Functional prototype by Santhosh-p653 · Pull Request #17 · interviewstreet/hackerrank-orchestrate-august26

Santhosh-p653 · 2026-08-02T07:21:57Z

Changes Implemented

Data Processing Layer

Added dataset loading support for:

Messages
Users
Groups
Group members
Business accounts
User business history
Message history
Message events
Images
Voice notes
Notification summaries
Sample messages

Context Building

Implemented MessageContext to enrich messages with:

User information
Group information
Business information
Historical interactions
Message events
Media context
Notification behavior
Business relationship history

Media handling is integrated directly into the context layer.

Retrieval System

Implemented similarity-based retrieval using rapidfuzz.

The retriever:

Searches historical examples
Finds similar messages
Provides evidence message IDs for explainability

Analyzer Modules

Added specialized analyzers:

Safety Analyzer
Priority Analyzer
Personalization Analyzer
Notification Load Analyzer
Message Type Analyzer
Business Analyzer
Group Analyzer
Media Analyzer

Each analyzer produces independent signals consumed by the decision engine.

Decision Engine

Implemented weighted scoring-based routing.

Signals considered:

Notify

Message priority
User personalization
Group relevance
Business relevance
Notification load
Media importance
Safety penalty

Mute

Safety risk
Low relevance
Low business importance

Digest

Notification balancing

The highest scoring action is selected as the final prediction.

Output Generation

Added centralized OutputGenerator.

Generated output:
dataset/output.csv

Testing

Added and validated automated tests.

Verified:

Output file generation
Required columns
Valid actions
Prediction generation for all messages

Final status:

✅ All tests passing
✅ Output generated successfully
✅ Submission format validated

Future Improvements

Potential enhancements:

Replace fuzzy retrieval with embedding-based semantic search
Add LLM-based reasoning agents
Introduce feedback-based learning
Add real-time message streaming support
Improve confidence calibration using ML models

Validation

The implementation successfully generates routing predictions for the complete dataset and produces explainable decisions with confidence scores and supporting evidence.

Santhosh-p653 added 30 commits August 2, 2026 09:03

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Santhosh-p653 added 30 commits August 2, 2026 10:00

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Functional prototype - #17

Functional prototype#17
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Santhosh-p653 commented Aug 2, 2026

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Santhosh-p653 commented Aug 2, 2026

Changes Implemented

Data Processing Layer

Context Building

Retrieval System

Analyzer Modules

Decision Engine

Notify

Mute

Digest

Output Generation

Testing

Future Improvements

Validation

Uh oh!

Reviewers

Assignees

Labels

Milestone

Development

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1 participant