by zmedelis · Agent Tool · ★ 366
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Tooling to build LLM applications: prompt templating and composition, agents, LLM memory, and other instruments for builders of AI applications.
| Stars | 366 |
| Forks | 28 |
| Language | Clojure |
| Category | Agent Tool |
| License | EPL-1.0 |
| Quality Score | 41.75/100 |
| Open Issues | 4 |
| Last Updated | 2026-01-08 |
| Created | 2023-01-01 |
| Est. Tokens | ~520k |
Looking for a bosquet alternative? If you're comparing bosquet with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, prov
The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for ca
A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
Integrating AI into every workflow with our open-source, no-code platform, powered by the actor model for dyna
Find, benchmark and install in CLI 170+ FREE coding LLM models across 15+ providers in real time
[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with
Explore other popular agent tool tools:
bosquet is Tooling to build LLM applications: prompt templating and composition, agents, LLM memory, and other instruments for builders of AI applications.. It is categorized as a Agent Tool with 366 GitHub stars.
bosquet is primarily written in Clojure. It covers topics such as ai, clojure, gpt.
You can find installation instructions and usage details in the bosquet GitHub repository at github.com/zmedelis/bosquet. The project has 366 stars and 28 forks, indicating an active community.
bosquet is released under the EPL-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to bosquet on Agent Skills Hub include langtrace, gateway, awesome-azure-openai-llm. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.