This PR adds the foundation for account-level SAML SSO configuration in
Chatwoot Enterprise. It introduces a new `AccountSamlSettings` model and
management API that allows accounts to configure their own SAML identity
providers independently, this also includes the certificate generation
flow
The implementation includes a new controller
(`Api::V1::Accounts::SamlSettingsController`) that provides CRUD
operations for SAML configuration
The feature is properly gated behind the 'saml' feature flag and
includes administrator-only authorization via Pundit policies.
## Linear reference:
https://linear.app/chatwoot/issue/CW-4649/re-imagine-assignments
## Description
This PR introduces the foundation for Assignment V2 system by
implementing agent_capacity and their association with inboxes and
users.
## Type of change
- [ ] New feature (non-breaking change which adds functionality)
## How Has This Been Tested?
Test Coverage:
- Controller specs for assignment policies CRUD operations
- Enterprise-specific specs for balanced assignment order
- Model specs for community/enterprise separation
## 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>
## Description
This PR introduces WhatsApp Embedded Signup functionality, enabling
users to connect their WhatsApp Business accounts through Meta's
streamlined OAuth flow without manual webhook configuration. This
significantly improves the user experience by automating the entire
setup process.
**Key Features:**
- Embedded signup flow using Facebook SDK and Meta's OAuth 2.0
- Automatic webhook registration and phone number configuration
- Enhanced provider selection UI with card-based design
- Real-time progress tracking during signup process
- Comprehensive error handling and user feedback
## Required Configuration
The following environment variables must be configured by administrators
before this feature can be used:
Super Admin Configuration (via
super_admin/app_config?config=whatsapp_embedded)
- `WHATSAPP_APP_ID`: The Facebook App ID for WhatsApp Business API
integration
- `WHATSAPP_CONFIGURATION_ID`: The Configuration ID for WhatsApp
Embedded Signup flow (obtained from Meta Developer Portal)
- `WHATSAPP_APP_SECRET`: The App Secret for WhatsApp Embedded Signup
flow (required for token exchange)
## How Has This Been Tested?
#### Backend Tests (RSpec):
- Authentication validation for embedded signup endpoints
- Authorization code validation and error handling
- Missing business parameter validation
- Proper response format for configuration endpoint
- Unauthorized access prevention
#### Manual Test Cases:
- Complete embedded signup flow (happy path)
- Provider selection UI navigation
- Facebook authentication popup handling
- Error scenarios (cancelled auth, invalid business data, API failures)
- Configuration presence/absence behavior
## Related Screenshots:
Fixes
https://linear.app/chatwoot/issue/CW-2131/spec-for-whatsapp-cloud-channels-sign-in-with-facebook
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
Co-authored-by: iamsivin <iamsivin@gmail.com>
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
Co-authored-by: Sojan Jose <sojan@pepalo.com>
# 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
- Add API support for creating a thread
- Add API support for creating a message
- Remove uuid from thread (no longer required, we will use existing
websocket connection to send messages)
- Update message_type to a column (user, assistant, assistant_thinking)
The agents can see the previous conversations with the copilot if needed
with this change. We would have to cleanup the data after a while. For
now, that is not considered.
This PR adds:
- A new model for copilot_threads (intentionally named thread instead of
conversation to avoid confusion), copilot_messages
- Add the controller to fetch previous threads and messages.
This pull request introduces several changes to implement and manage
usage limits for the Captain AI service. The key changes include adding
configuration for plan limits, updating error messages, modifying
controllers and models to handle usage limits, and updating tests to
ensure the new functionality works correctly.
## Implementation Checklist
- [x] Ability to configure captain limits per check
- [x] Update response for `usage_limits` to include captain limits
- [x] Methods to increment or reset captain responses limits in the
`limits` column for the `Account` model
- [x] Check documents limit using a count query
- [x] Ensure Captain hand-off if a limit is reached
- [x] Ensure limits are enforced for Copilot Chat
- [x] Ensure limits are reset when stripe webhook comes in
- [x] Increment usage for FAQ generation and Contact notes
- [x] Ensure documents limit is enforced
These changes ensure that the Captain AI service operates within the defined usage limits for different subscription plans, providing appropriate error messages and handling when limits are exceeded.
Currently, it’s unclear whether an FAQ item is generated from a
document, derived from a conversation, or added manually.
This PR resolves the issue by providing visibility into the source of
each FAQ. Users can now see whether an FAQ was generated or manually
added and, if applicable, by whom.
- Move the document_id to a polymorphic relation (documentable).
- Updated the APIs to accommodate the change.
- Update the service to add corresponding references.
- Updated the specs.
<img width="1007" alt="Screenshot 2025-01-15 at 11 27 56 PM"
src="https://github.com/user-attachments/assets/7d58f798-19c0-4407-b3e2-748a919d14af"
/>
---------
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
This PR introduces a review step for generated FAQs, allowing a human to
validate and approve them before use in customer interactions. While
hallucinations are minimal, this step ensures accurate and reliable FAQs
for Captain to use during LLM calls when responding to customers.
- Added a status field for the FAQ
- Allow the filter on the UI.
<img width="1072" alt="Screenshot 2025-01-15 at 6 39 26 PM"
src="https://github.com/user-attachments/assets/81dfc038-31e9-40e6-8a09-586ebc4e8384"
/>
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>
This PR refactors the schema we introduced in #7518 based on the feedback from production tests. Here is the change log
- Decouple Inbox association to a new table inbox_response_sources -> this lets us share the same response source between multiple inboxes
- Add a status field to responses. This ensures that, by default, responses are created in pending status. You can do quality assurance before making them active. In future, this status can be leveraged by the bot to auto-generate response questions from conversations which require a handoff
- Add response_source association to responses and remove hard dependency from response_documents. This lets users write free-form question answers based on conversations, which doesn't necessarily need a response source.
This commit introduces the ability to associate response sources to an inbox, allowing external webpages to be parsed by Chatwoot. The parsed data is converted into embeddings for use with GPT models when managing customer queries.
The implementation relies on the `pgvector` extension for PostgreSQL. Database migrations related to this feature are handled separately by `Features::ResponseBotService`. A future update will integrate these migrations into the default rails migrations, once compatibility with Postgres extensions across all self-hosted installation options is confirmed.
Additionally, a new GitHub action has been added to the CI pipeline to ensure the execution of specs related to this feature.
* feat: init auditlogs ui
* chore: add api
* fix: action
* chore: add action,username,time
* feat: add pagination support
* chore: format time
* chore: refactor
* chore: refactor auditlogs api response
* chore: update icon
* chore: rubocop fixes
* Fixes the way meta is handled in store
* Fixes meta not appearing issue
---------
Co-authored-by: Sojan Jose <sojan@pepalo.com>
Co-authored-by: Nithin David Thomas <1277421+nithindavid@users.noreply.github.com>
