feat: AI code generation — LLM generates fix actions from findings
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Yuriy
parent
2be548d078
commit
af3c81b04d
134
desktop/src-tauri/src/commands/generate_ai_actions.rs
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134
desktop/src-tauri/src/commands/generate_ai_actions.rs
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@ -0,0 +1,134 @@
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use crate::types::{Action, ActionKind};
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use serde::{Deserialize, Serialize};
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#[derive(Debug, Serialize, Deserialize)]
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pub struct GenerateActionsRequest {
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pub provider: String,
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pub model: String,
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pub api_key: Option<String>,
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pub base_url: Option<String>,
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pub context: String, // llm_context JSON
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pub findings_json: String, // findings array JSON
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pub project_path: String,
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pub max_tokens: Option<u32>,
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}
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#[derive(Debug, Serialize, Deserialize)]
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pub struct GenerateActionsResponse {
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pub ok: bool,
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pub actions: Vec<Action>,
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pub explanation: String,
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pub error: Option<String>,
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}
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#[derive(Debug, Deserialize)]
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struct LlmActionsOutput {
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actions: Vec<LlmAction>,
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explanation: String,
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}
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#[derive(Debug, Deserialize)]
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struct LlmAction {
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id: String,
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title: String,
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description: String,
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kind: String, // "create_file" | "update_file" | "create_dir"
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path: String,
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content: Option<String>,
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}
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#[tauri::command]
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pub async fn generate_ai_actions(
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request: GenerateActionsRequest,
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) -> Result<GenerateActionsResponse, String> {
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let api_key = request.api_key.clone().unwrap_or_default();
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if api_key.is_empty() && request.provider != "ollama" {
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return Ok(GenerateActionsResponse {
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ok: false,
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actions: vec![],
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explanation: String::new(),
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error: Some("API-ключ не указан.".into()),
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});
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}
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let user_prompt = format!(
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"Ты — PAPA YU, AI-аудитор проектов. На основе контекста и списка найденных проблем сгенерируй конкретные действия для исправления.\n\nВАЖНО: Отвечай ТОЛЬКО валидным JSON без markdown-обёртки. Формат:\n{{\n \"actions\": [\n {{\n \"id\": \"уникальный-id\",\n \"title\": \"Краткое название\",\n \"description\": \"Что делает\",\n \"kind\": \"create_file\",\n \"path\": \"путь/к/файлу\",\n \"content\": \"содержимое\"\n }}\n ],\n \"explanation\": \"Краткое объяснение\"\n}}\n\nДопустимые kind: \"create_file\", \"update_file\", \"create_dir\"\nПуть — относительный от корня проекта. Не более 10 действий.\nПуть проекта: {}\n\nПроблемы:\n{}",
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request.project_path,
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request.findings_json
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);
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let llm_request = super::ask_llm::LlmRequest {
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provider: request.provider,
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model: request.model,
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api_key: request.api_key,
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base_url: request.base_url,
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context: request.context,
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prompt: user_prompt,
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max_tokens: request.max_tokens.or(Some(4096)),
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};
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let llm_response = super::ask_llm::ask_llm(llm_request).await?;
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if !llm_response.ok {
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return Ok(GenerateActionsResponse {
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ok: false,
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actions: vec![],
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explanation: String::new(),
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error: llm_response.error,
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});
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}
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// Parse JSON from LLM response
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let content = llm_response.content.trim().to_string();
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// Strip markdown code fences if present
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let json_str = content
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.strip_prefix("```json")
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.or_else(|| content.strip_prefix("```"))
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.unwrap_or(&content)
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.strip_suffix("```")
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.unwrap_or(&content)
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.trim();
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match serde_json::from_str::<LlmActionsOutput>(json_str) {
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Ok(output) => {
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let actions: Vec<Action> = output
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.actions
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.into_iter()
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.filter_map(|a| {
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let kind = match a.kind.as_str() {
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"create_file" => ActionKind::CreateFile,
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"update_file" => ActionKind::UpdateFile,
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"create_dir" => ActionKind::CreateDir,
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"delete_file" => ActionKind::DeleteFile,
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_ => return None,
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};
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Some(Action {
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id: format!("ai-{}", a.id),
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title: a.title,
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description: a.description,
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kind,
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path: a.path,
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content: a.content,
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})
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})
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.collect();
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Ok(GenerateActionsResponse {
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ok: true,
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actions,
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explanation: output.explanation,
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error: None,
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})
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}
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Err(e) => Ok(GenerateActionsResponse {
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ok: false,
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actions: vec![],
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explanation: String::new(),
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error: Some(format!(
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"Ошибка парсинга ответа LLM: {}. Ответ: {}",
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e,
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&json_str[..json_str.len().min(200)]
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)),
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}),
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}
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}
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@ -1,6 +1,7 @@
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mod analyze_project;
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mod apply_actions;
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mod ask_llm;
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pub mod ask_llm;
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mod generate_ai_actions;
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mod get_app_info;
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mod preview_actions;
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mod undo_last;
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@ -8,6 +9,7 @@ mod undo_last;
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pub use analyze_project::analyze_project;
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pub use apply_actions::apply_actions;
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pub use ask_llm::ask_llm;
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pub use generate_ai_actions::generate_ai_actions;
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pub use get_app_info::get_app_info;
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pub use preview_actions::preview_actions;
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pub use undo_last::undo_last;
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@ -1,7 +1,7 @@
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mod commands;
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mod types;
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use commands::{analyze_project, apply_actions, ask_llm, get_app_info, preview_actions, undo_last};
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use commands::{analyze_project, apply_actions, ask_llm, generate_ai_actions, get_app_info, preview_actions, undo_last};
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#[cfg_attr(mobile, tauri::mobile_entry_point)]
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pub fn run() {
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@ -26,6 +26,7 @@ pub fn run() {
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undo_last,
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get_app_info,
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ask_llm,
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generate_ai_actions,
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])
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.run(tauri::generate_context!())
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.expect("error while running tauri application");
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@ -187,3 +187,30 @@ export async function askLlm(
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},
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});
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}
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// ---- AI Code Generation ----
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export interface GenerateActionsResponse {
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ok: boolean;
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actions: Action[];
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explanation: string;
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error?: string | null;
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}
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export async function generateAiActions(
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settings: LlmSettings,
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report: AnalyzeReport,
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): Promise<GenerateActionsResponse> {
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return invoke<GenerateActionsResponse>('generate_ai_actions', {
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request: {
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provider: settings.provider,
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model: settings.model,
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api_key: settings.apiKey || null,
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base_url: settings.baseUrl || null,
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context: JSON.stringify(report.llm_context),
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findings_json: JSON.stringify(report.findings),
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project_path: report.path,
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max_tokens: 4096,
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},
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});
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}
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@ -19,7 +19,7 @@ import {
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X,
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} from 'lucide-react';
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import { invoke } from '@tauri-apps/api/core';
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import { analyzeProject, askLlm, type AnalyzeReport, type Action, type ApplyResult, type UndoResult, type PreviewResult, type DiffItem, type LlmSettings, DEFAULT_LLM_SETTINGS } from '../lib/analyze';
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import { analyzeProject, askLlm, generateAiActions, type AnalyzeReport, type Action, type ApplyResult, type UndoResult, type PreviewResult, type DiffItem, type LlmSettings, DEFAULT_LLM_SETTINGS } from '../lib/analyze';
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import { animateFadeInUp } from '../lib/anime-utils';
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import { useAppStore } from '../store/app-store';
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@ -121,6 +121,73 @@ export function Tasks() {
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setIsAiAnalyzing(false);
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};
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const [isGeneratingActions, setIsGeneratingActions] = useState(false);
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const handleAiCodeGen = async (report: AnalyzeReport) => {
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const settings = loadLlmSettings();
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if (!settings.apiKey && settings.provider !== 'ollama') {
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setMessages((prev) => [
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...prev,
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{ role: 'system', text: '⚠️ API-ключ не настроен. Перейдите в Настройки LLM.' },
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]);
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return;
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}
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setIsGeneratingActions(true);
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setMessages((prev) => [...prev, { role: 'system', text: '🔧 AI генерирует исправления...' }]);
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try {
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const resp = await generateAiActions(settings, report);
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if (resp.ok && resp.actions.length > 0) {
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// Merge AI actions into the report
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const updatedReport = {
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...report,
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actions: [...(report.actions ?? []), ...resp.actions],
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};
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setLastReport(updatedReport);
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storeSetLastReport(updatedReport, report.path);
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// Init selection for new actions
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const newSelection: Record<string, boolean> = { ...selectedActions };
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resp.actions.forEach((a) => { newSelection[a.id] = true; });
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setSelectedActions(newSelection);
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// Update the last assistant message with new report
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setMessages((prev) => {
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const updated = [...prev];
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// Find the last assistant message with this report and update it
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for (let i = updated.length - 1; i >= 0; i--) {
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const msg = updated[i];
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if ('report' in msg && msg.report.path === report.path) {
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updated[i] = { ...msg, report: updatedReport };
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break;
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}
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}
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return [
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...updated,
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{ role: 'assistant', text: `🔧 **AI сгенерировал ${resp.actions.length} исправлений** (${settings.model}):\n\n${resp.explanation}` },
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];
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});
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} else if (resp.ok && resp.actions.length === 0) {
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setMessages((prev) => [
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...prev,
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{ role: 'system', text: '✓ AI не нашёл дополнительных исправлений — проект в хорошем состоянии.' },
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]);
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} else {
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setMessages((prev) => [
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...prev,
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{ role: 'system', text: `❌ Ошибка генерации: ${resp.error}` },
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]);
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}
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} catch (e) {
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setMessages((prev) => [
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...prev,
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{ role: 'system', text: `❌ Ошибка: ${e}` },
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]);
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}
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setIsGeneratingActions(false);
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};
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useEffect(() => {
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messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
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}, [messages]);
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@ -605,6 +672,8 @@ export function Tasks() {
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onUndo={handleUndoLast}
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onAiAnalysis={handleAiAnalysis}
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isAiAnalyzing={isAiAnalyzing}
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onAiCodeGen={handleAiCodeGen}
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isGeneratingActions={isGeneratingActions}
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/>
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)}
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</div>
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@ -803,6 +872,8 @@ function ReportBlock({
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onUndo: (projectPath: string) => void;
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onAiAnalysis?: (report: AnalyzeReport) => void;
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isAiAnalyzing?: boolean;
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onAiCodeGen?: (report: AnalyzeReport) => void;
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isGeneratingActions?: boolean;
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}) {
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if (error) {
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return <div className="text-sm text-destructive">Ошибка: {error}</div>;
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@ -948,6 +1019,17 @@ function ReportBlock({
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{isAiAnalyzing ? 'AI анализирует...' : 'AI Анализ'}
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</button>
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)}
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{isCurrentReport && onAiCodeGen && (
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<button
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type="button"
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onClick={() => onAiCodeGen(r)}
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disabled={isGeneratingActions}
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className="inline-flex items-center gap-2 px-3 py-1.5 rounded-lg border bg-green-600 text-white text-sm font-medium hover:opacity-90 disabled:opacity-50"
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>
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<RefreshCw className={`w-4 h-4 ${isGeneratingActions ? 'animate-spin' : ''}`} />
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{isGeneratingActions ? 'Генерирую...' : 'AI Исправления'}
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</button>
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)}
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<button
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type="button"
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onClick={() => onDownload(r)}
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