* fix: add stored values support for dataset columns
This commit introduces stored values functionality for dataset columns, including:
- Adding a `stored_values` flag to column deployment requests
- Implementing a mechanism to store column values during dataset deployment
- Updating data analyst and SQL generation agents to leverage stored values
- Creating a new utility module for stored values search and management
* refactor(stored_values): improve stored values implementation and schema management
This commit enhances the stored values functionality with several key improvements:
- Update schema and table creation to use organization ID as schema name
- Modify stored values storage to include column ID
- Improve value extraction and embedding generation process
- Remove unnecessary distance calculation in search results
- Clean up unused values_engine module
- Simplified message and tool structures in `types.rs`
- Updated `agent.rs` to use new type structures
- Enhanced error handling in agent tests with detailed error printing
- Updated `.cursorrules` with debugging recommendation
- Removed redundant fields and improved type flexibility
- Streamlined serialization and deserialization of AI client types
- Updated `types.rs` to support more complex message and response structures
- Added support for multi-content messages with `Content` struct
- Introduced optional fields and improved serialization handling
- Enhanced type flexibility for AI client responses
- Updated test cases to reflect new type structures
- Added `Default` implementation for `LiteLLMClient`
- Improved support for tool calls and streaming responses
- Updated test cases to use `mockito::Server::new_async()`
- Added request body validation in test mocks
- Improved test coverage for chat completion and streaming scenarios
- Updated .cursorrules with detailed testing guidelines
- Added dev dependencies for Mockito and Tokio async testing
- Updated .cursorrules with async test requirement
- Expanded utils modules with new serde_helpers and tools
- Added new AI client module for LiteLLM
- Introduced a new `assets` module to handle asset-related routes.
- Updated the user router to nest the `assets` routes under the user ID path, enhancing the organization of API endpoints.
- This change improves the structure and maintainability of the user-related routes in the API.
dal