- Introduce new database models for conversation sessions, messages, and artifacts to support conversation history tracking.
- Implement API routes for listing conversations and retrieving detailed conversation data, enhancing user interaction with historical records.
- Add a conversation recorder service to persist conversation messages in real-time without disrupting ongoing calls.
- Update the frontend to display conversation history, including filtering and sorting options, improving user experience.
- Enhance the pipeline to integrate conversation history recording seamlessly during interactions.
- Introduce a new `RuntimeTool` model to encapsulate tool data for runtime sessions, including attributes like `id`, `name`, `function_name`, `type`, and `description`.
- Update the `AssistantConfig` model to include a list of reusable tools, allowing for better management of tools within assistant configurations.
- Modify the `config_resolver` service to fetch and resolve tools associated with assistants, ensuring they are available during runtime.
- Refactor tool-related CRUD operations in the `tools` route to support the new runtime execution model, enhancing the overall tool management system.
- Update documentation and comments to reflect changes in tool execution and configuration handling, improving clarity for future development.
- Introduce a new `sync_default_tools` function in `session.py` to ensure essential reusable tools are created without overwriting existing edits.
- Update the `lifespan` context manager in `app.py` to call `sync_default_tools`, enhancing the initialization process for the application.
- This change improves the management of default tools within the system, ensuring they are available for use while preserving user modifications.
- Introduce a new `Tool` model and `AssistantToolBinding` for managing reusable tools within the application.
- Implement CRUD operations for tools in the new `tools` route, allowing for the creation, retrieval, updating, and deletion of tools.
- Update the `Assistant` model to include a list of tool IDs, enabling assistants to utilize these tools.
- Enhance the backend routes to synchronize tool bindings with assistants, ensuring proper management of tool associations.
- Add frontend components for tool management, including a tool picker in the assistant configuration, improving user experience in tool selection.
- Create a mobile call page to facilitate video calls, integrating camera and microphone selection for enhanced communication capabilities.
- Update API definitions to include tool-related types and operations, ensuring consistency across the application.
- Add a migration script to create the necessary database tables for tools and bindings, supporting the new functionality.
- Replace the `config.py` module with a new `settings.py` to streamline environment variable management, focusing on database, CORS, and TURN settings.
- Update references throughout the backend codebase to use the new `settings` module instead of the deprecated `config`.
- Modify the `.env.example` file to reflect the new configuration approach, indicating that model provider credentials should be maintained separately.
- Enhance the `AssistantConfig` model to clarify the source of runtime connection information, ensuring it is injected from model resources rather than relying on defaults from the environment.
- Introduce new user scripts for audio and video management in the Tampermonkey environment, enhancing WebRTC capabilities.
- Integrate Alembic for managing database schema migrations, replacing the previous SQL schema management.
- Update the FastAPI application to synchronize interface definitions at startup.
- Modify the Docker Compose command to run Alembic migrations before starting the API.
- Enhance the Makefile with new commands for database migration and revision management.
- Remove outdated SQL schema and seed files, transitioning to a more dynamic migration approach.
- Add initial migration scripts and configuration for Alembic, ensuring a structured database evolution.
- Extend the AssistantConfig model to include agent_interface_type, agent_values, and agent_secrets for enhanced agent management.
- Update ModelType to include "Agent" for broader capability support.
- Seed new agent models and configurations in the database for Dify, FastGPT, and OpenCode applications.
- Modify the Assistant routes to validate and handle agent capabilities.
- Implement agent resource resolution in the config resolver for runtime configuration.
- Enhance the interface catalog with agent-specific fields and definitions.
- Update frontend components to manage agent configurations, including form handling and state management for agent-related inputs.
- Add new database management targets: db-up, db-schema, db-seed-interface-definitions, and db-init to streamline database setup and seeding processes.
- Update db-seed and db-reset dependencies to include new initialization steps for better data integrity.
- Introduce new SQL files for schema definition and interface definitions seeding, ensuring a consistent database structure.
- Refactor existing seed scripts to align with new dependencies and improve clarity in database operations.
- 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.
