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代码清理
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@@ -52,7 +52,7 @@ class BaseChat(ABC):
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chat_scene: str = None
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chat_scene: str = None
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llm_model: Any = None
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llm_model: Any = None
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# By default, keep the last two rounds of conversation records as the context
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# By default, keep the last two rounds of conversation records as the context
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chat_retention_rounds: int = 1
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chat_retention_rounds: int = 0
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class Config:
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class Config:
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"""Configuration for this pydantic object."""
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"""Configuration for this pydantic object."""
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@@ -1,5 +1,4 @@
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import json
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import json
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import importlib
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from pilot.prompts.prompt_new import PromptTemplate
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from pilot.prompts.prompt_new import PromptTemplate
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from pilot.configs.config import Config
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from pilot.configs.config import Config
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from pilot.scene.base import ChatScene
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from pilot.scene.base import ChatScene
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@@ -8,30 +7,24 @@ from pilot.common.schema import SeparatorStyle
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CFG = Config()
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CFG = Config()
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PROMPT_SCENE_DEFINE = None
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PROMPT_SCENE_DEFINE = "You are a data analysis expert, please provide a professional data analysis solution"
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_DEFAULT_TEMPLATE = """
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_DEFAULT_TEMPLATE = """
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You are a {dialect} data analysis expert, please provide a professional data analysis solution according to the following situations
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According to the following table structure definition:
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According to the structure definition in the following tables:
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{table_info}
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{table_info}
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Provide professional data analysis to support the goal:
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Provide professional data analysis to support users' goals:
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{input}
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{input}
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Provide multi-dimensional analysis as much as possible according to the target requirements, no less than 4 and no more than 8 dimensions.
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Provide at least 4 and at most 8 dimensions of analysis according to user goals.
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The data columns of the analysis output should not exceed 4, do not use column pay_status in SQL where condition.
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The output data of the analysis cannot exceed 4 columns, and do not use columns such as pay_status in the SQL where condition for data filtering.
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According to the characteristics of the analyzed data, choose the most suitable one from the charts provided below for display, chart type:
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According to the characteristics of the analyzed data, choose the most suitable one from the charts provided below for data display, chart type:
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{supported_chat_type}
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{supported_chat_type}
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Pay attention to the length of the output content of the analysis result, do not exceed 4000tokens
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Pay attention to the length of the output content of the analysis result, do not exceed 4000tokens
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Give the correct {dialect} analysis SQL (don't use unprovided values such as 'paid'), analysis title, display method and summary of brief analysis thinking, and respond in the following json format:
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According to the characteristics of the analyzed data, choose the best one from the charts provided below to display, use different types of charts as much as possible,chart types:
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{supported_chat_type}
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Give {dialect} data analysis SQL(Do not use unprovided field value ), analysis title, display method and analytical thinking,respond in the following json format:
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{response}
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{response}
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Ensure the response is correct json and can be parsed by Python json.loads
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Ensure the response is correct json and can be parsed by Python json.loads
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"""
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"""
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RESPONSE_FORMAT = [
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RESPONSE_FORMAT = [
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