mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Eduard van Valkenburg
09309c1239
* added embeddingsclient and redid chatclient * added to init * added client tests * fixed typing * fixed slice import * fixed pyright
83 lines
2.5 KiB
Python
83 lines
2.5 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from collections.abc import AsyncIterable, Sequence
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from typing import Any, Generic, Protocol, TypeVar, runtime_checkable
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from ._types import ChatMessage, ChatResponse, ChatResponseUpdate, GeneratedEmbeddings
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TInput = TypeVar("TInput", contravariant=True)
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TEmbedding = TypeVar("TEmbedding")
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# region: ChatClient Protocol
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@runtime_checkable
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class ChatClient(Protocol):
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"""A protocol for a chat client that can generate responses."""
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async def get_response(
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self,
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messages: ChatMessage | Sequence[ChatMessage],
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**kwargs: Any,
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) -> ChatResponse:
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"""Sends input and returns the response.
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Args:
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messages: The sequence of input messages to send.
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**kwargs: Additional options for the request, such as ai_model_id, temperature, etc.
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See `ChatOptions` for more details.
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Returns:
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The response messages generated by the client.
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Raises:
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ValueError: If the input message sequence is `None`.
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"""
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...
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async def get_streaming_response(
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self,
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messages: ChatMessage | Sequence[ChatMessage],
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**kwargs: Any,
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) -> AsyncIterable[ChatResponseUpdate]:
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"""Sends input messages and streams the response.
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Args:
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messages: The sequence of input messages to send.
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**kwargs: Additional options for the request, such as ai_model_id, temperature, etc.
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See `ChatOptions` for more details.
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Yields:
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An async iterable of chat response updates containing the content of the response messages
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generated by the client.
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Raises:
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ValueError: If the input message sequence is `None`.
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"""
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...
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# region: Embedding Client
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@runtime_checkable
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class EmbeddingGenerator(Protocol, Generic[TInput, TEmbedding]):
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"""A protocol for an embedding generator that can create embeddings from input data."""
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async def generate(
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self,
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input_data: Sequence[TInput],
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**kwargs: Any,
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) -> GeneratedEmbeddings[TEmbedding]:
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"""Generates an embedding for the given input data.
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Args:
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input_data: The input data to generate an embedding for.
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**kwargs: Additional options for the request.
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Returns:
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The generated embedding, this acts like a list, but has additional metadata and usage details.
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"""
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...
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