--- title: "openagent vs selfhost-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/haohao-end-openagent-vs-kossakovsky-selfhost-ai" tools: ["haohao-end-openagent", "kossakovsky-selfhost-ai"] --- # openagent vs selfhost-ai *GraphCanon updated Jul 12, 2026* ## Verdict Pick openagent when openagent is primarily Python; selfhost-ai is Shell; pick selfhost-ai when selfhost-ai is primarily Shell; openagent is Python. [openagent](https://openllm.cloud) reports 828 GitHub stars, 80 forks, and 45 open issues, last pushed Jun 24, 2026. [selfhost-ai](https://github.com/kossakovsky/selfhost-ai#readme) has 897 stars, 228 forks, and 0 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [openagent's repository](https://github.com/Haohao-end/openagent) and [selfhost-ai's repository](https://github.com/kossakovsky/selfhost-ai). | | [openagent](/tools/haohao-end-openagent.md) | [selfhost-ai](/tools/kossakovsky-selfhost-ai.md) | | --- | --- | --- | | Tagline | What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation. | 🚀 Self-hosted AI automation platform. Deploy n8n, Ollama, Flowise, RAG, Supabase & 30+ tools with one command. Auto HTTPS. Free Zapier/Make alternative. | | Stars | 828 | 897 | | Forks | 80 | 228 | | Open issues | 45 | 0 | | Language | Python | Shell | | Adopt for | OpenAgent is a comprehensive platform for developers working on vertical AI agents and requires multiple setup steps including Docker, database configurations, and environment variables. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, LLM Frameworks, Vector Databases | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openagent](/tools/haohao-end-openagent.md) | [selfhost-ai](/tools/kossakovsky-selfhost-ai.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 16d | 1d | | Open issues (now) | 45 | 0 | | Security scan | No MCP manifest | No lockfile | | Full report | [trust report](/tools/haohao-end-openagent/trust.md) | [trust report](/tools/kossakovsky-selfhost-ai/trust.md) | ## Decision facts: openagent - **Requirements:** Requires Docker; Requires multiple keys for operation such as JWT_SECRET_KEY, POSTGRES_PASSWORD, REDIS_PASSWORD, WEAVIATE_API_KEY, and at least one provider API key. - **Adopt for:** OpenAgent is a comprehensive platform for developers working on vertical AI agents and requires multiple setup steps including Docker, database configurations, and environment variables. ## Choose when ### Choose openagent if… - openagent is primarily Python; selfhost-ai is Shell. - License: openagent is MIT, selfhost-ai is Apache-2.0. - Requirements: Requires Docker; Requires multiple keys for operation such as JWT_SECRET_KEY, POSTGRES_PASSWORD, REDIS_PASSWORD, WEAVIATE_API_KEY, and at least one provider API key.. - Tags unique to openagent: agent, celery, deepagents, deepresearch. - Use OpenAgent when you need to build AI agents that can perform deep reasoning tasks within specific industry domains leveraging visual workflows. ### Choose selfhost-ai if… - selfhost-ai is primarily Shell; openagent is Python. - License: selfhost-ai is Apache-2.0, openagent is MIT. - Tags unique to selfhost-ai: ai-agents, automation, chatgpt-alternative, dify. ## When NOT to use openagent - Avoid OpenAgent if your team lacks experience with Docker and setting up environment variables as outlined in the installation guide. - Do not use if developing lightweight AI agents that do not require complex reasoning loops or RAG, as this platform may introduce unnecessary complexity to simpler applications. ## When NOT to use selfhost-ai - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between openagent and selfhost-ai? openagent: What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation.. selfhost-ai: 🚀 Self-hosted AI automation platform. Deploy n8n, Ollama, Flowise, RAG, Supabase & 30+ tools with one command. Auto HTTPS. Free Zapier/Make alternative.. See the comparison table for live GitHub stats and shared categories. ### When should I choose openagent over selfhost-ai? Choose openagent over selfhost-ai when openagent is primarily Python; selfhost-ai is Shell; License: openagent is MIT, selfhost-ai is Apache-2.0; Requirements: Requires Docker; Requires multiple keys for operation such as JWT_SECRET_KEY, POSTGRES_PASSWORD, REDIS_PASSWORD, WEAVIATE_API_KEY, and at least one provider API key.; Tags unique to openagent: agent, celery, deepagents, deepresearch; Use OpenAgent when you need to build AI agents that can perform deep reasoning tasks within specific industry domains leveraging visual workflows. ### When should I choose selfhost-ai over openagent? Choose selfhost-ai over openagent when selfhost-ai is primarily Shell; openagent is Python; License: selfhost-ai is Apache-2.0, openagent is MIT; Tags unique to selfhost-ai: ai-agents, automation, chatgpt-alternative, dify. ### When should I avoid openagent? Avoid OpenAgent if your team lacks experience with Docker and setting up environment variables as outlined in the installation guide. Do not use if developing lightweight AI agents that do not require complex reasoning loops or RAG, as this platform may introduce unnecessary complexity to simpler applications. ### When should I avoid selfhost-ai? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is openagent or selfhost-ai more popular on GitHub? selfhost-ai has more GitHub stars (897 vs 828). Stars measure visibility, not whether either tool fits your constraints. ### Are openagent and selfhost-ai open source? Yes - both are open-source projects on GitHub (openagent: MIT, selfhost-ai: Apache-2.0). ### Where can I find alternatives to openagent or selfhost-ai? GraphCanon lists graph-backed alternatives at [openagent alternatives](/tools/haohao-end-openagent/alternatives) and [selfhost-ai alternatives](/tools/kossakovsky-selfhost-ai/alternatives) ([openagent markdown twin](/tools/haohao-end-openagent/alternatives.md), [selfhost-ai markdown twin](/tools/kossakovsky-selfhost-ai/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/haohao-end-openagent-vs-kossakovsky-selfhost-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openagent or selfhost-ai? openagent: Active. selfhost-ai: 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 openagent and selfhost-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openagent trust report](/tools/haohao-end-openagent/trust); [selfhost-ai trust report](/tools/kossakovsky-selfhost-ai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=haohao-end-openagent`](/api/graphcanon/graph?tool=haohao-end-openagent) - 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/_