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Advanced Implementations Guide

Overview

This guide covers advanced features and configurations for the Hello World Agent, including OpenRouter and LLM settings, streaming capabilities, and using multiple LLMs.

OpenRouter and LLM Settings

OpenRouter API

The agent uses the OpenRouter API for LLM access. Ensure you have a valid API key and set it in the .env file:

OPENROUTER_API_KEY=your_api_key_here

Configuring LLMs

You can configure LLM settings in the agent/config/agents.yaml file. This includes selecting the LLM model, setting parameters, and defining behavior.

Example Configuration

llm:
  model: "gpt-3.5-turbo"
  temperature: 0.7
  max_tokens: 1500
  top_p: 0.9

Using Multiple LLMs

To use multiple LLMs, define them in the configuration file and specify their usage in the agent's logic:

llms:
  primary:
    model: "gpt-3.5-turbo"
    temperature: 0.7
  secondary:
    model: "gpt-4"
    temperature: 0.5

In agent/main.py, implement logic to switch between LLMs based on task requirements.

Streaming Capabilities

Enabling Streaming

The agent supports streaming responses for real-time interaction. Enable streaming in the configuration file:

streaming:
  enabled: true
  buffer_size: 1024

Implementing Streaming

In agent/main.py, implement streaming logic to handle data in chunks. This allows for responsive interactions and efficient data processing.

Advanced Use Cases

Dynamic LLM Selection

Implement logic to dynamically select LLMs based on task complexity or user preferences. This can be achieved by analyzing the input prompt and choosing the appropriate model.

Custom LLM Parameters

Customize LLM parameters for specific tasks. For example, increase the temperature for creative tasks or reduce it for factual responses.

Multi-LLM Collaboration

Leverage multiple LLMs to collaborate on complex tasks. For example, use one LLM for data analysis and another for generating reports.

Best Practices

  1. Security: Keep your API keys secure and do not hard-code them in the source code.
  2. Performance: Monitor LLM performance and adjust parameters for optimal results.
  3. Scalability: Design your agent to scale with additional LLMs and increased data loads.
  4. Testing: Thoroughly test advanced configurations to ensure stability and reliability.

Conclusion

Advanced implementations allow you to harness the full potential of the Hello World Agent. By configuring OpenRouter and LLM settings, enabling streaming, and using multiple LLMs, you can create a powerful and flexible agent tailored to your needs.