autogen_ext.models.replay

class ReplayChatCompletionClient(chat_completions: Sequence[str | CreateResult])

Bases: object

A mock chat completion client that replays predefined responses using an index-based approach.

This class simulates a chat completion client by replaying a predefined list of responses. It supports both single completion and streaming responses. The responses can be either strings or CreateResult objects. The client now uses an index-based approach to access the responses, allowing for resetting the state.

Note

The responses can be either strings or CreateResult objects.

Parameters:

chat_completions (Sequence[Union[str, CreateResult]]) – A list of predefined responses to replay.

Raises:

ValueError("No more mock responses available") – If the list of provided outputs are exhausted.

Examples:

Simple chat completion client to return pre-defined responses.

from autogen_ext.models.replay import ReplayChatCompletionClient
from autogen_core.models import UserMessage


async def example():
    chat_completions = [
        "Hello, how can I assist you today?",
        "I'm happy to help with any questions you have.",
        "Is there anything else I can assist you with?",
    ]
    client = ReplayChatCompletionClient(chat_completions)
    messages = [UserMessage(content="What can you do?", source="user")]
    response = await client.create(messages)
    print(response.content)  # Output: "Hello, how can I assist you today?"

Simple streaming chat completion client to return pre-defined responses

import asyncio
from autogen_ext.models.replay import ReplayChatCompletionClient
from autogen_core.models import UserMessage


async def example():
    chat_completions = [
        "Hello, how can I assist you today?",
        "I'm happy to help with any questions you have.",
        "Is there anything else I can assist you with?",
    ]
    client = ReplayChatCompletionClient(chat_completions)
    messages = [UserMessage(content="What can you do?", source="user")]

    async for token in client.create_stream(messages):
        print(token, end="")  # Output: "Hello, how can I assist you today?"

    async for token in client.create_stream(messages):
        print(token, end="")  # Output: "I'm happy to help with any questions you have."

    asyncio.run(example())

Using .reset to reset the chat client state

import asyncio
from autogen_ext.models.replay import ReplayChatCompletionClient
from autogen_core.models import UserMessage


async def example():
    chat_completions = [
        "Hello, how can I assist you today?",
    ]
    client = ReplayChatCompletionClient(chat_completions)
    messages = [UserMessage(content="What can you do?", source="user")]
    response = await client.create(messages)
    print(response.content)  # Output: "Hello, how can I assist you today?"

    response = await client.create(messages)  # Raises ValueError("No more mock responses available")

    client.reset()  # Reset the client state (current index of message and token usages)
    response = await client.create(messages)
    print(response.content)  # Output: "Hello, how can I assist you today?" again


asyncio.run(example())

actual_usage() → RequestUsage

property capabilities: ModelCapabilities

Return mock capabilities.

count_tokens(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], tools: Sequence[Tool | ToolSchema] = []) → int

async create(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], tools: Sequence[Tool | ToolSchema] = [], json_output: bool | None = None, extra_create_args: Mapping[str, Any] = {}, cancellation_token: CancellationToken | None = None) → CreateResult

Return the next completion from the list.

async create_stream(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], tools: Sequence[Tool | ToolSchema] = [], json_output: bool | None = None, extra_create_args: Mapping[str, Any] = {}, cancellation_token: CancellationToken | None = None) → AsyncGenerator[str | CreateResult, None]

Return the next completion as a stream.

remaining_tokens(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], tools: Sequence[Tool | ToolSchema] = []) → int

reset() → None

Reset the client state and usage to its initial state.

total_usage() → RequestUsage