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Gemini-agent-example

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Multi-Agent Platforms & Frameworks
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Basic Information

This repository is a hands-on demonstration showing how to use Google's Gemini language model inside an application. It is presented as a free online agent example and includes a ready-to-run Jupyter/Colab notebook named Gemini_agents.ipynb that users can modify. The primary aim is to let developers and experimenters build simple language-based agents and utilities without using an OpenAI API key, leveraging free access to Gemini when billing is disabled. The README highlights common example tasks such as chatbots, search engine interfaces, and calculators while noting that the project is open source and licensed under the MIT License. The repository targets people who want a quick, runnable template to experiment with Gemini on Google Colab or on local low-powered machines.

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App URL
https://github.com/MikeChan-HK/Gemini-agent-example
Github Repository
https://github.com/MikeChan-HK/Gemini-agent-example/blob/main/README.md

App Details

Features
Contains a runnable example notebook Gemini_agents.ipynb designed for Jupyter Notebook or Google Colab. Demonstrates practical agent use cases such as chat interfaces, simple search tools, and calculator-style language tasks. Emphasizes free usage of Google Gemini API for projects with billing disabled. Provides basic getting started steps: clone the repository and open the notebook in Colab or Jupyter. The project is open source under the MIT License and welcomes contributions via pull requests. README mentions that the examples run on low-end hardware and on iPad-friendly environments. The repository focuses on being an accessible, minimal template rather than a full production framework.
Use Cases
This project helps developers and learners prototype language agents quickly by providing a concrete, editable notebook that integrates with Google Gemini. It reduces entry barriers by showing how to run examples on free Google Colab or modest local machines and by avoiding the need for an OpenAI API key. Users can adapt the notebook to build simple chatbots, search wrappers, or calculator assistants and use it as a starting point for experiments or educational demonstrations. The MIT License and invitation to contribute make it easy to fork and extend. The README"s step-by-step clone and run instructions simplify onboarding for non-expert users.

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