Practical overview
When it fits
Use Langextract when extracted fields need to remain traceable to their original wording, including long-document processing and review workflows.
Who it is for
- Python developers building document-processing pipelines
- Teams reviewing clinical notes, reports, contracts or policies
- Researchers creating source-grounded entity and relationship annotations
Documented uses
- Convert unstructured documents into structured records
- Preserve exact source locations for extracted values
- Review large extraction sets in interactive HTML visualizations
- Build few-shot extraction tasks without model fine-tuning
Requirements & limits
The project is presented as a public Apache-2.0 repository and Python library. Cloud-hosted Gemini workflows require an API key; the repository also identifies a local Ollama interface. A browser demo is described as running Romeo and Juliet extraction without installation.
- Exact character-span grounding supports source review and filtering of unlocated results.
- Few-shot examples define the extraction schema and influence model behavior.
- Long-document processing uses chunking, parallel processing and multiple passes.
- Interactive HTML visualization is generated for reviewing extracted entities in context.
- Provider choice includes Gemini-related cloud integrations and a built-in Ollama interface.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Define a grounded extraction task
Prepare a Langextract task that extracts ordered, source-matching fields from text.
Before you start
- Python
- Langextract
- An LLM provider; cloud-hosted Gemini requires an API key
- A clear extraction prompt
- At least one high-quality few-shot ExampleData example
Steps
Write a prompt describing the fields, attributes, ordering and wording rules to extract.
Create an ExampleData example with Extraction entries whose extraction_text values are verbatim spans from the example text.
Provide the task definition and source document to Langextract for extraction.
Review character intervals and filter results without a character interval when only source-grounded results are wanted.
Expected outcome
A structured extraction result whose supported items can be linked to exact source spans.
Guide limitations
- The supplied material does not provide detailed provider configuration or a complete execution example.
- Results can be influenced by the selected model, prompt, examples and task complexity.
- Few-shot-example content can be extracted instead of input content; unlocated results may have char_interval set to None.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 2 October 2026
- Original website title
- google/langextract · Official homepage title · retained in its source language