--- title: "awesome-ai-apps vs gateway" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arindam200-awesome-ai-apps-vs-trylonai-gateway" tools: ["arindam200-awesome-ai-apps", "trylonai-gateway"] --- # awesome-ai-apps vs gateway *GraphCanon updated Jul 15, 2026* ## Verdict Pick awesome-ai-apps when license: awesome-ai-apps is MIT, gateway is Other; pick gateway when license: gateway is Other, awesome-ai-apps is MIT. [awesome-ai-apps](https://raah.dev) reports 13k GitHub stars, 1.7k forks, and 79 open issues, last pushed Jun 28, 2026. [gateway](https://www.trylon.ai) has 126 stars, 12 forks, and 0 open issues, last pushed Jun 25, 2025. Figures are from public GitHub metadata via [awesome-ai-apps's repository](https://github.com/Arindam200/awesome-ai-apps) and [gateway's repository](https://github.com/trylonai/gateway). | | [awesome-ai-apps](/tools/arindam200-awesome-ai-apps.md) | [gateway](/tools/trylonai-gateway.md) | | --- | --- | --- | | Tagline | A collection of projects showcasing RAG, agents, workflows, and other AI use cases | Self-hosted firewall for securing AI applications with guardrails and content moderation. | | Stars | 13,064 | 126 | | Forks | 1,677 | 12 | | Open issues | 79 | 0 | | Language | Python | Python | | Adopt for | - | Self-hosted firewall for securing AI applications with guardrails and content moderation. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | AI Agents, Developer Tools, LLM Frameworks | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-ai-apps](/tools/arindam200-awesome-ai-apps.md) | [gateway](/tools/trylonai-gateway.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 12d | 385d | | Open issues (now) | 79 | 0 | | Owner type | User | Organization | | Full report | [trust report](/tools/arindam200-awesome-ai-apps/trust.md) | [trust report](/tools/trylonai-gateway/trust.md) | ## Decision facts: gateway - **Pricing:** freemium - Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment - **Requirements:** Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time - **Adopt for:** Self-hosted firewall for securing AI applications with guardrails and content moderation. ## Choose when ### Choose awesome-ai-apps if… - License: awesome-ai-apps is MIT, gateway is Other. - Tags unique to awesome-ai-apps: agents, ai, hacktoberfest, llm. - Also covers AI Agents, Developer Tools. ### Choose gateway if… - License: gateway is Other, awesome-ai-apps is MIT. - Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment. - Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time. - Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction. - Also covers Evaluation & Observability. - gateway ships Docker support for self-hosted deployment. - When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker ## When NOT to use awesome-ai-apps - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use gateway - Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments - Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security ## Common questions ### What is the difference between awesome-ai-apps and gateway? awesome-ai-apps: A collection of projects showcasing RAG, agents, workflows, and other AI use cases. gateway: Self-hosted firewall for securing AI applications with guardrails and content moderation.. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-ai-apps over gateway? Choose awesome-ai-apps over gateway when License: awesome-ai-apps is MIT, gateway is Other; Tags unique to awesome-ai-apps: agents, ai, hacktoberfest, llm; Also covers AI Agents, Developer Tools. ### When should I choose gateway over awesome-ai-apps? Choose gateway over awesome-ai-apps when License: gateway is Other, awesome-ai-apps is MIT; Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment; Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time; Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction; Also covers Evaluation & Observability; gateway ships Docker support for self-hosted deployment; When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker. ### When should I avoid awesome-ai-apps? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid gateway? Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security ### Is awesome-ai-apps or gateway more popular on GitHub? awesome-ai-apps has more GitHub stars (13,064 vs 126). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-ai-apps and gateway open source? Yes - both are open-source projects on GitHub (awesome-ai-apps: MIT, gateway: Other). ### Where can I find alternatives to awesome-ai-apps or gateway? GraphCanon lists graph-backed alternatives at [awesome-ai-apps alternatives](/tools/arindam200-awesome-ai-apps/alternatives) and [gateway alternatives](/tools/trylonai-gateway/alternatives) ([awesome-ai-apps markdown twin](/tools/arindam200-awesome-ai-apps/alternatives.md), [gateway markdown twin](/tools/trylonai-gateway/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/arindam200-awesome-ai-apps-vs-trylonai-gateway.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-ai-apps or gateway? awesome-ai-apps: Active. gateway: Dormant. 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 gateway? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-ai-apps trust report](/tools/arindam200-awesome-ai-apps/trust); [gateway trust report](/tools/trylonai-gateway/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arindam200-awesome-ai-apps`](/api/graphcanon/graph?tool=arindam200-awesome-ai-apps) - 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/_