Pre-GSoC: Multi-Dimensional Location-Proximity Framework with Docs, Code Stubs & Tests#85
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…tation, code stubs, and tests This PR establishes the foundation for multi-dimensional location-proximity analysis in DREAMS, building upon existing EXIF extraction (PR KathiraveluLab#77) and emotion proximity (PR KathiraveluLab#70). ## Documentation (9 new/updated files) - docs/api_design.md: REST API specification for location-proximity endpoints - docs/evaluation_metrics.md: Quantitative metrics and ablation study plan - docs/exif_extraction_research.md: Library comparison research (informed PR KathiraveluLab#77) - docs/integration_guide.md: Step-by-step integration instructions - docs/project_roadmap.md: GSoC 2026 timeline aligned with official dates (350h) - docs/risk_analysis.md: Risk matrix and mitigation strategies - docs/TEST_PLAN.md: Extended with 50+ location-proximity test cases - plans/pre_gsoc_contribution_plan.md: 7-week, 18-PR contribution roadmap - dreamsApp/docs/data-model.md: Added location_analysis and emotion_location_entries collections ## Code Implementation - dreamsApp/exif_extractor.py: NEW - Complete EXIF extraction with dual-library fallback - dreamsApp/location_proximity.py: Updated stubs with EXIFExtractor integration - ARCHITECTURE.md: Updated diagram to show integration with PR KathiraveluLab#77 and KathiraveluLab#70 - LOCATION_PROXIMITY_SUMMARY.md: Added acknowledgment of existing work ## Tests - tests/test_exif_extraction.py: NEW - Unit tests for EXIF extractor with mocking ## Code Quality - Removed emojis from entire project (8 files) for professional documentation - data_integrity/reporter.py: Replaced emoji indicators with text - dream-integration/app/templates/index.html: Replaced emoji UI elements - dreamsApp/app/dashboard/main.py: Removed emoji comments ## Integration Points - Builds upon PR KathiraveluLab#77 (kunal-595): Uses existing EXIFExtractor class - Complements PR KathiraveluLab#70 (AnvayKharb): Adds spatial proximity to time-aware emotion analysis - Aligns with PR KathiraveluLab#79 (anish1206): Emotion-location work supports CHIME framework ## Key Features - Multi-dimensional proximity: geographic + categorical + linguistic + cultural - Emotion-location hotspot detection - Semantic clustering with DBSCAN - MongoDB schema extensions for location data - Performance benchmarks and evaluation framework Total: 10 new files, 9 updated files, 350 hours planned for GSoC 2026 implementation
Summary of ChangesHello @KrishanYadav333, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request lays the groundwork for multi-dimensional location-proximity analysis in the DREAMS project, enabling semantic clustering and emotion-location pattern detection. It builds upon existing work in EXIF extraction and emotion proximity to provide a comprehensive framework for understanding the relationship between user emotions and their environment. The changes include documentation, code stubs, and tests, setting the stage for future GSoC development. Highlights
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Code Review
This pull request introduces a substantial amount of foundational work for a multi-dimensional location-proximity framework. The documentation is extensive and well-structured, covering API design, evaluation metrics, risk analysis, and a detailed project roadmap. The core code addition is the EXIFExtractor class, which robustly handles metadata extraction with a fallback mechanism, and is accompanied by a good set of unit tests. My review includes a few suggestions to improve the robustness and maintainability of the extractor implementation and points out a minor inconsistency in the test plan documentation. Overall, this is an excellent contribution that sets a clear path for the GSoC project.
| #### Test Case: PC-EC-003 | ||
| **Description**: Missing attribute handling | ||
| **Input**: Location with missing 'type' field |
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It looks like there's a duplicated test case definition here. Test Case: PC-EC-003 was updated earlier in the file (lines 252-256), but the old definition appears again at the end of this section. This seems to be a copy-paste error and should be removed to avoid confusion.
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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| **Version**: 1.0 | ||
| **Last Updated**: February 3, 2026 | ||
| **Author**: Krishan (GSoC 2026 Contributor) |
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This assumes the GSoC 2026 program acceptance. At this point, Google is yet to announce the accepted organization. Besides, it is not norm in open source organizations to have individual authors writing their names under the files they contribute. It is established through the commit history. Please remove the above text block, including version, last updated, and author.
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| **Plan Created**: December 2025 | ||
| **Total Estimated Effort**: 18 PRs across 7 weeks | ||
| **Primary Contributor**: Krishan (Pre-GSoC Contributor) No newline at end of file |
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Same here. Please avoid adding names to files. It is not norm in open source communities.
In general, the excessive md files may not be a good approach. Documents are great. But in the AI-slop era, people tend to ignore lengthy documents.
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I'll fix it rightaway.
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@KrishanYadav333 pls recreate the PR without extensive md documentation. Some of these md files should be moved to a GitHub discussion instead, where you can also include your name and updated time. The planning files shouldn't be in md files. You may be able to spot similar files in the Alaska repositories, and that simply means I (or whoever merged the PR) did not pay sufficient attention. |
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Thank you for the feedback, @pradeeban. I understand - I should have focused on technical contributions rather than extensive planning docs. |
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Summary
This pre-GSoC contribution establishes the foundation for multi-dimensional location-proximity analysis in DREAMS, enabling semantic clustering and emotion-location pattern detection for recovery journeys.
Building Upon:
dreamsApp/exif_extractor.pyOur Contribution: Multi-dimensional spatial proximity (geographic + categorical + linguistic + cultural) to complement existing time-aware emotion analysis.
What's Included
Documentation (9 files)
docs/api_design.md- REST API spec with 6 endpointsdocs/project_roadmap.md- GSoC 2026 timeline (May-Nov, 350h)docs/evaluation_metrics.md- Metrics & ablation study plandocs/integration_guide.md- Step-by-step integrationdocs/risk_analysis.md- 10 risks with mitigationsdocs/exif_extraction_research.md- Library comparisondocs/TEST_PLAN.md- Extended with 50+ test casesplans/pre_gsoc_contribution_plan.md- 7-week, 18-PR roadmapCode (3 files)
dreamsApp/exif_extractor.py- NEW: Complete EXIF extraction (173 lines)dreamsApp/location_proximity.py- Updated with EXIFExtractor integrationdreamsApp/docs/data-model.md- Added 2 MongoDB collectionsTests (2 files)
tests/test_exif_extraction.py- NEW: Unit tests with mockingdocs/TEST_PLAN.md- Location-proximity test casesKey Features
Integration Impact
New Capabilities:
Backward Compatible: All changes extend existing functionality without breaking current features.
Review Guide
docs/project_roadmap.mdfor overviewARCHITECTURE.mdfor integration pointsdreamsApp/exif_extractor.pyfor implementation qualitytests/test_exif_extraction.pyfor coveragedocs/integration_guide.mdfor impact assessmentEstimated review time: 2-3 hours
Type: Feature | Documentation | Tests