- Introduced the FeaturePrompt model to store prompts for AI features with fields for feature, model, settings, prompt, and version.
- Implemented unique constraints and verbose names for better clarity.
- Created initial migration for the FeaturePrompt model.
- Added a new app `copilot` with configuration for future development.

- Added `chats.apps.ai_features.copilot` to the `INSTALLED_APPS` in `settings.py` for better organization of AI features.
- Updated the `CopilotConfig` class to include the full app path for clarity and consistency.

…estions

- Removed `chats.apps.ai_features.copilot` from `INSTALLED_APPS` and added `chats.apps.ai_features.response_suggestions` for better organization.
- Deleted the `CopilotConfig` class and created a new `ResponseSuggestionsConfig` class.
- Introduced `ResponseSuggestionsService` to handle response suggestions functionality.

- Updated the `get_response_suggestion` method to accept a `room` parameter for improved context in response suggestions.
- Added type checking for the `Room` model to ensure compatibility during development.
- Included a TODO comment for future implementation of conversation injection into prompts.

…n ResponseSuggestionsService

- Introduced `CHATS_RESPONSE_SUGGESTIONS_MAX_MESSAGES` setting to control the number of messages considered for response suggestions.
- Enhanced `ResponseSuggestionsService` to log errors when the prompt does not contain the required placeholder and to log information when no messages are found in the room.
- Updated the `get_response_suggestion` method to utilize the new configuration for message retrieval.

…i/chats-engine into feature/response-generation

…Service

- Added error handling in the `get_response_suggestion` method to log errors when generating responses.
- Ensured that the conversation messages are processed correctly before generating the response.
- Improved logging for better traceability of issues related to response generation.

- Simplified the logic for slicing messages in the `get_response_suggestion` method to improve readability.
- Introduced a variable for the offset calculation to enhance clarity in message retrieval.

…i/chats-engine into feature/response-generation

- Adjusted the placement of the AWS_BEDROCK_REGION_NAME setting to ensure it is always available, regardless of S3 usage.

- Modified the `generate_text` method call to include the `prompt` parameter in the test case for better accuracy in response validation.

- Changed the Room reference in the `get_response_suggestion` method from `id` to `uuid` for consistency.
- Updated the ordering of messages from `created_at` to `created_on` to align with the model changes.
- Added unit tests for the ResponseSuggestionsService to ensure proper functionality and error handling in response generation.

- Removed unnecessary mocking of FeaturePrompt objects in the test cases for `generate_response_suggestion`.
- Updated the version of the invalid prompt in the test to ensure accurate testing of response suggestions.
- Enhanced clarity and maintainability of the test code by streamlining the setup process.

- Added a conditional check to ensure the offset calculation for message slicing only occurs when the message quantity exceeds the maximum limit.
- Enhanced the clarity of the message retrieval process in the `get_response_suggestion` method.

- Removed unused import of TYPE_CHECKING from services.py for improved clarity.
- Simplified the creation of FeaturePrompt objects in test_services.py by eliminating unnecessary variable assignment.