ChatFiles
by Community
Document Chatbot — multiple files. Powered by GPT / Embedding.
OSS
ChatFiles
Added 1 June 2026
Overview
ChatFiles is an open-source document chatbot that allows users to upload multiple files and query them using GPT and embedding models. It processes and indexes documents to enable conversational retrieval of information across uploaded content.
Best for
Best for
Developers needing a simple, customizable tool for document-based question answering
Use cases
- Extract answers from multiple uploaded PDFs or text documents
- Build a conversational interface for document-based Q&A
- Prototype retrieval-augmented generation workflows
Notes
ChatFiles is an open-source document chatbot that allows users to upload multiple files and query them using GPT and embedding models. It processes and indexes documents to enable conversational retrieval of information across uploaded content.
3,349 stars on GitHub. Last updated 2024-12-17. Licensed MIT.
Use cases
- Extract answers from multiple uploaded PDFs or text documents
- Build a conversational interface for document-based Q&A
- Prototype retrieval-augmented generation workflows
Pros
- Free and open-source with TypeScript codebase for easy customization
- Supports multiple file uploads simultaneously for broader context
- Leverages GPT and embedding models for accurate retrieval
Cons
- Requires self-hosting and API keys for underlying models
- No built-in support for non-text file types like images or spreadsheets
- Community-maintained with limited documentation compared to commercial alternatives
Indexed from awesome-langchain and enriched against its public facts.
Pros
- Free and open-source with TypeScript codebase for easy customization
- Supports multiple file uploads simultaneously for broader context
- Leverages GPT and embedding models for accurate retrieval
Cons
- Requires self-hosting and API keys for underlying models
- No built-in support for non-text file types like images or spreadsheets
- Community-maintained with limited documentation compared to commercial alternatives
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