---

name: langextract description: "Use LangExtract to extract structured data from unstructured text, configure model providers, save/visualize grounded outputs, and author provider plugins." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

LangExtract Repo Skill

Use this skill when the user wants to use the langextract Python package for source-grounded structured extraction from natural language, provider/back-end configuration, JSONL/HTML result review, or custom provider plugin authoring.

LangExtract's central workflow is: define a prompt and examples, call lx.extract(), inspect grounded AnnotatedDocument results, optionally save JSONL, and generate interactive HTML visualization. It supports Gemini by default, OpenAI/GPT through the openai extra, Ollama/local models, Vertex AI batch processing, and third-party provider plugins.

Install and smoke check

For ordinary package use:

python -m pip install langextract
python - <<'PY'
import langextract as lx
print(lx.__name__)
PY

For OpenAI provider support:

python -m pip install "langextract[openai]"

Cloud model calls require provider credentials such as GEMINI_API_KEY, LANGEXTRACT_API_KEY, or OPENAI_API_KEY. Ollama calls require a running Ollama service and a pulled local model.

Route by task

User task	Read next
Write or debug lx.extract() calls, examples, relationship attributes, output schemas, prompt validation, resolver params, long-document chunking, Unicode tokenization, or grounded span filtering.	sub-skills/extraction/SKILL.md
Choose/configure Gemini, Vertex AI, OpenAI/GPT, OpenAI-compatible endpoints, Ollama/local models, provider kwargs, route resolution, retries, or batch APIs.	sub-skills/providers/SKILL.md
Save AnnotatedDocument outputs to JSONL, reload JSONL, inspect serialized data, or generate/write interactive HTML visualizations.	sub-skills/visualization/SKILL.md
Create or troubleshoot a custom provider plugin package, entry point, router pattern, or schema adapter.	sub-skills/provider-plugins/SKILL.md
Need the public API map or version-sensitive refresh baseline.	references/api-map.md and references/repo-provenance.md
Cross-cutting install/import/provider/schema troubleshooting.	references/troubleshooting.md

Operating workflow

1. Identify whether the user's task is extraction design, provider configuration, output review, or provider extension.
2. Read the matching sub-skill before writing code. Read only sibling sub-skills when the request crosses boundaries, such as extraction plus visualization.
3. Keep secrets outside code. Use environment variables or caller-owned secret stores for provider API keys.
4. Start with short, literal text and show_progress=False while debugging. Scale to long documents, batch mode, multiple workers, or multiple passes only after examples and grounding look correct.
5. Treat char_interval=None as ungrounded output until diagnosed; visualization only highlights valid intervals.
6. Use bundled scripts as safe starters or diagnostics:
   • extraction examples: sub-skills/extraction/scripts/
   • provider route/Ollama checks: sub-skills/providers/scripts/
   • no-model JSONL/HTML smoke: sub-skills/visualization/scripts/save_and_visualize.py
   • provider plugin scaffold: sub-skills/provider-plugins/scripts/create_provider_plugin.py

Do not do these

• Do not tell the user to run examples, tests, scripts, or docs from a source checkout as part of using this skill. Use the bundled references/scripts here or write fresh user-project code.
• Do not enable fetch_urls=True for untrusted URLs; fetch and sanitize content yourself, then pass literal text.
• Do not combine output_schema with fence_output=True, YAML output, or provider-native schema kwargs.
• Do not claim live Gemini/OpenAI/Vertex/Ollama verification unless those credentialed or service-backed checks actually ran in the user's environment.
• Do not put API keys, local Python paths, virtualenv names, conda prefixes, or other machine-specific details in generated user code or reports.

Freshness

This skill was generated for LangExtract package version 1.6.0. Before relying on version-sensitive details, read references/repo-provenance.md. If package metadata, provider entry points, public signatures, or major evidence paths differ from that snapshot, refresh the skill.