how to use LlamaIndex agents using LLM

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# Welcome to Total Technology Zone - Tutorial 31

**Hi everyone, this is Ronnie! Welcome back to our channel, *Total Technology Zone*.** In today’s tutorial (*Tutorial 31*), we’ll explore how to use **Llama Index agents** with an **LLM**, specifically using **OpenAI’s GPT-4 model**. This marks an exciting milestone in our series as we get hands-on with **Llama Index agents**, focusing on the **React Agent**.

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### Tutorial Overview

In this session, I’ll guide you through:
- Setting up a Llama Index agent.
- Defining tools that the agent can leverage dynamically.
- Using a React agent to handle tasks by breaking them down step-by-step.

We’ll also see how the Llama Index agent chooses tools intelligently based on the task, ensuring efficient and context-aware operations.

By the end of this tutorial, you’ll have a clear understanding of how to configure and use Llama Index agents, paving the way for advanced use cases.

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### Why Llama Index Agents?

Llama Index agents are incredibly useful when:
1. **Complex Tasks Need Automation**:
- The agent can decide which tool to use based on the input question or requirement.
2. **Dynamic Tool Execution**:
- Multiple functions can be integrated, and the agent determines which function is most suitable.
3. **Scalability**:
- These agents can be scaled for large-scale integration projects involving multiple tools and LLMs.

In this tutorial, we’ll define simple tools (like multiplication and cosine calculation) to demonstrate these capabilities.

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### Key Concepts

1. **React Agent**:
- A type of agent that executes tasks step-by-step, using previous outputs to decide the next action.
- Ideal for tasks requiring logical flow or intermediate reasoning.

2. **Function Tools**:
- These are custom functions (e.g., multiplication or cosine calculation) that the agent can call dynamically.
- Once registered, the agent selects the appropriate tool based on the input query.

3. **Verbose Output**:
- Setting verbosity allows us to see the internal decision-making process of the agent, providing insights into how it selects tools and interprets inputs.

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### Demonstration

Here’s an outline of what we’ll achieve:
1. **Setup**:
- Configure Llama Index and OpenAI GPT-4.
2. **Tool Creation**:
- Define custom tools for simple tasks like multiplication and cosine calculation.
3. **Agent Integration**:
- Add these tools to a React agent.
4. **Testing**:
- Query the agent with various inputs and observe how it intelligently selects tools and processes requests.

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### Key Observations

- **Tool Selection**:
- The agent identifies the most suitable tool based on the input. For instance, when asked for the cosine of an angle, it chooses the cosine calculation tool automatically.
- **Step-by-Step Execution**:
- For tasks requiring intermediate steps (e.g., cube calculation), the agent breaks the problem into smaller parts and resolves them incrementally.
- **Error Handling**:
- The agent provides intelligent feedback and retries tasks as necessary, ensuring reliable execution.

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### Use Cases

This approach is incredibly beneficial for:
1. **Large-Scale Integrations**:
- Handling multiple tools or functions dynamically based on user input.
2. **Advanced Workflows**:
- Automating processes that require logical reasoning and intermediate steps.
3. **Custom Applications**:
- Creating intelligent systems that adapt to specific project requirements, such as dynamic calculations or data extraction.

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### Final Thoughts

This was an exciting tutorial demonstrating how to use the **React Agent** in Llama Index for dynamic tool execution.

**What’s Next?**
In the next tutorial, I’ll introduce **Function Call Agents** and explore another use case. Stay tuned for more intermediate and advanced concepts in the series.

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### Support Our Channel

Thank you for watching! If you find these tutorials helpful, please consider supporting us:
- **Subscribe** to the channel for more content on AI, Llama Index, and LangChain.
- **Like** and **Share** the video with anyone who might benefit.
- Hit the **bell icon** to stay updated on upcoming tutorials.

Your support means the world to me! Together, we can grow this channel and create a community of learners passionate about AI and generative technologies.

See you in the next tutorial. Until then, take care, happy learning, and goodbye! 😊