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[GH-ISSUE #5000] [FEAT]: Support GPT4All-style LocalDocs RAG with one-click indexing of multiple folders and all nested directories. #3139

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opened 2026-02-22 18:32:46 -05:00 by yindo · 3 comments
yindo commented 2026-02-22 18:32:46 -05:00
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Originally created by @TheAlex25 on GitHub (Feb 13, 2026).
Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/5000

What would you like to see?

Feature Request: LocalDocs-Style RAG with One-Click Multi-Folder Indexing in AnythingLLM

Title:
Support GPT4All-style LocalDocs RAG with one-click indexing of multiple folders and all nested directories.

Summary:
Add a LocalDocs-equivalent retrieval-augmented generation (RAG) feature to AnythingLLM that allows users to select one or more folders — including nested subfolders — from the operating system file explorer (Windows Explorer, macOS Finder, Ubuntu Files) and index them for semantic search and contextual retrieval in a single action. This would replace the current manual and clunky ingestion process.

Current Limitation:
AnythingLLM’s existing document ingestion for RAG requires manual uploads and repeated steps to add large collections or complex directory structures. There is no easy way to select entire folder trees at once for indexing.

Proposed Behavior:

  1. One-Click Folder Selection:
    Allow users to right-click one or multiple folders in the OS file explorer (Windows, macOS, Linux) and choose “Index with AnythingLLM LocalDocs” (or similar). This should recursively include all nested files and subfolders.

  2. Automatic Embedding and Vector Storage:
    Automatically process supported file formats (PDF, DOCX, TXT, MD, etc.), chunk content, generate embeddings, and store them in a local vector database without extra manual steps.

  3. Integrated Per-Query Retrieval:
    At runtime, automatically retrieve the most relevant document snippets from the indexed collection and include them in the prompt context.

  4. Source Transparency:
    Show clear source citations (file path and excerpt) for information used in responses.

Benefits:

  • Significantly simplifies ingestion of large document collections and complex directory structures.
  • Reduces friction for users with existing folder hierarchies.
  • Improves the RAG experience with transparent source attribution.

Success Criteria:

  • Users can select entire folder trees with one action in file explorer.
  • Indexing runs without repeated manual uploads.
  • Per-query retrieval is automatic and contextually relevant.
  • Responses include clear source references.

GPT4All's RAG Interface:

Image
Originally created by @TheAlex25 on GitHub (Feb 13, 2026). Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/5000 ### What would you like to see? ## Feature Request: LocalDocs-Style RAG with One-Click Multi-Folder Indexing in AnythingLLM **Title:** Support GPT4All-style LocalDocs RAG with one-click indexing of multiple folders and all nested directories. **Summary:** Add a LocalDocs-equivalent retrieval-augmented generation (RAG) feature to AnythingLLM that allows users to select one or more folders — including nested subfolders — from the operating system file explorer (Windows Explorer, macOS Finder, Ubuntu Files) and index them for semantic search and contextual retrieval in a single action. This would replace the current manual and clunky ingestion process. **Current Limitation:** AnythingLLM’s existing document ingestion for RAG requires manual uploads and repeated steps to add large collections or complex directory structures. There is no easy way to select entire folder trees at once for indexing. **Proposed Behavior:** 1. **One-Click Folder Selection:** Allow users to right-click one or multiple folders in the OS file explorer (Windows, macOS, Linux) and choose “Index with AnythingLLM LocalDocs” (or similar). This should recursively include all nested files and subfolders. 2. **Automatic Embedding and Vector Storage:** Automatically process supported file formats (PDF, DOCX, TXT, MD, etc.), chunk content, generate embeddings, and store them in a local vector database without extra manual steps. 3. **Integrated Per-Query Retrieval:** At runtime, automatically retrieve the most relevant document snippets from the indexed collection and include them in the prompt context. 4. **Source Transparency:** Show clear source citations (file path and excerpt) for information used in responses. **Benefits:** * Significantly simplifies ingestion of large document collections and complex directory structures. * Reduces friction for users with existing folder hierarchies. * Improves the RAG experience with transparent source attribution. **Success Criteria:** * Users can select entire folder trees with one action in file explorer. * Indexing runs without repeated manual uploads. * Per-query retrieval is automatic and contextually relevant. * Responses include clear source references. **GPT4All's RAG Interface:** <img width="1281" height="1456" alt="Image" src="https://github.com/user-attachments/assets/5d4e4b46-36a3-44f9-a0d7-5aa29d1b7c14" />
yindo added the enhancementfeature request labels 2026-02-22 18:32:46 -05:00
yindo changed title from [FEAT]: Support GPT4All-style LocalDocs RAG with one-click indexing of multiple folders and all nested directories. to [GH-ISSUE #5000] [FEAT]: Support GPT4All-style LocalDocs RAG with one-click indexing of multiple folders and all nested directories. 2026-06-05 14:50:30 -04:00
yindo commented 2026-06-05 14:50:31 -04:00
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@TheAlex25 commented on GitHub (Mar 13, 2026):

Good afternoon, @timothycarambat . Are there plans to add this feature? This is the only thing holding me back from using AnythingLLM. Also, in the very near future, I may begin helping individuals set up local LLMs, and the limitations of AnythingLLM when it comes to RAG is not the best.

<!-- gh-comment-id:4059124608 --> @TheAlex25 commented on GitHub (Mar 13, 2026): Good afternoon, @timothycarambat . Are there plans to add this feature? This is the only thing holding me back from using AnythingLLM. Also, in the very near future, I may begin helping individuals set up local LLMs, and the limitations of AnythingLLM when it comes to RAG is not the best.
yindo commented 2026-06-05 14:50:31 -04:00
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@timothycarambat commented on GitHub (Mar 16, 2026):

Linking #3561

<!-- gh-comment-id:4068680497 --> @timothycarambat commented on GitHub (Mar 16, 2026): Linking #3561
yindo commented 2026-06-05 14:50:31 -04:00
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@bulrush15 commented on GitHub (May 8, 2026):

Please do not force ALLM to get all files recursively, this is bad during the testing phase with 1000+ files. Have an option to recurse and add all files, the default is off (when a user is doing testing). Or have a limit of getting the first N files during testing, like the first 5 files. Then during testing I could change to 10. And when testing is done I could change "Limit number of files" to 0 which means get them all.

<!-- gh-comment-id:4405891018 --> @bulrush15 commented on GitHub (May 8, 2026): Please do not force ALLM to get all files recursively, this is bad during the testing phase with 1000+ files. Have an option to recurse and add all files, the default is off (when a user is doing testing). Or have a limit of getting the first N files during testing, like the first 5 files. Then during testing I could change to 10. And when testing is done I could change "Limit number of files" to 0 which means get them all.
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Reference: Mintplex-Labs/anything-llm#3139
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