* chore: move database model methods to /packages/data-schemas
* chore: add TypeScript ESLint rule to warn on unused variables
* refactor: model imports to streamline access
- Consolidated model imports across various files to improve code organization and reduce redundancy.
- Updated imports for models such as Assistant, Message, Conversation, and others to a unified import path.
- Adjusted middleware and service files to reflect the new import structure, ensuring functionality remains intact.
- Enhanced test files to align with the new import paths, maintaining test coverage and integrity.
* chore: migrate database models to packages/data-schemas and refactor all direct Mongoose Model usage outside of data-schemas
* test: update agent model mocks in unit tests
- Added `getAgent` mock to `client.test.js` to enhance test coverage for agent-related functionality.
- Removed redundant `getAgent` and `getAgents` mocks from `openai.spec.js` and `responses.unit.spec.js` to streamline test setup and reduce duplication.
- Ensured consistency in agent mock implementations across test files.
* fix: update types in data-schemas
* refactor: enhance type definitions in transaction and spending methods
- Updated type definitions in `checkBalance.ts` to use specific request and response types.
- Refined `spendTokens.ts` to utilize a new `SpendTxData` interface for better clarity and type safety.
- Improved transaction handling in `transaction.ts` by introducing `TransactionResult` and `TxData` interfaces, ensuring consistent data structures across methods.
- Adjusted unit tests in `transaction.spec.ts` to accommodate new type definitions and enhance robustness.
* refactor: streamline model imports and enhance code organization
- Consolidated model imports across various controllers and services to a unified import path, improving code clarity and reducing redundancy.
- Updated multiple files to reflect the new import structure, ensuring all functionalities remain intact.
- Enhanced overall code organization by removing duplicate import statements and optimizing the usage of model methods.
* feat: implement loadAddedAgent and refactor agent loading logic
- Introduced `loadAddedAgent` function to handle loading agents from added conversations, supporting multi-convo parallel execution.
- Created a new `load.ts` file to encapsulate agent loading functionalities, including `loadEphemeralAgent` and `loadAgent`.
- Updated the `index.ts` file to export the new `load` module instead of the deprecated `loadAgent`.
- Enhanced type definitions and improved error handling in the agent loading process.
- Adjusted unit tests to reflect changes in the agent loading structure and ensure comprehensive coverage.
* refactor: enhance balance handling with new update interface
- Introduced `IBalanceUpdate` interface to streamline balance update operations across the codebase.
- Updated `upsertBalanceFields` method signatures in `balance.ts`, `transaction.ts`, and related tests to utilize the new interface for improved type safety.
- Adjusted type imports in `balance.spec.ts` to include `IBalanceUpdate`, ensuring consistency in balance management functionalities.
- Enhanced overall code clarity and maintainability by refining type definitions related to balance operations.
* feat: add unit tests for loadAgent functionality and enhance agent loading logic
- Introduced comprehensive unit tests for the `loadAgent` function, covering various scenarios including null and empty agent IDs, loading of ephemeral agents, and permission checks.
- Enhanced the `initializeClient` function by moving `getConvoFiles` to the correct position in the database method exports, ensuring proper functionality.
- Improved test coverage for agent loading, including handling of non-existent agents and user permissions.
* chore: reorder memory method exports for consistency
- Moved `deleteAllUserMemories` to the correct position in the exported memory methods, ensuring a consistent and logical order of method exports in `memory.ts`.
* 🐛 fix: Normalize `output_text` blocks in Responses API input conversion
Treat `output_text` content blocks the same as `input_text` when
converting Responses API input to internal message format. Previously,
assistant messages containing `output_text` blocks fell through to the
default handler, producing `{ type: 'output_text' }` without a `text`
field, which caused downstream provider adapters (e.g. Bedrock) to fail
with "Unsupported content block type: output_text".
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: Remove ChatModelStreamHandler from OpenAI and Responses controllers
Eliminated the ChatModelStreamHandler from both OpenAIChatCompletionController and createResponse functions to streamline event handling. This change simplifies the code by relying on existing handlers for message deltas and reasoning deltas, enhancing maintainability and reducing complexity in the agent's event processing logic.
* feat: Enhance input conversion in Responses API
Updated the `convertInputToMessages` function to handle additional content types, including `input_file` and `refusal` blocks, ensuring they are converted to appropriate message formats. Implemented null filtering for content arrays and default values for missing fields, improving robustness. Added comprehensive unit tests to validate these changes and ensure correct behavior across various input scenarios.
* fix: Forward upstream provider status codes in error responses
Updated error handling in OpenAIChatCompletionController and createResponse functions to forward upstream provider status codes (e.g., Anthropic 400s) instead of masking them as 500. This change improves error reporting by providing more accurate status codes and error types, enhancing the clarity of error responses for clients.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: Implement token usage tracking for OpenAI and Responses controllers
- Added functionality to record token usage against user balances in OpenAIChatCompletionController and createResponse functions.
- Introduced new utility functions for managing token spending and structured token usage.
- Enhanced error handling for token recording to improve logging and debugging capabilities.
- Updated imports to include new usage tracking methods and configurations.
* test: Add unit tests for recordCollectedUsage function in usage.spec.ts
- Introduced comprehensive tests for the recordCollectedUsage function, covering various scenarios including handling empty and null collectedUsage, single and multiple usage entries, and sequential and parallel execution cases.
- Enhanced token handling tests to ensure correct calculations for both OpenAI and Anthropic formats, including cache token management.
- Improved overall test coverage for usage tracking functionality, ensuring robust validation of expected behaviors and outcomes.
* test: Add unit tests for OpenAI and Responses API controllers
- Introduced comprehensive unit tests for the OpenAIChatCompletionController and createResponse functions, focusing on the correct invocation of recordCollectedUsage for token spending.
- Enhanced tests to validate the passing of balance and transactions configuration to the recordCollectedUsage function.
- Ensured proper dependency injection of spendTokens and spendStructuredTokens in the usage recording process.
- Improved overall test coverage for token usage tracking, ensuring robust validation of expected behaviors and outcomes.
