Comparison
awesome-ai-apps vs awesome-ai-apps
Verdict
Pick awesome-ai-apps if awesome-ai-apps is a curated list of projects focusing on AI applications and innovations such as RAG technologies, AI agents, and workflows, emphasizing large language models using Python; pick awesome-ai-apps if awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models.
Markdown twin · awesome-ai-apps alternatives · awesome-ai-apps alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | awesome-ai-apps | awesome-ai-apps |
|---|---|---|
| Maintenance | Very active (2d since push) As of 4w · github_public_v1 | Slowing (182d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4w · github_public_v1 | Not a fork · Personal account As of 1w · 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 |
Tagline
- awesome-ai-apps
- A curated list of AI applications showcasing RAG, agents, and workflows.
- awesome-ai-apps
- A curated collection of AI Agents and LLM Apps with various tech stacks
Stars
- awesome-ai-apps
- 13k
- awesome-ai-apps
- 817
Forks
- awesome-ai-apps
- 1.7k
- awesome-ai-apps
- 174
Open issues
- awesome-ai-apps
- 89
- awesome-ai-apps
- 27
Language
- awesome-ai-apps
- Python
- awesome-ai-apps
- HTML
Adopt for
- awesome-ai-apps
- awesome-ai-apps is a curated list of projects focusing on AI applications and innovations such as RAG technologies, AI agents, and workflows, emphasizing large language models using Python.
- awesome-ai-apps
- awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models.
Persona
- awesome-ai-apps
- -
- awesome-ai-apps
- -
Runtime
- awesome-ai-apps
- -
- awesome-ai-apps
- -
License
- awesome-ai-apps
- MIT License ensures easy integration into both open source and proprietary projects without restrictions.
- awesome-ai-apps
- Apache-2.0
Last pushed
- awesome-ai-apps
- Jul 23, 2026
- awesome-ai-apps
- Feb 10, 2026
Categories
- awesome-ai-apps
- AI Agents, LLM Frameworks
- awesome-ai-apps
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- awesome-ai-apps
- Very active (96%)
- awesome-ai-apps
- Slowing (36%)
Days since push
- awesome-ai-apps
- 2d
- awesome-ai-apps
- 182d
Open issues (now)
- awesome-ai-apps
- 89
- awesome-ai-apps
- 27
Full report
- awesome-ai-apps
- Trust report
- awesome-ai-apps
- Trust report
Choose awesome-ai-apps if…
- awesome-ai-apps is primarily Python; awesome-ai-apps is HTML.
- License: awesome-ai-apps is MIT, awesome-ai-apps is Apache-2.0.
- Pricing: As an open-source project under the MIT License, awesome-ai-apps is free to use. There are no paid plans beyond potential third-party service integrations or support contracts..
- Requirements: Requires understanding of Python and familiarity with large language models and RAG technologies to benefit fully from the projects listed..
- Tags unique to awesome-ai-apps: hacktoberfest, mcp.
- Use awesome-ai-apps when looking to explore or implement Retrieval-Augmented Generation (RAG) in Python projects focused on enhancing search-based question answering.
When NOT to use awesome-ai-apps
- Avoid awesome-ai-apps if your project requires non-Python support, as all the included applications are built using Python.
- Do not use this repository if your focus is on backend-only AI services that do not involve RAG technologies or AI agents.
Choose awesome-ai-apps if…
- awesome-ai-apps is primarily HTML; awesome-ai-apps is Python.
- License: awesome-ai-apps is Apache-2.0, awesome-ai-apps is MIT.
- Tags unique to awesome-ai-apps: apps, automation, framework, genai.
- For exploring real-world implementations of AI agents across different technologies
When NOT to use awesome-ai-apps
- When seeking detailed implementation steps specific to one technology stack
- In scenarios demanding a deep dive into proprietary or less publicly-known application codes
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Arindam200/awesome-ai-apps) · observed Jul 26, 2026
- GitHub forks (Arindam200/awesome-ai-apps) · observed Jul 26, 2026
- Last push (Arindam200/awesome-ai-apps) · observed Jul 23, 2026
- License file (MIT) · observed Jul 26, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rohitg00/awesome-ai-apps) · observed Aug 12, 2026
- GitHub forks (rohitg00/awesome-ai-apps) · observed Aug 12, 2026
- Last push (rohitg00/awesome-ai-apps) · observed Feb 10, 2026
- License file (Apache-2.0) · observed Aug 12, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: awesome-ai-apps 13k · awesome-ai-apps 817 (synced Jul 26, 2026).
Common questions
- What is the difference between awesome-ai-apps and awesome-ai-apps?
- awesome-ai-apps: A curated list of AI applications showcasing RAG, agents, and workflows.. awesome-ai-apps: A curated collection of AI Agents and LLM Apps with various tech stacks. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-ai-apps over awesome-ai-apps?
- Choose awesome-ai-apps over awesome-ai-apps when awesome-ai-apps is primarily Python; awesome-ai-apps is HTML; License: awesome-ai-apps is MIT, awesome-ai-apps is Apache-2.0; Pricing: As an open-source project under the MIT License, awesome-ai-apps is free to use. There are no paid plans beyond potential third-party service integrations or support contracts.; Requirements: Requires understanding of Python and familiarity with large language models and RAG technologies to benefit fully from the projects listed.; Tags unique to awesome-ai-apps: hacktoberfest, mcp; Use awesome-ai-apps when looking to explore or implement Retrieval-Augmented Generation (RAG) in Python projects focused on enhancing search-based question answering.
- When should I choose awesome-ai-apps over awesome-ai-apps?
- Choose awesome-ai-apps over awesome-ai-apps when awesome-ai-apps is primarily HTML; awesome-ai-apps is Python; License: awesome-ai-apps is Apache-2.0, awesome-ai-apps is MIT; Tags unique to awesome-ai-apps: apps, automation, framework, genai; For exploring real-world implementations of AI agents across different technologies.
- When should I avoid awesome-ai-apps?
- Avoid awesome-ai-apps if your project requires non-Python support, as all the included applications are built using Python. Do not use this repository if your focus is on backend-only AI services that do not involve RAG technologies or AI agents.
- When should I avoid awesome-ai-apps?
- When seeking detailed implementation steps specific to one technology stack In scenarios demanding a deep dive into proprietary or less publicly-known application codes
- Is awesome-ai-apps or awesome-ai-apps more popular on GitHub?
- awesome-ai-apps has more GitHub stars (13,268 vs 817). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-ai-apps and awesome-ai-apps open source?
- Yes - both are open-source projects on GitHub (awesome-ai-apps: MIT, awesome-ai-apps: Apache-2.0).
- Where can I find alternatives to awesome-ai-apps or awesome-ai-apps?
- GraphCanon lists graph-backed alternatives at awesome-ai-apps alternatives and awesome-ai-apps alternatives (awesome-ai-apps markdown twin, awesome-ai-apps 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, awesome-ai-apps or awesome-ai-apps?
- awesome-ai-apps: Very active. awesome-ai-apps: 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 awesome-ai-apps and awesome-ai-apps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-ai-apps trust report; awesome-ai-apps trust report.