Weekly Research Progress Report

Week 27, 2025 (July 15 - July 21)

RNA Lab Navigator Local Deployment DEPLOYED

Status: Successfully deployed RNA Lab Navigator on local MacBook server and made accessible to lab members via institute network.

Component Progress Details
Local Server Setup
100%

MacBook Local Server Configuration:

Server Access Points:
  • Local: http://localhost:3000
  • Network: http://192.168.41.91:3000

Docker Architecture:

  • Frontend container (rna-lab-frontend)
  • Backend container (rna-lab-django)
  • PostgreSQL database (rna_postgres)
  • Weaviate vector database (rna_weaviate)
  • Redis container (rna_redis)

Management: Using GNU Screen sessions for persistent operation

Data Ingestion
100%

Research Documents Ingested:

  • ✅ 7 PhD theses successfully processed
  • ✅ 18 research papers indexed
  • ✅ Total documents: 25
RAG-LLM System Features:
  • Document chunking and embedding generation
  • Vector search using Weaviate
  • Question-answering with citations
  • Cross-document information retrieval
Beta Testing Status
50%

Current Status:

  • ✅ System deployed and accessible on institute network
  • ✅ Access details shared with lab members
  • ⏳ Awaiting user feedback
Note: Beta testing has been initiated. Lab members have been provided access to the system. Feedback collection is pending.
Network Configuration
100%

Institute Network Setup:

  • ✅ System accessible within institute network (192.168.41.x)
  • ✅ Port 3000 configured for access
  • ✅ Running from personal MacBook as server

Weekly Summary & Next Steps

This week focused on deploying the RNA Lab Navigator locally and making it accessible to lab members for testing. The system is now live on the institute network.

Key Accomplishments:

Immediate Next Steps:

  1. Monitor system performance and stability
  2. Collect feedback from lab members once they start using the system
  3. Address any technical issues that arise during usage
  4. Document user experiences and improvement suggestions

The RNA Lab Navigator is now deployed and ready for evaluation by lab members. The focus for the coming weeks will be on gathering user feedback and iterating based on real-world usage.

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