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>
Adds concierge.* and reservation.* Liquid variables to agent_instructions
so Sofia's orchestrator_prompt receives unit persona/knowledge/variables
and reservation data resolved from conversation.custom_attributes.current_unit_id.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Removes sentry flooding of unnecessary rubyllm logs of wrong API key.
Logs only system api key error since it would be P0.
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
# Pull Request Template
## Description
The initial version of prompt deciding to resolve or hand-off to human
agents was too conservative especially in cases where a link or an
action was told to customer. If the customer didn't respond, Captain was
told to hand it off to the agent, but customer may actually have solved
the issue. If not, they can come back and continue the conversation.
Removed two lines about the same and now we should not see needless
handoffs.
## 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
## 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
# Pull Request Template
## Description
For our account, the conversation completion evaluator was proving to be
too conservative. This resulted in queue noise.
This PR adds a line to handle gibberish/single worded messages with no
further context.
## 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.
<img width="3012" height="978" alt="CleanShot 2026-03-23 at 11 44 55@2x"
src="https://github.com/user-attachments/assets/328195e8-6ea0-4c3a-9049-ee80196eecad"
/>
<img width="2202" height="866" alt="CleanShot 2026-03-23 at 11 47 15@2x"
src="https://github.com/user-attachments/assets/8d51cff4-b18f-4582-9455-8119ec7eff3a"
/>
## 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
# Pull Request Template
## Description
Add account setting and store_accessor for
`captain_force_legacy_auto_resolve`.
Enterprise job now skips LLM evaluation when this flag is true and falls
back to legacy time-based resolution. Add spec to cover the fallback.
## Type of change
We recently rolled out Captain deciding if a conversation is resolved or
not. While it is an improvement for majority of customers, some still
prefer the old way of auto-resolving based on inactivity. This PR adds a
check.
## 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.
legacy_auto_resolve = true
<img width="1282" height="848" alt="CleanShot 2026-03-13 at 19 55 55@2x"
src="https://github.com/user-attachments/assets/dfdcc5d5-6d21-462b-87a6-a5e1b1290a8b"
/>
legacy_auto_resolve = false
<img width="1268" height="864" alt="CleanShot 2026-03-13 at 20 00 50@2x"
src="https://github.com/user-attachments/assets/f4719ec6-922a-4c3b-bc45-7b29eaced565"
/>
## 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
# Pull Request Template
## Description
Add an api_key override so internal conversation completions prefers
using the system API key and do not consume customer OpenAI credits.
## Type of change
Please delete options that are not relevant.
- [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.
specs and locally
## 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
# Pull Request Template
## Description
captain decides if conversation should be resolved or open
Fixes
https://linear.app/chatwoot/issue/AI-91/make-captain-resolution-time-configurable
Update: Added 2 entries in reporting events:
`conversation_captain_handoff` and `conversation_captain_resolved`
## Type of change
Please delete options that are not relevant.
- [x] New feature (non-breaking change which adds functionality)
- [x] This change requires a documentation update
## 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.
LLM call decides that conversation is resolved, drops a private note
<img width="1228" height="438" alt="image"
src="https://github.com/user-attachments/assets/fb2cf1e9-4b2b-458b-a1e2-45c53d6a0158"
/>
LLM call decides conversation is still open as query was not resolved
<img width="1215" height="573" alt="image"
src="https://github.com/user-attachments/assets/2d1d5322-f567-487e-954e-11ab0798d11c"
/>
## 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: Sojan Jose <sojan@pepalo.com>
Add a temporary `captain_disable_auto_resolve` boolean setting on
accounts to prevent Captain from resolving conversations. Guards both
the scheduled resolution job and the assistant's resolve tool.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
The [Galeria de Fotos] rules previously added to assistant_response_generator
only apply to the legacy V1 chat service. In V2 (captain_integration_v2),
scenario agents use scenario.liquid as their system prompt template, not
assistant_response_generator.
This adds conditional rules to scenario.liquid (matching the existing pattern
for faq_lookup and check_pix_payment) that activate for any scenario that
has the send_suite_images tool:
- Infer suite_category vs suite_number from context, no confirmation needed
- Never announce photo sending before the tool confirms images were found
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- 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
# Pull Request Template
## Description
Adds a new built-in tool that allows Captain scenarios to resolve
conversations programmatically. This enables automated workflows like
the misdirected contact deflector to close conversations after handling
them, while still allowing human review via label filtering.
## Type of change
Please delete options that are not relevant.
- [x] New feature (non-breaking change which adds functionality)
## 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.
tested by mentioning it to be used in captain v2 scenario
<img width="1180" height="828" alt="image"
src="https://github.com/user-attachments/assets/e70baf96-0c70-407e-af2c-328500ac5434"
/>
## 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: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Tanmay Deep Sharma <32020192+tds-1@users.noreply.github.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>
