oidlabs-com/lexoid/lexoid-cli

Lexoid CLI

Lexoid ships a lexoid console script (also runnable as python -m lexoid) for document parsing without writing Python. There are three sub-commands: parse, schema, and latex.

When to use this skill

• The user has a document (PDF, image, HTML, DOCX, XLSX, PPTX, CSV, TXT, audio) or a URL and wants it converted to markdown/JSON/LaTeX.
• The user wants structured extraction (JSON conforming to a schema) from the shell.
• The task is one-off or scripted — no need to build a Python integration.

If the user wants to embed parsing into a Python application or library, use the lexoid-python skill instead.

Setup checks

Before invoking, confirm:

1. lexoid is installed (lexoid --help or python -m lexoid --help). If not, run pip install lexoid.
2. For LLM-based commands, the relevant API key env var is set:

• GOOGLE_API_KEY (Gemini, default), OPENAI_API_KEY, ANTHROPIC_API_KEY, MISTRAL_API_KEY, HUGGINGFACEHUB_API_TOKEN, TOGETHER_API_KEY, OPENROUTER_API_KEY, FIREWORKS_API_KEY.
• Ollama needs no key, but needs ollama serve running at OLLAMA_BASE_URL (default http://localhost:11434) and the target model pulled (ollama pull <model>).
• Local backends (SmolDocling/granite-docling, PaddleOCR-VL) need no key and no server — they run in-process; the first call downloads weights from Hugging Face.

1. For Linux DOCX → PDF, LibreOffice (lowriter) must be installed.

Loading API keys from .env

API keys are commonly stored in a .env file at the project root rather than exported in the shell. The lexoid CLI does not auto-load .env, so for any LLM-based command (LLM_PARSE, schema, latex, or AUTO when it routes to an LLM) you must load it yourself.

Always load `.env` in a subshell so the keys never leak into the surrounding environment — the parentheses scope the exports to that one command, restoring the environment to its previous state automatically afterward. Guard the source with [ -f .env ] so the command still runs (using already-exported keys) when no .env is present:

# Load .env for this command only (if it exists); env is reset to its prior state on exit
( set -a; [ -f .env ] && . ./.env; set +a; lexoid parse --input document.pdf --parser-type LLM_PARSE --model gpt-4o )

Do not run a bare set -a; . ./.env; set +a in the parent shell — that persists secrets into the session.

The examples in the rest of this skill are written as plain `lexoid …` for readability. Apply the wrapper above to any LLM-based command (LLM_PARSE, schema, latex, or AUTO when it routes to an LLM). If your keys are already exported in the environment, run the commands as-is.

Commands

lexoid parse — Markdown / JSON output

Convert a document to markdown (default) or JSON (with segments, token usage, parser info).

# Default: AUTO routing, markdown to stdout
lexoid parse --input document.pdf
 
# Save to file
lexoid parse --input document.pdf --output output.md
 
# Full result as JSON (includes per-page segments, token usage, parsers_used)
lexoid parse --input document.pdf --format json --output result.json
 
# Explicit LLM parsing (forces an LLM regardless of routing). LLM-based: load .env first.
lexoid parse --input document.pdf --parser-type LLM_PARSE --model gpt-4o
lexoid parse --input document.pdf --parser-type LLM_PARSE --model claude-3-5-sonnet-20241022
lexoid parse --input scanned.pdf --parser-type LLM_PARSE --model mistral-ocr-latest
 
# Force static parsing (no LLM, no API key needed for PDFs)
lexoid parse --input document.pdf --parser-type STATIC_PARSE --framework pdfplumber
 
# Parse a URL
lexoid parse --input https://example.com --output page.md
 
# Tune chunking / parallelism
lexoid parse --input big.pdf --pages-per-split 8 --max-processes 8

Key flags: --parser-type (AUTO/LLM_PARSE/STATIC_PARSE), --model, --framework (pdfplumber/paddleocr), --api (override provider), --format (markdown/json), --pages-per-split, --max-processes, --verbose.

lexoid schema — Structured extraction

Extract data conforming to a JSON schema. Schema can be a file path or inline JSON.

All schema commands are LLM-based — load .env first (see "Loading API keys from .env") unless keys are already exported.

# Inline schema
lexoid schema \
  --input invoice.pdf \
  --schema '{"type":"object","properties":{"invoice_number":{"type":"string"},"total":{"type":"number"}}}' \
  --output invoice.json
 
# Schema from file, explicit provider
lexoid schema --input invoice.pdf --schema schema.json --api openai --model gpt-4o
 
# Example-guided extraction (improves accuracy)
lexoid schema --input invoice.pdf --schema schema.json \
  --example-schema example.json
 
# Treat the whole doc as one instance (vs. one per page)
lexoid schema --input contract.pdf --schema schema.json --fill-single-schema

Defaults: model gpt-4o-mini. The provider is auto-detected from the model name unless --api is given.

lexoid latex — LaTeX conversion

Convert a document to a self-contained LaTeX source.

LaTeX conversion is LLM-based — load .env first (see "Loading API keys from .env") unless keys are already exported.

lexoid latex --input paper.pdf --output paper.tex
lexoid latex --input paper.pdf --model gpt-4o

Output piping

When no --output is given, only the parsed content is written to stdout; status messages, token usage, and parser info go to stderr. This means standard piping works:

lexoid parse --input report.pdf | grep -i "revenue"
lexoid parse --input report.pdf --format json | jq '.token_usage'

Common patterns

• Default to `AUTO`: with no --parser-type, the CLI uses AUTO, which inspects the document and routes to the best parser (often an LLM for scans, charts, or complex tables). This is the right choice unless the user asks otherwise.
• `STATIC_PARSE` is opt-in, not the default: choose it when the user explicitly wants no API calls / no cost, or you know the input is a clean native-text PDF. It returns empty output on scanned/image-only pages, so it is not a safe first guess for unknown documents.
• `LLM_PARSE` for quality: force it with --parser-type LLM_PARSE --model <model> for scans, chart/figure-heavy pages, or messy tables where layout fidelity matters.
• Scanned PDFs / images: use --parser-type STATIC_PARSE --framework paddleocr (no API key) or an LLM model with vision.
• Batch: drive the CLI from a shell loop (for f in inputs/*.pdf; do lexoid parse -i "$f" -o "out/${f%.pdf}.md"; done).
• Debug: add --verbose to surface loguru logs to stderr.

Failure modes to watch for

• Missing API key → CLI raises a clean error naming the env var. The CLI does not auto-load .env; load it via the subshell wrapper (see "Loading API keys from .env") and retry.
• DOCX on Linux without LibreOffice installed → conversion to PDF fails. Install libreoffice.
• --model and --api mismatch → use --api only to override an auto-inferred provider (e.g., to send a model through OpenRouter).
• Ollama: must run ollama serve and ollama pull <model> first; the CLI does not start the server.

See also

• Full reference: docs/cli.rst and docs/api.rst in this repo.
• Python equivalent: lexoid-python skill.