The commit introduces a new feature to capture and display output from executed processes within the workflow runner. This includes adding a dedicated output buffer that collects stdout and stderr streams during process execution, implementing a display mechanism that shows the output in real-time or upon completion, and updating the relevant data structures to store process output alongside other execution metadata. The change modifies the core execution loop to pipe process output into the new buffer and exposes it through the workflow result interface for downstream consumption.
The profiles table previously lacked an index on the user_id column, causing full table scans during user lookups. This change adds a B-tree index on user_id to optimize query performance for profile retrieval operations.
The implementation now handles all edge cases and passes all test scenarios. Core logic has been refined to ensure consistent behavior across different input conditions. All previously failing test cases now pass successfully.
- Updated Makefile to simplify build targets for both main app and Python extension
- Implemented rpylib.c with chat and reset functions for OpenAI API communication
The new index on the `user_id` column in the `profiles` table improves query performance for user-specific lookups, reducing full table scans during authentication and profile retrieval operations.
- Include overview of project goals and key features
- Provide step-by-step installation and configuration guide
- Clarify usage examples and contribution guidelines
The README now includes a brief overview of the project's purpose and step-by-step guidance for local development setup, including prerequisites and installation commands.
The review now includes a full text body, a numeric rating field, and a timestamp for when the review was submitted. This enables richer display and sorting by date on the product page.
This commit introduces a new review feature that allows users to submit feedback and ratings for products. The implementation includes a review form component, backend API endpoint for storing reviews, and database migration for the reviews table. Users can now rate products on a scale of 1-5 stars and provide written feedback, which is displayed on the product detail page.
