LeXtract

LLM-powered text extraction library for Elixir. Based on Google's LangExtract

LeXtract enables you to extract structured information from unstructured text using Large Language Models (LLMs). It provides a simple, streaming API with support for multiple LLM providers.

Features

• Multi-Provider LLM Support - Works with OpenAI, Gemini, Anthropic, and other providers through ReqLLM
• Streaming API - Memory-efficient batch processing with lazy streams
• Automatic Text Chunking - Handles long documents with configurable chunk sizes and overlap
• Character-Level Alignment - Precise alignment of extractions to source text positions
• Schema Generation - Automatic schema inference from examples
• Template-Based Configuration - Reusable extraction templates in JSON or YAML
• Structured Output Mode - Enhanced reliability with schema validation
• Multi-Pass Extraction - Improved recall through multiple extraction passes
• Flexible Output Formats - Support for JSON and YAML output formats

Installation

Add lextract to your list of dependencies in mix.exs:

def deps do
  [
    {:lextract, "~> 0.1.0"}
  ]
end

Quick Start

Basic Entity Extraction

Extract named entities from text with inline template options:

{:ok, stream} = LeXtract.extract(
  "Dr. Smith prescribed aspirin 100mg to the patient.",
  prompt: "Extract medical entities from the text",
  examples: [
    %{
      text: "Patient takes ibuprofen 200mg",
      extractions: [
        %{extraction_class: "Medication", name: "ibuprofen", dosage: "200mg"}
      ]
    }
  ],
  model: "gpt-4o-mini",
  provider: :openai
)

annotated_docs = Enum.to_list(stream)

Using Template Files

Create a template file (JSON or YAML) for reusable extraction configurations:

# medication_template.yaml
description: Extract medication entities with dosage and frequency
examples:
  - text: "Patient takes aspirin 100mg twice daily"
    extractions:
      - extraction_class: Medication
        name: aspirin
        dosage: 100mg
        frequency: twice daily

Then extract using the template:

{:ok, stream} = LeXtract.extract(
  "Dr. Jones prescribed metformin 500mg once daily.",
  template_file: "medication_template.yaml",
  model: "gpt-4o-mini",
  provider: :openai
)

Batch Processing with Streams

Process multiple documents efficiently with streaming:

documents = [
  "First patient document...",
  "Second patient document...",
  "Third patient document..."
]

{:ok, stream} = LeXtract.extract(
  documents,
  prompt: "Extract medical conditions",
  examples: [...],
  model: "gpt-4o-mini",
  provider: :openai,
  batch_size: 5
)

stream
|> Stream.each(fn annotated_doc ->
  IO.puts("Document: #{annotated_doc.document_id}")
  IO.puts("Extractions: #{length(annotated_doc.extractions)}")
end)
|> Stream.run()

Structured Output Mode

For better reliability and schema validation, use structured output mode:

{:ok, stream} = LeXtract.extract(
  "Patient has hypertension and diabetes.",
  prompt: "Extract medical conditions",
  examples: [
    %{
      text: "Patient diagnosed with asthma",
      extractions: [
        %{extraction_class: "Condition", name: "asthma", severity: "mild"}
      ]
    }
  ],
  model: "gpt-4o-mini",
  provider: :openai,
  use_structured_output: true
)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.