# Pull Request Template
## Description
Adds channel type to Captain assistant traces in Langfuse
## Type of change
- [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.
<img width="906" height="672" alt="image"
src="https://github.com/user-attachments/assets/224cee95-56aa-4672-8f74-0c0052251db9"
/>
<img width="908" height="611" alt="image"
src="https://github.com/user-attachments/assets/ddd8ef0d-47c1-450c-a09f-27e82a34d04d"
/>
## 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>
# Pull Request Template
## Description
Fixes # (issue)
When we migrated to RubyLLM, images weren't being sent properly in
RubyLLM format to the model, so it did not understand images.
## 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 + local testing
Current behaviour on staging:
<img width="772" height="1012" alt="image"
src="https://github.com/user-attachments/assets/7b7d360f-dea4-48af-b20b-ee4c98a38a85"
/>
local testing with fix:
<img width="792" height="1216" alt="image"
src="https://github.com/user-attachments/assets/5ef82452-015e-4bda-a68f-884d00acb014"
/>
## 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>
We’ve been watching Sidekiq workers climb from ~600 MB at boot to
1.4–1.5 GB after an hour whenever attachment-heavy jobs run. This PR is
an experiment to curb that growth by streaming attachments instead of
loading the whole blob into Ruby: reply-mailer inline attachments,
Telegram uploads, and audio transcriptions now read/write in chunks. If
this keeps RSS stable in production we’ll keep it; otherwise we’ll roll
it back and keep digging
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?"
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 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.
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>
