Earlier, we were manually checking if a user was an agent and filtering
their conversations based on inboxes. This logic should have been part
of the conversation permissions service.
This PR moves the check to the right place and updates the logic
accordingly.
Other updates:
- Add support for search_conversations service for copilot.
- Use PermissionFilterService in contacts/conversations, conversations,
copilot search_conversations.
---------
Co-authored-by: Sojan <sojan@pepalo.com>
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
This PR adds a tool to search Linear issues. If the integration is
enabled for the account, the tool will return results as expected. Also
introduces support for an `active?` method, which allows third-party
Copilot tools to be conditionally enabled based on the status of the
integration on the account.
This PR introduces the concept of a tool registry. The implementation is
straightforward: you can define a tool by creating a class with a
function name. The function name gets registered in the registry and can
be referenced during LLM calls. When the LLM invokes a tool using the
registered name, the registry locates and executes the appropriate tool.
If the LLM calls an unregistered tool, the registry returns an error
indicating that the tool is not defined.
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>
- Refactor HandleStripeEventService to better manage features by plan
- Add constants for features available in each plan tier (Startup,
Business, Enterprise)
- Add channel_instagram to Startup plan features
- Improve downgrade handling to properly disable higher-tier features
- Clean up and optimize tests for maintainability
- Add comprehensive test coverage for plan upgrades and downgrades
---------
Co-authored-by: Muhsin Keloth <muhsinkeramam@gmail.com>
1. Add permission filter service to separate permission filtering logic
from conversation queries
2. Implement hierarchical permissions with cleaner logic:
- conversation_manage gives access to all conversations
- conversation_unassigned_manage gives access to unassigned and user's
conversations
- conversation_participating_manage gives access only to user's
conversations
---------
Co-authored-by: Pranav <pranav@chatwoot.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>
This PR adds service to automate account abuse detection. Currently
based on the signup name and URL, could potentially add more context
such as usage analysis, message metadata etc.
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"
/>
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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>
* 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>
- Reorganizing installation config settings to move more configurations into UI from environment variables
- Changes to installation config to support premium plans in the enterprise edition
- Fixes the broken premium indicator in account/show and accounts/edit page
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.
- Show the indicator if the last message is incoming and the conversation is in pending status.
- Remove list of articles displayed in the bot response.
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: Enable features on successful subscription
* fix: Add specs
* disable features for default plan
* Remove mark as cloud customers
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Co-authored-by: Pranav Raj S <pranav@chatwoot.com>
