AI Digest

The AI digest is a private, review-first recommendation flow. It should help the user maintain relationships without leaking identifying relationship data.

Main Files

Core LLM:

lib/core/llm/llm_config.dart
lib/core/llm/llm_service.dart
lib/core/llm/llm_diagnostics_log.dart
lib/core/llm/ollama/

Digest:

lib/features/ai_digest/application/anonymized_llm_context_builder.dart
lib/features/ai_digest/application/llm_digest_orchestrator.dart
lib/features/ai_digest/application/ai_digest_response_parser.dart
lib/features/ai_digest/application/llm_digest_background_scheduler.dart
lib/features/ai_digest/application/llm_digest_environment.dart
lib/features/ai_digest/data/llm_digest_config.dart
lib/features/ai_digest/data/llm_digest_run_store.dart
lib/features/ai_digest/presentation/ai_digest_review_view.dart
lib/app/data/relationship_repository_ai_digest.dart

Provider Support

LlmService supports:

OpenAI
Anthropic
Google AI
Ollama
OpenAI-compatible providers

Settings owns provider setup, model listing, diagnostics, and manual test actions.

Privacy Model

Scheduled digest prompts use pseudonymous person tokens:

{
  "personToken": "person_001",
  "relationshipCategory": "friend",
  "interests": ["coffee"],
  "capturedFacts": [...]
}

Do not include:

real names
aliases
sender names
source user IDs
source thread IDs
raw shared message text
sensitive facts
unreviewed facts
source URLs from private shares

Allowed context:

safe category labels
sanitized fact summaries
preference signal labels
relative windows such as "about 3 months ago"
shared_message_datetime when it is already stored as timestamp evidence

Digest Lifecycle

manual or scheduled trigger
  -> LlmDigestOrchestrator
  -> load config and run policy
  -> build anonymized context
  -> call LlmService.completeText
  -> parse JSON suggestions
  -> save AiSuggestionDrafts
  -> notify user
  -> user reviews, accepts, or dismisses

Suggestions never directly mutate people, reminders, or ideas without review.

Temporal Context

Shared message timestamp handling matters. If someone wrote "I am sick and ginger tea helped" four months ago, the correct durable outcome is probably a ginger tea preference, not a current health check-in.

Relevant fields:

SharedPayload.sharedMessageDateTime
SharedMessageEntry.sharedMessageDateTime
digest capturedFacts[].shared_message_datetime
digest capturedFacts[].sourceAge
digest preferenceSignals[].lastObserved

Prompts explicitly instruct models to avoid current check-ins from old temporary health/status evidence.

Web Grounding

Digest config can enable web grounding for current events. Grounded suggestions must include source URLs and should prefer official event or venue pages.

When web grounding is disabled, the model should avoid claims about current availability, prices, or event schedules unless the local input already contains concrete details.

Diagnostics

Settings exposes LLM diagnostics. Diagnostics should record metadata and lengths, not secrets. Do not log API keys or raw private relationship context beyond what the existing diagnostics intentionally capture.

Tests

Useful focused tests:

flutter test test/core/llm
flutter test test/features/ai_digest

When changing prompt payloads, update test/features/ai_digest/anonymized_llm_context_builder_test.dart so privacy constraints are protected by tests.

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