Translated🎭 277 plug-and-play AI expert roles — supporting 20 tools such as Claude Code/Cursor/Copilot, covering 20 departments including engineering/design/marketing/finance. Includes 64 original agents for the Chinese market (Xiaohongshu/Douyin/WeChat/Feishu/DingTalk/Qt host computer software/mechanical design). Paired with the orchestrator agency-orchestrator, a single sentence lets multiple experts collaborate automatically as a DAG.
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TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/
TranslatedUsing dense-compute cards to accelerate sparse, large-VRAM hosts, where the hosts include AI Max+ 395, M3 512G, DGX Spark, and others.
- llama-cpp
- pipeline-parallelism
- prefill-decode
- rtx-3060
A comprehensive observability solution for monitoring Claude Code usage, performance, and costs.
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.
Ruby library for defining, generating and validating JSON Schema
- anthropic-api
- json-api
- json-schema
- openai-api
Spends CPU cycles so you don't spend tokens. The LLM gets a briefing packet instead of a flashlight in a dark room.
Lightweight AI agent runtime for Go. Define multi-agent crews in YAML, run them with goroutines and channels, and let the runtime handle scheduling, parallelism, retries, and observability — without leaving the Go ecosystem.
Package to set up autonomous agents to trade on TBD
- agents
- agents-md
- ai-agents
- autonomous-agents