lexido
A terminal assistant, powered by Generative AI
Stars: 201
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.
README:
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.
-
Command Suggestions: Simply type
lexido [prompt]
to get actionable command suggestions. - Cross-Platform: Support for both Linux and macOS
-
Continued Conversations: Use
lexido -c [prompt]
to continue a previous conversation, allowing for context-aware suggestions. -
Piping Support: Pipe commands into Lexido (e.g.,
ls | lexido [prompt]
) for enhanced command list suggestions. - Efficiency: Designed with efficiency in mind, Lexido helps you get things done NOW.
Lexido is available on the AUR. Install it using the package manager of your choice such as:
yay -S lexido
Lexido is available on homebrew. Install it using the brew
command:
brew install lexido
Head to the releases tab to pick up a binary! Once downloaded, you'll want to make Lexido easily accessible from anywhere on your computer. Here's how:
-
Rename the downloaded file:
The downloaded file might have a long and specific name, like "v1.0-lexido-linux-amd64". For easier use, consider renaming it to just "lexido".
-
Make the file executable:
Open your terminal and navigate to the folder where you downloaded the Lexido binary. Then, run the following command to make the file executable:
chmod +x ./lexido
-
Move the file to your system's path:
Why do this? By placing the renamed and executable Lexido file in your system's path, you can run it from any terminal window without needing to specify the full path to the file. It's a shortcut for convenience!
Here's an example command assuming you downloaded Lexido to your Downloads folder:
mv ~/Downloads/lexido /usr/local/bin/lexido
Ensure you have Go installed on your system. Follow these steps to install Lexido:
- Clone the Lexido repository:
git clone https://github.com/micr0-dev/lexido.git
- Navigate to the Lexido directory:
cd lexido
- Build the project:
go build
- Optionally, move the Lexido binary to a location in your PATH for easy access.
If you want to run lexido completely locally you can do that as of version 1.3! This is done via Ollama, a tool for easily running large language models locally. It does all the hard work of installing LLMs for you!
You can install Ollama as follows:
curl -fsSL https://ollama.com/install.sh | sh
Running lexido locally is as easy as adding the -l
flag when you want to run locally, or using --setLocal
to run locally by default! You can also select the model you want to run with -m
and again set it to be the default with --setModel
. Be sure you have the model installed before attempting to run it with lexido however!
This guide provides instructions on how to create and customize the JSON configuration files necessary for API integration within lexido. Each configuration allows the application to interact with a different external API by specifying endpoints, headers, data templates, and specific fields to extract from API responses.
The default configuration template is provided as a baseline. This template includes placeholders that should be customized based on the specific API you want to integrate with.
{
"api_config": {
"url": "https://api.example.com/endpoint/v1/chat/completions",
"headers": {
"Content-Type": "application/json",
"Accept": "application/json"
},
"data_template": {
"model": "example-model",
"messages": "<PROMPT>"
},
"field_to_extract": "response"
}
}
- url: The endpoint URL of the API you are calling.
-
headers: HTTP headers to include with your request. Common headers include
Content-Type
andAccept
. -
data_template: The data body of your request.
<PROMPT>
will be replaced dynamically by the application. - field_to_extract: The field within the API response from which data should be extracted.
Below is an example configuration specifically set up for interacting with the oLlama API, which is assumed to run locally.
{
"api_config": {
"url": "http://localhost:11434/api/generate",
"headers": {
"Content-Type": "application/json",
"Accept": "application/json"
},
"data_template": {
"model": "llama3",
"prompt": "<PROMPT>"
},
"field_to_extract": "response"
}
}
-
Model: Depending on the capabilities of the API, you might need to change the
model
value to match the model provided by the API service. -
Prompt: The
<PROMPT>
placeholder indata_template
will be replaced with the actual query or command you wish to send to the API.
To create your own configuration:
- Copy the default configuration template. The location for the config is
~/.lexido/remoteConfig.json
- Replace the
url
,headers
,data_template
, andfield_to_extract
fields as needed for your specific API. - Ensure all placeholders like
<PROMPT>
are appropriately positioned where dynamic content is expected to be inserted by the application.
This configuration system is designed to be flexible and extendable, allowing for easy integration with various APIs by simply modifying the JSON configuration files. For advanced configurations, you may need to adjust additional parameters.
- To get command suggestions:
lexido "install teamspeak via docker"
- To continue with a previous prompt:
lexido -c "add more details or follow-up"
- To use with piping commands:
ls | lexido "what should I do with these files?"
The binary's size mainly consists of the built-in networking and encryption libraries of Go. A quick inspection showcases this:
> goweight
12 MB runtime
8.1 MB net/http
5.3 MB google.golang.org/protobuf/internal/impl
4.1 MB net
4.1 MB golang.org/x/net/http2
3.9 MB golang.org/x/sys/unix
3.7 MB crypto/tls
3.3 MB google.golang.org/grpc
Before requesting the LLM the program does what is known as prompt building or contextualization, it collects different data about your system and your current scenario to help the LLM more accurately answer. Giving the LLM context about your situation allows it to better understand what you are asking or how to reply.
If you have any more questions feel free to reach out and ask
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
If you use and enjoy lexido, you can buy me a coffee as a thank you! https://ko-fi.com/micr0byte
Distributed under the GNU Affero General Public License v3.0 or any later version. See LICENSE
for more information.
- Gemini Pro 1.0 for the LLM powering Lexido.
Made with 💚 by Micr0byte
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for lexido
Similar Open Source Tools
lexido
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.
bedrock-claude-chat
This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.
aimeos-typo3
Aimeos is a professional, full-featured, and high-performance e-commerce extension for TYPO3. It can be installed in an existing TYPO3 website within 5 minutes and can be adapted, extended, overwritten, and customized to meet specific needs.
june
june-va is a local voice chatbot that combines Ollama for language model capabilities, Hugging Face Transformers for speech recognition, and the Coqui TTS Toolkit for text-to-speech synthesis. It provides a flexible, privacy-focused solution for voice-assisted interactions on your local machine, ensuring that no data is sent to external servers. The tool supports various interaction modes including text input/output, voice input/text output, text input/audio output, and voice input/audio output. Users can customize the tool's behavior with a JSON configuration file and utilize voice conversion features for voice cloning. The application can be further customized using a configuration file with attributes for language model, speech-to-text model, and text-to-speech model configurations.
chatgpt-vscode
ChatGPT-VSCode is a Visual Studio Code integration that allows users to prompt OpenAI's GPT-4, GPT-3.5, GPT-3, and Codex models within the editor. It offers features like using improved models via OpenAI API Key, Azure OpenAI Service deployments, generating commit messages, storing conversation history, explaining and suggesting fixes for compile-time errors, viewing code differences, and more. Users can customize prompts, quick fix problems, save conversations, and export conversation history. The extension is designed to enhance developer experience by providing AI-powered assistance directly within VS Code.
aiconfig
AIConfig is a framework that makes it easy to build generative AI applications for production. It manages generative AI prompts, models and model parameters as JSON-serializable configs that can be version controlled, evaluated, monitored and opened in a local editor for rapid prototyping. It allows you to store and iterate on generative AI behavior separately from your application code, offering a streamlined AI development workflow.
patchwork
PatchWork is an open-source framework designed for automating development tasks using large language models. It enables users to automate workflows such as PR reviews, bug fixing, security patching, and more through a self-hosted CLI agent and preferred LLMs. The framework consists of reusable atomic actions called Steps, customizable LLM prompts known as Prompt Templates, and LLM-assisted automations called Patchflows. Users can run Patchflows locally in their CLI/IDE or as part of CI/CD pipelines. PatchWork offers predefined patchflows like AutoFix, PRReview, GenerateREADME, DependencyUpgrade, and ResolveIssue, with the flexibility to create custom patchflows. Prompt templates are used to pass queries to LLMs and can be customized. Contributions to new patchflows, steps, and the core framework are encouraged, with chat assistants available to aid in the process. The roadmap includes expanding the patchflow library, introducing a debugger and validation module, supporting large-scale code embeddings, parallelization, fine-tuned models, and an open-source GUI. PatchWork is licensed under AGPL-3.0 terms, while custom patchflows and steps can be shared using the Apache-2.0 licensed patchwork template repository.
sdfx
SDFX is the ultimate no-code platform for building and sharing AI apps with beautiful UI. It enables the creation of user-friendly interfaces for complex workflows by combining Comfy workflow with a UI. The tool is designed to merge the benefits of form-based UI and graph-node based UI, allowing users to create intricate graphs with a high-level UI overlay. SDFX is fully compatible with ComfyUI, abstracting the need for installing ComfyUI. It offers features like animated graph navigation, node bookmarks, UI debugger, custom nodes manager, app and template export, image and mask editor, and more. The tool compiles as a native app or web app, making it easy to maintain and add new features.
morphic
Morphic is an AI-powered answer engine with a generative UI. It utilizes a stack of Next.js, Vercel AI SDK, OpenAI, Tavily AI, shadcn/ui, Radix UI, and Tailwind CSS. To get started, fork and clone the repo, install dependencies, fill out secrets in the .env.local file, and run the app locally using 'bun dev'. You can also deploy your own live version of Morphic with Vercel. Verified models that can be specified to writers include Groq, LLaMA3 8b, and LLaMA3 70b.
rag-gpt
RAG-GPT is a tool that allows users to quickly launch an intelligent customer service system with Flask, LLM, and RAG. It includes frontend, backend, and admin console components. The tool supports cloud-based and local LLMs, enables deployment of conversational service robots in minutes, integrates diverse knowledge bases, offers flexible configuration options, and features an attractive user interface.
ChatGPT
The ChatGPT API Free Reverse Proxy provides free self-hosted API access to ChatGPT (`gpt-3.5-turbo`) with OpenAI's familiar structure, eliminating the need for code changes. It offers streaming response, API endpoint compatibility, and complimentary access without an API key. Installation options include Docker, PC/Server, and Termux on Android devices. The API can be accessed through a self-hosted local server or a pre-hosted API with an API key obtained from the Discord server. Usage examples are provided for Python and Node.js, and the project is licensed under AGPL-3.0.
magic-cli
Magic CLI is a command line utility that leverages Large Language Models (LLMs) to enhance command line efficiency. It is inspired by projects like Amazon Q and GitHub Copilot for CLI. The tool allows users to suggest commands, search across command history, and generate commands for specific tasks using local or remote LLM providers. Magic CLI also provides configuration options for LLM selection and response generation. The project is still in early development, so users should expect breaking changes and bugs.
agnai
Agnaistic is an AI roleplay chat tool that allows users to interact with personalized characters using their favorite AI services. It supports multiple AI services, persona schema formats, and features such as group conversations, user authentication, and memory/lore books. Agnaistic can be self-hosted or run using Docker, and it provides a range of customization options through its settings.json file. The tool is designed to be user-friendly and accessible, making it suitable for both casual users and developers.
shell-ai
Shell-AI (`shai`) is a CLI utility that enables users to input commands in natural language and receive single-line command suggestions. It leverages natural language understanding and interactive CLI tools to enhance command line interactions. Users can describe tasks in plain English and receive corresponding command suggestions, making it easier to execute commands efficiently. Shell-AI supports cross-platform usage and is compatible with Azure OpenAI deployments, offering a user-friendly and efficient way to interact with the command line.
aiexe
aiexe is a cutting-edge command-line interface (CLI) and graphical user interface (GUI) tool that integrates powerful AI capabilities directly into your terminal or desktop. It is designed for developers, tech enthusiasts, and anyone interested in AI-powered automation. aiexe provides an easy-to-use yet robust platform for executing complex tasks with just a few commands. Users can harness the power of various AI models from OpenAI, Anthropic, Ollama, Gemini, and GROQ to boost productivity and enhance decision-making processes.
rclip
rclip is a command-line photo search tool powered by the OpenAI's CLIP neural network. It allows users to search for images using text queries, similar image search, and combining multiple queries. The tool extracts features from photos to enable searching and indexing, with options for previewing results in supported terminals or custom viewers. Users can install rclip on Linux, macOS, and Windows using different installation methods. The repository follows the Conventional Commits standard and welcomes contributions from the community.
For similar tasks
lexido
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.
AgentForge
AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.
OSWorld
OSWorld is a benchmarking tool designed to evaluate multimodal agents for open-ended tasks in real computer environments. It provides a platform for running experiments, setting up virtual machines, and interacting with the environment using Python scripts. Users can install the tool on their desktop or server, manage dependencies with Conda, and run benchmark tasks. The tool supports actions like executing commands, checking for specific results, and evaluating agent performance. OSWorld aims to facilitate research in AI by providing a standardized environment for testing and comparing different agent baselines.
tgpt
tgpt is a cross-platform command-line interface (CLI) tool that allows users to interact with AI chatbots in the Terminal without needing API keys. It supports various AI providers such as KoboldAI, Phind, Llama2, Blackbox AI, and OpenAI. Users can generate text, code, and images using different flags and options. The tool can be installed on GNU/Linux, MacOS, FreeBSD, and Windows systems. It also supports proxy configurations and provides options for updating and uninstalling the tool.
CLI
Bito CLI provides a command line interface to the Bito AI chat functionality, allowing users to interact with the AI through commands. It supports complex automation and workflows, with features like long prompts and slash commands. Users can install Bito CLI on Mac, Linux, and Windows systems using various methods. The tool also offers configuration options for AI model type, access key management, and output language customization. Bito CLI is designed to enhance user experience in querying AI models and automating tasks through the command line interface.
oaic
Open AI Cellular is the core software for Open AI Cellular. It provides documentation on installation, quick start guide, and usage. The repository contains submodules and requires sphinx with the read-the-docs theme for building core documentation. The resulting documentation is stored in the 'docs/build/html' directory.
llm2sh
llm2sh is a command-line utility that leverages Large Language Models (LLMs) to translate plain-language requests into shell commands. It provides a convenient way to interact with your system using natural language. The tool supports multiple LLMs for command generation, offers a customizable configuration file, YOLO mode for running commands without confirmation, and is easily extensible with new LLMs and system prompts. Users can set up API keys for OpenAI, Claude, Groq, and Cerebras to use the tool effectively. llm2sh does not store user data or command history, and it does not record or send telemetry by itself, but the LLM APIs may collect and store requests and responses for their purposes.
Avalonia-Assistant
Avalonia-Assistant is an open-source desktop intelligent assistant that aims to provide a user-friendly interactive experience based on the Avalonia UI framework and the integration of Semantic Kernel with OpenAI or other large LLM models. By utilizing Avalonia-Assistant, you can perform various desktop operations through text or voice commands, enhancing your productivity and daily office experience.
For similar jobs
lexido
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.
kaito
Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.
ai-on-gke
This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources
tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
nvidia_gpu_exporter
Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.
tracecat
Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.
openinference
OpenInference is a set of conventions and plugins that complement OpenTelemetry to enable tracing of AI applications. It provides a way to capture and analyze the performance and behavior of AI models, including their interactions with other components of the application. OpenInference is designed to be language-agnostic and can be used with any OpenTelemetry-compatible backend. It includes a set of instrumentations for popular machine learning SDKs and frameworks, making it easy to add tracing to your AI applications.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students