xming521/WeClone

πŸš€ One-stop solution for creating your AI twin from chat history πŸ’‘ Fine-tune LLMs with your chat logs to capture your unique style, then bind to a chatbot...

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xming521/WeClone has 18k+ stars and 1.5k+ forks on GitHub, is written in Python, and was last pushed on Oct 9, 2026. Data as of . Signed-in members get hourly updates β€” create a free account.

Summary Information

Updated 8 minutes ago
Added to GitGenius on September 3rd, 2026
Created on January 31st, 2024
Open Issues & Pull Requests: 35 (+0)
GitHub issues: Enabled
Number of forks: 1,607
Total Stargazers: 18,303 (+0)
Total Subscribers: 83 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.9 hours
Mean response time: 19.2 days
90th percentile: 19.4 days
Tracked items: 111

How this project is maintained

67% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Three people close 73% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 27
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 439 days
Stale 30+ days: 26
Stale 90+ days: 24

Recent activity

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

Top labels

  • bug (27)
  • feature (25)
  • question (14)
  • good first issue (7)
  • documentation (6)
  • Windows (5)
  • Discussion (2)
  • Mac (2)

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Detailed Description

WeClone is a tool for creating AI digital avatars by fine-tuning language models with your chat history.

The tool addresses the problem of capturing someone's unique communication style and personality in a conversational AI system. It works by extracting chat data from messaging platforms, preprocessing that data to filter sensitive information, fine-tuning a language model on the processed conversations, and then deploying the resulting model as a chatbot. The approach keeps data processing and model training localized for privacy control, and supports multimodal input including images alongside text from chat logs.

WeClone suits anyone wanting to create a personalized chatbot that mimics their own conversational patterns or those of someone else. It works best for users with substantial chat history on supported platforms and who prioritize data privacy through local processing. The tool currently supports Telegram as a data source with image modal support, while WhatsApp, Discord, and Slack integrations are in development. The project includes end-to-end functionality spanning data export, preprocessing, model training, and deployment, distinguishing it from solutions that handle only individual stages of this pipeline.

The project receives issues from both core maintainers and external users, indicating real adoption beyond the development team without an overwhelming support burden. Maintainers typically respond to new issues and pull requests within hours. Work tracked in the issue system centers on bug fixes, feature requests, and user questions.