docs/source/en/chat_content_patterns.md

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# Chat message patterns

Chat models expect conversations as a list of dictionaries. Each dictionary uses `role` and `content` keys. The `content` key holds the user message passed to the model. Large language models accept text and tools and multimodal models combine text with images, videos, and audio.

Transformers uses a unified format where each modality type is specified explicitly, making it straightforward to mix and match inputs in a single message.

This guide covers message formatting patterns for each modality, tools, batch inference, and multi-turn conversations.

## Text

Text is the most basic content type. It's the foundation for all other patterns. Pass your message to `"content"` as a string.

```py
message = [
    {
        "role": "user",
        "content": "Explain the French Bread Law."
    }
]
```

You could also use the explicit `"type": "text"` format to keep your code consistent when you add images, videos, or audio later.

```py
message = [
    {
        "role": "user",
        "content": [{"type": "text", "text": "Explain the French Bread Law."}]
    }
]
```

## Tools

[Tools](./chat_extras) are functions a chat model can call, like getting real-time weather data, instead of generating it on its own.

The `assistant` role handles the tool request. Set `"type": "function"` in the `"tool_calls"` key and provide your tool to the `"function"` key. Append the assistant's tool request to your message.

```py
weather = {"name": "get_current_temperature", "arguments": {"location": "Paris, France", "unit": "celsius"}}
message.append(
    {
        "role": "assistant", 
        "tool_calls": [{"type": "function", "function": weather}]
    }
)
```

The `tool` role handles the result. Append it in `"content"`. This value should always be a string.

```py
message.append({"role": "tool", "content": "22"})
```

## Multimodal

Multimodal models extend this format to handle images, videos, and audio. Each input specifies its `"type"` and provides the media with `"url"` or `"path"`.

### Image

Set `"type": "image"` and use `"url"` for links or `"path"` for local files.

```py
message = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://assets.bonappetit.com/photos/57ad4ebc53e63daf11a4ddc7/master/w_1280,c_limit/kouign-amann.jpg"},
            {"type": "text", "text": "What pastry is shown in the image?"}
        ]
    }
]
```

### Video

Set `"type": "video"` and use `"url"` for links or `"path"` for local files.

```py
message = [
    {
        "role": "user",
        "content": [
            {"type": "video", "url": "https://static01.nyt.com/images/2019/10/01/dining/01Sourdough-GIF-1/01Sourdough-GIF-1-superJumbo.gif"},
            {"type": "text", "text": "What is shown in this video?"}
        ]
    }
]
```

### Audio

Set `"type": "audio"` and use `"url"` for links or `"path"` for local files.

```py
message = [
    {
        "role": "user",
        "content": [
            {"type": "audio", "url": "https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac"},
            {"type": "text", "text": "Transcribe the speech."}
        ]
    }
]
```

### Mixed multiple

The `content` list accepts any combination of types. The model processes all inputs together, enabling comparisons or cross-modal reasoning.

```py
message = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://assets.bonappetit.com/photos/57ad4ebc53e63daf11a4ddc7/master/w_1280,c_limit/kouign-amann.jpg"},
            {"type": "video", "url": "https://static01.nyt.com/images/2019/10/01/dining/01Sourdough-GIF-1/01Sourdough-GIF-1-superJumbo.gif"},
            {"type": "text", "text": "What does the image and video share in common?"},
        ],
    },
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://assets.bonappetit.com/photos/57ad4ebc53e63daf11a4ddc7/master/w_1280,c_limit/kouign-amann.jpg"},
            {"type": "image", "url": "https://assets.bonappetit.com/photos/57e191f49f19b4610e6b7693/master/w_1600%2Cc_limit/undefined"},
            {"type": "text", "text": "What type of pastries are these?"},
        ],
    }
]
```

## Batched

Batched inference processes multiple conversations in a single forward pass to improve throughput and efficiency. Wrap each conversation in its own list, then pass them together as a list of lists.

```py
messages = [
    [
        {"role": "user",
        "content": [
                {"type": "image", "url": "https://assets.bonappetit.com/photos/57ad4ebc53e63daf11a4ddc7/master/w_1280,c_limit/kouign-amann.jpg"},
                {"type": "text", "text": "What type of pastry is this?"}
            ]
        },
    ],
    [
        {"role": "user",
        "content": [
                {"type": "image", "url": "https://assets.bonappetit.com/photos/57e191f49f19b4610e6b7693/master/w_1600%2Cc_limit/undefined"},
                {"type": "text", "text": "What type of pastry is this?"}
            ]
        },
    ],
]
```

## Multi-turn

Conversations span multiple exchanges, alternating between `"user"` and `"assistant"` roles. Each turn adds a new message to the list, giving the model access to the full conversation history. This context helps the model generate more appropriate responses.

```py
message = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://assets.bonappetit.com/photos/57ad4ebc53e63daf11a4ddc7/master/w_1280,c_limit/kouign-amann.jpg"},
            {"type": "text", "text": "What pastry is shown in the image?"}
        ]
    },
    {
        "role": "assistant",
        "content": [{"type": "text", "text": "This is kouign amann, a laminated dough pastry (i.e., dough folded with layers of butter) that also incorporates sugar between layers so that during baking the sugar caramelizes."}]
    },
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://static01.nyt.com/images/2023/07/21/multimedia/21baguettesrex-hbkc/21baguettesrex-hbkc-videoSixteenByNineJumbo1600.jpg"},
            {"type": "text", "text": "Compare it to this image now."}
        ]
    }
]
```