feat: add local-first private AI digest workflow
Migrate app code into canonical feature slices, add phone-only AI digest scheduling and review, wire local notification/background task support, and cover the flow with tests.
This commit is contained in:
Rijad Zuzo
@@ -0,0 +1,328 @@
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import 'dart:convert';
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import 'package:dio/dio.dart';
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import 'package:flutter_riverpod/flutter_riverpod.dart';
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import 'package:relationship_saver/core/llm/captured_fact_draft_parser.dart';
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import 'package:relationship_saver/core/llm/llm_config.dart';
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import 'package:relationship_saver/features/people/domain/person_models.dart';
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import 'package:relationship_saver/features/share_intake/domain/share_models.dart';
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class LlmService {
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LlmService(this._ref);
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final Ref _ref;
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Future<LlmConfigState> get _config async {
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final state = _ref.read(llmConfigProvider);
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if (!state.isConfigured) {
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throw Exception('LLM not configured');
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}
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return state;
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}
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Future<List<GeneratedSignal>> generateSignals(
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List<PersonProfile> people,
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) async {
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final config = await _config;
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final apiKey = await _ref.read(llmConfigProvider.notifier).getApiKey();
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if (apiKey == null || apiKey.isEmpty) {
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throw Exception('No API key available');
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}
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final systemPrompt =
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'''You are a relationship assistant that helps users maintain meaningful connections with their friends and family.
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Based on the person's profile data, generate helpful signals such as:
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- Check-in reminders
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- Gift ideas
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- Follow-up suggestions
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- Relationship maintenance tips
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Return your response as a JSON array of signals, each with:
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- title: short actionable title
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- description: brief explanation
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- type: "recommendation", "gift", "followup", or "reminder"
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- personId: the person's ID (use a valid ID from the input if applicable)
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Only return the JSON array, no other text.''';
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final peopleContext = people
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.map(
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(p) =>
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'- ${p.name} (${p.relationship}): tags=${p.tags.join(", ")}, notes=${p.notes.isEmpty ? "none" : p.notes}, affinity=${p.affinityScore}',
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)
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.join('\n');
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final userPrompt =
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'''Here are the people in my life:
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$peopleContext
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Generate 3-5 helpful relationship signals for these people.''';
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try {
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final response = await _callLlm(
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provider: config.provider,
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apiKey: apiKey,
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systemPrompt: systemPrompt,
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userPrompt: userPrompt,
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);
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return _parseSignalsResponse(response, people);
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} catch (e) {
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throw Exception('Failed to generate signals: $e');
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}
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}
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Future<String> completeText({
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required String systemPrompt,
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required String userPrompt,
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}) async {
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final config = await _config;
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final String? apiKey = await _ref
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.read(llmConfigProvider.notifier)
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.getApiKey();
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if (apiKey == null || apiKey.isEmpty) {
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throw Exception('No API key available');
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}
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return _callLlm(
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provider: config.provider,
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apiKey: apiKey,
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systemPrompt: systemPrompt,
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userPrompt: userPrompt,
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);
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}
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Future<CapturedFactDraft?> suggestCaptureDraft(SharedPayload payload) async {
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final config = await _config;
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final String? apiKey = await _ref
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.read(llmConfigProvider.notifier)
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.getApiKey();
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if (apiKey == null || apiKey.isEmpty) {
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throw Exception('No API key available');
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}
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final String systemPrompt =
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'''You analyze shared messages and links for a relationship-tracking app.
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Return exactly one JSON object with:
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- type: one of "note", "like", "dislike", "importantDate", "giftIdea", "placeIdea", "activityIdea", "misc"
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- text: cleaned user-facing summary
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- label: short optional label
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- dateValue: ISO-8601 date if the content clearly describes an important date, otherwise null
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- confidence: number from 0 to 1
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- isSensitive: true only if the content looks private or sensitive
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Be conservative. If the content is ambiguous, prefer "note". Return JSON only.''';
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final String userPrompt =
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'''Source app: ${payload.sourceApp}
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Sender: ${payload.sourceDisplayName ?? "unknown"}
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Platform: ${payload.platform}
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URL: ${payload.url ?? "none"}
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Raw text:
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${payload.rawText}''';
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try {
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final String response = await _callLlm(
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provider: config.provider,
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apiKey: apiKey,
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systemPrompt: systemPrompt,
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userPrompt: userPrompt,
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);
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return parseCapturedFactDraftSuggestion(
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response,
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fallbackPayload: payload,
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);
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} catch (e) {
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throw Exception('Failed to suggest share capture draft: $e');
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}
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}
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Future<String> _callLlm({
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required LlmProvider provider,
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required String apiKey,
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required String systemPrompt,
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required String userPrompt,
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}) async {
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final dio = Dio(
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BaseOptions(
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connectTimeout: const Duration(seconds: 20),
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receiveTimeout: const Duration(seconds: 20),
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sendTimeout: const Duration(seconds: 20),
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),
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);
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switch (provider) {
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case LlmProvider.openai:
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return _callOpenAI(dio, apiKey, systemPrompt, userPrompt);
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case LlmProvider.anthropic:
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return _callAnthropic(dio, apiKey, systemPrompt, userPrompt);
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case LlmProvider.google:
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return _callGoogleAI(dio, apiKey, systemPrompt, userPrompt);
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}
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}
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Future<String> _callOpenAI(
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Dio dio,
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String apiKey,
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String systemPrompt,
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String userPrompt,
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) async {
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final Response<Map<String, dynamic>> response = await dio
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.post<Map<String, dynamic>>(
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'https://api.openai.com/v1/chat/completions',
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options: Options(
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headers: {
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'Authorization': 'Bearer $apiKey',
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'Content-Type': 'application/json',
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},
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),
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data: jsonEncode({
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'model': 'gpt-4o-mini',
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'messages': [
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{'role': 'system', 'content': systemPrompt},
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{'role': 'user', 'content': userPrompt},
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],
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'max_tokens': 1000,
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}),
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);
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final Map<String, dynamic> responseData = response.data!;
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final List<dynamic> choices = responseData['choices'] as List<dynamic>;
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final Map<String, dynamic> firstChoice = choices[0] as Map<String, dynamic>;
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final Map<String, dynamic> message =
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firstChoice['message'] as Map<String, dynamic>;
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final String content = message['content'] as String;
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return content;
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}
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Future<String> _callAnthropic(
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Dio dio,
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String apiKey,
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String systemPrompt,
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String userPrompt,
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) async {
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final Response<Map<String, dynamic>> response = await dio
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.post<Map<String, dynamic>>(
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'https://api.anthropic.com/v1/messages',
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options: Options(
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headers: {
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'x-api-key': apiKey,
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'anthropic-version': '2023-06-01',
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'Content-Type': 'application/json',
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},
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),
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data: jsonEncode({
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'model': 'claude-3-haiku-20240307',
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'system': systemPrompt,
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'messages': [
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{'role': 'user', 'content': userPrompt},
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],
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'max_tokens': 1000,
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}),
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);
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final Map<String, dynamic> responseData = response.data!;
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final List<dynamic> contentList = responseData['content'] as List<dynamic>;
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final Map<String, dynamic> firstContent =
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contentList[0] as Map<String, dynamic>;
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final String content = firstContent['text'] as String;
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return content;
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}
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Future<String> _callGoogleAI(
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Dio dio,
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String apiKey,
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String systemPrompt,
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String userPrompt,
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) async {
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final Response<Map<String, dynamic>>
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response = await dio.post<Map<String, dynamic>>(
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'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent',
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options: Options(headers: {'Content-Type': 'application/json'}),
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queryParameters: {'key': apiKey},
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data: jsonEncode({
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'systemInstruction': {
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'parts': [
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{'text': systemPrompt},
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],
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},
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'contents': [
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{
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'parts': [
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{'text': userPrompt},
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],
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},
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],
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'generationConfig': {'temperature': 0.7, 'maxOutputTokens': 1000},
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}),
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);
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final Map<String, dynamic> responseData = response.data!;
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final List<dynamic> candidates =
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responseData['candidates'] as List<dynamic>;
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final Map<String, dynamic> firstCandidate =
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candidates[0] as Map<String, dynamic>;
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final Map<String, dynamic> content =
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firstCandidate['content'] as Map<String, dynamic>;
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final List<dynamic> parts = content['parts'] as List<dynamic>;
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final Map<String, dynamic> firstPart = parts[0] as Map<String, dynamic>;
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final String contentText = firstPart['text'] as String;
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return contentText;
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}
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List<GeneratedSignal> _parseSignalsResponse(
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String response,
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List<PersonProfile> people,
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) {
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try {
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final jsonStart = response.indexOf('[');
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final jsonEnd = response.lastIndexOf(']');
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if (jsonStart == -1 || jsonEnd == -1) {
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return [];
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}
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final jsonStr = response.substring(jsonStart, jsonEnd + 1);
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final List<dynamic> items = jsonDecode(jsonStr) as List<dynamic>;
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return items.map((item) {
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final Map<String, dynamic> itemMap = item as Map<String, dynamic>;
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final String? personId = itemMap['personId'] as String?;
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final validPersonId =
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personId != null && people.any((p) => p.id == personId)
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? personId
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: (people.isNotEmpty ? people.first.id : null);
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return GeneratedSignal(
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title: itemMap['title'] as String? ?? 'Check in',
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description: itemMap['description'] as String? ?? '',
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type: itemMap['type'] as String? ?? 'recommendation',
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personId: validPersonId,
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);
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}).toList();
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} catch (e) {
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return [];
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}
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}
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}
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class GeneratedSignal {
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const GeneratedSignal({
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required this.title,
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required this.description,
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required this.type,
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this.personId,
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});
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final String title;
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final String description;
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final String type;
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final String? personId;
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}
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final llmServiceProvider = Provider<LlmService>((Ref ref) {
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return LlmService(ref);
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});
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