We empower you building AI Agents that you can run locally, without coding.
LocalAGI is a powerful, self-hostable AI Agent platform designed for maximum privacy and flexibility. A complete drop-in replacement for OpenAI's Responses APIs with advanced agentic capabilities. No clouds. No data leaks. Just pure local AI that works on consumer-grade hardware (CPU and GPU).
Are you tired of AI wrappers calling out to cloud APIs, risking your privacy? So were we.
LocalAGI ensures your data stays exactly where you want it—on your hardware. No API keys, no cloud subscriptions, no compromise.
- 🎛 No-Code Agents: Easy-to-configure multiple agents via Web UI.
- 🖥 Web-Based Interface: Simple and intuitive agent management.
- 🤖 Advanced Agent Teaming: Instantly create cooperative agent teams from a single prompt.
- 📡 Connectors Galore: Built-in integrations with Discord, Slack, Telegram, GitHub Issues, and IRC.
- 🛠 Comprehensive REST API: Seamless integration into your workflows. Every agent created will support OpenAI Responses API out of the box.
- 📚 Short & Long-Term Memory: Powered by LocalRecall.
- 🧠 Planning & Reasoning: Agents intelligently plan, reason, and adapt.
- 🔄 Periodic Tasks: Schedule tasks with cron-like syntax.
- 💾 Memory Management: Control memory usage with options for long-term and summary memory.
- 🖼 Multimodal Support: Ready for vision, text, and more.
- 🔧 Extensible Custom Actions: Easily script dynamic agent behaviors in Go (interpreted, no compilation!).
- 🛠 Fully Customizable Models: Use your own models or integrate seamlessly with LocalAI.
# Clone the repository
git clone https://github.com/mudler/LocalAGI
cd LocalAGI
# CPU setup
docker compose up -f docker-compose.yml
# GPU setup
docker compose up -f docker-compose.gpu.yml
Access your agents at http://localhost:8080
- ✓ Ultimate Privacy: No data ever leaves your hardware.
- ✓ Flexible Model Integration: Supports GGUF, GGML, and more thanks to LocalAI.
- ✓ Developer-Friendly: Rich APIs and intuitive interfaces.
- ✓ Effortless Setup: Simple Docker compose setups and pre-built binaries.
- ✓ Feature-Rich: From planning to multimodal capabilities, connectors for Slack, MCP support, LocalAGI has it all.
LocalAGI is part of the powerful Local family of privacy-focused AI tools:
- LocalAI: Run Large Language Models locally.
- LocalRecall: Retrieval-Augmented Generation with local storage.
- LocalAGI: Deploy intelligent AI agents securely and privately.
Explore detailed documentation including:
Variable | What It Does |
---|---|
LOCALAGI_MODEL |
Your go-to model |
LOCALAGI_MULTIMODAL_MODEL |
Optional model for multimodal capabilities |
LOCALAGI_LLM_API_URL |
OpenAI-compatible API server URL |
LOCALAGI_LLM_API_KEY |
API authentication |
LOCALAGI_TIMEOUT |
Request timeout settings |
LOCALAGI_STATE_DIR |
Where state gets stored |
LOCALAGI_LOCALRAG_URL |
LocalRecall connection |
LOCALAGI_ENABLE_CONVERSATIONS_LOGGING |
Toggle conversation logs |
LOCALAGI_API_KEYS |
A comma separated list of api keys used for authentication |
Download ready-to-run binaries from the Releases page.
Requirements:
- Go 1.20+
- Git
- Bun 1.2+
# Clone repo
git clone https://github.com/mudler/LocalAGI.git
cd LocalAGI
# Build it
cd webui/react-ui && bun i && bun run build
cd ../..
go build -o localagi
# Run it
./localagi
The development workflow is similar to the source build, but with additional steps for hot reloading of the frontend:
# Clone repo
git clone https://github.com/mudler/LocalAGI.git
cd LocalAGI
# Install dependencies and start frontend development server
cd webui/react-ui && bun i && bun run dev
Then in seperate terminal:
# Start development server
cd ../.. && go run main.go
Note: see webui/react-ui/.vite.config.js for env vars that can be used to configure the backend URL
Link your agents to the services you already use. Configuration examples below.
{
"token": "YOUR_PAT_TOKEN",
"repository": "repo-to-monitor",
"owner": "repo-owner",
"botUserName": "bot-username"
}
After creating your Discord bot:
{
"token": "Bot YOUR_DISCORD_TOKEN",
"defaultChannel": "OPTIONAL_CHANNEL_ID"
}
Don't forget to enable "Message Content Intent" in Bot(tab) settings! Enable " Message Content Intent " in the Bot tab!
Use the included slack.yaml
manifest to create your app, then configure:
{
"botToken": "xoxb-your-bot-token",
"appToken": "xapp-your-app-token"
}
- 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 ))
Get a token from @botfather, then:
{
"token": "your-bot-father-token"
}
Connect to IRC networks:
{
"server": "irc.example.com",
"port": "6667",
"nickname": "LocalAGIBot",
"channel": "#yourchannel",
"alwaysReply": "false"
}
Endpoint | Method | Description | Example |
---|---|---|---|
/api/agents |
GET | List all available agents | Example |
/api/agent/:name/status |
GET | View agent status history | Example |
/api/agent/create |
POST | Create a new agent | Example |
/api/agent/:name |
DELETE | Remove an agent | Example |
/api/agent/:name/pause |
PUT | Pause agent activities | Example |
/api/agent/:name/start |
PUT | Resume a paused agent | Example |
/api/agent/:name/config |
GET | Get agent configuration | |
/api/agent/:name/config |
PUT | Update agent configuration | |
/api/meta/agent/config |
GET | Get agent configuration metadata | |
/settings/export/:name |
GET | Export agent config | Example |
/settings/import |
POST | Import agent config | Example |
Endpoint | Method | Description | Example |
---|---|---|---|
/api/actions |
GET | List available actions | |
/api/action/:name/run |
POST | Execute an action | |
/api/agent/group/generateProfiles |
POST | Generate group profiles | |
/api/agent/group/create |
POST | Create a new agent group |
Endpoint | Method | Description | Example |
---|---|---|---|
/api/chat/:name |
POST | Send message & get response | Example |
/api/notify/:name |
POST | Send notification to agent | Example |
/api/sse/:name |
GET | Real-time agent event stream | Example |
/v1/responses |
POST | Send message & get response | OpenAI's Responses |
Curl Examples
curl -X GET "http://localhost:3000/api/agents"
curl -X GET "http://localhost:3000/api/agent/my-agent/status"
curl -X POST "http://localhost:3000/api/agent/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
}'
curl -X DELETE "http://localhost:3000/api/agent/my-agent"
curl -X PUT "http://localhost:3000/api/agent/my-agent/pause"
curl -X PUT "http://localhost:3000/api/agent/my-agent/start"
curl -X GET "http://localhost:3000/api/agent/my-agent/config"
curl -X PUT "http://localhost:3000/api/agent/my-agent/config" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4",
"system_prompt": "You are an AI assistant."
}'
curl -X GET "http://localhost:3000/settings/export/my-agent" --output my-agent.json
curl -X POST "http://localhost:3000/settings/import" \
-F "file=@/path/to/my-agent.json"
curl -X POST "http://localhost:3000/api/chat/my-agent" \
-H "Content-Type: application/json" \
-d '{"message": "Hello, how are you today?"}'
curl -X POST "http://localhost:3000/api/notify/my-agent" \
-H "Content-Type: application/json" \
-d '{"message": "Important notification"}'
curl -N -X GET "http://localhost:3000/api/sse/my-agent"
Note: For proper SSE handling, you should use a client that supports SSE natively.
The agent configuration defines how an agent behaves and what capabilities it has. You can view the available configuration options and their descriptions by using the metadata endpoint:
curl -X GET "http://localhost:3000/api/meta/agent/config"
This will return a JSON object containing all available configuration fields, their types, and descriptions.
Here's an example of the agent configuration structure:
{
"name": "my-agent",
"model": "gpt-4",
"multimodal_model": "gpt-4-vision",
"hud": true,
"standalone_job": false,
"random_identity": false,
"initiate_conversations": true,
"enable_planning": 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
}
MIT License — See the LICENSE file for details.
LOCAL PROCESSING. GLOBAL THINKING.
Made with ❤️ by mudler