LOCAL AGENT
AI that stays where it belongs — on your machine.
[](https://goreportcard.com/report/github.com/mudler/LocalAgent)
[](https://opensource.org/licenses/MIT)
[](https://github.com/mudler/LocalAgent/stargazers)
[](https://github.com/mudler/LocalAgent/issues)
## TAKE BACK CONTROL
**LocalAgent** is an AI platform that runs 100% on your hardware. No clouds. No data sharing. No compromises.
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. Are you tired of agent wrappers to cloud APIs? me too.
## WHY LOCALAGENT?
- **✓ 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
## THE LOCAL ECOSYSTEM
LocalAgent is part of a trinity of tools designed to keep AI under your control:
- [**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
## Features
### Powerful WebUI
### Connectors ready-to-go
## QUICK START
### One-Command Docker Setup
The fastest way to get everything running — LocalRAG, LocalAI, and LocalAgent pre-configured:
```bash
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 |
| `LOCALAGENT_API_KEYS` | A comma separated list of api keys used for authentication |
## 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 it
go build -o localagent
# Run it
./localagent
```
## CONNECTORS
Link your agents to the services you already use. Configuration examples below.
### GitHub Issues
```json
{
"token": "YOUR_PAT_TOKEN",
"repository": "repo-to-monitor",
"owner": "repo-owner",
"botUserName": "bot-username"
}
```
### Discord
After [creating your Discord bot](https://discordpy.readthedocs.io/en/stable/discord.html):
```json
{
"token": "Bot YOUR_DISCORD_TOKEN",
"defaultChannel": "OPTIONAL_CHANNEL_ID"
}
```
> Don't forget to enable "Message Content Intent" in Bot settings!
### Slack
Use the included `slack.yaml` manifest to create your app, then configure:
```json
{
"botToken": "xoxb-your-bot-token",
"appToken": "xapp-your-app-token"
}
```
### Telegram
Get a token from @botfather, then:
```json
{
"token": "your-bot-father-token"
}
```
### IRC
Connect to IRC networks:
```json
{
"server": "irc.example.com",
"port": "6667",
"nickname": "LocalAgentBot",
"channel": "#yourchannel",
"alwaysReply": "false"
}
```
## REST API
### Agent Management
| 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) |
| `/api/agent/:name/config` | GET | Get agent configuration | |
| `/api/agent/:name/config` | PUT | Update agent configuration | |
### 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) |
| `/v1/responses` | POST | Send message & get response | [OpenAI's Responses](https://platform.openai.com/docs/api-reference/responses/create) |
Curl Examples
#### Get All Agents
```bash
curl -X GET "http://localhost:3000/agents"
```
#### Get Agent Status
```bash
curl -X GET "http://localhost:3000/status/my-agent"
```
#### 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.
### 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.
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