Przebudowanie aplikacji, usprawnione AI, dodanie combo buildera

lib/presentation/chat/chat_controller.dart

@@ -1,10 +1,13 @@
-import 'dart:convert';
 import 'package:dio/dio.dart';
 import 'package:riverpod_annotation/riverpod_annotation.dart';
 import 'package:trainhub_flutter/core/constants/ai_constants.dart';
 import 'package:trainhub_flutter/domain/repositories/chat_repository.dart';
+import 'package:trainhub_flutter/domain/repositories/exercise_repository.dart';
 import 'package:trainhub_flutter/domain/repositories/note_repository.dart';
+import 'package:trainhub_flutter/domain/repositories/training_plan_repository.dart';
 import 'package:trainhub_flutter/data/services/ai_process_manager.dart';
+import 'package:trainhub_flutter/data/services/ai_settings_service.dart';
+import 'package:trainhub_flutter/data/services/llm_client.dart';
 import 'package:trainhub_flutter/injection.dart';
 import 'package:trainhub_flutter/presentation/chat/chat_state.dart';
 import 'package:uuid/uuid.dart';
@@ -18,22 +21,27 @@ AiProcessManager aiProcessManager(AiProcessManagerRef ref) {
   return manager;
 }
 
+@riverpod
+AiSettingsService aiSettingsService(AiSettingsServiceRef ref) {
+  final service = getIt<AiSettingsService>();
+  service.addListener(() => ref.notifyListeners());
+  return service;
+}
+
 @riverpod
 class ChatController extends _$ChatController {
   late ChatRepository _repo;
   late NoteRepository _noteRepo;
-
-  final _dio = Dio(
-    BaseOptions(
-      connectTimeout: AiConstants.serverConnectTimeout,
-      receiveTimeout: AiConstants.serverReceiveTimeout,
-    ),
-  );
+  late LlmClient _llm;
+  CancelToken? _cancelToken;
 
   @override
   Future<ChatState> build() async {
     _repo = getIt<ChatRepository>();
     _noteRepo = getIt<NoteRepository>();
+    _llm = getIt<LlmClient>();
+    // Abort any in-flight generation when the user leaves the chat page.
+    ref.onDispose(() => _cancelToken?.cancel());
     final aiManager = ref.read(aiProcessManagerProvider);
     if (aiManager.status == AiServerStatus.offline) {
       aiManager.startServers();
@@ -67,8 +75,9 @@ class ChatController extends _$ChatController {
     state = AsyncValue.data(
       current.copyWith(
         sessions: sessions,
-        activeSession:
-            current.activeSession?.id == id ? null : current.activeSession,
+        activeSession: current.activeSession?.id == id
+            ? null
+            : current.activeSession,
         messages: current.activeSession?.id == id ? [] : current.messages,
       ),
     );
@@ -80,12 +89,44 @@ class ChatController extends _$ChatController {
     final sessionId = await _resolveSession(current, content);
     await _persistUserMessage(sessionId, content);
     final contextChunks = await _searchKnowledgeBase(content);
-    final systemPrompt = _buildSystemPrompt(contextChunks);
+    final trainingContext = await _buildTrainingContext();
+    final systemPrompt = _buildSystemPrompt(contextChunks, trainingContext);
     final history = _buildHistory();
     final fullAiResponse = await _streamResponse(systemPrompt, history);
     await _persistAssistantResponse(sessionId, content, fullAiResponse);
   }
 
+  /// Summarizes the user's exercise library and training plans so the model
+  /// can reference and plan around real data. Only attached when a cloud
+  /// provider is active — the local 4B model's context is too small for it.
+  Future<String> _buildTrainingContext() async {
+    if (getIt<LlmClient>().activeProvider == AiProvider.local) return '';
+    try {
+      final exercises = await getIt<ExerciseRepository>().getAll();
+      final plans = await getIt<TrainingPlanRepository>().getAll();
+
+      final buffer = StringBuffer();
+      if (exercises.isNotEmpty) {
+        buffer.writeln("### The trainer's exercise library:");
+        for (final e in exercises.take(150)) {
+          buffer.write('- ${e.name}');
+          final tags = e.tags;
+          if (tags != null && tags.isNotEmpty) buffer.write(' [$tags]');
+          buffer.writeln();
+        }
+      }
+      if (plans.isNotEmpty) {
+        buffer.writeln("\n### The trainer's training plans:");
+        for (final plan in plans.take(30)) {
+          buffer.writeln('- ${plan.name}');
+        }
+      }
+      return buffer.toString();
+    } catch (_) {
+      return '';
+    }
+  }
+
   Future<String> _resolveSession(ChatState current, String content) async {
     if (current.activeSession != null) return current.activeSession!.id;
     final session = await _repo.createSession();
@@ -144,61 +185,51 @@ class ChatController extends _$ChatController {
     return contextChunks;
   }
 
+  /// Most recent messages only — an unbounded history would eventually
+  /// overflow the model context and slow every request down.
   List<Map<String, String>> _buildHistory() {
     final messages = state.valueOrNull?.messages ?? [];
-    return messages
-        .map((m) => <String, String>{
-              'role': m.isUser ? 'user' : 'assistant',
-              'content': m.content,
-            })
+    final recent = messages.length > AiConstants.chatHistoryLimit
+        ? messages.sublist(messages.length - AiConstants.chatHistoryLimit)
+        : messages;
+    return recent
+        .map(
+          (m) => <String, String>{
+            'role': m.isUser ? 'user' : 'assistant',
+            'content': m.content,
+          },
+        )
         .toList();
   }
 
+  /// Stops an in-flight generation. The partial response streamed so far is
+  /// kept and persisted like a normal reply.
+  void stopGeneration() => _cancelToken?.cancel();
+
   Future<String> _streamResponse(
     String systemPrompt,
     List<Map<String, String>> history,
   ) async {
     final generateStep = _createStep('Generating response...');
     String fullAiResponse = '';
+    _cancelToken = CancelToken();
     try {
-      final response = await _dio.post<ResponseBody>(
-        AiConstants.chatApiUrl,
-        options: Options(responseType: ResponseType.stream),
-        data: {
-          'messages': [
-            {'role': 'system', 'content': systemPrompt},
-            ...history,
-          ],
-          'temperature': AiConstants.chatTemperature,
-          'stream': true,
-        },
-      );
+      final stream = _llm.streamChat([
+        {'role': 'system', 'content': systemPrompt},
+        ...history,
+      ], cancelToken: _cancelToken);
       _updateStep(
         generateStep.id,
         status: ThinkingStepStatus.running,
         title: 'Writing...',
       );
-      final stream = response.data!.stream;
-      await for (final chunk in stream) {
-        final textChunk = utf8.decode(chunk);
-        for (final line in textChunk.split('\n')) {
-          if (!line.startsWith('data: ')) continue;
-          final dataStr = line.substring(6).trim();
-          if (dataStr == '[DONE]') break;
-          if (dataStr.isEmpty) continue;
-          try {
-            final data = jsonDecode(dataStr);
-            final delta = data['choices']?[0]?['delta']?['content'] ?? '';
-            if (delta.isNotEmpty) {
-              fullAiResponse += delta;
-              final updatedState = state.valueOrNull;
-              if (updatedState != null) {
-                state = AsyncValue.data(
-                  updatedState.copyWith(streamingContent: fullAiResponse),
-                );
-              }
-            }
-          } catch (_) {}
+      await for (final delta in stream) {
+        fullAiResponse += delta;
+        final updatedState = state.valueOrNull;
+        if (updatedState != null) {
+          state = AsyncValue.data(
+            updatedState.copyWith(streamingContent: fullAiResponse),
+          );
         }
       }
       _updateStep(
@@ -207,21 +238,29 @@ class ChatController extends _$ChatController {
         title: 'Response generated',
       );
     } on DioException catch (e) {
-      fullAiResponse += '\n\n[AI model communication error]';
-      _updateStep(
-        generateStep.id,
-        status: ThinkingStepStatus.error,
-        title: 'Generation failed',
-        details: '${e.message}',
-      );
+      if (CancelToken.isCancel(e)) {
+        _updateStep(
+          generateStep.id,
+          status: ThinkingStepStatus.completed,
+          title: 'Stopped by user',
+        );
+      } else {
+        _updateStep(
+          generateStep.id,
+          status: ThinkingStepStatus.error,
+          title: 'Generation failed',
+          details: e.message ?? e.toString(),
+        );
+      }
     } catch (e) {
-      fullAiResponse += '\n\n[Unexpected error]';
       _updateStep(
         generateStep.id,
         status: ThinkingStepStatus.error,
         title: 'Generation failed',
         details: e.toString(),
       );
+    } finally {
+      _cancelToken = null;
     }
     return fullAiResponse;
   }
@@ -231,6 +270,17 @@ class ChatController extends _$ChatController {
     String userContent,
     String aiResponse,
   ) async {
+    // A failed generation yields an empty response — leave the error visible
+    // in the thinking steps instead of saving an empty assistant message.
+    if (aiResponse.trim().isEmpty) {
+      final current = state.valueOrNull;
+      if (current != null) {
+        state = AsyncValue.data(
+          current.copyWith(isTyping: false, streamingContent: null),
+        );
+      }
+      return;
+    }
     await _repo.addMessage(
       sessionId: sessionId,
       role: 'assistant',
@@ -289,18 +339,32 @@ class ChatController extends _$ChatController {
     state = AsyncValue.data(current.copyWith(thinkingSteps: updatedSteps));
   }
 
-  static String _buildSystemPrompt(List<String> chunks) {
-    if (chunks.isEmpty) return AiConstants.baseSystemPrompt;
-    final contextBlock = chunks
-        .asMap()
-        .entries
-        .map((e) => '[${e.key + 1}] ${e.value}')
-        .join('\n\n');
-    return '${AiConstants.baseSystemPrompt}\n\n'
-        '### Relevant notes from the trainer\'s knowledge base:\n'
+  static String _buildSystemPrompt(
+    List<String> chunks,
+    String trainingContext,
+  ) {
+    final buffer = StringBuffer(AiConstants.baseSystemPrompt);
+    if (trainingContext.isNotEmpty) {
+      buffer.write('\n\n$trainingContext');
+      buffer.write(
+        '\nWhen designing or discussing training plans, prefer exercises '
+        'from the library above and reference existing plans by name.',
+      );
+    }
+    if (chunks.isNotEmpty) {
+      final contextBlock = chunks
+          .asMap()
+          .entries
+          .map((e) => '[${e.key + 1}] ${e.value}')
+          .join('\n\n');
+      buffer.write(
+        '\n\n### Relevant notes from the trainer\'s knowledge base:\n'
         '$contextBlock\n\n'
         'Use the above context to inform your response when relevant. '
         'If the context is not directly applicable, rely on your general '
-        'fitness knowledge.';
+        'fitness knowledge.',
+      );
+    }
+    return buffer.toString();
   }
 }