This PR ensures that only conversations from quick conversation channels
are resolved, avoiding resolutions on the email channel (we still need
to improve the UX here). It also updates the FAQ generation logic,
limiting it to conversations that had at least one human interaction.
This PR introduces several improvements to the Captain AI dashboard
section:
- New billing page, with new colors, layout and meters for Captain usage
- Updated the base paywall component to use new colors
- Updated PageLayout.vue, it's more generic and can be used for other
pages as well
- Use flags to toggle empty state and loading state
- Add prop for `featureFlag` to show the paywall slot based on feature
enabled on account
- Update `useAccount` to add a `isCloudFeatureEnabled`
- **Removed feature flag checks from captain route definitions**, so the
captain entry will always be visible on the sidebar
- Add banner to Captain pages for the following cases
- Responses usage is over 80%
- Documents limit is fully exhausted
### Screenshots
<details><summary>Free plan</summary>
<p>


</p>
</details>
<details><summary>Paid plan</summary>
<p>


</p>
</details>
---------
Co-authored-by: Sojan Jose <sojan@pepalo.com>
Co-authored-by: Pranav <pranav@chatwoot.com>
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.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>
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 allows setting scripts for `vueapp.html.erb` via super admin
config. This PR has the following changes
1. Allow `DASHBOARD_SCRIPTS` in internal config
2. Remove existing scripts from `vueapp.html.erb`
3. Add scripts from `GlobalConfig` to `vueapp.html.erb`
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
This PR has the following changes
1. Add `AZURE_APP_ID` and `AZURE_APP_SECRET` to installation config
2. Add Microsoft config to `super_admin/features.yml`
3. Replace usage of `ENV.fetch` with `GlobalConfigService.load` for
fetch App ID and Secret
* feat: add push notification when SLA missed
* chore: sent notification only for inbox members
* feat: add conv particpants+admins to SLA notification list
* chore: add spec to ensure notification is created
* chore: refactor to multiple alerts for SLA conditions
* chore: add sla_policy as secondary_actor in notification
- This PR adds a UI to validate the response source quality quickly. It also helps to test with sample questions and update responses in the database when missing.
Co-authored-by: Pranav Raj S <pranav@chatwoot.com>