arc53/docsgpt

Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API...

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Summary Information

Updated 21 minutes ago
Added to GitGenius on September 3rd, 2026
Created on February 2nd, 2023
Open Issues & Pull Requests: 137 (+0)
GitHub issues: Enabled
Number of forks: 2,144
Total Stargazers: 18,245 (+1)
Total Subscribers: 103 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 7.4 hours
Mean response time: 19.6 days
90th percentile: 29.0 days
Tracked items: 320

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 95% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "frontend" is answered fastest, typically in about 2 hours, while "application" waits about 4 days. Only 6% of issues opened in the past year have been closed. Three people close 95% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 22
New in 7 days: 0
Closed in 7 days: 1
Avg open age: 200 days
Stale 30+ days: 15
Stale 90+ days: 7

Recent activity

Opened in 7 days: 0
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • help wanted (78)
  • frontend (76)
  • hacktoberfest (72)
  • javascript (50)
  • backend (45)
  • enhancement (42)
  • python (41)
  • application (39)

Detailed Description

DocsGPT is an open-source AI platform for building intelligent agents and assistants that process documents and enable enterprise search through natural language interaction.

The tool addresses the challenge of extracting actionable insights from diverse document formats and data sources. It ingests PDFs, Office documents, web content, audio files, and data from URLs and web crawlers, then uses retrieval-augmented generation to answer questions with source citations. Users can build custom agents through a built-in Agent Builder, connect to external APIs and tools to enable agent actions, and choose their language model provider or run models locally for complete privacy control.

Organizations should consider this tool if they need to make internal documentation searchable and queryable through conversational interfaces, or if they want to build AI agents with access to proprietary knowledge bases. It suits teams that require deployment flexibility—whether on-premises, in Kubernetes clusters, or in the cloud—and those concerned with data privacy. The platform supports multiple language model providers including OpenAI, Google, and Anthropic, as well as local alternatives like Ollama, giving adopters control over their inference infrastructure.

The project maintains a substantial user base reporting real-world issues, with almost all open issues raised by outside users rather than the core team. Maintainers typically respond to new issues and pull requests within a day. Work in the issue tracker is dominated by frontend, Hacktoberfest, and JavaScript-related tasks.