This pull request adds a new component called ThoughtsButton for
displaying thoughts in the chat messages. The ThoughtsButton component
is used to show a tooltip with the thoughts text when the user hovers
over the button.
# Description
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also include relevant motivation and context.
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## Screenshots (if appropriate):
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] New and existing unit tests pass locally with my changes
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## Screenshots (if appropriate):
Adds a new "Privacy & Compliance" page to the Quivr documentation.
- **Introduces a comprehensive overview** of Quivr's commitment to
privacy and compliance, including the open-source security model,
responsible telemetry use, row-level policy enforcement, local data
handling, and LLM compatibility.
- **Details the open-source security model**, emphasizing transparency
and community-driven security enhancements.
- **Explains the responsible use of telemetry**, highlighting minimal
data collection, anonymization, secure storage, and opt-out options.
- **Describes row-level policy enforcement** for database security,
ensuring controlled data access.
- **Clarifies local data handling**, ensuring all data remains local
with no external data transfer without user consent.
- **Highlights compatibility with any LLM**, including local server-run
models, offering flexibility for user needs.
- **Includes information on SOC2 compliance** through partnership with
Porter & Oneleet, aiming for compliance within 90 days for managed
instances.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=e9ecbf64-d06d-45b6-ab73-c04b9ed7916d).
This pull request refactors the generate_answer and generate_stream
functions in order to improve code readability and maintainability. It
also adds new fields to the cited_answer model and updates the system
message template.
# Description
Applying dark mode to icons in tiptap.
## Checklist before requesting a review
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## Screenshots:
<img width="906" alt="image"
src="https://github.com/QuivrHQ/quivr/assets/33584382/c8d86fa2-0f58-4c44-82d2-5162a5e025cd">
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] Any dependent changes have been merged
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# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
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## Checklist before requesting a review
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- [ ] Any dependent changes have been merged
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# Description
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## Checklist before requesting a review
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my feature works
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- [ ] Any dependent changes have been merged
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# Description
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## Checklist before requesting a review
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
Please delete options that are not relevant.
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally 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
## Screenshots (if appropriate):
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally 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
## Screenshots (if appropriate):
This pull request fixes the sender email address in the
`resend_invitation_email` function in the `resend_invitation_email.py`
file. The `from` field has been changed to `sender` to ensure that the
correct email address is used when sending the invitation email.
This pull request updates the ChatLiteLLM model to "gpt-4o" and adds a
row-level security (RLS) optimization for notifications. It also
includes a new SQL script to drop and create a policy for allowing user
access to all notifications.
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally 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
## Screenshots (if appropriate):
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
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- [x] My code follows the style guidelines of this project
- [x] I have performed a self-review of my code
- [x] I have commented hard-to-understand areas
- [x] I have ideally 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
## Screenshots (if appropriate):
<!--
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----
| <a href="https://ellipsis.dev" target="_blank"><img
src="https://avatars.githubusercontent.com/u/80834858?s=400&u=31e596315b0d8f7465b3ee670f25cea677299c96&v=4"
alt="Ellipsis" width="30px" height="30px"/></a> | 🚀 This PR
description was created by [Ellipsis](https://www.ellipsis.dev) for
commit bb45566f8a. |
|--------|--------|
### Summary:
This PR updates the `useLanguageHook` and `UserSettingsProvider`
functions to use the `shortName` of the selected language when changing
the language and to retrieve and store the dark mode setting from and to
local storage, respectively.
**Key points**:
- Updated `useLanguageHook` in
`/frontend/app/user/components/LanguageSelect/hooks/useLanguageHook.ts`
to use `shortName` of selected language when changing language.
- Updated `UserSettingsProvider` in
`/frontend/lib/context/UserSettingsProvider/User-settings.provider.tsx`
to retrieve dark mode setting from local storage.
- Updated listener for `change` event on `mediaQueryList` in
`UserSettingsProvider` to store updated dark mode setting in local
storage.
----
Generated with ❤️ by [ellipsis.dev](https://www.ellipsis.dev)
<!--
ELLIPSIS_HIDDEN
-->
---------
Co-authored-by: Zewed <dewez.antoine2@gmail.com>
This pull request adds support for the gpt-4o model to the existing
codebase. It includes changes to the BrainConfig, openAiFreeModels,
defineMaxTokens, model_compatible_with_function_calling, create_graph,
main, and process_assistant functions.
This pull request fixes the import statements for OllamaEmbeddings in
multiple files. The import statements are updated to use the correct
package name "langchain_community.embeddings" instead of
"langchain.embeddings.ollama". This ensures that the code can be
compiled and executed without any import errors.
This pull request adds comprehensive docstrings to the Brain classes
within the `backend/modules/brain/integrations` directory, enhancing
code documentation and readability. The changes include:
- **BigBrain (`Big/Brain.py`)**: Adds a class-level docstring explaining
the purpose and functionality of the BigBrain class, along with
method-level docstrings detailing the operations performed by each
method.
- **ClaudeBrain (`Claude/Brain.py`)**: Introduces a class-level
docstring that describes the ClaudeBrain class's integration with the
Claude model for conversational AI capabilities, and method-level
docstrings that clarify the purpose of each method.
- **GPT4Brain (`GPT4/Brain.py`)**: Updates include a detailed
class-level docstring outlining the GPT4Brain's integration with GPT-4
for real-time answers and tool support, along with method-level
docstrings explaining the functionality of each method.
- **NotionBrain (`Notion/Brain.py`)**: Adds a class-level docstring that
describes the NotionBrain's role in leveraging Notion data for
knowledge-based responses.
- **ProxyBrain (`Proxy/Brain.py`)**: Incorporates a class-level
docstring explaining the ProxyBrain's function as a dynamic language
model selector and method-level docstrings detailing the operations of
each method.
These additions ensure that each Brain class and its methods are
well-documented, providing clear insights into their purposes and
functionalities.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=b4e301ad-828e-4424-95ec-6e378d5d3849).
Updates the GPT-4 documentation and the `GPT4Brain` class to include
detailed information about the tools available for GPT4Brain and their
use cases.
- **Documentation (`docs/brains/gpt4.mdx`):**
- Adds a new section titled "Tools Available for GPT4Brain" that
describes specific tools: WebSearchTool, ImageGeneratorTool,
URLReaderTool, and EmailSenderTool.
- Provides use cases for each tool, demonstrating how they can be
utilized within GPT4Brain for various scenarios, such as generating
images, reading content from URLs, and sending emails.
- **Code (`backend/modules/brain/integrations/GPT4/Brain.py`):**
- Updates the class documentation to include information about the tools
available for GPT4Brain and outlines use cases for WebSearchTool,
ImageGeneratorTool, URLReaderTool, and EmailSenderTool.
- Maintains the existing functionality of the `GPT4Brain` class,
ensuring compatibility with the newly documented tools and use cases.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=2c2c1666-e5fb-4a06-bb08-ca967f4fe276).
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally 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
## Screenshots (if appropriate):
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
Updates the `docs/brains/gpt4.mdx` documentation to include detailed
instructions on adding a GPT-4 Brain to Quivr and configuring it within
the Supabase integration table.
- Adds a new section titled "Adding GPT-4 Brain to Quivr" that outlines
the steps required to integrate a GPT-4 Brain into Quivr, including
accessing the Supabase dashboard and navigating to the integration
table.
- Provides step-by-step instructions for adding a custom brain named
gpt4 in the Supabase integration table and configuring the necessary
settings for the GPT-4 Brain, such as API keys and preferences.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=81c5fd43-eb46-407c-a40f-c0b0b3a41925).
This pull request introduces comprehensive documentation for configuring
Supabase in Quivr, including details on CLI usage, running migrations,
resetting the database, and deploying to a hosted version of Supabase.
- **Documentation Addition**: Adds a new document
`docs/configuring/supabase-setup.mdx` that provides a step-by-step guide
on setting up Supabase for Quivr. This includes initializing Supabase,
configuring environment variables, using the Supabase CLI for migrations
and database resets, and deploying to a hosted Supabase environment.
- **Documentation Navigation Update**: Updates `docs/mint.json` to
include a reference to the newly added `supabase-setup.mdx` in the
configuring section, ensuring users can easily find this resource.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=cadcc1b3-ff9d-4650-b92a-28cadcc3ebdf).
This pull request fixes the value of NEXT_PUBLIC_AUTH_MODES in the
docker-compose.yml file. The previous value was incorrect and has been
updated to the correct value.
This pull request adds the `NEXT_PUBLIC_AUTH_MODES` variable to the
`.env.example` file. This variable allows the application to specify the
authentication modes that are supported.
This pull request adds a new feature to generate images using the OpenAI
DALL-E model. The `ImageGeneratorTool` class is implemented to handle
the image generation functionality.
This pull request adds a GitHub Actions workflow for building and
pushing Docker images to Amazon ECR. The workflow is triggered on every
push to the main branch and includes steps for configuring AWS
credentials, logging in to Amazon ECR, GitHub Container Registry, and
Docker Hub, setting up Docker Buildx, creating a Docker cache storage
backend, and building, tagging, and pushing the Docker image to Amazon
ECR.
