefinition {
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name: "search_files".to_string(),
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description: "Searches for text patterns across all files in the project. Use this to find functions, variables, or code patterns when you don't know which file they're in."
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.to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
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"query": { "type": "string", "description": "The text pattern to search for across all files" }
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},
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"required": ["query"]
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}),
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},
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},
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ToolDefinition {
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kind: "function".to_string(),
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function: ToolFunctionDefinition {
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name: "exec_shell".to_string(),
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description: "Executes a shell command in the project root directory. Use this to run tests, build commands, git operations, or any command-line tool. Examples: cargo check, npm test, git status.".to_string(),
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parameters: json!({
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"type": "object",
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"properties": {
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"command": {
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"type": "string",
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"description": "The command binary to execute (e.g., 'git', 'cargo', 'npm', 'ls')"
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},
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"args": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Array of arguments to pass to the command (e.g., ['status'] for git status)"
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}
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},
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"required": ["command", "args"]
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}),
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},
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},
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]
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}
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