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>
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>
## 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?"
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>
This PR implements the following features
- FAQs from conversations will be generated in account language
- Contact notes will be generated in account language
- Copilot chat will respond in user language, unless the agent asks the
question in a different language
## Changes
### Copilot Chat
- Update the prompt to include an instruction for the language, the bot
will reply in asked language, but will default to account language
- Update the `ChatService` class to include pass the language to
`SystemPromptsService`
### FAQ and Contact note generation
- Update contact note generator and conversation generator to include
account locale
- Pass the account locale to `SystemPromptsService`
<details><summary>Screenshots</summary>
#### FAQs being generated in system langauge
#### Copilot responding in system language
</details>
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
Co-authored-by: Pranav <pranav@chatwoot.com>
Migration Guide: https://chwt.app/v4/migration
This PR imports all the work related to Captain into the EE codebase. Captain represents the AI-based features in Chatwoot and includes the following key components:
- Assistant: An assistant has a persona, the product it would be trained on. At the moment, the data at which it is trained is from websites. Future integrations on Notion documents, PDF etc. This PR enables connecting an assistant to an inbox. The assistant would run the conversation every time before transferring it to an agent.
- Copilot for Agents: When an agent is supporting a customer, we will be able to offer additional help to lookup some data or fetch information from integrations etc via copilot.
- Conversation FAQ generator: When a conversation is resolved, the Captain integration would identify questions which were not in the knowledge base.
- CRM memory: Learns from the conversations and identifies important information about the contact.
---------
Co-authored-by: Vishnu Narayanan <vishnu@chatwoot.com>
Co-authored-by: Sojan <sojan@pepalo.com>
Co-authored-by: iamsivin <iamsivin@gmail.com>
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
