yomo

# YoMo [](https://codecov.io/gh/yomorun/yomo) YoMo is an open-source LLM Function Calling Framework for building scalable and ultra-fast AI Agents. We care about: **Empowering Exceptional Customer Experiences in the Age of AI** We believe that seamless and responsive AI interactions are key to delivering outstanding customer experiences. YoMo is built with this principle at its core, focusing on speed, reliability, and scalability. ## Features | | **Features** | | | -- | ------------ | -- | | ⚡️ | **Serverless LLM Tools** | Deploy and Manage LLM Tools / Skills seamlessly. | | | **Enhanced Security** | TLS v1.3 encryption is applied to every data packet by design, ensuring robust security for your AI agent communications. | | | **Effortless Agents DevOps** | Streamline the entire lifecycle of your LLM tools, from development to deployment. Significantly reduces operational overhead, allowing you to focus exclusively on creating innovative AI agent functionalities. | | | **Geo-Distributed Architecture** | Bring AI inference and tools closer to your users with our globally distributed architecture, resulting in significantly faster response times and a superior user experience for your AI agents. | ## Getting Started Let's build a simple AI agent with LLM Function Calling to provide weather information: ### Step 1. Install CLI ```sh curl -fsSL https://get.yomo.run | sh ``` Verify the installation: ```sh yomo --version ``` ### Step 2. Start the server Use Ollama as the LLM provider: ```sh ollama pull ornith ``` Launch the server: ```sh yomo serve ``` You can also use the `--config` flag to specify a custom coniguration yaml file. ### Step 3. Implement the LLM Function Calling ```sh yomo init ``` Finished, now, let's run it: ```bash yomo run -n get-weather ./app ``` ### Done, let's have a try ```sh curl http://127.0.0.1:9001/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "messages": [ { "role": "user", "content": "I am going for a hike on the Yarra Bend Park Loop. What should I wear?" } ] }' ``` You'll receive a helpful response like this: ``` … ``` ### Explore More Examples Check out our [Servereless LLM Function Calling Examples](https://github.com/yomorun/llm-function-calling-examples) for more use cases and inspiration. ## Documentation Read more about YoMo on [yomo.run](https://yomo.run/). ## Focuses on Geo-distributed AI Inference Infra It’s no secret that today’s users want instant AI inference, every AI application is more powerful when it response quickly. But, currently, when we talk about `distribution`, it represents **distribution in data center**. The AI model is far away from their users from all over the world. If an application can be deployed anywhere close to their end users, solve the problem, this is **Geo-distributed System Architecture**: ## Contributing First off, thank you for considering making contributions. It's people like you that make YoMo better. There are many ways in which you can participate in the project, for example: - File a [bug report](https://github.com/yomorun/yomo/issues/new?assignees=&labels=bug&template=bug_report.md&title=%5BBUG%5D). Be sure to include information like what version of YoMo you are using, what your operating system is, and steps to recreate the bug. - Suggest a new feature. - Read our [contributing guidelines](https://github.com/yomorun/yomo/blob/master/CONTRIBUTING.md) to learn about what types of contributions we are looking for. - We have also adopted a [code of conduct](https://github.com/yomorun/yomo/blob/master/CODE_OF_CONDUCT.md) that we expect project participants to adhere to. ## Devleopment - Build ```sh cargo build --release ./target/release/yomo --help ``` - Use Ollama as the LLM provider: ```sh ollama pull ornith ``` - Run YoMo server: ```sh ./target/release/yomo serve ``` - Initialize a Serverless LLM Tool project: ```sh ./target/release/yomo init ``` then edit `./app/src/app.ts` in the project. - Run YoMo serverless tool: ```sh ./target/release/yomo run --name get-weather ./app ``` - Send a request to the LLM agent: ```sh curl \ --request POST \ --url http://127.0.0.1:9001/v1/chat/completions \ --header 'Content-Type: application/json' \ --data '{ "messages": [ { "role": "user", "content": "How is the weather in London?" } ] }' ``` - Send a request to the serverless function directly: ```sh curl \ --request POST \ --url http://127.0.0.1:9001/tool/get-weather \ --header 'Content-Type: application/json' \ --data '{ "args":"{\"city\":\"London\"}" }' ``` ## License [Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0.html)