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[GH-ISSUE #1877] [BUG]: Can not save & embed files in workspace with name containing "+" #1224

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opened 2026-02-22 18:23:47 -05:00 by yindo · 2 comments
yindo commented 2026-02-22 18:23:47 -05:00
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Originally created by @paul-sonnenschein on GitHub (Jul 16, 2024).
Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/1877

Originally assigned to: @timothycarambat on GitHub.

How are you running AnythingLLM?

Docker (remote machine)

What happened?

AnythingLLM is setup using Docker compose, using a LocalAI LLM backend, LanceDB vector database and the built-in embedder.

Creating a new workspace containing the letter "+" works without any error. However attempting to "Save & Embed" an uploaded file results in an error message instead of a successful embedding. Attempting to embed in a workspace not containing the letter "+" reports success.

Expected behavior:

Either the workspace creating fails with a suitable error message indicating the unsupported character or a supported table name is selected automatically.

Error message + Log output:

Error message:

Invalid table name ("test+test"): Table names can only contain alphanumeric characters, underscores, hyphens, and periods

Log excerpt:

[backend] info: Adding new vectorized document into namespace
[backend] info: Cached vectorized results of custom-documents/Not-emtpy.txt-f6ee5465-6e12-44b3-9309-466ab7b39d5e.json found! Using cached data to save on embed costs.
[backend] error: addDocumentToNamespace
[backend] error: Failed to vectorize
[backend] info: [Event Logged] - workspace_documents_added

Are there known steps to reproduce?

  1. Setup AnythingLLM
  2. Create a workspace with an appropiate name, e.g. "Test+Test".
  3. Upload a non-empty file.
  4. Select "Move to workspace"
  5. Press Save and Embed
Originally created by @paul-sonnenschein on GitHub (Jul 16, 2024). Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/1877 Originally assigned to: @timothycarambat on GitHub. ### How are you running AnythingLLM? Docker (remote machine) ### What happened? AnythingLLM is setup using Docker compose, using a LocalAI LLM backend, LanceDB vector database and the built-in embedder. Creating a new workspace containing the letter "`+`" works without any error. However attempting to "Save & Embed" an uploaded file results in an error message instead of a successful embedding. Attempting to embed in a workspace not containing the letter "`+`" reports success. #### Expected behavior: Either the workspace creating fails with a suitable error message indicating the unsupported character or a supported table name is selected automatically. #### Error message + Log output: Error message: ``` Invalid table name ("test+test"): Table names can only contain alphanumeric characters, underscores, hyphens, and periods ``` Log excerpt: ``` [backend] info: Adding new vectorized document into namespace [backend] info: Cached vectorized results of custom-documents/Not-emtpy.txt-f6ee5465-6e12-44b3-9309-466ab7b39d5e.json found! Using cached data to save on embed costs. [backend] error: addDocumentToNamespace [backend] error: Failed to vectorize [backend] info: [Event Logged] - workspace_documents_added ``` ### Are there known steps to reproduce? 1. Setup AnythingLLM 2. Create a workspace with an appropiate name, e.g. "`Test+Test`". 3. Upload a non-empty file. 4. Select "Move to workspace" 5. Press Save and Embed
yindo added the possible buginvestigating labels 2026-02-22 18:23:47 -05:00
yindo closed this issue 2026-02-22 18:23:47 -05:00
yindo commented 2026-02-22 18:23:47 -05:00
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@CLBarajas commented on GitHub (Jul 17, 2024):

I think this can also affect transcripts pulled from the YouTube data connector, if the video title includes a "+" character.

@CLBarajas commented on GitHub (Jul 17, 2024): I think this can also affect transcripts pulled from the YouTube data connector, if the video title includes a "+" character.
yindo commented 2026-02-22 18:23:47 -05:00
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@vincenthaney commented on GitHub (Jul 18, 2024):

Hey! I am still experiencing this issue. I am executing exactly the same steps above.

I tried with .TXT and .PDF files.

I get a warning from LanceDB: invalid ENV settings.

Here is the env file:
`# Auto-dump ENV from system call on 17:27:25 GMT+0000 (Coordinated Universal Time)
LLM_PROVIDER='ollama'
EMBEDDING_MODEL_PREF='nomic-embed-text:latest'
OLLAMA_BASE_PATH='http://host.docker.internal:11434'
OLLAMA_MODEL_PREF='llama3'
OLLAMA_MODEL_TOKEN_LIMIT='4096'
EMBEDDING_BASE_PATH='http://host.docker.internal:11434'
EMBEDDING_MODEL_MAX_CHUNK_LENGTH='8192'
STORAGE_DIR='/app/server/storage'
SERVER_PORT='3001'
SIG_KEY=
SIG_SALT=

Please note that Ollama is working properly.

Here's the log from the server:
`[backend] info: [EncryptionManager] Loaded existing key & salt for encrypting arbitrary data.
[collector] info: -- Working New Text Document (2).txt --
[collector] info: [SUCCESS]: New Text Document (2).txt converted & ready for embedding.

[backend] info: [CollectorApi] Document New Text Document (2).txt uploaded processed and successfully. It is now available in documents.
[backend] info: [TELEMETRY SENT]
[backend] info: [Event Logged] - document_uploaded
[backend] info: Adding new vectorized document into namespace
[backend] info: [NativeEmbedder] Initialized
[backend] info: [RecursiveSplitter] Will split with
[backend] info: Chunks created from document:
[backend] info: [NativeEmbedder] Embedded Chunk 1 of 4
[backend] info: [NativeEmbedder] Embedded Chunk 2 of 4
[backend] info: [NativeEmbedder] Embedded Chunk 3 of 4
[backend] info: [NativeEmbedder] Embedded Chunk 4 of 4
[backend] info: Inserting vectorized chunks into LanceDB collection.
[backend] error: addDocumentToNamespace
[backend] error: Failed to vectorize
[backend] info: [TELEMETRY SENT]
[backend] info: [Event Logged] - workspace_documents_added`

Please let me know if you find a fix for this! Thanks

@vincenthaney commented on GitHub (Jul 18, 2024): Hey! I am still experiencing this issue. I am executing exactly the same steps above. I tried with .TXT and .PDF files. I get a warning from LanceDB: invalid ENV settings. Here is the env file: `# Auto-dump ENV from system call on 17:27:25 GMT+0000 (Coordinated Universal Time) LLM_PROVIDER='ollama' EMBEDDING_MODEL_PREF='nomic-embed-text:latest' OLLAMA_BASE_PATH='http://host.docker.internal:11434' OLLAMA_MODEL_PREF='llama3' OLLAMA_MODEL_TOKEN_LIMIT='4096' EMBEDDING_BASE_PATH='http://host.docker.internal:11434' EMBEDDING_MODEL_MAX_CHUNK_LENGTH='8192' STORAGE_DIR='/app/server/storage' SERVER_PORT='3001' SIG_KEY=<automatically provided key> SIG_SALT=<automatically provided salt> Please note that Ollama is working properly. Here's the log from the server: `[backend] info: [EncryptionManager] Loaded existing key & salt for encrypting arbitrary data. [collector] info: -- Working New Text Document (2).txt -- [collector] info: [SUCCESS]: New Text Document (2).txt converted & ready for embedding. [backend] info: [CollectorApi] Document New Text Document (2).txt uploaded processed and successfully. It is now available in documents. [backend] info: [TELEMETRY SENT] [backend] info: [Event Logged] - document_uploaded [backend] info: Adding new vectorized document into namespace [backend] info: [NativeEmbedder] Initialized [backend] info: [RecursiveSplitter] Will split with [backend] info: Chunks created from document: [backend] info: [NativeEmbedder] Embedded Chunk 1 of 4 [backend] info: [NativeEmbedder] Embedded Chunk 2 of 4 [backend] info: [NativeEmbedder] Embedded Chunk 3 of 4 [backend] info: [NativeEmbedder] Embedded Chunk 4 of 4 [backend] info: Inserting vectorized chunks into LanceDB collection. [backend] error: addDocumentToNamespace [backend] error: Failed to vectorize [backend] info: [TELEMETRY SENT] [backend] info: [Event Logged] - workspace_documents_added` Please let me know if you find a fix for this! Thanks
yindo changed title from [BUG]: Can not save & embed files in workspace with name containing "+" to [GH-ISSUE #1877] [BUG]: Can not save & embed files in workspace with name containing "+" 2026-06-05 14:39:36 -04:00
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Reference: Mintplex-Labs/anything-llm#1224
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