--- title: "langextract vs annotateai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/google-langextract-vs-neuml-annotateai" tools: ["google-langextract", "neuml-annotateai"] --- # langextract vs annotateai *GraphCanon updated Sep 20, 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 annotateai if annotateai uses LLMs to automate the annotation of scientific and medical papers. It's open-source under Apache-2.0, categorized as an LLM Framework and Data & Retrieval tool. [langextract](https://pypi.org/project/langextract/) reports 39k GitHub stars, 2.7k forks, and 125 open issues, last pushed Sep 13, 2026. [annotateai](https://github.com/neuml/annotateai) has 426 stars, 43 forks, and 0 open issues, last pushed May 5, 2026. Figures are from public GitHub metadata via [langextract's repository](https://github.com/google/langextract) and [annotateai's repository](https://github.com/neuml/annotateai). | | [langextract](/tools/google-langextract.md) | [annotateai](/tools/neuml-annotateai.md) | | --- | --- | --- | | Tagline | Python library for extracting structured information from unstructured text using LLMs | Automatically annotate papers using LLMs | | Stars | 38,614 | 426 | | Forks | 2,704 | 43 | | Open issues | 125 | 0 | | 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. | annotateai uses LLMs to automate the annotation of scientific and medical papers. It's open-source under Apache-2.0, categorized as an LLM Framework and Data & Retrieval tool. | | 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. | Apache-2.0 | | 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) | [annotateai](/tools/neuml-annotateai.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 4d | 137d | | Open issues (now) | 125 | 0 | | Stars delta | +214 (30d) | +4 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Full report | [trust report](/tools/google-langextract/trust.md) | [trust report](/tools/neuml-annotateai/trust.md) | ## Shared compatibility - **Python**: [langextract](/tools/google-langextract.md) - Python runtime; [annotateai](/tools/neuml-annotateai.md) - Python runtime ## 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: annotateai - **Adopt for:** annotateai uses LLMs to automate the annotation of scientific and medical papers. It's open-source under Apache-2.0, categorized as an LLM Framework and Data & Retrieval tool. ## Choose when ### Choose langextract if… - 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 annotateai if… - Tags unique to annotateai: ai, artificial-intelligence, machine-learning, medical. - Need automated annotations for large volumes of scientific or medical papers - Leaner open-issue backlog (0). ## 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 annotateai - Require detailed, custom annotations that go beyond general LLML capabilities - Situations where regulatory approval necessitates human review over machine-generated annotations ## Common questions ### What is the difference between langextract and annotateai? langextract: Python library for extracting structured information from unstructured text using LLMs. annotateai: Automatically annotate papers using LLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose langextract over annotateai? Choose langextract over annotateai when 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 annotateai over langextract? Choose annotateai over langextract when Tags unique to annotateai: ai, artificial-intelligence, machine-learning, medical; Need automated annotations for large volumes of scientific or medical papers; Leaner open-issue backlog (0). ### 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 annotateai? Require detailed, custom annotations that go beyond general LLML capabilities Situations where regulatory approval necessitates human review over machine-generated annotations ### Is langextract or annotateai more popular on GitHub? langextract has more GitHub stars (38,614 vs 426). Stars measure visibility, not whether either tool fits your constraints. ### Are langextract and annotateai open source? Yes - both are open-source projects on GitHub (langextract: Apache-2.0, annotateai: Apache-2.0). ### Where can I find alternatives to langextract or annotateai? GraphCanon lists graph-backed alternatives at [langextract alternatives](/tools/google-langextract/alternatives) and [annotateai alternatives](/tools/neuml-annotateai/alternatives) ([langextract markdown twin](/tools/google-langextract/alternatives.md), [annotateai markdown twin](/tools/neuml-annotateai/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-neuml-annotateai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langextract or annotateai? langextract: Very active. annotateai: Slowing. 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 annotateai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langextract trust report](/tools/google-langextract/trust); [annotateai trust report](/tools/neuml-annotateai/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/_