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https://github.com/csunny/DB-GPT.git
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feat(core): Support i18n (#1327)
This commit is contained in:
Fangyin Cheng
GitHub
@@ -1,10 +1,12 @@
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"""Flow operators package."""
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from dbgpt.core.operators.flow.composer_operator import ( # noqa: F401
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from .composer_operator import ( # noqa: F401
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ConversationComposerOperator,
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PromptFormatDictBuilderOperator,
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)
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from .dict_operator import MergeStringToDictOperator # noqa: F401
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__ALL__ = [
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"ConversationComposerOperator",
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"PromptFormatDictBuilderOperator",
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"MergeStringToDictOperator",
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]
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@@ -29,6 +29,7 @@ from dbgpt.core.interface.operators.message_operator import (
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from dbgpt.core.interface.operators.prompt_operator import HistoryPromptBuilderOperator
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from dbgpt.core.interface.prompt import ChatPromptTemplate
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from dbgpt.core.interface.storage import StorageInterface
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from dbgpt.util.i18n_utils import _
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class ConversationComposerOperator(MapOperator[CommonLLMHttpRequestBody, ModelRequest]):
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@@ -38,82 +39,86 @@ class ConversationComposerOperator(MapOperator[CommonLLMHttpRequestBody, ModelRe
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"""
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metadata = ViewMetadata(
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label="Conversation Composer Operator",
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label=_("Conversation Composer Operator"),
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name="conversation_composer_operator",
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category=OperatorCategory.CONVERSION,
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description="A composer operator for conversation.\nIncluding chat history "
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"handling, prompt composing, etc. Output is ModelRequest.",
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description=_(
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"A composer operator for conversation.\nIncluding chat history "
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"handling, prompt composing, etc. Output is ModelRequest."
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),
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parameters=[
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Parameter.build_from(
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"Prompt Template",
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_("Prompt Template"),
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"prompt_template",
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ChatPromptTemplate,
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description="The prompt template for the conversation.",
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description=_("The prompt template for the conversation."),
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),
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Parameter.build_from(
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"Human Message Key",
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_("Human Message Key"),
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"human_message_key",
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str,
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optional=True,
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default="user_input",
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description="The key for human message in the prompt format dict.",
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description=_("The key for human message in the prompt format dict."),
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),
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Parameter.build_from(
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"History Key",
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_("History Key"),
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"history_key",
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str,
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optional=True,
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default="chat_history",
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description="The chat history key, with chat history message pass to "
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"prompt template.",
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description=_(
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"The chat history key, with chat history message pass to "
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"prompt template."
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),
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),
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Parameter.build_from(
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"Keep Start Rounds",
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_("Keep Start Rounds"),
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"keep_start_rounds",
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int,
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optional=True,
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default=None,
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description="The start rounds to keep in the chat history.",
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description=_("The start rounds to keep in the chat history."),
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),
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Parameter.build_from(
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"Keep End Rounds",
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_("Keep End Rounds"),
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"keep_end_rounds",
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int,
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optional=True,
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default=10,
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description="The end rounds to keep in the chat history.",
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description=_("The end rounds to keep in the chat history."),
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),
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Parameter.build_from(
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"Conversation Storage",
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_("Conversation Storage"),
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"storage",
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StorageInterface,
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optional=True,
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default=None,
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description="The conversation storage(Not include message detail).",
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description=_("The conversation storage(Not include message detail)."),
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),
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Parameter.build_from(
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"Message Storage",
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_("Message Storage"),
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"message_storage",
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StorageInterface,
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optional=True,
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default=None,
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description="The message storage.",
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description=_("The message storage."),
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),
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],
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inputs=[
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IOField.build_from(
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"Common LLM Http Request Body",
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_("Common LLM Http Request Body"),
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"common_llm_http_request_body",
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CommonLLMHttpRequestBody,
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description="The common LLM http request body.",
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description=_("The common LLM http request body."),
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)
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],
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outputs=[
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IOField.build_from(
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"Model Request",
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_("Model Request"),
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"model_request",
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ModelRequest,
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description="The model request with chat history prompt.",
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description=_("The model request with chat history prompt."),
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)
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],
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)
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@@ -184,10 +189,10 @@ class ConversationComposerOperator(MapOperator[CommonLLMHttpRequestBody, ModelRe
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history_prompt_build_task >> model_request_build_task
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return composer_dag
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async def after_dag_end(self):
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async def after_dag_end(self, event_loop_task_id: int):
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"""Execute after dag end."""
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# Should call after_dag_end() of sub dag
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await self._sub_compose_dag._after_dag_end()
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await self._sub_compose_dag._after_dag_end(event_loop_task_id)
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class PromptFormatDictBuilderOperator(
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@@ -199,35 +204,37 @@ class PromptFormatDictBuilderOperator(
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"""
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metadata = ViewMetadata(
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label="Prompt Format Dict Builder Operator",
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label=_("Prompt Format Dict Builder Operator"),
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name="prompt_format_dict_builder_operator",
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category=OperatorCategory.CONVERSION,
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description="A operator to build prompt format dict from common LLM http "
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"request body.",
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description=_(
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"A operator to build prompt format dict from common LLM http "
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"request body."
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),
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parameters=[
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Parameter.build_from(
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"Human Message Key",
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_("Human Message Key"),
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"human_message_key",
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str,
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optional=True,
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default="user_input",
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description="The key for human message in the prompt format dict.",
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description=_("The key for human message in the prompt format dict."),
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)
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],
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inputs=[
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IOField.build_from(
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"Common LLM Http Request Body",
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_("Common LLM Http Request Body"),
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"common_llm_http_request_body",
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CommonLLMHttpRequestBody,
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description="The common LLM http request body.",
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description=_("The common LLM http request body."),
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)
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],
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outputs=[
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IOField.build_from(
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"Prompt Format Dict",
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_("Prompt Format Dict"),
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"prompt_format_dict",
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Dict[str, Any],
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description="The prompt format dict.",
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dict,
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description=_("The prompt format dict."),
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)
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],
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)
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@@ -239,7 +246,7 @@ class PromptFormatDictBuilderOperator(
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async def map(self, input_value: CommonLLMHttpRequestBody) -> Dict[str, Any]:
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"""Build prompt format dict from common LLM http request body."""
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extra_data = input_value.context.extra if input_value.context.extra else {}
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extra_data = input_value.extra if input_value.extra else {}
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return {
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self._human_message_key: input_value.messages,
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**extra_data,
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76
dbgpt/core/operators/flow/dict_operator.py
Normal file
76
dbgpt/core/operators/flow/dict_operator.py
Normal file
@@ -0,0 +1,76 @@
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"""Dict tool operators."""
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from typing import Dict
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from dbgpt.core.awel import JoinOperator
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from dbgpt.core.awel.flow import IOField, OperatorCategory, Parameter, ViewMetadata
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from dbgpt.util.i18n_utils import _
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class MergeStringToDictOperator(JoinOperator[Dict[str, str]]):
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"""Merge two strings to a dict."""
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metadata = ViewMetadata(
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label=_("Merge String to Dict Operator"),
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name="merge_string_to_dict_operator",
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category=OperatorCategory.COMMON,
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description=_(
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"Merge two strings to a dict, the fist string which is the value from first"
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" upstream is the value of the key `first_key`, the second string which is "
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"the value from second upstream is the value of the key `second_key`."
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),
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parameters=[
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Parameter.build_from(
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_("First Key"),
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"first_key",
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str,
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optional=True,
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default="user_input",
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description=_("The key for the first string, default is `user_input`."),
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),
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Parameter.build_from(
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_("Second Key"),
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"second_key",
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str,
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optional=True,
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default="context",
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description=_("The key for the second string, default is `context`."),
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),
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],
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inputs=[
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IOField.build_from(
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_("First String"),
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"first",
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str,
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description=_("The first string from first upstream."),
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),
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IOField.build_from(
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_("Second String"),
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"second",
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str,
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description=_("The second string from second upstream."),
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),
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],
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outputs=[
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IOField.build_from(
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_("Output"),
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"output",
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dict,
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description=_(
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"The merged dict. example: "
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"{'user_input': 'first', 'context': 'second'}."
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),
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),
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],
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)
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def __init__(
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self, first_key: str = "user_input", second_key: str = "context", **kwargs
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):
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"""Create a MergeStringToDictOperator instance."""
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self._first_key = first_key
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self._second_key = second_key
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super().__init__(combine_function=self._merge_to_dict, **kwargs)
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def _merge_to_dict(self, first: str, second: str) -> Dict[str, str]:
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return {self._first_key: first, self._second_key: second}
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