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Native data AI application framework based on AWEL+AGENT (#1152)

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Co-authored-by: Fangyin Cheng <staneyffer@gmail.com>
Co-authored-by: lcx01800250 <lcx01800250@alibaba-inc.com>
Co-authored-by: licunxing <864255598@qq.com>
Co-authored-by: Aralhi <xiaoping0501@gmail.com>
Co-authored-by: xuyuan23 <643854343@qq.com>
Co-authored-by: aries_ckt <916701291@qq.com>
Co-authored-by: hzh97 <2976151305@qq.com>
This commit is contained in:
明天
2024-02-07 17:43:27 +08:00
committed by GitHub
parent dbb9ac83b1
commit d5afa6e206
328 changed files with 22606 additions and 3282 deletions
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72
dbgpt/model/operators/llm_operator.py
View File

@@ -3,8 +3,16 @@ from abc import ABC
from typing import Optional
from dbgpt.component import ComponentType
from dbgpt.core import LLMClient
from dbgpt.core import LLMClient, ModelOutput, ModelRequest
from dbgpt.core.awel import BaseOperator
from dbgpt.core.awel.flow import (
IOField,
OperatorCategory,
OperatorType,
Parameter,
ResourceCategory,
ViewMetadata,
)
from dbgpt.core.operators import BaseLLM, BaseLLMOperator, BaseStreamingLLMOperator
logger = logging.getLogger(__name__)
@@ -54,6 +62,36 @@ class LLMOperator(MixinLLMOperator, BaseLLMOperator):
and if we can't connect to the model serving cluster, we will use the :class:`OpenAILLMClient` as the llm_client.
"""
metadata = ViewMetadata(
label="LLM Operator",
name="llm_operator",
category=OperatorCategory.LLM,
description="The LLM operator.",
parameters=[
Parameter.build_from(
"LLM Client",
"llm_client",
LLMClient,
optional=True,
default=None,
description="The LLM Client.",
),
],
inputs=[
IOField.build_from(
"Model Request", "model_request", ModelRequest, "The model request."
)
],
outputs=[
IOField.build_from(
"Model Output",
"model_output",
ModelOutput,
description="The model output.",
)
],
)
def __init__(self, llm_client: Optional[LLMClient] = None, **kwargs):
super().__init__(llm_client)
BaseLLMOperator.__init__(self, llm_client, **kwargs)
@@ -68,6 +106,38 @@ class StreamingLLMOperator(MixinLLMOperator, BaseStreamingLLMOperator):
and if we can't connect to the model serving cluster, we will use the :class:`OpenAILLMClient` as the llm_client.
"""
metadata = ViewMetadata(
label="Streaming LLM Operator",
name="streaming_llm_operator",
operator_type=OperatorType.STREAMIFY,
category=OperatorCategory.LLM,
description="The streaming LLM operator.",
parameters=[
Parameter.build_from(
"LLM Client",
"llm_client",
LLMClient,
optional=True,
default=None,
description="The LLM Client.",
),
],
inputs=[
IOField.build_from(
"Model Request", "model_request", ModelRequest, "The model request."
)
],
outputs=[
IOField.build_from(
"Model Output",
"model_output",
ModelOutput,
description="The model output.",
is_list=True,
)
],
)
def __init__(self, llm_client: Optional[LLMClient] = None, **kwargs):
super().__init__(llm_client)
BaseStreamingLLMOperator.__init__(self, llm_client, **kwargs)