Expanded the list of providers for which models are fetched dynamically to include Ollama and Llamafile, removing the need for manual model addition in the user interface for these providers. This simplifies the user experience and ensures users always have access to the latest models without manual intervention.
Adds support for using Ollama 2 as a model provider. This includes:
- Adding Ollama 2 to the list of supported providers in the UI
- Updating the model identification logic to properly handle Ollama 2 models
- Modifying the model loading and runtime configuration to work with Ollama 2
- Implementing Ollama 2 specific functionality in the embedding and chat models
This change allows users to leverage the capabilities of Ollama 2 for both embeddings and conversational AI tasks.
Add support for LlamaFile, a new model provider that allows users to interact with models stored in LlamaFile format. This includes:
- Adding an icon for LlamaFile in the provider selection menu.
- Updating the model provider selection to include LlamaFile.
- Updating the model handling logic to properly identify and process LlamaFile models.
- Updating the API providers list to include LlamaFile.
This enables users to leverage the capabilities of LlamaFile models within the application.
Adds a new "Temporary Chat" mode for quick, non-persistent conversations. The new mode is available in the header bar and will trigger a visually distinct chat experience with a temporary background color. Temporary chats do not save to the chat history and are meant for short, one-off interactions. This feature enhances flexibility and provides a more convenient option for users who need to quickly interact with the AI without committing the conversation to their history.
Adds a new setting to control the maximum number of tokens generated by the model. This provides more control over the length of responses and can be useful for limiting the amount of text generated in certain situations.
This commit introduces a new feature that displays generation information for each message in the chat.
The generation info is displayed in a popover and includes details about the model used, the prompt, and other relevant information. This helps users understand how their messages were generated and troubleshoot any issues that may arise.
The generation info is retrieved from the LLM response and is stored in the database alongside other message details.
This commit also includes translations for the generation info label in all supported languages.
Adds a "Save" button to the edit message form in Playground, allowing users to save changes without immediately submitting them. This also introduces a new `isSend` flag to the `onEditFormSubmit` prop, enabling developers to control whether a message should be sent immediately or saved for later submission. This enhances flexibility and user control during the message editing process.
Adds pin/unpin functionality to the chat history sidebar, allowing users to keep important conversations readily accessible. This improves user experience and helps organize past interactions.
This feature includes:
- Pin/unpin buttons in the chat history sidebar.
- Updated database schema to include `is_pinned` field for chat history items.
- Localized translations for pin/unpin actions.
- Updated UI to display pinned items at the top of the list.
Adds a new "Download Code" button to the code block component, allowing users to download the code displayed for offline use.
This feature enhances user convenience and provides a more versatile experience for exploring and utilizing code snippets.
Refine the Playground's UI to improve user experience:
- Streamline chat window layout for better message readability
- Introduce a knowledge selection dropdown for easier context setting
- Improve image upload integration for a smoother workflow
- Optimize spacing and styling for a more polished visual appearance
Adds an HTML preview feature to the code block component, allowing users to view the rendered output of their HTML code snippets. This improves the user experience by providing a more interactive and informative way to understand the code.
Shorten the displayed embedding model names in the knowledge settings by removing the "embedding" suffix. This improves readability and makes the table more concise.
Adds model type support for chat and embedding models. This allows users to specify which type of model they want to use when adding custom models.
Additionally, this commit introduces a more descriptive interface for adding custom models, enhancing the clarity of the model selection process.
Update the user interface for the OpenAI settings to be more informative and consistent. Improved language around "OpenAI API Settings" to be more accurate and less technical. Also added a helpful tip for using LM Studio as a provider.
Refactor embedding models and their handling to improve performance and simplify the process.
Add a new model selection mechanism, and enhance the UI for model selection, offering clearer and more user-friendly options for embedding models.
Refactor embeddings to use a common model for page assist and RAG, further improving performance and streamlining the workflow.
When using the LM Studio provider, the model selection modal was incorrectly appearing. This commit prevents the modal from appearing when the provider is set to LM Studio. This ensures that the user experience is consistent across all providers.
Make the loading state of OpenAI models more visually appealing and user-friendly by replacing the default `Spin` component with a more contextually relevant loading animation within a centered container. This provides a better visual cue to users while models are being fetched.
Add a provider selection dropdown to the OpenAI settings, enabling users to choose from pre-configured options like "Azure" or "Custom." This streamlines setup and allows for more flexibility in configuring OpenAI API endpoints. The dropdown pre-populates base URLs and names based on the selected provider.
The dropdown also automatically populates base URLs and names based on the selected provider, further simplifying the configuration process.
Adds support for OpenAI models, allowing users to leverage various OpenAI models directly from the application. This includes custom OpenAI models and OpenAI-specific configurations for seamless integration.
This commit introduces a new UI for managing models within the OpenAI integration. This UI allows users to view, add, and delete OpenAI models associated with their OpenAI providers. It includes functionality to fetch and refresh model lists, as well as to search for specific models. These changes enhance the user experience by offering greater control over their OpenAI model interactions.
This commit also includes improvements to the existing OpenAI configuration UI, enabling users to seamlessly manage multiple OpenAI providers and associated models.
