Comparison
knowledge-gpt vs unstract
Verdict
Pick knowledge-gpt if knowledge-gpt: Python toolkit for indexing and Q&A sessions with info sources using GPT & transformers; 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.
Markdown twin · knowledge-gpt alternatives · unstract alternatives
GraphCanon updated Oct 4, 2026
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Trust & integrity
| Signal | knowledge-gpt | unstract |
|---|---|---|
| Maintenance | Dormant (1243d since push) As of Sep 20, 2026 · github_public_v1 | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Oct 4, 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
- knowledge-gpt
- Extract knowledge from all information sources using GPT and other language models. Index and conduct Q&A sessions with information sources.
- unstract
- LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows
Stars
- knowledge-gpt
- 292
- unstract
- 7.2k
Forks
- knowledge-gpt
- 52
- unstract
- 718
Open issues
- knowledge-gpt
- 8
- unstract
- 95
Language
- knowledge-gpt
- Python
- unstract
- Python
Adopt for
- knowledge-gpt
- knowledge-gpt: Python toolkit for indexing and Q&A sessions with info sources using GPT & transformers.
- 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
- knowledge-gpt
- -
- unstract
- -
Runtime
- knowledge-gpt
- -
- unstract
- -
License
- knowledge-gpt
- MIT
- unstract
- AGPL-3.0
Last pushed
- knowledge-gpt
- Apr 25, 2023
- unstract
- Sep 18, 2026
Categories
- knowledge-gpt
- Data & Retrieval, Evaluation & Observability, LLM Frameworks, Model Training
- unstract
- Data & Retrieval, LLM Frameworks
Trust and health
Maintenance
- knowledge-gpt
- Dormant (18%)
- unstract
- Very active (96%)
Days since push
- knowledge-gpt
- 1243d
- unstract
- 1d
Open issues (now)
- knowledge-gpt
- 8
- unstract
- 95
Stars delta
- knowledge-gpt
- +1 (30d)
- unstract
- +313 (30d)
Open issues delta
- knowledge-gpt
- 0 (30d)
- unstract
- +7 (30d)
Full report
- knowledge-gpt
- Trust report
- unstract
- Trust report
Choose knowledge-gpt if…
- License: knowledge-gpt is MIT, unstract is AGPL-3.0.
- Tags unique to knowledge-gpt: context, embedding-vectors, gpt, huggingface-transformers.
- Also covers Evaluation & Observability, Model Training.
- knowledge-gpt ships Docker support for self-hosted deployment.
- When you need a flexible, model-agnostic approach for Q&A over diverse data sources
When NOT to use knowledge-gpt
- Avoid if strictly needing real-time response performance without indexing capabilities
- Not recommended if focusing solely on visual or multimedia content extraction
Choose unstract if…
- License: unstract is AGPL-3.0, knowledge-gpt 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (geeks-of-data/knowledge-gpt) · observed Sep 20, 2026
- GitHub forks (geeks-of-data/knowledge-gpt) · observed Sep 20, 2026
- Last push (geeks-of-data/knowledge-gpt) · observed Apr 25, 2023
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Zipstack/unstract) · observed Sep 20, 2026
- GitHub forks (Zipstack/unstract) · observed Sep 20, 2026
- Last push (Zipstack/unstract) · observed Sep 18, 2026
- License file (AGPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
GitHub stars on cards: knowledge-gpt 292 · unstract 7.2k (synced Sep 20, 2026).
Common questions
- What is the difference between knowledge-gpt and unstract?
- knowledge-gpt: Extract knowledge from all information sources using GPT and other language models. Index and conduct Q&A sessions with information sources.. 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 knowledge-gpt over unstract?
- Choose knowledge-gpt over unstract when License: knowledge-gpt is MIT, unstract is AGPL-3.0; Tags unique to knowledge-gpt: context, embedding-vectors, gpt, huggingface-transformers; Also covers Evaluation & Observability, Model Training; knowledge-gpt ships Docker support for self-hosted deployment; When you need a flexible, model-agnostic approach for Q&A over diverse data sources.
- When should I choose unstract over knowledge-gpt?
- Choose unstract over knowledge-gpt when License: unstract is AGPL-3.0, knowledge-gpt 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 knowledge-gpt?
- Avoid if strictly needing real-time response performance without indexing capabilities Not recommended if focusing solely on visual or multimedia content extraction
- 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 knowledge-gpt or unstract more popular on GitHub?
- unstract has more GitHub stars (7,245 vs 292). Stars measure visibility, not whether either tool fits your constraints.
- Are knowledge-gpt and unstract open source?
- Yes - both are open-source projects on GitHub (knowledge-gpt: MIT, unstract: AGPL-3.0).
- Where can I find alternatives to knowledge-gpt or unstract?
- GraphCanon lists graph-backed alternatives at knowledge-gpt alternatives and unstract alternatives (knowledge-gpt 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, knowledge-gpt or unstract?
- knowledge-gpt: Dormant. 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 knowledge-gpt and unstract?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: knowledge-gpt trust report; unstract trust report.