--- title: "langextract vs unstract" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/google-langextract-vs-zipstack-unstract" tools: ["google-langextract", "zipstack-unstract"] --- # langextract vs unstract *GraphCanon updated Oct 4, 2026* ## Verdict Pick langextract if langextract is a Python library designed for extracting structured data from unstructured text using large language models, offering precise source grounding and interactive visualization; pick unstract if unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. [langextract](https://pypi.org/project/langextract/) reports 39k GitHub stars, 2.7k forks, and 125 open issues, last pushed Sep 13, 2026. [unstract](https://unstract.com) has 7.2k stars, 718 forks, and 95 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [langextract's repository](https://github.com/google/langextract) and [unstract's repository](https://github.com/Zipstack/unstract). | | [langextract](/tools/google-langextract.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Tagline | Python library for extracting structured information from unstructured text using LLMs | LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows | | Stars | 38,614 | 7,245 | | Forks | 2,704 | 718 | | Open issues | 125 | 95 | | Language | Python | Python | | Adopt for | Langextract is a Python library designed for extracting structured data from unstructured text using large language models, offering precise source grounding and interactive visualization. | Unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. | | Persona | - | - | | Runtime | - | - | | License | 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. | AGPL-3.0 | | Categories | Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langextract](/tools/google-langextract.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Days since push | 4d | 1d | | Open issues (now) | 125 | 95 | | Stars delta | +214 (30d) | +313 (30d) | | Open issues delta | +3 (30d) | +7 (30d) | | Full report | [trust report](/tools/google-langextract/trust.md) | [trust report](/tools/zipstack-unstract/trust.md) | ## Decision facts: langextract - **Pricing:** 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. - **Requirements:** 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. - **Adopt for:** Langextract is a Python library designed for extracting structured data from unstructured text using large language models, offering precise source grounding and interactive visualization. - **License detail:** 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. ## Decision facts: unstract - **Adopt for:** Unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license. ## Choose when ### Choose langextract if… - License: langextract is Apache-2.0, unstract is AGPL-3.0. - Pricing: 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: 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.. - Tags unique to langextract: gemini, gemini-ai, gemini-api, gemini-flash. - langextract ships Docker support for self-hosted deployment. - When you need to extract structured data from unstructured text with precise source grounding and interactive visualization capabilities. ### Choose unstract if… - License: unstract is AGPL-3.0, langextract is Apache-2.0. - Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai. - You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ## When NOT to use langextract - 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. ## When NOT to use unstract - Your workflow strictly adheres to closed-source software management policies and requires proprietary control. - Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing. - Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency. ## Common questions ### What is the difference between langextract and unstract? langextract: Python library for extracting structured information from unstructured text using LLMs. unstract: LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose langextract over unstract? Choose langextract over unstract when License: langextract is Apache-2.0, unstract is AGPL-3.0; Pricing: 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: 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.; Tags unique to langextract: gemini, gemini-ai, gemini-api, gemini-flash; langextract ships Docker support for self-hosted deployment; When you need to extract structured data from unstructured text with precise source grounding and interactive visualization capabilities. ### When should I choose unstract over langextract? Choose unstract over langextract when License: unstract is AGPL-3.0, langextract is Apache-2.0; Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai; You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ### When should I avoid langextract? 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. ### When should I avoid unstract? Your workflow strictly adheres to closed-source software management policies and requires proprietary control. Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing. Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency. ### Is langextract or unstract more popular on GitHub? langextract has more GitHub stars (38,614 vs 7,245). Stars measure visibility, not whether either tool fits your constraints. ### Are langextract and unstract open source? Yes - both are open-source projects on GitHub (langextract: Apache-2.0, unstract: AGPL-3.0). ### Where can I find alternatives to langextract or unstract? GraphCanon lists graph-backed alternatives at [langextract alternatives](/tools/google-langextract/alternatives) and [unstract alternatives](/tools/zipstack-unstract/alternatives) ([langextract markdown twin](/tools/google-langextract/alternatives.md), [unstract markdown twin](/tools/zipstack-unstract/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/google-langextract-vs-zipstack-unstract.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langextract or unstract? langextract: Very active. unstract: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for langextract and unstract? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langextract trust report](/tools/google-langextract/trust); [unstract trust report](/tools/zipstack-unstract/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=google-langextract`](/api/graphcanon/graph?tool=google-langextract) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_