## Documentation Index

Fetch the complete documentation index at: [/llms.txt](https://docs.cognigy.com/llms.txt)

Use this file to discover all available pages before exploring further.

In Cognigy.AI, you can use the `api.getLLMTokenUsageForSession()` API call in a [Code Node](https://docs.cognigy.com/ai/for-developers/code/overview) or an [Extension Node](https://docs.cognigy.com/ai/for-developers/extensions) to fetch the Large Language Model (LLM) total token usage in a conversation or chat session. This way, you can track your [LLM providers](https://docs.cognigy.com/ai/agents/develop/gen-ai-and-llms/providers/all-providers) costs. The LLM Session Token Counter retrieves the token usage information via LLM provider-specific API calls to return the exact number of tokens the LLM uses. If the information isn’t available by the provider, Cognigy.AI estimates the token usage.

## Prerequisite

- You have added a Node that uses an LLM to your Flow, for example, an [AI Agent Node](https://docs.cognigy.com/ai/agents/develop/node-reference/ai/ai-agent), [LLM Prompt Node](https://docs.cognigy.com/ai/agents/develop/node-reference/service/llm-prompt), [Search Extract Output Node](https://docs.cognigy.com/ai/agents/develop/node-reference/other-nodes/knowledge-search), or [Agent Copilot Nodes](https://docs.cognigy.com/ai/agents/develop/node-reference/agent-copilot/overview).

## Limitations

- The LLM Session Token Counter doesn’t support embedding models from Aleph Alpha.

## Fetching Session-Wide Token Usage

1. Add a [Code Node](https://docs.cognigy.com/ai/for-developers/code/overview) after the Node that uses an LLM, for example, after an [AI Agent Node](https://docs.cognigy.com/ai/agents/develop/node-reference/ai/ai-agent).
2. Add the following code to the Code Node:

```javascript
   const tokens = api.getLLMTokenUsageForSession();
   ```

This Code Node fetches the total token usage in the session and stores it in the `token` variable.

Returned JSON Object

The following JSON example shows an object returned by `api.getLLMTokenUsageForSession()`:

```json
{
    "1c945b38-5dbb-4fcf-9fdd-112bd8177f9c": {
        "IlmDisplayName": "openAI - text- embedding-3-large - 1735891122507",
        "providerType": "openAI",
        "modelType" : "text-embedding-3-large",
        "usage": {
            "inputTokens": 6,
            "outputTokens": 0
        }
    },
    "ce190e1f-eff7-4f6b-9074-9f705375a3d3": {
        "IlmDisplayName": "openAI - gpt-40 - 1735891179896",
        "providerType": "openAI",
        "modelType": "gpt-40",
        "usage": {
            "inputTokens": 441,
            "outputTokens": 106
        }
    }
}
```

| Key               | Type   | Description                                                                                             | Example                                      |
|-------------------|--------|---------------------------------------------------------------------------------------------------------|----------------------------------------------|
| llmReferenceId    | String | The LLM reference ID.                                                                                   | `ce190e1f-eff7-4f6b-9074-9f705375a3d3`    |
| llmDisplayName    | String | The name of the LLM.                                                                                   | `openAI - gpt-40 - 1735891179896`          |
| providerType      | String | The LLM provider.                                                                                       | `openAI`                                    |
| modelType         | String | The LLM model.                                                                                        | `gpt-40`                                    |
| usage             | Object | The object containing information about the session total token usage.                                 | -                                            |
| inputTokens       | Number | The number of input tokens.                                                                             | 441                                          |
| outputTokens      | Number | The number output tokens. The output tokens count for embedding models is always 0 since embedding models output embedding vectors instead of tokens. | 106                                          |

For testing in the Interaction Panel, you can output the JSON object by adding `api.say()` at the end of your [Code Node](https://docs.cognigy.com/ai/for-developers/code/api-functions).

## More Information

- [Overview](https://docs.cognigy.com/ai/agents/develop/gen-ai-and-llms/llms)
- [LLM Providers](https://docs.cognigy.com/ai/agents/develop/gen-ai-and-llms/providers/all-providers)
- [Model Support by Feature](https://docs.cognigy.com/ai/agents/develop/gen-ai-and-llms/model-support-by-feature)

Last modified on April 21, 2026.