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Message API

The Message class represents individual interactions within a thread. It handles text and multimodal content, attachments, metrics, and metadata for each message in a conversation.

Initialization

from tyler.models.message import Message
from datetime import datetime, UTC

# Basic text message
message = Message(
role="user",
content="Hello!"
)

# Multimodal message (text + images)
message = Message(
role="user",
content=[
{
"type": "text",
"text": "What's in this image?"
},
{
"type": "image_url",
"image_url": {
"url": "path/to/image.jpg"
}
}
]
)

# Message with file attachment
message = Message(
role="assistant",
content="Here's the analysis",
file_content=pdf_bytes, # Raw file bytes
filename="document.pdf" # Will be automatically converted to attachment
)

# Tool message
message = Message(
role="tool",
name="weather_tool",
content='{"temperature": 72}',
tool_call_id="call_123" # Required for tool messages
)

# Message with source and attributes
message = Message(
role="user",
content="Hello!",
source={
"entity": {
"id": "U123456",
"name": "John Doe",
"type": "user"
},
"platform": {
"name": "slack",
"attributes": {
"thread_ts": "1234567890.123456"
}
}
},
attributes={"customer_id": "456"}
)

Parameters

ParameterTypeRequiredDefaultDescription
idstrNoAuto-generatedUnique message identifier (SHA-256 hash of content)
roleLiteral["system", "user", "assistant", "tool"]YesNoneMessage role
sequenceOptional[int]NoNoneMessage sequence in thread (0 for system, incremental for others)
contentOptional[Union[str, List[Union[TextContent, ImageContent]]]]NoNoneMessage content (text or multimodal)
nameOptional[str]NoNoneTool name (for tool messages)
tool_call_idOptional[str]NoNoneTool call ID (required for tool messages)
tool_callsOptional[list]NoNoneTool calls (for assistant messages)
attributesDictNoCustom metadata
timestampdatetimeNonow(UTC)Message timestamp
sourceOptional[MessageSource]NoNoneSource information (see MessageSource structure)
attachmentsList[Attachment]No[]File attachments
metricsDict[str, Any]NoDefault metricsMessage metrics and analytics

Source Structure

# TypedDict definitions for source structure
class PlatformSource(TypedDict, total=False):
name: str # Name of the platform (slack, discord, etc.)
attributes: Optional[Dict[str, Any]] # Platform-specific attributes

class EntitySource(TypedDict, total=False):
id: str # Unique identifier for the entity
name: str # Human-readable name of the entity
type: Literal["user", "agent", "tool"] # Type of entity
attributes: Optional[Dict[str, Any]] # All other entity-specific attributes

class MessageSource(TypedDict, total=False):
entity: Optional[EntitySource] # Information about the entity that created the message
platform: Optional[PlatformSource] # Information about the platform where the message was created

Content Types

# TypedDict definitions for content types
class ImageUrl(TypedDict):
url: str

class ImageContent(TypedDict):
type: Literal["image_url"]
image_url: ImageUrl

class TextContent(TypedDict):
type: Literal["text"]
text: str

Metrics Structure

{
"model": None, # Model used for generation
"timing": {
"started_at": None, # Start timestamp
"ended_at": None, # End timestamp
"latency": 0 # Processing time in milliseconds
},
"usage": {
"completion_tokens": 0,
"prompt_tokens": 0,
"total_tokens": 0
},
"weave_call": {
"id": "", # Weave trace ID
"ui_url": "" # Weave UI URL
}
}

Methods

model_dump

Convert message to a dictionary suitable for JSON serialization.

def model_dump(self, mode: str = "json") -> Dict[str, Any]

Parameters:

  • mode: Serialization mode, either "json" or "python"
    • "json": Converts datetimes to ISO strings (default)
    • "python": Keeps datetimes as datetime objects

Returns a complete dictionary representation including:

{
"id": str,
"role": str,
"sequence": int,
"content": Union[str, List],
"name": Optional[str],
"tool_call_id": Optional[str],
"tool_calls": Optional[List],
"timestamp": str, # ISO format with timezone (if mode="json")
"source": Optional[Dict],
"metrics": Dict,
"attributes": Dict,
"attachments": Optional[List[Dict]] # Serialized attachments
}

For attachments, each attachment is serialized as:

{
"filename": str,
"mime_type": str,
"file_id": Optional[str],
"storage_path": Optional[str],
"storage_backend": Optional[str],
"status": str, # "pending", "stored", or "failed"
"attributes": Optional[Dict] # Processed content and metadata
}

The attributes field contains file-specific information such as extracted text, image analysis, or parsed JSON data, depending on the file type.

to_chat_completion_message

Return message in the format expected by chat completion APIs.

def to_chat_completion_message(self, file_store: Optional[FileStore] = None) -> Dict[str, Any]

Parameters:

  • file_store: Optional FileStore instance for accessing file URLs

Returns:

{
"role": str,
"content": str,
"sequence": int,
"name": Optional[str], # For tool messages
"tool_calls": Optional[List], # For assistant messages
"tool_call_id": Optional[str] # For tool messages
}

For messages with attachments:

  • User and tool messages: Adds file references to content
  • Assistant messages: Adds "Generated Files:" section with file references

add_attachment

Add an attachment to the message.

def add_attachment(
self,
attachment: Union[Attachment, bytes],
filename: Optional[str] = None
) -> None

Parameters

ParameterTypeRequiredDefaultDescription
attachmentUnion[Attachment, bytes]YesNoneAttachment object or raw bytes
filenameOptional[str]With bytesNoneRequired when attachment is bytes

Examples

# Add using raw bytes
message.add_attachment(pdf_bytes, filename="document.pdf")

# Add using Attachment object
attachment = Attachment(filename="data.json", content=json_bytes)
message.add_attachment(attachment)

_serialize_tool_calls

Helper method to serialize tool calls into a JSON-friendly format.

def _serialize_tool_calls(self, tool_calls) -> Optional[List[Dict]]

Handles various tool call formats:

  • OpenAI response objects with model_dump or to_dict methods
  • Objects with direct attribute access
  • Dictionary representations
  • Returns None if no valid tool calls are found

Working with Attachments

The Message class provides seamless integration with the Attachment model for handling files in conversations.

Attachment Storage Flow

When a message with attachments is added to a thread and saved:

  1. The ThreadStore.save() method triggers processing of all attachments
  2. Each attachment's process_and_store() method is called
  3. The attachment content is analyzed and processed based on file type
  4. The file is stored in the configured storage backend
  5. The attachment's metadata is updated:
    • status changes from "pending" to "stored"
    • file_id and storage_path are set
    • attributes is populated with file-specific information

Attachment Types and Processing

Different file types receive specialized processing:

File TypeMIME TypeAttributes Added
Imagesimage/*type, overview, text (OCR), analysis
Documentsapplication/pdftype, text (extracted), overview
Texttext/*type, preview, text
JSONapplication/jsontype, overview, parsed_content
Audioaudio/*type, description
Other*type, description

Accessing Attachment Content

# Get raw content bytes
content_bytes = await attachment.get_content_bytes()

# Access processed attributes
if attachment.attributes:
# Common attributes
file_type = attachment.attributes.get("type")
url = attachment.attributes.get("url")

# Type-specific attributes
if file_type == "image":
text = attachment.attributes.get("text") # OCR text
overview = attachment.attributes.get("overview") # Description
elif file_type == "document":
text = attachment.attributes.get("text") # Extracted text
elif file_type == "json":
parsed = attachment.attributes.get("parsed_content") # Parsed JSON

Attachment URLs

The Message model automatically handles attachment URLs when converting to chat completion format:

# Get chat completion format
chat_message = message.to_chat_completion_message()

# For messages with attachments, URLs are included in the content
# Example: [File: /files/path/to/file.pdf (application/pdf)]

The URL is retrieved from:

  1. attachment.attributes["url"] if available
  2. Constructed from attachment.storage_path if not

Field Validators

ensure_timezone

Ensures timestamp is timezone-aware UTC.

@field_validator("timestamp", mode="before")
def ensure_timezone(cls, value: datetime) -> datetime

validate_role

Validate role field.

@field_validator("role")
def validate_role(cls, v: str) -> str

Ensures role is one of: system, user, assistant, tool

validate_tool_message

Validate tool message requirements.

@model_validator(mode='after')
def validate_tool_message(self) -> 'Message'

Ensures tool messages have required tool_call_id

validate_tool_calls

Validate tool_calls field structure.

@field_validator("tool_calls")
def validate_tool_calls(cls, v: list) -> list

Ensures tool calls have proper structure with id, type, and function fields

validate_source

Validate source field structure.

@field_validator("source")
def validate_source(cls, v) -> Optional[Dict]

Ensures the source field has the correct structure with valid entity type if present.

Best Practices

  1. Message Sequencing

    # System messages get sequence 0
    system_msg = Message(role="system", content="System prompt")
    thread.add_message(system_msg) # Gets sequence 0

    # Other messages get incremental sequences
    user_msg = Message(role="user", content="Hello")
    thread.add_message(user_msg) # Gets sequence 1
  2. File Handling

    # Add file during creation
    message = Message(
    content="Here's a file",
    file_content=bytes_data,
    filename="document.pdf"
    )

    # Or add after creation
    message.add_attachment(bytes_data, filename="data.pdf")

    # Add attachment with explicit attributes
    attachment = Attachment(
    filename="image.jpg",
    content=image_bytes,
    mime_type="image/jpeg",
    attributes={
    "type": "image",
    "overview": "A landscape photograph"
    }
    )
    message.add_attachment(attachment)

    # Let ThreadStore handle attachment storage
    thread.add_message(message)
    await thread_store.save(thread) # Will process and store attachments
  3. Tool Messages

    # Tool messages require tool_call_id
    tool_msg = Message(
    role="tool",
    name="web_search",
    content="Search results...",
    tool_call_id="call_123"
    )
  4. Metrics Tracking

    # Update metrics after processing
    message.metrics.update({
    "model": "gpt-4o",
    "timing": {
    "started_at": start_time,
    "ended_at": end_time,
    "latency": latency_ms # in milliseconds
    },
    "usage": {
    "completion_tokens": response.usage.completion_tokens,
    "prompt_tokens": response.usage.prompt_tokens,
    "total_tokens": response.usage.total_tokens
    }
    })
  5. Source Attribution

    # Using detailed source attribution
    message = Message(
    role="user",
    content="Hello",
    source={
    "entity": {
    "id": "U123456",
    "name": "John Doe",
    "type": "user",
    "attributes": {
    "email": "john@example.com"
    }
    },
    "platform": {
    "name": "slack",
    "attributes": {
    "channel_id": "C123456",
    "thread_ts": "1234567890.123456"
    }
    }
    }
    )
  6. Attachment URL Handling

    # The Message model automatically handles attachment URLs in chat completions
    # When converting a message to chat completion format:
    chat_message = message.to_chat_completion_message(file_store)

See Also