AI Analysis integration & JOSS Updates #47
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…odule - Add proper error handling for missing status files - Fix Python f-string formatting - Improve file reading logic for better reliability
… between processes
docs: update README with AI analysis details and contribution guidelines - Clarify that AI analysis is optional and requires Synapse agent ID - Add specific Synapse agent ID (LOWYSX3QSQ) in examples - Reorder output files to highlight AI analysis as final report - Add note about AI analysis providing qualitative summary - Update output file descriptions to clarify metrics vs summary - Add reference to new CONTRIBUTING.md file
- Rename SynapseAnalysis process to AIAnalysis for clarity - Update module include statement to use new AIAnalysis module - Remove Generate Report - Update workflow documentation to reflect AI analysis step - Add debug print statement for AI input tuple - Keep Synapse agent ID requirement for AI analysis - Maintain existing workflow structure and data flow
Create new AIAnalysis.nf module that: - Uses Synapse agent to analyze repository quality - Takes Almanack and JOSS results as input - Generates qualitative analysis and recommendations - Includes timeout handling (600s) for long-running analyses - Provides detailed error handling and logging - Outputs results in JSON format with repository-specific naming The module integrates with Synapse's AI capabilities to provide: - High-level summary of repository strengths and weaknesses - Prioritized recommendations for improvement - JOSS readiness assessment - Specific action items for repository enhancement
- Add support for both JSON and CSV input formats - Implement comprehensive README content analysis - Add detailed dependency management assessment - Improve test coverage evaluation - Add scoring system for JOSS criteria - Enhance error handling and logging - Add support for multiple programming languages - Implement detailed status reporting with improvement suggestions Key improvements: - Better handling of different input formats - More thorough analysis of repository documentation - Enhanced dependency checking across multiple languages - Improved test result parsing and scoring - Better error handling and reporting
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@BWMac thank you for the suggestions! Ready for review again 🫡 |
BWMac
reviewed
May 27, 2025
Co-authored-by: Brad Macdonald <[email protected]>
Co-authored-by: Brad Macdonald <[email protected]>
Co-authored-by: Brad Macdonald <[email protected]>
If you script is executable and in the bin directory it is on the PATH for Nextflow Co-authored-by: Brad Macdonald <[email protected]>
Co-authored-by: Brad Macdonald <[email protected]>
Co-authored-by: Brad Macdonald <[email protected]>
Co-authored-by: Brad Macdonald <[email protected]>
- files are directly on the path for Nextflow if in bin
BWMac
approved these changes
May 27, 2025
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AI Analysis (Fixes #40, #41)
This is done by using AWS Bedrock and Synapse integration. The implementation includes a custom AWS Bedrock agent, hosted as a Synapse agent, which interacts with the Synapse Python client using the Agent class. This approach skips the need for direct API tokens, however the user would still need a Synapse account + PAT to use this feature, instructions in README.
Key Features
cc-toolkit-agent, provides a summary report in HTML format, offering detailed insights into repository analysis.README Enhancements (Fixes #26)
Key Changes
input.csvin a table/markdown format for better understanding.JOSS Analysis & Testing (Fixes #14)
Key Features
Captured in JOSSAnalysis.nf:
Configuring CODEOWNERS (Fixes #43)