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CLI-first knowledge ingestion

veryfront knowledge ingest is the primary CLI workflow for getting documents into a project’s knowledge base. It finds a source file, parses it, and writes generated markdown back into the project. Use one command for the standard path: 
veryfront knowledge ingest uploads/contracts/q1.pdf --json
That also works for an exact list of uploaded files: 
veryfront knowledge ingest uploads/contracts/a.pdf uploads/contracts/b.pdf uploads/contracts/c.pdf --json
The command handles the orchestration for you:
  • Resolves whether the input is a remote upload or a local file
  • Pulls remote uploads into the workspace when needed
  • Parses supported documents into markdown
  • Uses docling for supported PDF, Office, and HTML sources
  • Writes the resulting knowledge/*.md file back into the project

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Why this matters

This flow is especially useful for agent workflows and demos:
  • A user drops one or more files into uploads/
  • A knowledge agent starts a sandbox
  • The agent runs veryfront knowledge ingest ...
  • The parsed markdown lands in the project’s knowledge base
That keeps knowledge ingestion predictable, scriptable, and much easier to explain than ad-hoc parser scripts.

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Prerequisites

Authenticate with the CLI and make sure the target project is known: 
export VERYFRONT_API_TOKEN=<TOKEN>
export VERYFRONT_PROJECT_SLUG=my-project
Or log in interactively: 
veryfront login
veryfront knowledge ingest requires python3. Inside a Veryfront sandbox, docling and the fallback parser packages are already installed. The embedded parser uses docling first for PDF, Office, and HTML extraction. If you run the CLI outside a Veryfront sandbox, install docling and the fallback parser packages to match the sandbox parsing path: 
pip install docling pandas openpyxl xlrd pdfplumber python-docx python-pptx beautifulsoup4 lxml
If docling is unavailable or fails to extract a specific file, non-text formats fall back to the built-in parser dependencies listed above.

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Single-file examples

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Ingest a remote upload

Use uploads/... to reference a file from the project’s remote uploads store: 
veryfront knowledge ingest uploads/contracts/q1.pdf --json

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Ingest a local file

Use a local path to ingest a file that already exists on disk: 
veryfront knowledge ingest ./contracts/q1.pdf --json
Inside a sandbox, use a local relative path when the upload is already present in the workspace: 
veryfront knowledge ingest ./uploads/contracts/q1.pdf --json

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Exact-file batch ingestion

To ingest a specific list of files without ingesting the entire folder: 
veryfront knowledge ingest uploads/contracts/a.pdf uploads/contracts/b.pdf uploads/contracts/c.pdf --json
The command preserves input order in the JSON ingested array, so agent workflows can match each output back to the original source path. Inside the sandbox, knowledge ingest may run longer than typical shell commands, since slow but valid docling runs are allowed to complete.

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Batch ingestion

To ingest every supported file under a remote uploads prefix: 
veryfront knowledge ingest --path uploads/contracts --all --json
To recurse through a local directory: 
veryfront knowledge ingest --path ./contracts --all --recursive --json
Each source document becomes its own markdown file in the project knowledge tree. Use --path ... --all only when you want everything under that uploads prefix or local directory. For an exact file list, pass the file paths as positional arguments instead.

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What the JSON output looks like

With --json, the command returns a machine-readable job result with ingested, skipped, and failed arrays: 
{
  "kind": "knowledge_ingest",
  "version": 1,
  "metadata": {
    "requested_count": 1,
    "source_mode": "explicit_sources",
    "knowledge_path": "knowledge"
  },
  "summary": {
    "requested_count": 1,
    "ingested_count": 1,
    "skipped_count": 0,
    "failed_count": 0
  },
  "ingested": [
    {
      "source": "uploads/demo/notes.txt",
      "localSourcePath": "<LOCAL_SOURCE_PATH>",
      "outputPath": "<OUTPUT_PATH>",
      "remotePath": "knowledge/demo-notes.md",
      "slug": "demo-notes",
      "sourceType": "txt",
      "summary": "Converted document to markdown (87 chars).",
      "stats": {
        "characters": 87,
        "lines": 3
      },
      "warnings": []
    }
  ],
  "skipped": [],
  "failed": []
}
This is useful for agent pipelines that want to confirm exactly what was created. The exact stats shape varies by source type, but the top-level result fields are the same.

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Path rules

The source path determines how the command behaves:
  • uploads/... means a remote project upload
  • ./uploads/... means a local file or directory relative to the current working directory
  • multiple explicit sources are passed as positional arguments: veryfront knowledge ingest <source...> --json
That distinction matters because uploads/... triggers the remote upload download step, while local paths skip it.

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Supported file types

veryfront knowledge ingest supports these source formats:
  • pdf
  • csv
  • tsv
  • docx
  • xlsx
  • xls
  • pptx
  • html
  • htm
  • txt
  • json
  • md
  • mdx

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Low-level commands still exist

If you need finer control, the lower-level building blocks are still available: 
veryfront uploads list
veryfront uploads pull uploads/contracts/q1.pdf --output ./q1.pdf
veryfront files get knowledge/demo-notes.md
veryfront files put knowledge/demo-notes.md --from ./demo-notes.md
But for most agent-facing knowledge ingestion, veryfront knowledge ingest should be the default.

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Troubleshooting

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Unknown command: knowledge

Your installed CLI is older than the branch or release that added the command. Update the CLI or run the current source tree directly with: 
cd veryfront-code
deno run -A cli/main.ts knowledge ingest uploads/contracts/q1.pdf --json

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Missing API token

Set VERYFRONT_API_TOKEN, run veryfront login, or make sure your local CLI config already has a saved token.

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Could not determine project slug

Set VERYFRONT_PROJECT_SLUG or pass the project explicitly: 
veryfront knowledge ingest uploads/contracts/q1.pdf --project my-project --json

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Python package errors

Install the parser packages listed above, or run the command inside a Veryfront sandbox where the knowledge-ingestion stack is already available.

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docling is not installed

Inside a Veryfront sandbox, docling is already installed. Outside a Veryfront sandbox, install docling if you want the same extraction path locally. If docling is not installed or extraction fails, the command falls back to the Python parser stack for supported formats. For agent prompts and system instructions, this is the simplest reliable pattern:
  1. Prefer veryfront knowledge ingest for adding documents to knowledge
  2. Use uploads/... for files that came from the project’s upload store
  3. Use local paths only when the file is already present in the workspace
  4. Fall back to uploads and files CRUD commands only when you need manual control

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Verify it worked

After ingesting a source, the command writes one or more markdown files under the project’s knowledge/ directory: 
ls knowledge/
A working ingestion lists the new knowledge/<name>.md entry. Open the generated markdown and confirm the parsed content matches the original. For automation, capture the JSON output of the command directly: 
veryfront knowledge ingest uploads/sample.pdf --json | jq '.ingested'
The ingested array names every file the command wrote. If the array is empty or the command exited non-zero, check skipped, failed, and the command output for the reason.

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Next

  • Sandbox: run CLI workflows inside isolated workspaces
  • Agents: build agent workflows that can call tools and shell commands
  • Workflows: orchestrate repeatable multi-step automation