Llama-3 Groq Tool Use Agent

Deploy and interact with Groq's Llama-3-Groq-8B-Tool-Use model, a specialized variant of Llama 3 fine-tuned for function calling and tool use scenarios.

What This Skill Does

This skill helps you set up and use the Llama-3-Groq-8B-Tool-Use model, which excels at:

Function calling and API interactions

Structured tool invocation

Conversational AI with action capabilities

Multi-step reasoning with external tools

Instructions

When the user wants to work with the Llama-3 Groq Tool Use model, follow these steps:

1. Understand the Use Case

Ask the user what they want to accomplish:

Are they deploying a GaiaNet node with this model?

Do they need function calling capabilities for their application?

Are they integrating tool use into a conversational AI system?

2. GaiaNet Deployment (if applicable)

If deploying via GaiaNet:

**Configuration Requirements:**

Model: `gaianet/Llama-3-Groq-8B-Tool-Use-GGUF`

Prompt template: `groq-llama3-tool`

Context size: `8192` tokens

**Setup Steps:**

1. Follow GaiaNet quick start: https://docs.gaianet.ai/node-guide/quick-start

2. Customize node config with the specifications above

3. Reference: https://docs.gaianet.ai/node-guide/customize

3. Function Calling Integration

For applications requiring function calling:

**Prompt Format:**

Use the `groq-llama3-tool` template

Structure tool definitions clearly

Provide function schemas in the expected format

**Best Practices:**

Keep context under 8192 tokens

Define tools with clear descriptions and parameter schemas

Handle function responses in a structured way

Chain multiple tool calls when needed

4. Code Integration Example

If the user needs code examples, provide implementation patterns for:

Setting up the model endpoint

Defining callable functions/tools

Parsing function call responses

Handling multi-turn conversations with tool use

5. Testing and Validation

Help the user:

Test function calling capabilities

Validate tool invocation accuracy

Debug prompt formatting issues

Optimize context window usage

Model Details

**Base Model:** Groq/Llama-3-Groq-8B-Tool-Use

**Quantization:** GGUF format (llama.cpp b3405)

**License:** Llama 3

**Language:** English

**Context Window:** 8192 tokens

**Specialization:** Function calling and tool use

Important Notes

This is a quantized GGUF model optimized for inference efficiency

Requires the specific `groq-llama3-tool` prompt template for best results

Context size limit is 8192 tokens - manage conversation history accordingly

Best suited for scenarios requiring structured tool interactions

Not suitable for training/fine-tuning (inference only)

Example Usage

**User:** "Help me set up the Llama-3 Groq tool use model for my customer service bot"

**Agent Response:**

1. Identify required tools (e.g., database lookup, ticket creation, knowledge base search)

2. Configure GaiaNet node or local deployment with correct prompt template

3. Define function schemas for each tool

4. Implement conversation flow with tool calling logic

5. Test with sample customer queries

**User:** "I need this model to call APIs in my application"

**Agent Response:**

1. Review API endpoints to expose as tools

2. Create function definitions with parameter schemas

3. Set up the model with `groq-llama3-tool` template

4. Implement API call execution layer

5. Handle responses and continue conversation flow

Llama-3 Groq Tool Use Agent

Llama-3 Groq Tool Use Agent

What This Skill Does

Instructions

1. Understand the Use Case

2. GaiaNet Deployment (if applicable)

3. Function Calling Integration

4. Code Integration Example

5. Testing and Validation

Model Details

Important Notes

Example Usage

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