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@moonbox3
moonbox3 authored Dec 19, 2024
2 parents b6f216e + f50117f commit 928a5b9
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107 changes: 48 additions & 59 deletions python/semantic_kernel/connectors/ai/anthropic/services/anthropic_chat_completion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
import json
import logging
import sys
from collections.abc import AsyncGenerator
from collections.abc import AsyncGenerator, Callable
from typing import Any, ClassVar

if sys.version_info >= (3, 12):
Expand All @@ -26,7 +26,10 @@
from semantic_kernel.connectors.ai.anthropic.prompt_execution_settings.anthropic_prompt_execution_settings import (
AnthropicChatPromptExecutionSettings,
)
from semantic_kernel.connectors.ai.anthropic.services.utils import MESSAGE_CONVERTERS
from semantic_kernel.connectors.ai.anthropic.services.utils import (
MESSAGE_CONVERTERS,
update_settings_from_function_call_configuration,
)
from semantic_kernel.connectors.ai.anthropic.settings.anthropic_settings import AnthropicSettings
from semantic_kernel.connectors.ai.chat_completion_client_base import ChatCompletionClientBase
from semantic_kernel.connectors.ai.function_call_choice_configuration import FunctionCallChoiceConfiguration
Expand All @@ -43,10 +46,10 @@
from semantic_kernel.contents.utils.finish_reason import FinishReason as SemanticKernelFinishReason
from semantic_kernel.exceptions.service_exceptions import (
ServiceInitializationError,
ServiceInvalidRequestError,
ServiceInvalidResponseError,
ServiceResponseException,
)
from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata
from semantic_kernel.utils.experimental_decorator import experimental_class
from semantic_kernel.utils.telemetry.model_diagnostics.decorators import (
trace_chat_completion,
Expand Down Expand Up @@ -130,6 +133,19 @@ def get_prompt_execution_settings_class(self) -> type["PromptExecutionSettings"]
def service_url(self) -> str | None:
return str(self.async_client.base_url)

@override
def _update_function_choice_settings_callback(
self,
) -> Callable[[FunctionCallChoiceConfiguration, "PromptExecutionSettings", FunctionChoiceType], None]:
return update_settings_from_function_call_configuration

@override
def _reset_function_choice_settings(self, settings: "PromptExecutionSettings") -> None:
if hasattr(settings, "tool_choice"):
settings.tool_choice = None
if hasattr(settings, "tools"):
settings.tools = None

@override
@trace_chat_completion(MODEL_PROVIDER_NAME)
async def _inner_get_chat_message_contents(
Expand Down Expand Up @@ -172,6 +188,7 @@ async def _inner_get_streaming_chat_message_contents(
async for message in response:
yield message

@override
def _prepare_chat_history_for_request(
self,
chat_history: "ChatHistory",
Expand All @@ -195,14 +212,37 @@ def _prepare_chat_history_for_request(
system_message_content = None
system_message_count = 0
formatted_messages: list[dict[str, Any]] = []
for message in chat_history.messages:
# Skip system messages after the first one is found
if message.role == AuthorRole.SYSTEM:
for i in range(len(chat_history)):
prev_message = chat_history[i - 1] if i > 0 else None
curr_message = chat_history[i]
if curr_message.role == AuthorRole.SYSTEM:
# Skip system messages after the first one is found
if system_message_count == 0:
system_message_content = message.content
system_message_content = curr_message.content
system_message_count += 1
elif curr_message.role == AuthorRole.USER or curr_message.role == AuthorRole.ASSISTANT:
formatted_messages.append(MESSAGE_CONVERTERS[curr_message.role](curr_message))
elif curr_message.role == AuthorRole.TOOL:
if prev_message is None:
# Under no circumstances should a tool message be the first message in the chat history
raise ServiceInvalidRequestError("Tool message found without a preceding message.")
if prev_message.role == AuthorRole.USER or prev_message.role == AuthorRole.SYSTEM:
# A tool message should not be found after a user or system message
# Please NOTE that in SK there are the USER role and the TOOL role, but in Anthropic
# the tool messages are considered as USER messages. We are checking against the SK roles.
raise ServiceInvalidRequestError("Tool message found after a user or system message.")

formatted_message = MESSAGE_CONVERTERS[curr_message.role](curr_message)
if prev_message.role == AuthorRole.ASSISTANT:
# The first tool message after an assistant message should be a new message
formatted_messages.append(formatted_message)
else:
# Append the tool message to the previous tool message.
# This indicates that the assistant message requested multiple parallel tool calls.
# Anthropic requires that parallel Tool messages are grouped together in a single message.
formatted_messages[-1][content_key] += formatted_message[content_key]
else:
formatted_messages.append(MESSAGE_CONVERTERS[message.role](message))
raise ServiceInvalidRequestError(f"Unsupported role in chat history: {curr_message.role}")

if system_message_count > 1:
logger.warning(
Expand Down Expand Up @@ -280,50 +320,6 @@ def _create_streaming_chat_message_content(
function_invoke_attempt=function_invoke_attempt,
)

def update_settings_from_function_call_configuration_anthropic(
self,
function_choice_configuration: FunctionCallChoiceConfiguration,
settings: "PromptExecutionSettings",
type: "FunctionChoiceType",
) -> None:
"""Update the settings from a FunctionChoiceConfiguration."""
if (
function_choice_configuration.available_functions
and hasattr(settings, "tools")
and hasattr(settings, "tool_choice")
):
settings.tools = [
self.kernel_function_metadata_to_function_call_format_anthropic(f)
for f in function_choice_configuration.available_functions
]

if (
settings.function_choice_behavior
and settings.function_choice_behavior.type_ == FunctionChoiceType.REQUIRED
) or type == FunctionChoiceType.REQUIRED:
settings.tool_choice = {"type": "any"}
else:
settings.tool_choice = {"type": type.value}

def kernel_function_metadata_to_function_call_format_anthropic(
self,
metadata: KernelFunctionMetadata,
) -> dict[str, Any]:
"""Convert the kernel function metadata to function calling format."""
return {
"name": metadata.fully_qualified_name,
"description": metadata.description or "",
"input_schema": {
"type": "object",
"properties": {p.name: p.schema_data for p in metadata.parameters},
"required": [p.name for p in metadata.parameters if p.is_required],
},
}

@override
def _update_function_choice_settings_callback(self):
return self.update_settings_from_function_call_configuration_anthropic

async def _send_chat_request(self, settings: AnthropicChatPromptExecutionSettings) -> list["ChatMessageContent"]:
"""Send the chat request."""
try:
Expand Down Expand Up @@ -389,10 +385,3 @@ def _get_tool_calls_from_message(self, message: Message) -> list[FunctionCallCon
)

return tool_calls

@override
def _reset_function_choice_settings(self, settings: "PromptExecutionSettings") -> None:
if hasattr(settings, "tool_choice"):
settings.tool_choice = None
if hasattr(settings, "tools"):
settings.tools = None
74 changes: 59 additions & 15 deletions python/semantic_kernel/connectors/ai/anthropic/services/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,15 @@
from collections.abc import Callable, Mapping
from typing import Any

from semantic_kernel.connectors.ai.function_call_choice_configuration import FunctionCallChoiceConfiguration
from semantic_kernel.connectors.ai.function_choice_behavior import FunctionChoiceType
from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
from semantic_kernel.contents.chat_message_content import ChatMessageContent
from semantic_kernel.contents.function_call_content import FunctionCallContent
from semantic_kernel.contents.function_result_content import FunctionResultContent
from semantic_kernel.contents.text_content import TextContent
from semantic_kernel.contents.utils.author_role import AuthorRole
from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata

logger: logging.Logger = logging.getLogger(__name__)

Expand Down Expand Up @@ -50,29 +54,32 @@ def _format_assistant_message(message: ChatMessageContent) -> dict[str, Any]:
"type": "tool_use",
"id": item.id or "",
"name": item.name or "",
"input": item.arguments if isinstance(item.arguments, Mapping) else json.loads(item.arguments or ""),
"input": item.arguments
if isinstance(item.arguments, Mapping)
else json.loads(item.arguments)
if item.arguments
else {},
})
else:
logger.warning(
f"Unsupported item type in Assistant message while formatting chat history for Anthropic: {type(item)}"
)

formatted_message: dict[str, Any] = {"role": "assistant", "content": []}

if message.content:
# Only include the text content if it is not empty.
# Otherwise, the Anthropic client will throw an error.
formatted_message["content"].append({ # type: ignore
"type": "text",
"text": message.content,
})
if tool_calls:
return {
"role": "assistant",
"content": [
{
"type": "text",
"text": message.content,
},
*tool_calls,
],
}
# Only include the tool calls if there are any.
# Otherwise, the Anthropic client will throw an error.
formatted_message["content"].extend(tool_calls) # type: ignore

return {
"role": "assistant",
"content": message.content,
}
return formatted_message


def _format_tool_message(message: ChatMessageContent) -> dict[str, Any]:
Expand Down Expand Up @@ -108,3 +115,40 @@ def _format_tool_message(message: ChatMessageContent) -> dict[str, Any]:
AuthorRole.ASSISTANT: _format_assistant_message,
AuthorRole.TOOL: _format_tool_message,
}


def update_settings_from_function_call_configuration(
function_choice_configuration: FunctionCallChoiceConfiguration,
settings: PromptExecutionSettings,
type: FunctionChoiceType,
) -> None:
"""Update the settings from a FunctionChoiceConfiguration."""
if (
function_choice_configuration.available_functions
and hasattr(settings, "tools")
and hasattr(settings, "tool_choice")
):
settings.tools = [
kernel_function_metadata_to_function_call_format(f)
for f in function_choice_configuration.available_functions
]

if (
settings.function_choice_behavior and settings.function_choice_behavior.type_ == FunctionChoiceType.REQUIRED
) or type == FunctionChoiceType.REQUIRED:
settings.tool_choice = {"type": "any"}
else:
settings.tool_choice = {"type": type.value}


def kernel_function_metadata_to_function_call_format(metadata: KernelFunctionMetadata) -> dict[str, Any]:
"""Convert the kernel function metadata to function calling format."""
return {
"name": metadata.fully_qualified_name,
"description": metadata.description or "",
"input_schema": {
"type": "object",
"properties": {p.name: p.schema_data for p in metadata.parameters},
"required": [p.name for p in metadata.parameters if p.is_required],
},
}
4 changes: 1 addition & 3 deletions python/tests/integration/completions/chat_completion_test_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,9 +66,7 @@
onnx_setup: bool = is_service_setup_for_testing(
["ONNX_GEN_AI_CHAT_MODEL_FOLDER"], raise_if_not_set=False
) # Tests are optional for ONNX
anthropic_setup: bool = is_service_setup_for_testing(
["ANTHROPIC_API_KEY", "ANTHROPIC_CHAT_MODEL_ID"], raise_if_not_set=False
) # We don't have an Anthropic deployment
anthropic_setup: bool = is_service_setup_for_testing(["ANTHROPIC_API_KEY", "ANTHROPIC_CHAT_MODEL_ID"])
# When testing Bedrock, after logging into AWS CLI this has been set, so we can use it to check if the service is setup
bedrock_setup: bool = is_service_setup_for_testing(["AWS_DEFAULT_REGION"], raise_if_not_set=False)

Expand Down
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