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Multimodal Data Models

Multimodal content types.

A modality is just a content part of a Message: the OpenAI/litellm chat-completion content is either a string or a list of parts, and an image or an audio clip is one of those parts. So multimodal input is plain chat-completion — Image and Audio are special types you drop straight into a ChatMessage's content list, mixed with the text that usually goes with them:

synalinks.ChatMessage(
    role="user",
    content=[
        "What is in this picture? Answer in one sentence.",
        synalinks.Image(url="https://example.com/cat.png"),
    ],
)

ChatMessage normalizes each element to its wire part (a plain str becomes a text part, an Image/Audio becomes its own part), so the message stays a strict chat-completion message and flows through the normal generator path.

Two ways a source becomes a payload

A url or path is just a reference; at some point the actual bytes have to be read and inlined as a base64 data: URI so every provider — including local ones that cannot fetch a URL themselves — receives the same self-contained payload. There are two moments that can happen, for two different use cases:

  1. At construction, when you build an Image(url=...) / Audio(path=...) in Python. The bytes are fetched/read immediately, so an unreachable source fails loudly right where it is written and the object is reusable without re-fetching. This is the right default for hand-written, interactive use.

  2. Per batch, at inference, for content built from raw JSON rather than the Python constructor — most importantly Dataset rows, which go through ChatMessages.model_validate_json(...). There the image_url/input_audio parts stay as lightweight references (a url/path), so a dataset of a million images never inlines a million payloads into memory. Resolution is deferred to resolve_content_media, which the language model calls on the messages it is about to send — i.e. only the current batch's media is ever resolved at once, and it is freed as soon as the request goes out.

A payload already inline — base64 data, or a data: URI — is left untouched by both paths, so the per-batch resolver is a no-op on construction-resolved content.

Adding a modality (video, documents, ...) is a new DataModel here with a to_content_part() method; nothing else in the stack needs to change.

Audio

Bases: DataModel

An audio content part for a chat message.

Provide a source — a url, a local file path, or raw base64 data — and a container format (e.g. "wav" or "mp3"). The chat-completion input_audio part carries inline base64 only, so a url/path is fetched and inlined at construction.

Source code in synalinks/src/backend/pydantic/media.py 
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@synalinks_export(
    [
        "synalinks.backend.Audio",
        "synalinks.Audio",
    ]
)
class Audio(DataModel):
    """An audio content part for a chat message.

    Provide a source — a `url`, a local file `path`, or raw base64 `data` — and
    a container `format` (e.g. ``"wav"`` or ``"mp3"``). The chat-completion
    `input_audio` part carries inline base64 only, so a `url`/`path` is fetched
    and inlined at construction.
    """

    url: Optional[str] = Field(
        default=None,
        description="An http(s) URL pointing to the audio; fetched at construction.",
    )
    path: Optional[str] = Field(
        default=None,
        description="A local file path to the audio; read at construction.",
    )
    data: Optional[str] = Field(
        default=None,
        description="Raw base64-encoded audio bytes.",
    )
    format: Optional[str] = Field(
        default=None,
        description="The audio container format, e.g. `wav` or `mp3`.",
    )

    @model_validator(mode="after")
    def _inline_source(self):
        """Fetch/read a `url`/`path` source and inline it as base64 `data`.

        Runs once, at construction. A payload already given as base64 `data` is
        left untouched.
        """
        if self.data is not None:
            return self
        read = _read_source(self.url, self.path)
        if read is not None:
            raw, _ = read
            self.data = base64.b64encode(raw).decode("ascii")
        return self

    def to_content_part(self):
        """Render this audio as an OpenAI/litellm `input_audio` content part."""
        return {
            "type": "input_audio",
            "input_audio": {"data": self.data, "format": self.format},
        }

to_content_part()

Render this audio as an OpenAI/litellm input_audio content part.

Source code in synalinks/src/backend/pydantic/media.py 
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def to_content_part(self):
    """Render this audio as an OpenAI/litellm `input_audio` content part."""
    return {
        "type": "input_audio",
        "input_audio": {"data": self.data, "format": self.format},
    }

Image

Bases: DataModel

An image content part for a chat message.

Provide exactly one source: a url (http(s):// or a data: URI), a local file path, or raw base64 data (with its mime_type). Drop it into a ChatMessage's content list next to the accompanying text. A url/path is resolved to the actual payload at construction (see the module docstring).

Source code in synalinks/src/backend/pydantic/media.py 
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@synalinks_export(
    [
        "synalinks.backend.Image",
        "synalinks.Image",
    ]
)
class Image(DataModel):
    """An image content part for a chat message.

    Provide exactly one source: a `url` (``http(s)://`` or a ``data:`` URI), a
    local file `path`, or raw base64 `data` (with its `mime_type`). Drop it
    into a `ChatMessage`'s content list next to the accompanying text. A
    `url`/`path` is resolved to the actual payload at construction (see the
    module docstring).
    """

    url: Optional[str] = Field(
        default=None,
        description="An http(s) URL or a `data:` URI pointing to the image.",
    )
    path: Optional[str] = Field(
        default=None,
        description="A local file path to the image; read at construction.",
    )
    data: Optional[str] = Field(
        default=None,
        description="Raw base64-encoded image bytes (used with `mime_type`).",
    )
    mime_type: Optional[str] = Field(
        default=None,
        description="The image MIME type, e.g. `image/png` (used with `data`).",
    )

    @model_validator(mode="after")
    def _inline_source(self):
        """Fetch/read a `url`/`path` source and inline it as base64 `data`.

        Runs once, at construction. A source already inline — base64 `data` or
        a ``data:`` URI in `url` — is left untouched.
        """
        if self.data is not None:
            return self
        read = _read_source(self.url, self.path)
        if read is not None:
            raw, mime = read
            self.data = base64.b64encode(raw).decode("ascii")
            if self.mime_type is None:
                self.mime_type = mime
        return self

    def to_content_part(self):
        """Render this image as an OpenAI/litellm `image_url` content part.

        A resolved image emits an inline base64 ``data:`` URI; a bare ``data:``
        URI `url` is passed through as-is.
        """
        if self.data:
            mime = self.mime_type or "image/png"
            return {
                "type": "image_url",
                "image_url": {"url": f"data:{mime};base64,{self.data}"},
            }
        return {"type": "image_url", "image_url": {"url": self.url}}

to_content_part()

Render this image as an OpenAI/litellm image_url content part.

A resolved image emits an inline base64 data: URI; a bare data: URI url is passed through as-is.

Source code in synalinks/src/backend/pydantic/media.py 
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def to_content_part(self):
    """Render this image as an OpenAI/litellm `image_url` content part.

    A resolved image emits an inline base64 ``data:`` URI; a bare ``data:``
    URI `url` is passed through as-is.
    """
    if self.data:
        mime = self.mime_type or "image/png"
        return {
            "type": "image_url",
            "image_url": {"url": f"data:{mime};base64,{self.data}"},
        }
    return {"type": "image_url", "image_url": {"url": self.url}}

normalize_content(content)

Normalize a ChatMessage.content value to its chat-completion shape.

A plain string or a non-list value is returned unchanged; a list has each element mapped through _normalize_content_element.

Source code in synalinks/src/backend/pydantic/media.py 
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def normalize_content(content):
    """Normalize a `ChatMessage.content` value to its chat-completion shape.

    A plain string or a non-list value is returned unchanged; a list has each
    element mapped through `_normalize_content_element`.
    """
    if isinstance(content, list):
        return [_normalize_content_element(e) for e in content]
    return content

resolve_content_media(messages) async

Resolve every deferred media reference in messages to an inline payload.

messages is a list of chat-completion wire dicts (one batch's worth). Any image_url part pointing at an http(s)/file:// source, and any input_audio part carrying a deferred url/path/marker source, is fetched/read and inlined as base64. Parts that are already inline — a data: URI or base64 data, e.g. content built from a constructed Image/Audio — are left untouched, so construction-resolved messages and text-only conversations pay nothing.

Source code in synalinks/src/backend/pydantic/media.py 
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async def resolve_content_media(messages):
    """Resolve every deferred media reference in `messages` to an inline payload.

    `messages` is a list of chat-completion wire dicts (one batch's worth). Any
    `image_url` part pointing at an ``http(s)``/``file://`` source, and any
    `input_audio` part carrying a deferred `url`/`path`/marker source, is
    fetched/read and inlined as base64. Parts that are already inline — a
    ``data:`` URI or base64 `data`, e.g. content built from a constructed
    `Image`/`Audio` — are left untouched, so construction-resolved messages and
    text-only conversations pay nothing.
    """
    for message in messages:
        content = message.get("content")
        if not isinstance(content, list):
            continue
        for part in content:
            if not isinstance(part, dict):
                continue
            if part.get("type") == "image_url":
                await _resolve_image_part(part)
            elif part.get("type") == "input_audio":
                await _resolve_audio_part(part)
    return messages