llm_agents vs agency

Common questions

What is the difference between llm_agents and agency?

llm_agents: Library to build agents controlled by LLMs. agency: Library for exploring Large Language Models and generative AI in Go. See the comparison table for live GitHub stats and shared categories.

When should I choose llm_agents over agency?

Choose llm_agents over agency when llm_agents is primarily Python; agency is Go; Requirements: Min 1 GB RAM; Requires the installation of requirements specified by running pip install -r requirements.txt followed by pip install -e ..; Dependencies include setting up environment variables for OPENAI_API_KEY to use OpenAI API and optionally SERPAPI_API_KEY if Google search tool is utilized.; Tags unique to llm_agents: deep-learning, langchain, llms, machine-learning; Use llm_agents when you require a lightweight solution for building agents controlled by LLMs with specific tools such as Python REPL execution or Hacker News search.

When should I choose agency over llm_agents?

Choose agency over llm_agents when agency is primarily Go; llm_agents is Python; Pricing: Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository.; Tags unique to agency: agents, generative-ai, go, language models; Also covers LLM Frameworks; If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency.

When should I avoid llm_agents?

Avoid llm_agents if you need a more robust and feature-rich product for complex tasks that require extensive integration capabilities beyond Python REPL, Google search, and Hacker News. Do not choose it when you are looking for advanced abstraction layers like those found in LangChain, as llm_agents aims to remain simple with fewer files and a straightforward core.

When should I avoid agency?

Avoid agency if your primary programming expertise lies outside of the Go ecosystem. Not recommended if you require real-time performance characteristics that surpass what typical LLM exploration libraries can provide.

Is llm_agents or agency more popular on GitHub?

llm_agents has more GitHub stars (1,054 vs 514). Stars measure visibility, not whether either tool fits your constraints.

Are llm_agents and agency open source?

Yes - both are open-source projects on GitHub (llm_agents: MIT, agency: MIT).

Where can I find alternatives to llm_agents or agency?

GraphCanon lists graph-backed alternatives at llm_agents alternatives and agency alternatives (llm_agents markdown twin, agency 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, llm_agents or agency?

llm_agents: Dormant. agency: 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 llm_agents and agency?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm_agents trust report; agency trust report.