--- title: "gpt-home vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/judahpaul16-gpt-home-vs-pguso-agents-from-scratch" tools: ["judahpaul16-gpt-home", "pguso-agents-from-scratch"] --- # gpt-home vs agents-from-scratch *GraphCanon updated Sep 20, 2026* ## Verdict Pick gpt-home if gpt-home offers DIY enthusiasts and Python developers a guide to set up personalized smart home assistants with LiteLLM and LangGraph on Raspberry Pi, aiming for greater customization compared to commercial offerings; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning. [gpt-home](https://hub.docker.com/r/judahpaul/gpt-home) reports 649 GitHub stars, 68 forks, and 0 open issues, last pushed Sep 13, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 1.0k stars, 251 forks, and 4 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [gpt-home's repository](https://github.com/judahpaul16/gpt-home) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [gpt-home](/tools/judahpaul16-gpt-home.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | Create personalized smart home assistants with ChatGPT on Raspberry Pi | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 649 | 1,017 | | Forks | 68 | 251 | | Open issues | 0 | 4 | | Language | Python | Python | | Adopt for | gpt-home offers DIY enthusiasts and Python developers a guide to set up personalized smart home assistants with LiteLLM and LangGraph on Raspberry Pi, aiming for greater customization compared to commercial offerings. | agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | AI Agents, Model Training | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gpt-home](/tools/judahpaul16-gpt-home.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 6d | 56d | | Open issues (now) | 0 | 4 | | Stars delta | +5 (30d) | +63 (30d) | | Open issues delta | 0 (30d) | +1 (30d) | | Full report | [trust report](/tools/judahpaul16-gpt-home/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: gpt-home - **Adopt for:** gpt-home offers DIY enthusiasts and Python developers a guide to set up personalized smart home assistants with LiteLLM and LangGraph on Raspberry Pi, aiming for greater customization compared to commercial offerings. ## Decision facts: agents-from-scratch - **Requirements:** Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs. - **Adopt for:** agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. - **License detail:** MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. ## Choose when ### Choose gpt-home if… - License: gpt-home is GPL-3.0, agents-from-scratch is MIT. - Tags unique to gpt-home: ai, automation, docker, fastapi. - Also covers Model Training. - gpt-home ships Docker support for self-hosted deployment. - If you need high customization in your smart home assistant capabilities, such as integrating unique voice commands or automations that fit your specific home environment. ### Choose agents-from-scratch if… - License: agents-from-scratch is MIT, gpt-home is GPL-3.0. - Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.. - Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm. - Also covers Developer Tools. - You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ## When NOT to use gpt-home - If rapid deployment and immediate functionality are prioritized over customization. The DIY nature requires technical skills and time investment. - In scenarios preferring commercial-grade reliability and support, where maintaining the setup can be more demanding with self-made systems. ## When NOT to use agents-from-scratch - You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. - If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ## Common questions ### What is the difference between gpt-home and agents-from-scratch? gpt-home: Create personalized smart home assistants with ChatGPT on Raspberry Pi. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose gpt-home over agents-from-scratch? Choose gpt-home over agents-from-scratch when License: gpt-home is GPL-3.0, agents-from-scratch is MIT; Tags unique to gpt-home: ai, automation, docker, fastapi; Also covers Model Training; gpt-home ships Docker support for self-hosted deployment; If you need high customization in your smart home assistant capabilities, such as integrating unique voice commands or automations that fit your specific home environment. ### When should I choose agents-from-scratch over gpt-home? Choose agents-from-scratch over gpt-home when License: agents-from-scratch is MIT, gpt-home is GPL-3.0; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm; Also covers Developer Tools; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ### When should I avoid gpt-home? If rapid deployment and immediate functionality are prioritized over customization. The DIY nature requires technical skills and time investment. In scenarios preferring commercial-grade reliability and support, where maintaining the setup can be more demanding with self-made systems. ### When should I avoid agents-from-scratch? You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ### Is gpt-home or agents-from-scratch more popular on GitHub? agents-from-scratch has more GitHub stars (1,017 vs 649). Stars measure visibility, not whether either tool fits your constraints. ### Are gpt-home and agents-from-scratch open source? Yes - both are open-source projects on GitHub (gpt-home: GPL-3.0, agents-from-scratch: MIT). ### Where can I find alternatives to gpt-home or agents-from-scratch? GraphCanon lists graph-backed alternatives at [gpt-home alternatives](/tools/judahpaul16-gpt-home/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([gpt-home markdown twin](/tools/judahpaul16-gpt-home/alternatives.md), [agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/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/judahpaul16-gpt-home-vs-pguso-agents-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gpt-home or agents-from-scratch? gpt-home: Very active. agents-from-scratch: Steady. 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 gpt-home and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gpt-home trust report](/tools/judahpaul16-gpt-home/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=judahpaul16-gpt-home`](/api/graphcanon/graph?tool=judahpaul16-gpt-home) - 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/_