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Remove evaluation scripts and sample data for MentorMe recommendation system
Doanh Van Vu- Deleted `evaluate_recommendations.py`, `evaluation_report.md`, `sample_mentee_evaluation.json`, `sample_mentor_upsert.json`, and related JSON files for unique careers, domains, and skills to streamline the project structure. - This cleanup aligns with recent refactoring efforts and focuses on maintaining only essential components for the recommendation system.5d75507
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Enhance logging for scoring and reranking processes
Doanh Van Vu- Added detailed logging in `reranker_service.py` to report the ranking of candidates, including mentor ID, rating, and scores. - Improved logging in `scoring.py` to provide insights into the final ranking of mentors, including their scores and applied weights, enhancing traceability and debugging capabilities.3c1cd35
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Enhance RecommendationRequest model and mentee query text generation
Doanh Van Vu- Added new optional fields to the RecommendationRequest model: `career_name`, `domain_names`, `mentor_domain_names`, and `skill_names` for improved data representation. - Updated the `build_mentee_query_text` function to utilize the new fields, enhancing the clarity of the generated text by including career names and domain names instead of just IDs.a4869e5
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Refactor recommendation request and mentee query text handling
Doanh Van Vu- Updated the RecommendationRequest model to remove unnecessary fields and added `mentor_domain_ids` and `career_id` for improved data structure. - Modified the `build_mentee_query_text` function to reflect changes in the mentee data structure, enhancing clarity by including `career_id`, `domain_ids`, and `mentor_domain_ids` while removing references to `desired_skills`, `current_skills`, and `interests`.71703c8 -
Remove ScheduleDto and related availability fields from models and text builder
Doanh Van Vu- Deleted the ScheduleDto class and its references from the MentorUpsertRequest and RecommendationRequest models, simplifying the data structure. - Updated the text building functions to exclude availability-related information, enhancing clarity in mentor and mentee summaries. - This change aligns with recent refactoring efforts to streamline mentor availability handling.769cb8f -
Refactor mentor availability handling across services
Doanh Van Vu- Removed the `available_slots` and `has_availability` fields from the MentorUpsertRequest and RecommendationRequest models, streamlining the data structure. - Updated the PineconeService and RecommendationService to eliminate references to availability metrics in logging and processing. - Simplified scoring logic in the rerank_mentors function by removing the availability score calculation, enhancing performance and clarity. - Adjusted the mentor text building process to exclude available slots information, improving the output format.69934b0 -
Add test for recommend mentors endpoint and enhance logging in services
Doanh Van Vu- Introduced a new test script `test_api.py` to validate the recommend mentors API endpoint. - Enhanced logging in `embedding_service.py`, `pinecone_service.py`, `recommendation_service.py`, `reranker_service.py`, and `scoring.py` to include timing information for various operations, improving traceability and performance monitoring. - Improved error handling and logging messages for better clarity and debugging support.6a14fa9 -
Initial commit of the MentorMe AI Recommendation Server, including core application structure, environment configuration, Docker setup, and essential services for mentor recommendations and health checks.
Doanh Van Vu1904012