> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/Arize-ai/openinference/llms.txt
> Use this file to discover all available pages before exploring further.

# Tool Calling

> Function/tool call and result representation

This document describes how tool/function calling is represented in OpenInference spans.

## Tool Definitions

Tools available to the LLM are represented using the `llm.tools` prefix with flattened attributes:

### Attribute Pattern

```
llm.tools.<index>.tool.json_schema
```

The `json_schema` contains the complete tool definition as a JSON string, including:

* Tool type (usually "function")
* Function name
* Function description
* Parameter schema

### Example Tool Definition

```json theme={null}
{
  "llm.tools.0.tool.json_schema": "{\"type\": \"function\", \"function\": {\"name\": \"get_weather\", \"description\": \"Get current weather for a location\", \"parameters\": {\"type\": \"object\", \"properties\": {\"location\": {\"type\": \"string\", \"description\": \"City and state\"}}, \"required\": [\"location\"]}}}"
}
```

## Tool Calls in Messages

When an LLM generates tool calls, they are represented in the output messages:

### Attribute Pattern for Tool Calls

```
llm.output_messages.<messageIndex>.message.tool_calls.<toolCallIndex>.tool_call.<attribute>
```

Where:

* `<messageIndex>` is the zero-based index of the message
* `<toolCallIndex>` is the zero-based index of the tool call within the message
* `<attribute>` is the specific tool call attribute

### Tool Call Attributes

* `tool_call.id`: Unique identifier for the tool call
* `tool_call.function.name`: Name of the function being called
* `tool_call.function.arguments`: JSON string containing the function arguments

### Example Tool Call

```json theme={null}
{
  "llm.output_messages.0.message.role": "assistant",
  "llm.output_messages.0.message.tool_calls.0.tool_call.id": "call_abc123",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.name": "get_weather",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.arguments": "{\"location\": \"San Francisco, CA\"}"
}
```

## Multiple Tool Calls

When an LLM makes multiple tool calls in a single response:

```json theme={null}
{
  "llm.output_messages.0.message.role": "assistant",
  "llm.output_messages.0.message.tool_calls.0.tool_call.id": "call_001",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.name": "get_weather",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.arguments": "{\"location\": \"New York\"}",
  "llm.output_messages.0.message.tool_calls.1.tool_call.id": "call_002",
  "llm.output_messages.0.message.tool_calls.1.tool_call.function.name": "get_weather",
  "llm.output_messages.0.message.tool_calls.1.tool_call.function.arguments": "{\"location\": \"London\"}"
}
```

## Tool Results

Tool results are typically represented as input messages with role "tool":

```json theme={null}
{
  "llm.input_messages.3.message.role": "tool",
  "llm.input_messages.3.message.content": "{\"temperature\": 72, \"condition\": \"sunny\"}",
  "llm.input_messages.3.message.tool_call_id": "call_abc123",
  "llm.input_messages.3.message.name": "get_weather"
}
```

The `message.tool_call_id` links the result back to the original tool call. The `message.name` attribute MAY be set to identify which function produced the result — it typically matches `tool_call.function.name` from the corresponding tool call.

## Complete Tool Call Flow Example

### 1. User Request

```json theme={null}
{
  "llm.input_messages.0.message.role": "user",
  "llm.input_messages.0.message.content": "What's the weather in Boston?"
}
```

### 2. Available Tools

```json theme={null}
{
  "llm.tools.0.tool.json_schema": "{\"type\": \"function\", \"function\": {\"name\": \"get_weather\", \"description\": \"Get current weather\", \"parameters\": {\"type\": \"object\", \"properties\": {\"location\": {\"type\": \"string\"}}}}}"
}
```

### 3. LLM Tool Call

```json theme={null}
{
  "llm.output_messages.0.message.role": "assistant",
  "llm.output_messages.0.message.tool_calls.0.tool_call.id": "call_123",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.name": "get_weather",
  "llm.output_messages.0.message.tool_calls.0.tool_call.function.arguments": "{\"location\": \"Boston, MA\"}"
}
```

### 4. Tool Result (in next request)

```json theme={null}
{
  "llm.input_messages.2.message.role": "tool",
  "llm.input_messages.2.message.content": "{\"temperature\": 65, \"condition\": \"cloudy\"}",
  "llm.input_messages.2.message.tool_call_id": "call_123"
}
```

### 5. Final Response

```json theme={null}
{
  "llm.output_messages.0.message.role": "assistant",
  "llm.output_messages.0.message.content": "The current weather in Boston is 65°F and cloudy."
}
```

## Legacy Attributes

<Warning>
  Some implementations may use legacy attributes for function calling. New implementations should use the `tool_calls` structure described above.
</Warning>

Legacy attributes:

* `message.function_call_name`: Function name (deprecated, use tool\_calls)
* `message.function_call_arguments_json`: Function arguments (deprecated, use tool\_calls)
* `llm.function_call`: Complete function call as JSON (deprecated)