PromptMessage
Chat message structures and role enumerations for LLM conversations.Overview
Message types define chat messages with roles and multi-modal content arrays. These are the building blocks for all prompt conversations in the Adaline SDK.MessageRole
See the dedicated MessageRole page for full documentation. Message role enumeration for chat messages.from adaline_api.models.message_role import MessageRole
MessageRole is a str enum with the following values:
| Value | Enum Member | Description |
|---|---|---|
"system" | MessageRole.SYSTEM | System instructions or context |
"user" | MessageRole.USER | User messages and input |
"assistant" | MessageRole.ASSISTANT | AI assistant responses |
"tool" | MessageRole.TOOL | Tool/function responses |
from adaline_api.models.message_role import MessageRole
role = MessageRole.USER # 'user'
role = MessageRole.SYSTEM # 'system'
role = MessageRole.ASSISTANT # 'assistant'
role = MessageRole.TOOL # 'tool'
# String comparison works
assert MessageRole.USER == "user"
PromptMessage
Chat message with role and multi-modal content for LLM conversations.from adaline_api.models.prompt_message import PromptMessage
Fields
The message sender role. One of:
"system", "user", "assistant", "tool".Array of content items. See MessageContent.
Examples
Simple Text Message
from adaline_api.models.prompt_message import PromptMessage
from adaline_api.models.message_content import MessageContent
from adaline_api.models.text_content import TextContent
message = PromptMessage(
role="user",
content=[
MessageContent(actual_instance=TextContent(
modality="text",
value="Hello, how are you?"
))
]
)
System Message
system_message = PromptMessage(
role="system",
content=[
MessageContent(actual_instance=TextContent(
modality="text",
value="You are a helpful AI assistant."
))
]
)
Multi-Modal Message
from adaline_api.models.image_content import ImageContent
from adaline_api.models.image_content_value import ImageContentValue
multi_modal = PromptMessage(
role="user",
content=[
MessageContent(actual_instance=TextContent(
modality="text",
value="Describe this image"
)),
MessageContent(actual_instance=ImageContent(
modality="image",
detail="high",
value=ImageContentValue.from_dict({
"type": "url",
"url": "https://example.com/img.jpg"
})
))
]
)
Conversation History
conversation: list[PromptMessage] = [
PromptMessage(
role="system",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="You are helpful."
))]
),
PromptMessage(
role="user",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="What is 2+2?"
))]
),
PromptMessage(
role="assistant",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="2+2 equals 4."
))]
),
PromptMessage(
role="user",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="And 3+3?"
))]
),
PromptMessage(
role="assistant",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="3+3 equals 6."
))]
),
]
Tool Call Sequence
import json
from adaline_api.models.tool_call_content import ToolCallContent
from adaline_api.models.tool_response_content import ToolResponseContent
# User asks
user_msg = PromptMessage(
role="user",
content=[MessageContent(actual_instance=TextContent(
modality="text",
value="What is the weather in Paris?"
))]
)
# Assistant requests tool
assistant_tool = PromptMessage(
role="assistant",
content=[MessageContent(actual_instance=ToolCallContent(
modality="tool-call",
index=0,
id="call_123",
name="get_weather",
arguments=json.dumps({"city": "Paris"})
))]
)
# Tool responds
tool_msg = PromptMessage(
role="tool",
content=[MessageContent(actual_instance=ToolResponseContent(
modality="tool-response",
index=0,
id="call_123",
name="get_weather",
data=json.dumps({"temp": 24, "conditions": "sunny"})
))]
)
# Assistant answers
assistant_answer = PromptMessage(
role="assistant",
content=[MessageContent(actual_instance=TextContent(
modality="text",
value="In Paris it is sunny and 24°C."
))]
)
Using with Deployments
from adaline.main import Adaline
from adaline_api.models.prompt_message import PromptMessage
from adaline_api.models.message_content import MessageContent
from adaline_api.models.text_content import TextContent
adaline = Adaline()
deployment = await adaline.get_latest_deployment(
prompt_id="prompt_abc123",
deployment_environment_id="environment_abc123"
)
# Get messages from deployment
system_messages: list[PromptMessage] = deployment.prompt.messages
# Add user message
user_message = PromptMessage(
role="user",
content=[MessageContent(actual_instance=TextContent(
modality="text",
value="Hello!"
))]
)
# Combine for API call
all_messages = [*system_messages, user_message]
Helper Functions
from adaline_api.models.prompt_message import PromptMessage
from adaline_api.models.message_content import MessageContent
from adaline_api.models.text_content import TextContent
from adaline_api.models.image_content import ImageContent
def create_text_message(role: str, text: str) -> PromptMessage:
return PromptMessage(
role=role,
content=[MessageContent(actual_instance=TextContent(
modality="text", value=text
))]
)
def get_message_text(message: PromptMessage) -> str:
texts = []
for c in message.content:
if isinstance(c.actual_instance, TextContent):
texts.append(c.actual_instance.value)
return " ".join(texts)
def has_images(message: PromptMessage) -> bool:
return any(
isinstance(c.actual_instance, ImageContent)
for c in message.content
)
def filter_by_role(
messages: list[PromptMessage], role: str
) -> list[PromptMessage]:
return [m for m in messages if m.role == role]
# Usage
msg = create_text_message("user", "Hello!")
text = get_message_text(msg) # 'Hello!'
has_img = has_images(msg) # False
Serialization
All autogen models supportto_dict(), to_json(), from_dict(), and from_json() for serialization.
message = PromptMessage(
role="user",
content=[MessageContent(actual_instance=TextContent(
modality="text", value="Hello!"
))]
)
# To dict / JSON
d = message.to_dict()
j = message.to_json()
# From dict / JSON
restored = PromptMessage.from_dict(d)
restored = PromptMessage.from_json(j)
JSON Examples
Simple
{
"role": "user",
"content": [
{ "modality": "text", "value": "Hello!" }
]
}
With Image
{
"role": "user",
"content": [
{ "modality": "text", "value": "Describe this" },
{
"modality": "image",
"detail": "high",
"value": {
"type": "url",
"url": "https://example.com/image.jpg"
}
}
]
}
Tool Call
{
"role": "assistant",
"content": [
{
"modality": "tool-call",
"index": 0,
"id": "call_123",
"name": "get_weather",
"arguments": "{\"city\":\"Paris\"}"
}
]
}