Feature/perf api readiness#3
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…ices - Improved type annotations in `performance_baseline.py` and `scoring_evaluation.py` for better clarity and flexibility. - Simplified the assignment of `identities` in `_ranking_identity_map` and consolidated `fallback_order` construction in `generate_top5_audit_visualization.py`. - Cleaned up test files by removing unnecessary blank lines to enhance code consistency.
…equirements - Expanded the objective to clarify the integration of dashboard, API, and CLI for strategy workflows. - Added detailed requirements for the dashboard experience, including dataset handling, filter controls, and strategy controls. - Specified dashboard behavior constraints and acceptance criteria for end-to-end functionality. - Updated sections on CLI specifications and rollout plans to align with new dashboard features and ensure consistency across interfaces.
- Added detailed implementation steps for Phase A, including request/response contracts, service interfaces, API route skeletons, and CLI command mappings. - Specified validation rules, placeholder responses, and testing requirements to ensure contract stability and successful execution of Phase A. - Defined criteria for completion of Phase A to facilitate a smooth transition to Phase B.
- Added new ranking schema models including RankingFilters, RankingStrategy, ResultWindow, and RankingQueryRequest to define the structure and validation rules for ranking queries. - Introduced corresponding response models such as RankingQueryResponse, ListingDetailResponse, and ProfileDetailResponse to standardize API responses. - Implemented validation logic to ensure data integrity for request and response payloads, including checks for price bounds and pagination constraints. - Created unit tests to validate the functionality and correctness of the new ranking models and their validation rules.
- Added a note about the 500ish dataset scraped from Propflux and its relocation to the project samples folder in PROJECT_NOTE.md. - Expanded Week 3 specification to include open questions regarding agent prompts, profile storage, and dashboard exposure, enhancing clarity on implementation considerations. - Corrected a typo in the scoring metadata section of the Week 3 specification.
- Updated the Week 3 specification to include comprehensive guidelines for managing profiles in the dashboard, emphasizing CRUD operations, default profiles, and weight overrides. - Added a TODO section in `ranking_query.py` outlining critical research tasks related to weights and signals for strategy presets, highlighting the importance of an evaluation process for each strategy profile.
…t insights - Enhanced the Week 3 specification by incorporating further details on profile management, including best practices for CRUD operations and weight adjustments. - Updated the TODO section in `ranking_query.py` to reflect new research tasks related to profiling strategies, emphasizing the need for a thorough evaluation process.
- Updated the Week 3 specification to refine the language around profile reference persistence and removed references to profile snapshots for clarity. - Specified that the dashboard does not perform profile CRUD or alias remapping in Week 3, ensuring a clear understanding of the scope. - Adjusted sections to emphasize the use of `profile_id` instead of `profile_version`, aligning with the overall profile management strategy.
- Introduced new CLI commands for ranking queries, listing details, profiles listing, and profile resolution, expanding the command set available to users. - Implemented JSON payload handling for ranking queries and listing details, allowing for structured output and file writing options. - Updated the PROJECT_NOTE.md to remove outdated dataset references and clarify project goals. - Enhanced test coverage for CLI commands to ensure new functionalities are included in help outputs.
- Introduced functionality to load and validate scoring profiles from a configuration file, allowing for dynamic profile management. - Updated the profile resolution logic to utilize alias mappings and ensure profiles are correctly defined and validated against supported signals. - Modified tests to reflect changes in profile handling, including environment path overrides and validation of profile definitions. - Adjusted CLI test cases to align with new profile identifiers and weight configurations.
- Updated the `run_ranking_query` function to accept a database session, enabling persistence of ranking runs and associated scoring profiles. - Introduced a new helper function `_persist_ranking_run` to handle the storage of ranking run details and profile backups. - Modified CLI command to utilize the database session for improved data management. - Added tests to verify the persistence of ranking runs and the reuse of profile backups, ensuring data integrity across multiple queries.
…PI app - Added the ranking router to the FastAPI application, enabling access to ranking-related endpoints. - Implemented a custom exception handler for RequestValidationError to provide structured error responses. - Updated documentation to reflect the new ranking functionality and error handling improvements.
…n steps - Added comprehensive guidelines for the Phase B ranking and query implementation, outlining execution order and specific tasks for filtering, scoring, and persistence. - Included criteria for successful completion of Phase B, emphasizing the need for deterministic sorting, error handling, and testing requirements. - Updated acceptance criteria to reflect the transition from placeholder responses to real ranked outputs, ensuring alignment with the overall project goals.
- Updated the `listing_detail` command to include database session management, improving error handling for missing ranking runs and listings. - Introduced new exceptions for better clarity on ranking errors: `RankingRunNotFound`, `RankingListingNotInRun`, and `RankingListingRowMissing`. - Enhanced the ranking query service to handle dataset source validation, ensuring proper error responses for unknown sources. - Updated tests to reflect changes in dataset source handling and error scenarios, ensuring robust coverage for new functionalities.
… logic - Introduced a new CLI command `inspect-rejections` to generate a cross-reference report of rejected dataset entries, providing insights into validation errors and rejected rows. - Enhanced the dataset validation service with a new function `build_rejection_cross_reference` to aggregate rejection diagnostics and examples. - Updated the `PropfluxListing` schema with field validators to coerce boolean-like values and format prices correctly, improving data integrity during validation. - Added tests to ensure proper handling of boolean coercion and price formatting in the `PropfluxListing` schema, enhancing overall validation coverage.
…n steps - Delivered a comprehensive outline for Phase C of the dashboard, detailing the user flow from dataset source selection to ranking and detail inspection. - Included specific implementation steps for dashboard state management, request composition, and error handling. - Established criteria for successful completion of Phase C, ensuring alignment with backend services and user experience expectations. - Emphasized the importance of maintaining consistency between the dashboard, API, and CLI behaviors.
- Implemented a new API endpoint `/datasets/sources` to list dataset sources along with their job details and validation status. - Introduced `DatasetSourceSummaryResponse` schema to structure the response data for the new endpoint. - Updated tests to validate the functionality of the dataset sources endpoint, ensuring proper response structure and status codes. - Enhanced the ranking routes with necessary imports and database queries to support the new feature.
…ions - Added instructions for resetting the database in both Docker and local environments to the README. - Updated the setup checklist to include optional, destructive database reset commands for clarity during setup. - Improved the overall organization and readability of the documentation to assist developers in managing database states effectively.
- Changed the `NEXT_PUBLIC_API_BASE_URL` in the Docker Compose file to point to `http://localhost:8000` for local development. - Added a new helper function `_display_backend_output_path` in the CLI to format report paths correctly, ensuring that both absolute and relative paths are handled appropriately. - Updated CLI commands to utilize the new report path formatting, improving output clarity for users.
…valuation - Updated the performance baseline service to capture latency metrics for `ranking_list_api`, `filtered_ranking_api`, and `listing_detail_api`. - Implemented SLO evaluations for the new API latency metrics, moving them from deferred to measured status. - Added index tuning migration to optimize performance. - Updated tests to validate the new metrics and SLO assessments, ensuring comprehensive coverage of the changes. - Revised project documentation to reflect the enhancements made in Phase D.
…handling - Introduced a new field `profile_row_id` to the `ResolvedProfile` schema, ensuring it is validated to be greater than or equal to 1. - Updated the `run_ranking_query` function to correctly instantiate `ResolvedProfile` with the new `profile_row_id` from the ranking run. - Adjusted tests to validate the inclusion of `profile_row_id` in the response and ensure consistency with the ranking run data. - Enhanced documentation to reflect changes in profile management and the new field's significance.
- Included a reference to the full implementation specification for the Week 4 dashboard in both the PROJECT_NOTE.md and README.md files. - Enhanced project documentation to ensure clarity on the upcoming dashboard features and implementation details.
- Added a new router for runs diagnostics to the FastAPI application, enabling endpoints for run summaries and details. - Enhanced the `list_dataset_sources` function to support filtering by ingestion job status and search queries. - Introduced new fields in the `RankingResultItem` schema for additional listing details, including `listing_url`, `bedrooms`, `bathrooms`, `province`, and `source_site`. - Updated the `RankingRun` model to include `records_considered`, improving tracking of processed records during ranking runs. - Expanded the API documentation to reflect new endpoints and features related to runs diagnostics and ranking queries. - Adjusted tests to validate the new functionalities and ensure accurate responses from the updated endpoints.
- Introduced a new error banner component to display API request failures across various dashboard pages, improving user feedback during data loading. - Updated the `fetchJson` function to provide more informative error messages when API requests fail, enhancing debugging capabilities. - Added a new test specification for the dashboard frontend to ensure comprehensive coverage of error handling scenarios. - Updated the README to include a reference to the new dashboard frontend QA/test specification, improving documentation clarity.
- Added a new error banner style to enhance the display of error messages across various dashboard pages, improving user experience during API request failures. - Updated error handling in multiple components to utilize a new `formatThrownApiError` function, providing clearer and more structured error messages. - Refactored error display logic to use multiline formatting for better readability, ensuring users receive comprehensive feedback on issues encountered. - Enhanced the `fetchJson` function to throw a custom `ApiError` for better error management and debugging.
- Introduced a new toast error style to visually differentiate error messages in the dashboard. - Updated the toast context to support different tones, allowing for more informative user feedback. - Refactored error handling in the ControlWorkbench component to utilize the new toast functionality, improving user experience during error scenarios.
- Added a new filter bar for source status selection and search input in the dashboard. - Introduced styles for the filter components, including a status dropdown and a search input field. - Enhanced user experience by allowing filtering of sources based on ingestion job status and search queries.
- Added a new comparison section to the runs page, allowing users to select a baseline and candidate run for side-by-side metadata comparison. - Introduced new styles for the comparison picker and result display, enhancing the user interface. - Implemented logic to fetch and compare run details, displaying differences in a structured format. - Added error handling for comparison operations, improving user feedback during data loading and error scenarios.
- Updated button styles to include inline-flex display, center alignment, and improved padding for better visual consistency. - Added alignment for action items in the dashboard to ensure a more cohesive layout. - Enhanced button text properties for improved readability and user experience.
…ompleteness - Revised the README to enhance the description of PropSignal's core functionalities and target audience. - Expanded the configuration guide to include detailed explanations of environment variables, config files, and Docker defaults. - Improved the organization of documentation for better accessibility, including links to relevant guides for dashboard and CLI usage. - Added a glossary section to clarify terms used across the platform, aiding user understanding.
- Revised the README to provide a clearer overview of PropSignal's capabilities and architecture, emphasizing the full-stack nature of the project. - Expanded CLI usage documentation to include detailed command references and examples for ingestion, scoring, and ranking operations. - Updated the CI workflow to include unit tests for the frontend, improving overall test coverage and reliability. - Enhanced the architecture documentation to reflect recent changes and provide historical context for reviewers. - Improved the setup checklist for clarity and completeness, ensuring a smoother onboarding experience for new developers.
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