A Python package designed to provide production-ready templates for Generative AI agents on Google Cloud. It allows developers to focus on agent logic by automating the surrounding infrastructure, including CI/CD pipelines, observability, security, and deployment via Cloud Run or Agent Engine.
Key features and offerings include:
- Pre-built agent templates such as ReAct, RAG (Retrieval-Augmented Generation), multi-agent systems, and real-time multimodal agents using Gemini.
- Automated CI/CD integration with Google Cloud Build and GitHub Actions.
- Data pipelines for RAG using Terraform, supporting Vertex AI Search and Vector Search.
- Support for various frameworks including Google's Agent Development Kit (ADK) and LangGraph.
- Integration with the Gemini CLI for architectural guidance directly in the terminal.
Key features and offerings include:
- Pre-built agent templates such as ReAct, RAG (Retrieval-Augmented Generation), multi-agent systems, and real-time multimodal agents using Gemini.
- Automated CI/CD integration with Google Cloud Build and GitHub Actions.
- Data pipelines for RAG using Terraform, supporting Vertex AI Search and Vector Search.
- Support for various frameworks including Google's Agent Development Kit (ADK) and LangGraph.
- Integration with the Gemini CLI for architectural guidance directly in the terminal.
llm-tool provides a command-line utility for running large language models locally. It includes scripts for pulling models from the internet, starting them, and managing them using various commands such as 'run', 'ps', 'kill', 'rm', and 'pull'. Additionally, it offers a Python script named 'querylocal.py' for querying these models. The repository also come
