Comparison
langextract vs unstructured
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 unstructured if unstructured is an open-source ETL solution for transforming complex documents into clean, structured formats for language models, supporting workflows like partitioning, enrichments, chunking, and embedding.
Markdown twin · langextract alternatives · unstructured alternatives
GraphCanon updated Sep 20, 2026
22views this month
vs
Trust & integrity
| Signal | langextract | unstructured |
|---|---|---|
| Maintenance | Very active (4d since push) As of Sep 18, 2026 · github_public_v1 | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- langextract
- Python library for extracting structured information from unstructured text using LLMs
- unstructured
- Convert documents to structured data effortlessly
Stars
- langextract
- 39k
- unstructured
- 15k
Forks
- langextract
- 2.7k
- unstructured
- 1.3k
Open issues
- langextract
- 125
- unstructured
- 309
Language
- langextract
- Python
- unstructured
- HTML
Adopt for
- langextract
- Langextract is a Python library designed for extracting structured data from unstructured text using large language models, offering precise source grounding and interactive visualization.
- unstructured
- Unstructured is an open-source ETL solution for transforming complex documents into clean, structured formats for language models, supporting workflows like partitioning, enrichments, chunking, and embedding.
Persona
- langextract
- -
- unstructured
- -
Runtime
- langextract
- -
- unstructured
- -
License
- langextract
- 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.
- unstructured
- Apache-2.0
Last pushed
- langextract
- Sep 13, 2026
- unstructured
- Sep 15, 2026
Categories
- langextract
- Data & Retrieval, LLM Frameworks
- unstructured
- Data & Retrieval, Developer Tools, Model Training
Trust and health
Days since push
- langextract
- 4d
- unstructured
- 3d
Open issues (now)
- langextract
- 125
- unstructured
- 309
Stars delta
- langextract
- +214 (30d)
- unstructured
- +208 (30d)
Open issues delta
- langextract
- +3 (30d)
- unstructured
- +32 (30d)
Full report
- langextract
- Trust report
- unstructured
- Trust report
Typed relationship
langextract alternative unstructuredBoth LangExtract and unstructured aim to convert unstructured text into structured data using AI techniques.
Shared compatibility
- Python · langextract: Python runtime · unstructured: Python runtime
Choose langextract if…
- langextract is primarily Python; unstructured is HTML.
- 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..
- Both LangExtract and unstructured aim to convert unstructured text into structured data using AI techniques.
- Tags unique to langextract: gemini, gemini-ai, gemini-api, gemini-flash.
- Also covers LLM Frameworks.
- When you need to extract structured data from unstructured text with precise source grounding and interactive visualization capabilities.
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.
Choose unstructured if…
- unstructured is primarily HTML; langextract is Python.
- Both LangExtract and unstructured aim to convert unstructured text into structured data using AI techniques.
- Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing.
- Also covers Developer Tools, Model Training.
- When you need to convert a variety of document types, including PDFs and images, into structured data formats suitable for language models.
When NOT to use unstructured
- If you are working with simple text files that do not require complex parsing or enrichment processes.
- When you need a tool that supports real-time document processing, as Unstructured is optimized for batch processing and may not be suitable for real-time applications.
- If you are looking for a solution that does not require setting up a Docker environment or managing dependencies with uv.
- When you need a tool that supports a wider range of document types beyond PDFs and images, as Unstructured may not cover all your document format needs.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (google/langextract) · observed Sep 20, 2026
- GitHub forks (google/langextract) · observed Sep 20, 2026
- Last push (google/langextract) · observed Sep 13, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (Unstructured-IO/unstructured) · observed Sep 20, 2026
- GitHub forks (Unstructured-IO/unstructured) · observed Sep 20, 2026
- Last push (Unstructured-IO/unstructured) · observed Sep 15, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: langextract 39k · unstructured 15k (synced Sep 20, 2026).
Common questions
- What is the difference between langextract and unstructured?
- langextract: Python library for extracting structured information from unstructured text using LLMs. unstructured: Convert documents to structured data effortlessly. See the comparison table for live GitHub stats and shared categories.
- When should I choose langextract over unstructured?
- Choose langextract over unstructured when langextract is primarily Python; unstructured is HTML; 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.; Both LangExtract and unstructured aim to convert unstructured text into structured data using AI techniques; Tags unique to langextract: gemini, gemini-ai, gemini-api, gemini-flash; Also covers LLM Frameworks; When you need to extract structured data from unstructured text with precise source grounding and interactive visualization capabilities.
- When should I choose unstructured over langextract?
- Choose unstructured over langextract when unstructured is primarily HTML; langextract is Python; Both LangExtract and unstructured aim to convert unstructured text into structured data using AI techniques; Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing; Also covers Developer Tools, Model Training; When you need to convert a variety of document types, including PDFs and images, into structured data formats suitable for language models.
- 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 unstructured?
- If you are working with simple text files that do not require complex parsing or enrichment processes. When you need a tool that supports real-time document processing, as Unstructured is optimized for batch processing and may not be suitable for real-time applications. If you are looking for a solution that does not require setting up a Docker environment or managing dependencies with uv. When you need a tool that supports a wider range of document types beyond PDFs and images, as Unstructured may not cover all your document format needs.
- Is langextract or unstructured more popular on GitHub?
- langextract has more GitHub stars (38,614 vs 15,446). Stars measure visibility, not whether either tool fits your constraints.
- Are langextract and unstructured open source?
- Yes - both are open-source projects on GitHub (langextract: Apache-2.0, unstructured: Apache-2.0).
- Where can I find alternatives to langextract or unstructured?
- GraphCanon lists graph-backed alternatives at langextract alternatives and unstructured alternatives (langextract markdown twin, unstructured markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, langextract or unstructured?
- langextract: Very active. unstructured: 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 unstructured?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langextract trust report; unstructured trust report.