feat: AI code generation — LLM generates fix actions from findings

desktop/src-tauri/src/commands/generate_ai_actions.rs

@@ -0,0 +1,134 @@
+use crate::types::{Action, ActionKind};
+use serde::{Deserialize, Serialize};
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct GenerateActionsRequest {
+    pub provider: String,
+    pub model: String,
+    pub api_key: Option<String>,
+    pub base_url: Option<String>,
+    pub context: String,        // llm_context JSON
+    pub findings_json: String,  // findings array JSON
+    pub project_path: String,
+    pub max_tokens: Option<u32>,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct GenerateActionsResponse {
+    pub ok: bool,
+    pub actions: Vec<Action>,
+    pub explanation: String,
+    pub error: Option<String>,
+}
+
+#[derive(Debug, Deserialize)]
+struct LlmActionsOutput {
+    actions: Vec<LlmAction>,
+    explanation: String,
+}
+
+#[derive(Debug, Deserialize)]
+struct LlmAction {
+    id: String,
+    title: String,
+    description: String,
+    kind: String,       // "create_file" | "update_file" | "create_dir"
+    path: String,
+    content: Option<String>,
+}
+
+#[tauri::command]
+pub async fn generate_ai_actions(
+    request: GenerateActionsRequest,
+) -> Result<GenerateActionsResponse, String> {
+    let api_key = request.api_key.clone().unwrap_or_default();
+    if api_key.is_empty() && request.provider != "ollama" {
+        return Ok(GenerateActionsResponse {
+            ok: false,
+            actions: vec![],
+            explanation: String::new(),
+            error: Some("API-ключ не указан.".into()),
+        });
+    }
+
+    let user_prompt = format!(
+        "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{}",
+        request.project_path,
+        request.findings_json
+    );
+
+    let llm_request = super::ask_llm::LlmRequest {
+        provider: request.provider,
+        model: request.model,
+        api_key: request.api_key,
+        base_url: request.base_url,
+        context: request.context,
+        prompt: user_prompt,
+        max_tokens: request.max_tokens.or(Some(4096)),
+    };
+
+    let llm_response = super::ask_llm::ask_llm(llm_request).await?;
+
+    if !llm_response.ok {
+        return Ok(GenerateActionsResponse {
+            ok: false,
+            actions: vec![],
+            explanation: String::new(),
+            error: llm_response.error,
+        });
+    }
+
+    // Parse JSON from LLM response
+    let content = llm_response.content.trim().to_string();
+    // Strip markdown code fences if present
+    let json_str = content
+        .strip_prefix("```json")
+        .or_else(|| content.strip_prefix("```"))
+        .unwrap_or(&content)
+        .strip_suffix("```")
+        .unwrap_or(&content)
+        .trim();
+
+    match serde_json::from_str::<LlmActionsOutput>(json_str) {
+        Ok(output) => {
+            let actions: Vec<Action> = output
+                .actions
+                .into_iter()
+                .filter_map(|a| {
+                    let kind = match a.kind.as_str() {
+                        "create_file" => ActionKind::CreateFile,
+                        "update_file" => ActionKind::UpdateFile,
+                        "create_dir" => ActionKind::CreateDir,
+                        "delete_file" => ActionKind::DeleteFile,
+                        _ => return None,
+                    };
+                    Some(Action {
+                        id: format!("ai-{}", a.id),
+                        title: a.title,
+                        description: a.description,
+                        kind,
+                        path: a.path,
+                        content: a.content,
+                    })
+                })
+                .collect();
+
+            Ok(GenerateActionsResponse {
+                ok: true,
+                actions,
+                explanation: output.explanation,
+                error: None,
+            })
+        }
+        Err(e) => Ok(GenerateActionsResponse {
+            ok: false,
+            actions: vec![],
+            explanation: String::new(),
+            error: Some(format!(
+                "Ошибка парсинга ответа LLM: {}. Ответ: {}",
+                e,
+                &json_str[..json_str.len().min(200)]
+            )),
+        }),
+    }
+}

desktop/src-tauri/src/commands/mod.rs

@@ -1,6 +1,7 @@
 mod analyze_project;
 mod apply_actions;
-mod ask_llm;
+pub mod ask_llm;
+mod generate_ai_actions;
 mod get_app_info;
 mod preview_actions;
 mod undo_last;
@@ -8,6 +9,7 @@ mod undo_last;
 pub use analyze_project::analyze_project;
 pub use apply_actions::apply_actions;
 pub use ask_llm::ask_llm;
+pub use generate_ai_actions::generate_ai_actions;
 pub use get_app_info::get_app_info;
 pub use preview_actions::preview_actions;
 pub use undo_last::undo_last;

desktop/src-tauri/src/lib.rs

@@ -1,7 +1,7 @@
 mod commands;
 mod types;
 
-use commands::{analyze_project, apply_actions, ask_llm, get_app_info, preview_actions, undo_last};
+use commands::{analyze_project, apply_actions, ask_llm, generate_ai_actions, get_app_info, preview_actions, undo_last};
 
 #[cfg_attr(mobile, tauri::mobile_entry_point)]
 pub fn run() {
@@ -26,6 +26,7 @@ pub fn run() {
       undo_last,
       get_app_info,
       ask_llm,
+      generate_ai_actions,
     ])
     .run(tauri::generate_context!())
     .expect("error while running tauri application");

desktop/ui/src/lib/analyze.ts

@@ -187,3 +187,30 @@ export async function askLlm(
     },
   });
 }
+
+// ---- AI Code Generation ----
+
+export interface GenerateActionsResponse {
+  ok: boolean;
+  actions: Action[];
+  explanation: string;
+  error?: string | null;
+}
+
+export async function generateAiActions(
+  settings: LlmSettings,
+  report: AnalyzeReport,
+): Promise<GenerateActionsResponse> {
+  return invoke<GenerateActionsResponse>('generate_ai_actions', {
+    request: {
+      provider: settings.provider,
+      model: settings.model,
+      api_key: settings.apiKey || null,
+      base_url: settings.baseUrl || null,
+      context: JSON.stringify(report.llm_context),
+      findings_json: JSON.stringify(report.findings),
+      project_path: report.path,
+      max_tokens: 4096,
+    },
+  });
+}

desktop/ui/src/pages/Tasks.tsx

@@ -19,7 +19,7 @@ import {
   X,
 } from 'lucide-react';
 import { invoke } from '@tauri-apps/api/core';
-import { analyzeProject, askLlm, type AnalyzeReport, type Action, type ApplyResult, type UndoResult, type PreviewResult, type DiffItem, type LlmSettings, DEFAULT_LLM_SETTINGS } from '../lib/analyze';
+import { analyzeProject, askLlm, generateAiActions, type AnalyzeReport, type Action, type ApplyResult, type UndoResult, type PreviewResult, type DiffItem, type LlmSettings, DEFAULT_LLM_SETTINGS } from '../lib/analyze';
 import { animateFadeInUp } from '../lib/anime-utils';
 import { useAppStore } from '../store/app-store';
 
@@ -121,6 +121,73 @@ export function Tasks() {
     setIsAiAnalyzing(false);
   };
 
+  const [isGeneratingActions, setIsGeneratingActions] = useState(false);
+
+  const handleAiCodeGen = async (report: AnalyzeReport) => {
+    const settings = loadLlmSettings();
+    if (!settings.apiKey && settings.provider !== 'ollama') {
+      setMessages((prev) => [
+        ...prev,
+        { role: 'system', text: '⚠️ API-ключ не настроен. Перейдите в Настройки LLM.' },
+      ]);
+      return;
+    }
+
+    setIsGeneratingActions(true);
+    setMessages((prev) => [...prev, { role: 'system', text: '🔧 AI генерирует исправления...' }]);
+
+    try {
+      const resp = await generateAiActions(settings, report);
+      if (resp.ok && resp.actions.length > 0) {
+        // Merge AI actions into the report
+        const updatedReport = {
+          ...report,
+          actions: [...(report.actions ?? []), ...resp.actions],
+        };
+        setLastReport(updatedReport);
+        storeSetLastReport(updatedReport, report.path);
+
+        // Init selection for new actions
+        const newSelection: Record<string, boolean> = { ...selectedActions };
+        resp.actions.forEach((a) => { newSelection[a.id] = true; });
+        setSelectedActions(newSelection);
+
+        // Update the last assistant message with new report
+        setMessages((prev) => {
+          const updated = [...prev];
+          // Find the last assistant message with this report and update it
+          for (let i = updated.length - 1; i >= 0; i--) {
+            const msg = updated[i];
+            if ('report' in msg && msg.report.path === report.path) {
+              updated[i] = { ...msg, report: updatedReport };
+              break;
+            }
+          }
+          return [
+            ...updated,
+            { role: 'assistant', text: `🔧 **AI сгенерировал ${resp.actions.length} исправлений** (${settings.model}):\n\n${resp.explanation}` },
+          ];
+        });
+      } else if (resp.ok && resp.actions.length === 0) {
+        setMessages((prev) => [
+          ...prev,
+          { role: 'system', text: '✓ AI не нашёл дополнительных исправлений — проект в хорошем состоянии.' },
+        ]);
+      } else {
+        setMessages((prev) => [
+          ...prev,
+          { role: 'system', text: `❌ Ошибка генерации: ${resp.error}` },
+        ]);
+      }
+    } catch (e) {
+      setMessages((prev) => [
+        ...prev,
+        { role: 'system', text: `❌ Ошибка: ${e}` },
+      ]);
+    }
+    setIsGeneratingActions(false);
+  };
+
   useEffect(() => {
     messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
   }, [messages]);
@@ -605,6 +672,8 @@ export function Tasks() {
                         onUndo={handleUndoLast}
                         onAiAnalysis={handleAiAnalysis}
                         isAiAnalyzing={isAiAnalyzing}
+                        onAiCodeGen={handleAiCodeGen}
+                        isGeneratingActions={isGeneratingActions}
                       />
                     )}
                   </div>
@@ -803,6 +872,8 @@ function ReportBlock({
   onUndo: (projectPath: string) => void;
   onAiAnalysis?: (report: AnalyzeReport) => void;
   isAiAnalyzing?: boolean;
+  onAiCodeGen?: (report: AnalyzeReport) => void;
+  isGeneratingActions?: boolean;
 }) {
   if (error) {
     return <div className="text-sm text-destructive">Ошибка: {error}</div>;
@@ -948,6 +1019,17 @@ function ReportBlock({
                 {isAiAnalyzing ? 'AI анализирует...' : 'AI Анализ'}
               </button>
             )}
+            {isCurrentReport && onAiCodeGen && (
+              <button
+                type="button"
+                onClick={() => onAiCodeGen(r)}
+                disabled={isGeneratingActions}
+                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"
+              >
+                <RefreshCw className={`w-4 h-4 ${isGeneratingActions ? 'animate-spin' : ''}`} />
+                {isGeneratingActions ? 'Генерирую...' : 'AI Исправления'}
+              </button>
+            )}
             <button
               type="button"
               onClick={() => onDownload(r)}