GraphCanon
Home/Compare/llm-app vs unstract

Comparison

llm-app vs unstract

Verdict

Pick llm-app if llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz; 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.

Markdown twin · llm-app alternatives · unstract alternatives

GraphCanon updated 1w

llm-app logo

llm-app

pathwaycom/llm-app

★ 59kpushed Jul 5, 2026
vs
unstract logo

unstract

Zipstack/unstract

★ 6.9kpushed Jul 27, 2026

Trust & integrity

Signalllm-appunstract
Maintenance
Steady (41d since push)
As of 1w · github_public_v1
Very active (0d since push)
As of 4w · github_public_v1
Provenance
Not a fork · Organization account
As of 1w · github_public_v1
Not a fork · Organization account
As of 4w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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
llm-app trust reportunstract trust reportTrust methodology

Tagline

llm-app
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.
unstract
LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows

Stars

llm-app
59k
unstract
6.9k

Forks

llm-app
1.5k
unstract
663

Open issues

llm-app
8
unstract
88

Language

llm-app
Jupyter Notebook
unstract
Python

Adopt for

llm-app
llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz
unstract
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

llm-app
-
unstract
-

Runtime

llm-app
-
unstract
-

License

llm-app
MIT
unstract
AGPL-3.0

Last pushed

llm-app
Jul 5, 2026
unstract
Jul 27, 2026

Categories

llm-app
Data & Retrieval, LLM Frameworks, Vector Databases
unstract
Data & Retrieval, LLM Frameworks

Trust and health

Maintenance

llm-app
Steady (60%)
unstract
Very active (96%)

Days since push

llm-app
41d
unstract
0d

Open issues (now)

llm-app
8
unstract
88

Stars delta

llm-app
+11 (30d)
unstract
Unknown

Open issues delta

llm-app
-2 (30d)
unstract
Unknown

Full report

llm-app
Trust report
unstract
Trust report

Choose llm-app if…

  • llm-app is primarily Jupyter Notebook; unstract is Python.
  • License: llm-app is MIT, unstract is AGPL-3.0.
  • Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others..
  • Tags unique to llm-app: chatbot, hugging-face, retrieval-augmented-generation, vector-database.
  • Also covers Vector Databases.
  • - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.

When NOT to use llm-app

  • - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app.
  • - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
GitHubDetails

Choose unstract if…

  • unstract is primarily Python; llm-app is Jupyter Notebook.
  • License: unstract is AGPL-3.0, llm-app is MIT.
  • 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 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.
GitHubDetails

Explore

llm-app trust report →unstract trust report →Data & Retrieval category →LLM Frameworks category →Vector Databases category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: llm-app 59k · unstract 6.9k (synced Aug 16, 2026).

Common questions

What is the difference between llm-app and unstract?
llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. 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 llm-app over unstract?
Choose llm-app over unstract when llm-app is primarily Jupyter Notebook; unstract is Python; License: llm-app is MIT, unstract is AGPL-3.0; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, retrieval-augmented-generation, vector-database; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.
When should I choose unstract over llm-app?
Choose unstract over llm-app when unstract is primarily Python; llm-app is Jupyter Notebook; License: unstract is AGPL-3.0, llm-app is MIT; 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 llm-app?
- You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
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 llm-app or unstract more popular on GitHub?
llm-app has more GitHub stars (59,037 vs 6,932). Stars measure visibility, not whether either tool fits your constraints.
Are llm-app and unstract open source?
Yes - both are open-source projects on GitHub (llm-app: MIT, unstract: AGPL-3.0).
Where can I find alternatives to llm-app or unstract?
GraphCanon lists graph-backed alternatives at llm-app alternatives and unstract alternatives (llm-app markdown twin, unstract 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, llm-app or unstract?
llm-app: Steady. 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 llm-app and unstract?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-app trust report; unstract trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.