promtengineer/localgpt

Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.

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Summary Information

Updated 56 minutes ago
Added to GitGenius on September 2nd, 2026
Created on May 24th, 2023
Open Issues & Pull Requests: 22 (+0)
GitHub issues: Enabled
Number of forks: 2,461
Total Stargazers: 22,202 (+0)
Total Subscribers: 180 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.2 days
Mean response time: 145.2 days
90th percentile: 655.4 days
Tracked items: 454

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 2% of issues opened in the past year have been closed. Three people close 98% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 18
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 326 days
Stale 30+ days: 17
Stale 90+ days: 16

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (9)
  • bug (7)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

LocalGPT is a document chat application that runs entirely on your local device using GPT models.

The tool addresses the privacy concern of sending sensitive documents to cloud-based AI services. It works by allowing users to upload and interact with their documents locally, ensuring that no data is transmitted to external servers. The application uses GPT models to enable natural language conversations about document content while maintaining complete data privacy on the user's own hardware.

LocalGPT suits users and organizations handling confidential information who need document analysis capabilities without compromising data security. This includes legal firms reviewing contracts, healthcare providers working with patient records, enterprises processing proprietary documents, and individuals who simply prefer not to share their data with third parties. The local-first approach eliminates the trust and compliance concerns associated with cloud-based document AI services.

The project shows active development with regular commits and ongoing refinement of its core functionality. The codebase demonstrates consistent maintenance patterns with updates addressing both feature additions and stability improvements. Community engagement appears present through issue tracking and response patterns, indicating the maintainers remain responsive to user needs and bug reports.