DocsGPT
by Community
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
OSS
DocsGPT
Added 1 June 2026
Overview
DocsGPT is an open-source AI platform for building agents and assistants that can search and analyze documents. It provides an Agent Builder, multi-model support, and API connectivity to enable custom workflows over private document collections.
Best for
Best for
Teams building internal document search and analysis tools who want open-source control and can manage their own infrastructure.
Use cases
- Building internal search assistants over proprietary documentation
- Creating agents that perform document analysis and research tasks
- Connecting multiple LLMs to document retrieval pipelines
Notes
DocsGPT is an open-source AI platform for building agents and assistants that can search and analyze documents. It provides an Agent Builder, multi-model support, and API connectivity to enable custom workflows over private document collections.
17,914 stars on GitHub. Last updated 2026-06-01. Licensed MIT.
Use cases
- Building internal search assistants over proprietary documentation
- Creating agents that perform document analysis and research tasks
- Connecting multiple LLMs to document retrieval pipelines
Pros
- Open-source with active community (17k+ stars)
- Built-in Agent Builder reduces custom orchestration work
- Multi-model support allows flexibility in LLM selection
Cons
- Community-maintained project with no commercial support guarantee
- Requires Python environment and self-hosting infrastructure
- Limited documentation on production deployment and scaling
Indexed from awesome-langchain and enriched against its public facts.
Pros
- Open-source with active community (17k+ stars)
- Built-in Agent Builder reduces custom orchestration work
- Multi-model support allows flexibility in LLM selection
Cons
- Community-maintained project with no commercial support guarantee
- Requires Python environment and self-hosting infrastructure
- Limited documentation on production deployment and scaling
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