{"data":{"slug":"google-langextract","name":"langextract","tagline":"Python library for extracting structured information from unstructured text using LLMs","github_url":"https://github.com/google/langextract","owner":"google","repo":"langextract","owner_avatar_url":"https://avatars.githubusercontent.com/u/1342004?v=4","primary_language":"Python","stars":38614,"forks":2704,"topics":["gemini","gemini-ai","gemini-api","gemini-flash","gemini-pro","information-extration","large-language-models","llm","nlp","python","structured-data"],"archived":false,"github_pushed_at":"2026-09-13T18:57:36+00:00","maintenance_label":"Very active","stars_delta_30d":214,"url":"https://www.graphcanon.com/tools/google-langextract","markdown_url":"https://www.graphcanon.com/tools/google-langextract.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/google-langextract","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=google-langextract","description":"A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.","homepage_url":"https://pypi.org/project/langextract/","license":"Apache-2.0","open_issues":125,"watchers":172,"ai_summary":"Provides tools for extracting structured data from unstructured text leveraging large language models with interactive visualization and precise source grounding.","readme_excerpt":"## Quick Start\n\n> **Note:** Using cloud-hosted models like Gemini requires an API key. See the [API Key Setup](#api-key-setup-for-cloud-models) section for instructions on how to get and configure your key.\n\nExtract structured information with just a few lines of code.\n\n---\n\n# For basic installation:\npip install -e .\n\n---\n\n### Docker\n\n```bash\ndocker build -t langextract .\ndocker run --rm -e LANGEXTRACT_API_KEY=\"your-api-key\" langextract python your_script.py\n```\n\n---\n\n# Install with test dependencies\npip install -e \".[test]\"","github_created_at":"2025-07-08T20:46:06+00:00","created_at":"2026-07-07T17:31:42.949054+00:00","updated_at":"2026-09-20T04:32:33.15402+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"gemini","name":"gemini"},{"slug":"gemini-ai","name":"gemini-ai"},{"slug":"gemini-api","name":"gemini-api"},{"slug":"gemini-flash","name":"gemini-flash"},{"slug":"gemini-pro","name":"gemini-pro"},{"slug":"information-extraction","name":"information-extraction"},{"slug":"large-language-models","name":"large-language-models"},{"slug":"llm","name":"llm"}],"trust":{"provenance":{"is_fork":false,"github_id":1016323751,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:40:32.473Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":2,"days_since_push":4,"last_release_at":"2026-09-13T18:57:37Z","stars_delta_30d":214,"open_issues_delta_30d":3},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:40:35.221Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:40:31.142Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-18T08:40:31.142Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-18T08:40:31.142Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-18T08:40:31.142Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-18T08:40:31.142Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The library itself is free to use, but using cloud-hosted models like Gemini may incur costs based on the provider's pricing model."},"requirements":{"notes":["Installation requires Python and pip.","For cloud-hosted models, an API key is required and must be configured as per the documentation."],"min_ram_gb":4,"requires_docker":true},"constraints":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":true},"when_to_use":["When you need to extract structured data from unstructured text with precise source grounding and interactive visualization capabilities.","If your project requires integration with cloud-hosted models like Gemini, as langextract supports these with API key configuration.","For Python-based projects that benefit from a library that simplifies the process of leveraging large language models for information extraction."],"when_not_to_use":["If your project does not require the use of large language models for information extraction, as langextract is specifically designed around this functionality.","When you do not have access to or do not wish to use cloud-hosted models like Gemini, as langextract requires an API key for these services.","If your project does not need interactive visualization or precise source grounding features, as these are specific to langextract and may not be necessary for all use cases."],"source":"enrich:decision_facts","observed_at":"2026-09-18T11:43:44.263Z"},"constraint_facets":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":true},"decision_summary":[{"label":"Pricing","value":"freemium - The library itself is free to use, but using cloud-hosted models like Gemini may incur costs based on the provider's pricing model."},{"label":"Requirements","value":"Min 4 GB RAM; Requires Docker; Installation requires Python and pip.; For cloud-hosted models, an API key is required and must be configured as per the documentation."},{"label":"Adopt for","value":"Langextract is a Python library designed for extracting structured data from unstructured text using large language models, offering precise source grounding and interactive visualization."},{"label":"License detail","value":"Langextract is available under the Apache-2.0 license, allowing for broad use in both commercial and non-commercial projects with the requirement to include the license text and copyright notice."}]}}