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mudler
2025-05-11 18:41:43 +02:00
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README.md
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@@ -265,6 +265,9 @@ go build -o localagi
LocalAGI can be used as a Go library to programmatically create and manage AI agents. Let's start with a simple example of creating a single agent: LocalAGI can be used as a Go library to programmatically create and manage AI agents. Let's start with a simple example of creating a single agent:
<details>
<summary><strong>Basic Usage: Single Agent</strong></summary>
```go ```go
import ( import (
"github.com/mudler/LocalAGI/core/agent" "github.com/mudler/LocalAGI/core/agent"
@@ -311,7 +314,10 @@ This basic example shows how to:
- Configure basic features like knowledge base and reasoning - Configure basic features like knowledge base and reasoning
- Start and stop the agent - Start and stop the agent
#### Advanced Usage with Agent Pools </details>
<details>
<summary><strong>Advanced Usage: Agent Pools</strong></summary>
For managing multiple agents, you can use the AgentPool system: For managing multiple agents, you can use the AgentPool system:
@@ -386,6 +392,11 @@ pool.Stop("my-agent")
err = pool.Remove("my-agent") err = pool.Remove("my-agent")
``` ```
</details>
<details>
<summary><strong>Available Features</strong></summary>
Key features available through the library: Key features available through the library:
- **Single Agent Management**: Create and manage individual agents with basic configuration - **Single Agent Management**: Create and manage individual agents with basic configuration
@@ -400,6 +411,8 @@ Key features available through the library:
For more details about available configuration options and features, refer to the [Agent Configuration Reference](#agent-configuration-reference) section. For more details about available configuration options and features, refer to the [Agent Configuration Reference](#agent-configuration-reference) section.
</details>
### Development ### Development
The development workflow is similar to the source build, but with additional steps for hot reloading of the frontend: The development workflow is similar to the source build, but with additional steps for hot reloading of the frontend: