- Introduce new fields in AssistantConfig, schemas, and database models to support vision capabilities, including `vision_enabled` and `vision_model_resource_id`.
- Enhance validation logic in routes to ensure proper handling of vision models and their requirements.
- Update the AssistantPage and related frontend components to include options for enabling vision understanding and selecting appropriate vision models.
- Modify database seed scripts to include vision-related data for assistants, ensuring consistent setup.
- Refactor related functions to integrate vision model handling in the audio-visual processing pipeline.
- Introduce a new `support_image_input` field in model resources, allowing models to indicate support for image input.
- Update the backend models, schemas, and database seed scripts to accommodate the new field.
- Enhance the AssistantConfig and related routes to handle image input capabilities, ensuring proper validation and error handling.
- Modify the frontend components to include toggles for enabling visual understanding and filtering models based on image input support.
- Implement necessary adjustments in the voice preview and pipeline to integrate video stream handling alongside audio functionalities.
- Add new fields to AssistantConfig for realtime interface configuration, including types, values, and secrets.
- Introduce StepFunRealtimeService to handle speech-to-speech processing via WebSocket, integrating STT, LLM, and TTS functionalities.
- Refactor pipeline execution to support a new realtime mode, allowing direct text input processing and immediate responses.
- Update model resource testing to include validation for StepFun Realtime connections.
- Enhance service factory to create realtime services based on configuration settings.
- Modify README documentation to reflect new realtime capabilities and usage instructions.
- Introduce a new model structure for managing interface definitions and model resources, enhancing the backend's capability to handle various service integrations.
- Update the Makefile to reflect changes in database seeding and resource management commands.
- Remove the deprecated credentials management routes and replace them with a unified model registry API.
- Modify existing routes and schemas to align with the new model structure, ensuring seamless integration with the frontend.
- Enhance database seeding scripts to populate new model resources and their configurations.
- Update README documentation to reflect the new architecture and usage instructions for model resources and interface definitions.
- Introduce new Xfyun ASR and TTS services, enabling integration with iFlytek's voice recognition and synthesis capabilities.
- Update AssistantConfig model to include interface types for STT and TTS.
- Enhance credential testing to validate Xfyun credentials.
- Modify service factory to create Xfyun services based on configuration.
- Update README with new configuration details for Xfyun integration.
- Add new frontend components for visualizing audio streams and managing user interactions.
- Introduce new fields for voice, speed, and language in the AssistantConfig and ProviderCredential models to support TTS and ASR configurations.
- Update the database schema and seeding script to accommodate the new fields, ensuring backward compatibility.
- Implement credential testing endpoints and logic to validate OpenAI-compatible credentials, enhancing user experience and reliability.
- Modify frontend components to include new fields in the credential forms and improve connection testing feedback.
- Refactor related services and API interactions to support the new credential testing feature.
- Change 'DeepSeek-V3' to 'DeepSeek-Chat' and update its API key.
- Rename 'OpenAI TTS' to 'SiliconFlow-CosyVoice2-0.5B' and update its details.
- Add new models: 'SiliconFlow-TeleSpeechASR' and 'SiliconFlow-Qwen3-Embedding-4B' with corresponding API keys and configurations.
- Adjust existing entries to ensure consistency in the database seeding process.
- Update Makefile to include new database seed commands for assistants and credentials.
- Refactor assistant model to use explicit fields instead of a config dictionary, improving data integrity and clarity.
- Implement new seeding SQL script for assistants, ensuring dependencies on credentials are respected.
- Modify backend routes and frontend components to accommodate the new assistant structure, including direct field access for prompt, API URL, and keys.
- Enhance the AssistantPage component to handle the new data structure and streamline the save process for different assistant types.
Add CRUD functionality for knowledge bases, including routes for listing, creating, updating, and deleting knowledge bases. Update the assistant model to include foreign key references to knowledge bases and modify the assistant configuration to handle external API keys securely. Refactor related services and routes to accommodate these changes, ensuring proper handling of credential resolution and configuration normalization.
