Files
storkit/src-tauri/src/commands/chat.rs

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Rust
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use crate::commands::{fs, search, shell};
use crate::llm::ollama::OllamaProvider;
use crate::llm::types::{
Message, ModelProvider, Role, ToolCall, ToolDefinition, ToolFunctionDefinition,
};
use crate::state::SessionState;
use serde::Deserialize;
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use serde_json::json;
use tauri::State;
#[derive(Deserialize)]
pub struct ProviderConfig {
pub provider: String, // "ollama"
pub model: String,
pub base_url: Option<String>,
pub enable_tools: Option<bool>,
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}
const MAX_TURNS: usize = 10;
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#[tauri::command]
pub async fn get_ollama_models(base_url: Option<String>) -> Result<Vec<String>, String> {
let url = base_url.unwrap_or_else(|| "http://localhost:11434".to_string());
OllamaProvider::get_models(&url).await
}
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#[tauri::command]
pub async fn chat(
messages: Vec<Message>,
config: ProviderConfig,
state: State<'_, SessionState>,
) -> Result<Vec<Message>, String> {
// 1. Setup Provider
let provider: Box<dyn ModelProvider> = match config.provider.as_str() {
"ollama" => Box::new(OllamaProvider::new(
config
.base_url
.unwrap_or_else(|| "http://localhost:11434".to_string()),
)),
_ => return Err(format!("Unsupported provider: {}", config.provider)),
};
// 2. Define Tools
let tool_defs = get_tool_definitions();
let tools = if config.enable_tools.unwrap_or(true) {
tool_defs.as_slice()
} else {
&[]
};
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// 3. Agent Loop
let mut current_history = messages.clone();
let mut new_messages: Vec<Message> = Vec::new();
let mut turn_count = 0;
loop {
if turn_count >= MAX_TURNS {
return Err("Max conversation turns reached.".to_string());
}
turn_count += 1;
// Call LLM
let response = provider
.chat(&config.model, &current_history, tools)
.await
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.map_err(|e| format!("LLM Error: {}", e))?;
// Process Response
if let Some(tool_calls) = response.tool_calls {
// The Assistant wants to run tools
let assistant_msg = Message {
role: Role::Assistant,
content: response.content.unwrap_or_default(),
tool_calls: Some(tool_calls.clone()),
tool_call_id: None,
};
current_history.push(assistant_msg.clone());
new_messages.push(assistant_msg);
// Execute Tools
for call in tool_calls {
let output = execute_tool(&call, &state).await;
let tool_msg = Message {
role: Role::Tool,
content: output,
tool_calls: None,
// For Ollama/Simple flow, we just append.
// For OpenAI strict, this needs to match call.id.
tool_call_id: call.id,
};
current_history.push(tool_msg.clone());
new_messages.push(tool_msg);
}
} else {
// Final text response
let assistant_msg = Message {
role: Role::Assistant,
content: response.content.unwrap_or_default(),
tool_calls: None,
tool_call_id: None,
};
// We don't push to current_history needed for next loop, because we are done.
new_messages.push(assistant_msg);
break;
}
}
Ok(new_messages)
}
async fn execute_tool(call: &ToolCall, state: &State<'_, SessionState>) -> String {
let name = call.function.name.as_str();
// Parse arguments. They come as a JSON string from the LLM abstraction.
let args: serde_json::Value = match serde_json::from_str(&call.function.arguments) {
Ok(v) => v,
Err(e) => return format!("Error parsing arguments: {}", e),
};
match name {
"read_file" => {
let path = args["path"].as_str().unwrap_or("").to_string();
match fs::read_file(path, state.clone()).await {
Ok(content) => content,
Err(e) => format!("Error: {}", e),
}
}
"write_file" => {
let path = args["path"].as_str().unwrap_or("").to_string();
let content = args["content"].as_str().unwrap_or("").to_string();
match fs::write_file(path, content, state.clone()).await {
Ok(_) => "File written successfully.".to_string(),
Err(e) => format!("Error: {}", e),
}
}
"list_directory" => {
let path = args["path"].as_str().unwrap_or("").to_string();
match fs::list_directory(path, state.clone()).await {
Ok(entries) => serde_json::to_string(&entries).unwrap_or_default(),
Err(e) => format!("Error: {}", e),
}
}
"search_files" => {
let query = args["query"].as_str().unwrap_or("").to_string();
match search::search_files(query, state.clone()).await {
Ok(results) => serde_json::to_string(&results).unwrap_or_default(),
Err(e) => format!("Error: {}", e),
}
}
"exec_shell" => {
let command = args["command"].as_str().unwrap_or("").to_string();
let args_vec: Vec<String> = args["args"]
.as_array()
.map(|arr| {
arr.iter()
.map(|v| v.as_str().unwrap_or("").to_string())
.collect()
})
.unwrap_or_default();
match shell::exec_shell(command, args_vec, state.clone()).await {
Ok(output) => serde_json::to_string(&output).unwrap_or_default(),
Err(e) => format!("Error: {}", e),
}
}
_ => format!("Unknown tool: {}", name),
}
}
fn get_tool_definitions() -> Vec<ToolDefinition> {
vec![
ToolDefinition {
kind: "function".to_string(),
function: ToolFunctionDefinition {
name: "read_file".to_string(),
description: "Reads the content of a file in the project.".to_string(),
parameters: json!({
"type": "object",
"properties": {
"path": { "type": "string", "description": "Relative path to the file" }
},
"required": ["path"]
}),
},
},
ToolDefinition {
kind: "function".to_string(),
function: ToolFunctionDefinition {
name: "write_file".to_string(),
description: "Writes content to a file. Overwrites if exists.".to_string(),
parameters: json!({
"type": "object",
"properties": {
"path": { "type": "string", "description": "Relative path to the file" },
"content": { "type": "string", "description": "The full content to write" }
},
"required": ["path", "content"]
}),
},
},
ToolDefinition {
kind: "function".to_string(),
function: ToolFunctionDefinition {
name: "list_directory".to_string(),
description: "Lists files and directories at a path.".to_string(),
parameters: json!({
"type": "object",
"properties": {
"path": { "type": "string", "description": "Relative path to list (use '.' for root)" }
},
"required": ["path"]
}),
},
},
ToolDefinition {
kind: "function".to_string(),
function: ToolFunctionDefinition {
name: "search_files".to_string(),
description: "Searches for text content across all files in the project."
.to_string(),
parameters: json!({
"type": "object",
"properties": {
"query": { "type": "string", "description": "The string to search for" }
},
"required": ["query"]
}),
},
},
ToolDefinition {
kind: "function".to_string(),
function: ToolFunctionDefinition {
name: "exec_shell".to_string(),
description: "Executes a shell command in the project root.".to_string(),
parameters: json!({
"type": "object",
"properties": {
"command": {
"type": "string",
"description": "The command to run (e.g., 'git', 'cargo', 'ls')"
},
"args": {
"type": "array",
"items": { "type": "string" },
"description": "Arguments for the command"
}
},
"required": ["command", "args"]
}),
},
},
]
}