Function Calling in LlamaIndex: A Technical Guide

🎉 What is LlamaIndex?

🤔 Why Use Function Calling?

• Efficiency: Instead of dealing with multiple round trips between the LLM and back-end APIs, you can consolidate operations into a SINGLE request. This means quicker responses for end users.
• Rich Interactions: You can design your applications to answer complex queries in a single call. The model will resolve tasks using different functions rather than relying solely on its internal knowledge.
• Endless Possibilities: It opens up numerous avenues for developers, from integrating with external services to crafting more interactive user experiences.

🔍 Understanding the Basics of Function Calling

1. Define Functions: You’ll start by setting up your functions, specifying what each function does and its expected inputs.
2. Integrate APIs: If your function needs to call external APIs, set these integrations as tools to expand your app's capabilities.
3. Implementing Agents: With defined functions in place, you can create agents that execute these functions based on user prompts.

🚀 Getting Started with Function Calling

Step 1: Install LlamaIndex

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pip install llama-index

Step 2: Define Your Functions

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from llama_index.core.tools import FunctionTool

def multiply(a: int, b: int) -> int:
    return a * b

def add(a: int, b: int) -> int:
    return a + b

# Create FunctionTools for each function
multiply_tool = FunctionTool.from_defaults(fn=multiply)
add_tool = FunctionTool.from_defaults(fn=add)

Step 3: Create Your LLM Agent

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from llama_index.agent.openai import OpenAIAgent
from llama_index.llms.openai import OpenAI

llm = OpenAI(model="gpt-3.5-turbo")
agent = OpenAIAgent.from_tools([multiply_tool, add_tool], llm=llm, verbose=True)

Step 4: Call Your Functions in a Single Turn

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response = agent.chat("What is (121 * 3) + 42?")
print(response)

🎨 Crafting Complex Interactions

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# An example of chaining functions
response = agent.chat("Calculate (121 * 3) and then add 42")
print(response)

💻 Multi-Function Calling

What's the Difference?

Setting It Up

• Just like with single function calls, all you need to do is define your functions.
• Utilize the agent to call everything in one go and get responses that combine outputs from multiple functions.

🛠️ Best Practices for Function Calling in LlamaIndex

• Clear Documentation: Make sure your function parameters and expected responses are clear. This makes it easier for other developers (or your future self) to understand the logic.
• Error Handling: Implement error handling for your functions to avoid runtime errors that may confuse users.
• Use Meaningful Names: When defining your tools and functions, use descriptive names. This makes it easier to understand what each tool should do at a glance.
• Start Simple: Begin with a few functions and gradually expand as you get comfortable with LlamaIndex’s architecture.

🌐 Join the LlamaIndex Community

💡 Enhance Your Experience with Arsturn

📚 Conclusion