---
title: "Call the API with the TIR SDK"
description: "Call a GenAI API model with the TIR SDK, which fills in the request body for the eight models it knows by name."
content_type: "how-to"
product: "genai-api"
platform: "TIR"
url: "/tir/genai-api/how-to/call-the-api-with-the-tir-sdk/"
topic: ["call-the-api"]
---

# Call the API with the TIR SDK

<!-- cspell:ignore mixtral codellama parakeet -->

The TIR SDK calls a fixed list of eight models for you and fills in the request body, so you pass
only the model name and your data. The examples call Whisper Large V3, one of the eight, and you can
use any of them that is available in the GenAI API list. See [Is a model on GenAI API guaranteed to stay
available?](/tir/genai-api/faq/#is-a-model-on-genai-api-guaranteed-to-stay-available).

## Before you begin

You need:

- A Personal Access Token. See [Get started with TIR GenAI
  API](/tir/genai-api/get-started/).
- Your project ID.

The eight models the TIR SDK knows are `llama-2-13b-chat`, `stable-diffusion-2-1`,
`mixtral-8x7b-instruct`, `codellama-13b-instruct`, `whisper-large-v3`, `e5-mistral-7b-instruct`,
`llama-3-8b-instruct`, and `parakeet-ctc-asr`. Any other model name raises "model not present".
Call that model with the [OpenAI SDK](/tir/genai-api/how-to/call-the-api-with-the-openai-sdk/) or
[REST](/tir/genai-api/how-to/call-the-api-with-rest/) instead.

## Install the TIR SDK

```bash
pip install e2enetworks
```

## Initialize the client

```python
from e2enetworks.cloud import tir

tir.init(api_key="<your-api-key>", access_token="<your-auth-token>")
tir_client = tir.ModelAPIClient(project="<your-project-id>")
```

`<your-auth-token>` is the Auth Token from your Personal Access Token. Copy it from the Create
Token dialog or, later, from the **Personal Access Tokens** list. `<your-api-key>` is that same
token's API Key. To get it, use the **Download Config File** action next to the token in the list;
the file holds both values. `<your-project-id>` is the project the token belongs to.

You can also set these as environment variables and initialize the client with no arguments; the
SDK then reads them from the environment:

```bash
export E2E_TIR_API_KEY=<your-api-key>
export E2E_TIR_ACCESS_TOKEN=<your-auth-token>
```

## Call the model

Whisper Large V3 takes the path to a local audio file of up to 50 MB. The SDK uploads the file for
you before it calls the model:

```python
response = tir_client.infer(
    model_name="whisper-large-v3",
    data={
        "input": "<path-to-your-local-audio-file>",
        "task": "transcribe",
        "language": "english",
        # "max_new_tokens": 200,          # optional: 1 to 445
        # "return_timestamps": "sentence", # optional: none, sentence, or word
    },
)
print(response.outputs[0].data)
```

Replace `<path-to-your-local-audio-file>` with the path to the audio file on your machine. `task`
and `language` are required; set `language` to the language spoken in the audio. The two commented
lines are optional: one caps the length of the transcript, and the other adds timestamps to it.

## Read the transcription

`response.outputs[0].data` holds the transcription.

To call any other model in the catalog, see [Call the API with
REST](/tir/genai-api/how-to/call-the-api-with-rest/) or, for a text or embedding model, [Call the
API with the OpenAI SDK](/tir/genai-api/how-to/call-the-api-with-the-openai-sdk/). If the call
fails, see [Troubleshooting TIR GenAI API](/tir/genai-api/troubleshooting/genai-api/).