Lays the data + job foundation for tracking customer interactions,
recurrence, and Pix conversion on Contact. Design decisions negotiated
with Rodrigo (see docs to come):
Rules:
- Gap of 30h from last message defines separate interactions
- Qualified interaction = >=2 customer msgs + >=2 attendant msgs,
both with textual content (>= 2 letters)
- One-shot consultation = >=1+1 but below the qualified threshold
(tracked as secondary KPI)
- Excludes contacts labeled `equipe_interna`
- is_recurring = interactions_count >= 2
- pix_generated_count counts all PixCharges; reservations_paid_count
only counts those with status = paid
Surface area:
- Migration adds denormalized stats to contacts + indexes for fast filtering
- Captain::ContactStats::InteractionCalculatorService computes the stats
for a single contact (pure, no persistence)
- Captain::Retention::RecalculateContactStatsJob persists them for one
contact (idempotent)
- Captain::Retention::RecalculateAllContactStatsJob runs daily at 3am BRT,
enqueues per-contact jobs for everyone active in the last 120 days
- Event-driven refresh: CaptainListener#conversation_resolved enqueues
recalc; Captain::PixCharge after_create/after_update enqueues recalc
on status change
No UI yet — that's the next layer.
Consolida o trabalho desta branch de abril/2026 em um bloco pronto pra
testar em staging antes do merge pra main.
## Correções de memória semântica
- ExtractionService: Princípio Zero + Regra de Ouro (ação consumada vs intenção).
- Cenário Daniela_Reservas: Passo 0 de classificação (consulta/intenção/fora).
## Roleta da Sorte (end-to-end)
- Schema Supabase + 7 RPCs atômicas (server-side, idempotentes).
- Services: Offer, Redeem, WeeklyReport.
- Jobs: OfferRouletteJob (hook em ConfirmationService após Pix pago),
NotifyRevealed + Scheduler de fallback.
- Tool manual GenerateRoletaLinkTool + endpoint público /roleta/notify.
- Dashboard /captain/roleta com Resgate + Relatório + anomaly detection.
## Cenário Reclamacoes_Ouvidoria
- Triagem P1-P4, framework LAST, Three-level listening, Self-check.
- Sem compensação material, detecção de cliente frustrado eleva prioridade.
## Analytics
- Funil de conversão /captain/funnel: 5 etapas via regex, zero LLM.
- Detector de churn via ChurnOutreach* (cron dias úteis 10h-17h BRT).
## Trabalho pré-existente incluído
- Captain Executive Reports (ceo_digest, mattermost_delivery).
- get_reserva_preco_tool, Lifecycle ajustes, Reservations UI polimentos.
## Outros
- .gitignore: patterns pra credenciais.
- Migrations de scenarios idempotentes.
- i18n completa pt_BR+en pra roleta/funnel.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Replace no-op stub with full perform body: find delivery by id, skip if
blank, delegate to Captain::Lifecycle::Dispatcher#call. Add retry_on
with polynomially_longer backoff (3 attempts). Spec covers dispatcher
delegation and graceful skip for missing records.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Arquitetura corrigida: templates agora pertencem à inbox (WhatsApp),
não à unidade PIX (que é uma config financeira, não de mensagens)
- Migration: troca FK captain_unit_id -> inbox_id (up/down explícito)
- Model: belongs_to :inbox; scope for_inbox
- Controller: escopo via account.inboxes.find(inbox_id)
- Rotas: move de captain/units/:id → inboxes/:id/notification_templates
- Scanner job: joins(:conversation).where(conversations: {inbox_id:})
- UI: página /captain/notifications com seletor de inbox no topo
(chips clicáveis, templates carregam por watch no selectedInboxId)
- i18n PT/EN: novas keys INBOX_LABEL, SELECT_INBOX_HINT, EMPTY
- Adiciona check_in_at/duration_hours ao schema do tool CreateReservationIntent
para que a IA capture o horário EXATO de chegada informado pelo cliente
- Cria captain_notification_templates: label, content, timing_minutes,
timing_direction (before/after), active, position
- Implementa SendNotificationService com interpolação de variáveis
(guest_name, check_in_time, check_out_time, suite_name, unit_name)
- Implementa NotificationScannerJob (Sidekiq-cron a cada 5min) com
janela de tolerância de ±5min e idempotência via metadata JSONB
- API REST: /captain/units/:unit_id/notification_templates (CRUD)
- Store Vuex captainNotificationTemplates + API client
- UI: página de gestão de templates com editor inline e botão '+'
- Configura rota captain_settings_notifications
- i18n PT/EN para todas as strings novas
- Rubocop e ESLint: zero offenses
- Adiciona SYSTEM_PROMPT_LEAK_PATTERNS no ResponseBuilderJob para detectar quando o LLM retornou o system prompt em vez de uma resposta ao cliente
- Filtra mensagens contaminadas do historico de conversas antes de enviar ao LLM (evita contaminacao em espiral)
- Adiciona guardrail no validate_message_content! que redireciona para handoff humano em caso de vazamento detectado
- Cria Captain::Errors::SystemPromptLeakError para tipagem do erro
- Atualiza assistant.liquid com tags INSTRUCOES_INTERNAS e REGRA CRITICA para instruir o LLM a nao reproduzir o system prompt como resposta
Implementa a página Relatórios IA com geração de análises semanais
por IA baseadas nas conversas de cada unidade/caixa de entrada.
Funcionalidades:
- Página /settings/captain/reports com dois tabs (Insights IA / Operacional)
- Botão "Gerar Análise" que enfileira job Sidekiq
- Filtro por unidade ou caixa de entrada
- Exibe insights com status (pendente/processando/concluído/falhou)
- Mostra top_topics, ai_failures e period_summary
- Estado vazio com CTA para gerar primeiro relatório
Backend:
- InsightsController com endpoints index/show/generate
- GenerateInsightsJob que processa conversas com LLM
- ConversationInsightService com chunking e merge inteligente
- Migração para adicionar inbox_id à tabela captain_conversation_insights
- Link sidebar "Relatórios IA" em /settings/captain/reports
Frontend:
- Vuex store captainReports com actions/mutations/getters
- API client CaptainReportsAPI (getInsights, generateInsight)
- i18n en e pt_BR para CAPTAIN_REPORTS.*
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Melhorias na ferramenta send_suite_images para resolver confusão entre
categoria e número de suíte:
1. **Descrições de parâmetros mais claras**
- suite_category: exemplos específicos (Hidromassagem, ALEXA, STILO)
- suite_number: apenas números (101, 102, 103) - remove exemplos confusos
2. **Instruções explícitas no system prompt**
- Seção [Galeria de Fotos] com regras claras
- Prioriza suite_category quando ambíguo
- Evita confirmações desnecessárias com cliente
3. **Mensagens de erro melhoradas**
- Sugere buscar por categoria quando busca por número falha
- Feedback mais útil para a IA
Resultado esperado:
- Cliente: "Me manda foto da suite Alexa"
- IA: busca por suite_category="Alexa" ✓ (sem pedir confirmação)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
# Pull Request Template
## Description
Please include a summary of the change and issue(s) fixed. Also, mention
relevant motivation, context, and any dependencies that this change
requires.
Fixes:
The LLM call was wrapped in a transaction. This is an anti-pattern and
caused idle-connections which PG eventually terminated with
`PQconsumeInput() FATAL: terminating connection due to
idle-in-transaction timeout`
This resulted in activity messages being missing in some conversations
on captain handoff, failures queueing up for retry and captain
responding long after conversation was marked open/snoozed.
## Type of change
- [x] Bug fix (non-breaking change which fixes an issue)
## How Has This Been Tested?
Please describe the tests that you ran to verify your changes. Provide
instructions so we can reproduce. Please also list any relevant details
for your test configuration.
locally and specs
## Checklist:
- [x] My code follows the style guidelines of this project
- [x] I have performed a self-review of my code
- [x] I have commented on my code, particularly in hard-to-understand
areas
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] New and existing unit tests pass locally with my changes
- [x] Any dependent changes have been merged and published in downstream
modules
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
## Summary
- Fix captain response builder not getting triggered for cases where
responses are created as completed.
## Testing Instructions
- Test articles with firecrawl
- Test articles without firecrawl
- Test PDF documents
---------
Co-authored-by: Pranav <pranav@chatwoot.com>
## Linear Link:
https://linear.app/chatwoot/issue/CW-5636/pdf-faqs-captain-generates-faqs-in-the-english-only
## Description
PDF Faqs should be generated in the same language as set in account
## Type of change
- [ ] Bug fix (non-breaking change which fixes an issue)
## How Has This Been Tested?
This has been tested via UI, by setting account language to arabic and
upload the pdf for faq generation (pdf content in Hindi)
<img width="1045" height="1085" alt="image"
src="https://github.com/user-attachments/assets/10385181-578e-4933-afc4-4609a6abcec8"
/>
## Checklist:
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented on my code, particularly in hard-to-understand
areas
- [ ] I have made corresponding changes to the documentation
- [ ] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged and published in downstream
modules
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
There were customer reported issues with FAQs which were generated in a
different langauge than what they were expecting. The reason behind this
was that the language of the account was not considered in the prompt
provided. If the language of the content was say Spanish, and the
account locale was english. The output was not predicable. The output
depends on the model and the execution time.
This PR would update the prompt to behave consistently with the account
locale. Even though the content provided is in a different language, it
would generate FAQs in the account locale.
Changes:
- Updated the prompt to include a detailed expectation of the FAQs
quality along with the language
- Added specs for the services where the prompt generator is called.
Tested the prompt using Phoenix playground across GPT 5, GPT 4.1, GPT
4.0. The reasoning setting for GPT 5 needs to be low so that it doesn't
generate random questions like "What was this updated?"
# Pull Request Template
## Linear links:
-
https://linear.app/chatwoot/issue/CW-4479/if-image-is-sent-by-the-customer-send-it-to-openai
## Description
This pull request adds “Captain image support” to Chatwoot. It
introduces multimodal message handling so that when a customer sends an
image, Captain can forward the file to OpenAI’s vision endpoint,
generate a caption/analysis
## Type of change
Please delete options that are not relevant.
- [x] New feature (non-breaking change which adds functionality)
## How Has This Been Tested?
<img width="891" alt="image"
src="https://github.com/user-attachments/assets/c7cc98ed-cc44-4865-a53a-83d129e2fe2c"
/>
## Checklist:
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented on my code, particularly in hard-to-understand
areas
- [ ] I have made corresponding changes to the documentation
- [ ] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged and published in downstream
modules
---------
Co-authored-by: Pranav <pranav@chatwoot.com>
- Enable jobs by default when a copilot thread or a message is created.
- Rename thread_id to copilot_thread_id to keep it consistent with the
model name
- Add a spec for search_linear_issues service
Show captain messages under the name of the assistant which generated
the message.
- Add support for `Captain::Assistant` sender type
- Add push_event_data for captain_assistants
- Add activity message handler for captain_assistants
- Update UI to show captain messages under the name of the assistant
- Fix the issue where openAI errors when image is sent
- Add support for custom name of the assistant
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
- Fixed Firecrawl webhook payloads to ensure proper data handling and
delivery.
- Removed unused Robin AI code to improve codebase cleanliness and
maintainability.
- Implement authentication for the Firecrawl endpoint to improve
security. A key is generated to secure the webhook URLs from FireCrawl.
---------
Co-authored-by: Pranav <pranavrajs@gmail.com>
