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<p align="center">
<img src="https://github.com/user-attachments/assets/304ad402-5ddc-441b-a4b9-55ff9eec72be" alt="LocalAgent Logo" width="200"/>
<img src="https://github.com/user-attachments/assets/304ad402-5ddc-441b-a4b9-55ff9eec72be" alt="LocalAgent Logo" width="220"/>
</p>
<h1 align="center">LOCAL AGENT</h1>
<h3 align="center"><em>AI that stays where it belongs — on your machine.</em></h3>
<div align="center">
[![Go Report Card](https://goreportcard.com/badge/github.com/mudler/LocalAgent)](https://goreportcard.com/report/github.com/mudler/LocalAgent)
@@ -11,143 +14,140 @@
</div>
**LocalAgent** is an AI Agent platform with the aim to runs 100% locally on your machine. Designed for privacy, efficiency, and flexibility, LocalAgent allows you to build, deploy, and interact with AI agents without sending your data to external services.
## TAKE BACK CONTROL
## Features
**LocalAgent** is an AI platform that runs 100% on your hardware. No clouds. No data sharing. No compromises.
- **100% Local Execution**: All processing happens on your own hardware - no data leaves your machine
- **Multiple Model Support**: Compatible with various local LLM formats (GGUF, GGML, etc.)
- **Extensible Architecture**: Build custom agents with specialized capabilities
- **Web-based GUI**: User-friendly interface for easy interaction with your agents
- **RESTful API**: Comprehensive API for developers to integrate LocalAgent into their applications
- **Works well locally!**: It is well tested and meant to work with [LocalAI](https://github.com/mudler/LocalAI)
- **Cross-platform**: Works on Linux, macOS, and Windows
Built for those who value privacy as non-negotiable, LocalAgent lets you deploy intelligent agents that never phone home. Your data stays where you put it — period.
LocalAgent is part of a set of open source tools aimed to streamline AI usage locally, see also its sister projects:
## WHY LOCALAGENT?
- [LocalAI](https://github.com/mudler/LocalAI)
- [LocalRAG](https://github.com/mudler/LocalRAG)
- **✓ TRUE PRIVACY** — Everything runs on your hardware, nothing leaves your machine
- **✓ MODEL FREEDOM** — Works with local LLM formats (GGUF, GGML) you already have
- **✓ BUILD YOUR WAY** — Extensible architecture for custom agents with specialized skills
- **✓ SLICK INTERFACE** — Clean web UI for hassle-free agent interactions
- **✓ DEV-FRIENDLY** — Comprehensive REST API for seamless integration
- **✓ PLAYS WELL WITH OTHERS** — Optimized for [LocalAI](https://github.com/mudler/LocalAI)
- **✓ RUN ANYWHERE** — Linux, macOS, Windows — we've got you covered
## Installation
## THE LOCAL ECOSYSTEM
### Prerequisites
LocalAgent is part of a trinity of tools designed to keep AI under your control:
For building from source:
- [**LocalAI**](https://github.com/mudler/LocalAI) — Run LLMs on your hardware
- [**LocalRAG**](https://github.com/mudler/LocalRAG) — Local Retrieval-Augmented Generation
- [**LocalAgent**](https://github.com/mudler/LocalAgent) — Deploy AI agents that respect your privacy
- Go 1.20 or later
- Git
## QUICK START
### From Source
### One-Command Docker Setup
The fastest way to get everything running — LocalRAG, LocalAI, and LocalAgent pre-configured:
```bash
# Clone the repository
docker-compose up
```
> No API keys. No cloud subscriptions. No external dependencies. Just AI that works.
### Manual Launch
Run the binary and you're live:
```bash
./localagent
```
Access your agents at `http://localhost:3000`
### Environment Configuration
| Variable | What It Does |
|----------|--------------|
| `LOCALAGENT_MODEL` | Your go-to model |
| `LOCALAGENT_MULTIMODAL_MODEL` | Optional model for multimodal capabilities |
| `LOCALAGENT_LLM_API_URL` | OpenAI-compatible API server URL |
| `LOCALAGENT_API_KEY` | API authentication |
| `LOCALAGENT_TIMEOUT` | Request timeout settings |
| `LOCALAGENT_STATE_DIR` | Where state gets stored |
| `LOCALAGENT_LOCALRAG_URL` | LocalRAG connection |
| `LOCALAGENT_ENABLE_CONVERSATIONS_LOGGING` | Toggle conversation logs |
## INSTALLATION OPTIONS
### Pre-Built Binaries
Download ready-to-run binaries from the [Releases](https://github.com/mudler/LocalAgent/releases) page.
### Source Build
Requirements:
- Go 1.20+
- Git
```bash
# Clone repo
git clone https://github.com/mudler/LocalAgent.git
cd LocalAgent
# Build the application
# Build it
go build -o localagent
# Run LocalAgent
# Run it
./localagent
```
### Using Docker containers
## CONNECTORS
```bash
docker run -ti -p 3000:3000 -v quay.io/mudler/localagent
```
Link your agents to the services you already use. Configuration examples below.
### Pre-built Binaries
Download the pre-built binaries for your platform from the [Releases](https://github.com/mudler/LocalAgent/releases) page.
## Getting Started
After installation, you can start LocalAgent with default settings:
```bash
./localagent
```
This will start both the API server and the web interface. By default, the web interface is accessible at `http://localhost:3000`.
### Environment Variables
LocalAgent can be configured using the following environment variables:
| Variable | Description |
|-------------------------------|--------------------------------------------------|
| `LOCALAGENT_MODEL` | Specifies the test model to use |
| `LOCALAGENT_MULTIMODAL_MODEL` | Specifies a separate model to use with multimodal capabilities (optional, if LOCALAGENT_MODEL does not support multimodality) |
| `LOCALAGENT_LLM_API_URL` | URL of the API server |
| `LOCALAGENT_API_KEY` | API key for authentication |
| `LOCALAGENT_TIMEOUT` | Timeout duration for requests |
| `LOCALAGENT_STATE_DIR` | Directory to store state information |
| `LOCALAGENT_LOCALRAG_URL` | LocalRAG URL |
| `LOCALAGENT_ENABLE_CONVERSATIONS_LOGGING`| Enable or disable logging of conversations |
## Documentation
### Connectors
LocalAgent can be connected to a wide range of services. Each service support a set of configuration, examples are provided below for every connector.
#### Github (issues)
Create an user and a PAT token, and associate to a repository:
### GitHub Issues
```json
{
"token": "PAT_TOKEN",
"repository": "repository-to-watch-issues",
"owner": "repository-owner",
"botUserName": "username"
"token": "YOUR_PAT_TOKEN",
"repository": "repo-to-monitor",
"owner": "repo-owner",
"botUserName": "bot-username"
}
```
#### Discord
### Discord
Follow the steps in: https://discordpy.readthedocs.io/en/stable/discord.html to create a discord bot.
The token of the bot is in the "Bot" tab. Also enable " Message Content Intent " in the Bot tab!
After [creating your Discord bot](https://discordpy.readthedocs.io/en/stable/discord.html):
```json
{
"token": "Bot DISCORDTOKENHERE",
"defaultChannel": "OPTIONALCHANNELINT"
"token": "Bot YOUR_DISCORD_TOKEN",
"defaultChannel": "OPTIONAL_CHANNEL_ID"
}
```
> Don't forget to enable "Message Content Intent" in Bot settings!
#### Slack
### Slack
See slack.yaml
- Create a new App from a manifest (copy-paste from `slack.yaml`)
- Create Oauth token bot token from "OAuth & Permissions" -> "OAuth Tokens for Your Workspace"
- Create App level token (from "Basic Information" -> "App-Level Tokens" ( `scope connections:writeRoute authorizations:read` ))
In the UI, when configuring the connector:
Use the included `slack.yaml` manifest to create your app, then configure:
```json
{
"botToken": "xoxb-...",
"appToken": "xapp-1-..."
"botToken": "xoxb-your-bot-token",
"appToken": "xapp-your-app-token"
}
```
#### Telegram
### Telegram
Ask a token to @botfather
In the UI, when configuring the connector:
Get a token from @botfather, then:
```json
{ "token": "botfathertoken" }
{
"token": "your-bot-father-token"
}
```
#### IRC
### IRC
Connect to IRC servers and interact with channels:
Connect to IRC networks:
```json
{
@@ -159,26 +159,133 @@ Connect to IRC servers and interact with channels:
}
```
The IRC connector supports:
- Connecting to IRC servers without encryption
- Joining a specified channel
- Responding to direct mentions (or all messages if alwaysReply is "true")
- Direct messaging with users
## REST API
### REST API
### Agent Management
The LocalAgent API follows RESTful principles and uses JSON for request and response bodies.
| Endpoint | Method | Description | Example |
|----------|--------|-------------|---------|
| `/agents` | GET | List all available agents | [Example](#get-all-agents) |
| `/status/:name` | GET | View agent status history | [Example](#get-agent-status) |
| `/create` | POST | Create a new agent | [Example](#create-agent) |
| `/delete/:name` | DELETE | Remove an agent | [Example](#delete-agent) |
| `/pause/:name` | PUT | Pause agent activities | [Example](#pause-agent) |
| `/start/:name` | PUT | Resume a paused agent | [Example](#start-agent) |
| `/settings/export/:name` | GET | Export agent config | [Example](#export-agent) |
| `/settings/import` | POST | Import agent config | [Example](#import-agent) |
### Chat Interactions
| Endpoint | Method | Description | Example |
|----------|--------|-------------|---------|
| `/chat/:name` | POST | Send message & get response | [Example](#send-message) |
| `/notify/:name` | GET | Send notification to agent | [Example](#notify-agent) |
| `/sse/:name` | GET | Real-time agent event stream | [Example](#agent-sse-stream) |
<details>
<summary><strong>Curl Examples</strong></summary>
#### Get All Agents
```bash
curl -X GET "http://localhost:3000/agents"
```
## License
#### Get Agent Status
```bash
curl -X GET "http://localhost:3000/status/my-agent"
```
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
#### Create Agent
```bash
curl -X POST "http://localhost:3000/create" \
-H "Content-Type: application/json" \
-d '{
"name": "my-agent",
"model": "gpt-4",
"system_prompt": "You are an AI assistant.",
"enable_kb": true,
"enable_reasoning": true
}'
```
#### Delete Agent
```bash
curl -X DELETE "http://localhost:3000/delete/my-agent"
```
#### Pause Agent
```bash
curl -X PUT "http://localhost:3000/pause/my-agent"
```
#### Start Agent
```bash
curl -X PUT "http://localhost:3000/start/my-agent"
```
#### Export Agent
```bash
curl -X GET "http://localhost:3000/settings/export/my-agent" --output my-agent.json
```
#### Import Agent
```bash
curl -X POST "http://localhost:3000/settings/import" \
-F "file=@/path/to/my-agent.json"
```
#### Send Message
```bash
curl -X POST "http://localhost:3000/chat/my-agent" \
-H "Content-Type: application/json" \
-d '{"message": "Hello, how are you today?"}'
```
#### Notify Agent
```bash
curl -X GET "http://localhost:3000/notify/my-agent" \
-d "message=Important notification"
```
#### Agent SSE Stream
```bash
curl -N -X GET "http://localhost:3000/sse/my-agent"
```
Note: For proper SSE handling, you should use a client that supports SSE natively.
</details>
### Agent Configuration Reference
```json
{
"name": "my-agent",
"model": "gpt-4",
"multimodal_model": "gpt-4-vision",
"hud": true,
"standalone_job": false,
"random_identity": false,
"initiate_conversations": true,
"identity_guidance": "You are a helpful assistant.",
"periodic_runs": "0 * * * *",
"permanent_goal": "Help users with their questions.",
"enable_kb": true,
"enable_reasoning": true,
"kb_results": 5,
"can_stop_itself": false,
"system_prompt": "You are an AI assistant.",
"long_term_memory": true,
"summary_long_term_memory": false
}
```
## LICENSE
MIT License — See the [LICENSE](LICENSE) file for details.
---
<p align="center">
<strong>LOCAL PROCESSING. GLOBAL THINKING.</strong><br>
Made with ❤️ by <a href="https://github.com/mudler">mudler</a>
</p>