Upload Files as Text

Ever wanted to hand a PDF, a code file, or a spreadsheet to the AI and just say "read this"? LibreChat's unified uploader routes the file to the provider or extracts its text automatically based on its type and the selected endpoint.

You attach a file, LibreChat extracts the text from it, and the full content gets pasted straight into your conversation. The AI can then read every word of it — no plugins, no vector databases, no extra services to configure. It works out of the box.

How to use it

When you select several files, LibreChat skips individual duplicates and files over the per-file size limit, names the skipped files in a notice, and continues uploading the valid files. The file-count and total-batch-size limits still apply to the files that remain; if the surviving batch exceeds either limit, the batch is rejected together. Single-file behavior is unchanged.

Paste long text as a file

In the normal message composer, LibreChat can turn a paste longer than 2,500 characters into an Upload as Text attachment. This keeps a large paste out of the input while still providing its contents to the model through the conversation context. The first attachment is named pasted-text.txt; additional pasted-text attachments receive numbered names.

The browser-local Paste long text as a file setting is enabled by default under Settings > Chat > Sending. Shorter pastes and text pasted while answering an Agent's Ask User form remain inline. If context uploads are unavailable, the text also remains inline. If an attachment upload fails, LibreChat restores the text to the composer when it can do so without overwriting a newer draft.

Pasted-text attachments follow the same file-size, token, and fileTokenLimit rules as other Upload as Text files.

What happens under the hood

When an upload is routed to text, LibreChat doesn't dump raw bytes into the prompt. It runs through a processing pipeline to extract clean, readable text:

1. MIME type detection — LibreChat checks what kind of file you uploaded (PDF, image, audio, source code, etc.) by inspecting its MIME type.
2. Method selection — Based on the file type and what services are available, it picks the best extraction method using this priority:

3. Token truncation — The extracted text is trimmed to the fileTokenLimit (default: 100,000 tokens) so it doesn't blow past the model's context window.
4. Prompt injection — The text gets included in the conversation context, right alongside your message.

When you preview or download an Upload as Text attachment, LibreChat serves the extracted text stored with the file record. Downloads use a .txt filename even when OCR or another parser produced the stored text and there is no original backing file to stream.

Which files are supported

LibreChat normalizes shell-script MIME variants reported by Chrome on Linux (application/x-shellscript) and libmagic (text/x-shellscript) to the canonical application/x-sh before checking the endpoint allowlist. Custom supportedMimeTypes rules must still permit application/x-sh.

Unified uploads and tool provisioning

By default, one attachment action replaces the old destination chooser. LibreChat decides how the file reaches the model, while tools are provisioned lazily:

Operators can restore the earlier destination chooser with fileConfig.legacyFileUploadUX, or control automatic routing with defaultLLMDeliveryPath.

Typical routing:

The context capability

Under the hood, Upload as Text is powered by the context capability. This is what controls whether the feature appears in your chat UI.

endpoints:
  agents:
    capabilities:
      - "context"  # This is what enables "Upload as Text"

The same context capability also powers Agent File Context (uploading files through the Agent Builder to embed text into an agent's system instructions). The difference is where the text ends up:

Token limits and truncation

When a file is too long to fit in the model's context window, LibreChat truncates the extracted text to stay within bounds. This happens automatically — you don't need to worry about it, but it's good to know how it works.

fileConfig:
  fileTokenLimit: 100000  # Default: 100,000 tokens

Rules of thumb:

• 100k tokens ≈ a 300-page book (plenty for most use cases)
• If you're working with very large files, consider File Search (RAG) instead — it only retrieves the relevant sections rather than stuffing everything into context

Optional: boosting extraction with OCR

Text parsing works fine for digitally-created documents (PDFs saved from Word, code files, plain text). But if you're uploading scanned documents, photos of pages, or images with text, the built-in parser won't get great results.

That's where OCR comes in. When configured, LibreChat automatically uses OCR for file types that benefit from it — you don't need to do anything differently as a user.

File handling configuration reference

This section is for admins who want to control which file types get processed by which method. The defaults work well — you only need to touch this if you want to fine-tune behavior.

Troubleshooting

Related

• OCR for Documents — Set up optical character recognition for images and scans
• RAG API (Chat with Files) — Semantic search over large document collections
• Agents — File Context — Embed file content into an agent's system instructions
• File Config reference — Full YAML schema for file handling