Agents
SEA-LION models can be used as intelligent agents capable of tool-calling, multi-step reasoning, and complex task execution. The SEA-LION v3 family, such as aisingapore/Llama-SEA-LION-v3-70B-IT, can be utilized for agent-based applications with tool-calling capabilities.
Agents built with SEA-LION can:
Execute complex, multi-step workflows
Integrate with external tools and APIs
Perform real-time information retrieval
Handle specialized tasks like translation, calculation, and web search
Chain multiple operations together intelligently
Available Frameworks
The following guides provide technical how-tos for building SEA-LION agents using different frameworks:
Learn how to build powerful agents using AWS's Strands Agents SDK, including:
Basic agent setup using in-built tools
Custom tool development
Using agents as tools
Multi-tool agent example
Develop and deploy agents with Google ADK:
Basic agent setup with custom tools and agent-as-a-tool
Custom tool development
Using agents as tools
Running multi-tool agent via in-built web interface/CLI
Recommended Models
For optimal agent performance, we recommend using the following SEA-LION models:
aisingapore/Llama-SEA-LION-v3-70B-IT/aisingapore/Llama-SEA-LION-v3-8B-IT- Suitable for tool-calling, long context tasks or creative response.aisingapore/Gemma-SEA-LION-v3-9B-IT- Suitable for smaller tasks with succinct response.aisingapore/Llama-SEA-LION-v3.5-70B-R/aisingapore/Llama-SEA-LION-v3.5-8B-R- Display reasoning process and long context tasks.
Key Features
Tool Integration: SEA-LION agents can seamlessly integrate with both built-in tools (calculations, time queries) and custom tools (web search, translation, APIs).
Multi-Agent Systems: Agents can be composed together in multiple ways. Specialized agents serving as tools, running in sequential workflow, or passing to each other in a loop.
Streaming Responses: Built-in support for real-time streaming responses for better user experience.
Flexible Configuration: Easy environment-based configuration for different deployment scenarios.
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