Hermes Pipeline
5593e60b91
Extracted from: https://github.com/omerbsezer/Fast-LLM-Agent-MCP.git Score: 1.0
11 lines
1.1 KiB
Markdown
11 lines
1.1 KiB
Markdown
# Examples: langgraph-multi-agent-router
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## Usage Example
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```python
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# How to use this skill
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# Inputs: User query string (e.g., destination location), BedrockModel configuration (model_id, temperature, top_p), Pre-configured agents with specific system prompts and tool sets
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# Process: Researcher agent executes with system prompt to gather raw destination facts (places, history, accommodations, food, web pages) using BedrockModel and available tools (calculator, current_time) → Travel guide agent receives raw research output and structures it into labeled sections (Must-See Attractions, Historical Highlights, Accommodation Areas, Culinary Delights, Suggested Web Pages) → Writer agent receives the structured guide and synthesizes it into a professional client-facing response with clear formatting and emphasis on the suggested web pages
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# Outputs: Raw research data (JSON string containing gathered facts), Structured guide content (markdown-formatted travel guide with labeled sections), Final client response (professional formatted response ready for delivery)
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```
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