- Add `writeSupplierWorkbook` function to create Excel workbooks for supplier analysis results.
- Introduce `SupplierExportSummary` type for summarizing export data.
- Create tests for `writeSupplierWorkbook` to ensure correct sheet creation and data population.
- Implement supplier scoring logic in `supplier-scoring.ts` to evaluate product profitability and demand.
- Add tests for supplier scoring to validate scoring logic and verdict determination.
- Enhance UPC file analysis to integrate supplier scoring and export results to Excel.
- Update database writing logic to accommodate new supplier analysis results.
- Refactor types to include supplier-specific data structures and scoring metrics.
- Ensure proper cleanup of temporary files after tests.
- Updated test case to reflect changes in processing mid-range matches based on sellability.
- Modified `processCategory` function to implement strict and soft sellability gates.
- Introduced new command-line arguments for category selection and sellability gate configuration.
- Enhanced error handling and validation for new arguments.
- Improved logging for category processing and budget usage.
This new pipeline identifies products meeting specific monthly sold, price, seller count, and Amazon buy box share criteria across categories. It fetches comprehensive product data from Keepa and SP-API, analyzes it using an LLM, and persists the results.
A key enhancement is the introduction of a dedicated Redis cache for Keepa and SP-API responses. This reduces API token consumption and improves performance for subsequent runs by caching enriched ASIN data with a 12-hour TTL. Products are saved regardless of their sellability status to provide a complete view.
Reduces API token consumption by disabling stats and buybox data for UPC-to-ASIN mapping requests. Additionally, introduces a run-level cache to avoid redundant lookups for the same UPC across different batch chunks.
Introduces the capability to resolve UPCs to ASINs using the Keepa API. This includes a new `upc-file` command for processing large Excel files of UPCs, a `upc` CLI tool for quick lookups, and API endpoints for web-based integration. The analysis pipeline was refactored into a reusable module to support both standard ASIN leads and new UPC-driven workflows.
- Introduced `amazonIsSeller` and `amazonBuyboxSharePct90d` fields in KeepaData type.
- Updated database schema and queries to store Amazon seller status and buy box share percentage.
- Enhanced product analysis results with new metrics from Keepa API.
- Modified frontend components to display Amazon seller status and buy box share percentage.
- Implemented reanalysis functionality for products to refresh Amazon-related metrics.
- Introduces a new script to discover categories and identify products with high monthly sales volume.
- Filters candidates based on sellability status and a configurable monthly sold threshold.
- Enriches product data with Keepa and SP-API metrics before performing LLM-based analysis.
- Persists results to SQLite and includes unit tests for the core processing logic.
- Adds new columns to the `results` table for tracking spreadsheet-sourced financial data, supplier details, and lead metadata.
- Implements `ensureResultsTableColumns` to automatically migrate existing databases with the new schema.
- Simplifies LLM evaluation logic by removing mandatory skip triggers for Amazon-exclusive and single-seller products.
- Standardizes formatting for database index and table creation statements.
- Implemented main dashboard with run metrics and filtering options.
- Created detailed view for individual runs with results and anomalies.
- Added product listing page with filtering and pagination.
- Introduced utility functions for formatting dates and numbers.
- Styled components with CSS for a clean and responsive layout.
- Set up HTML entry point and linked to the main JavaScript file.
- Updated TypeScript configuration to include DOM types.
- Replaces Excel output with structured database tables for tracking category analysis runs and product results.
- Implements a blacklist to exclude specific category IDs from the bestseller pipeline.
- Adds unit tests for category processing and enhances logging with levels and timestamps.
- Introduces foreign key enforcement and updated schema definitions in the database module.
- Updated `sp-test.ts` to enhance argument parsing and error handling for sellability checks.
- Refactored `types.ts` to maintain consistent formatting and improve readability.
- Improved `writer.ts` for better result handling and CSV writing, ensuring clarity in output.
- Adjusted `tsconfig.json` formatting for consistency and readability.
- Implemented database initialization and connection management in `database.ts` using Bun's SQLite.
- Created `runs` and `results` tables to track historical analysis metadata and detailed product performance.
- Updated `writer.ts` to persist analysis results to the database within a transaction, replacing the previous CSV output logic.
- Updated README and `.gitignore` to reflect the new persistent storage capability.
- Added `amazon-sp-api` dependency to package.json.
- Enhanced configuration to include SP-API credentials and settings.
- Implemented SP-API client initialization and error handling in sp-api.ts.
- Developed functions to fetch product sellability and pricing data.
- Updated main processing logic in index.ts to incorporate sellability checks before fetching pricing.
- Modified LLM analysis to account for sellability status and reasons.
- Created a new sp-test.ts script for testing SP-API connectivity and sellability.
- Updated types.ts to define SellabilityInfo and extend SpApiData.
- Enhanced result reporting in writer.ts to include sellability information.
- Add README.md with installation and usage instructions.
- Create bun.lock for dependency management.
- Add package.json to define project metadata and dependencies.
- Implement caching with Redis in cache.ts for ASIN data.
- Configure environment variables in config.ts for API keys and Redis URL.
- Develop main application logic in index.ts to read products, fetch data, and analyze results.
- Integrate Keepa API for product data retrieval in keepa.ts.
- Create LLM analysis functionality in llm.ts for product viability assessment.
- Implement product reading from Excel files in reader.ts.
- Stub SP-API integration in sp-api.ts for future implementation.
- Define TypeScript types in types.ts for product and analysis data structures.
- Write results to console and CSV in writer.ts.
- Configure TypeScript settings in tsconfig.json for project compilation.
