UnisKB/apps/application/chat_pipeline/I_base_chat_pipeline.py

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# coding=utf-8
"""
@project: maxkb
@Author
@file I_base_chat_pipeline.py
@date2024/1/9 17:25
@desc:
"""
import time
from abc import abstractmethod
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from typing import Type
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from rest_framework import serializers
from dataset.models import Paragraph
class ParagraphPipelineModel:
def __init__(self, _id: str, document_id: str, dataset_id: str, content: str, title: str, status: str,
is_active: bool, comprehensive_score: float, similarity: float, dataset_name: str, document_name: str,
hit_handling_method: str, directly_return_similarity: float, meta: dict = None):
self.id = _id
self.document_id = document_id
self.dataset_id = dataset_id
self.content = content
self.title = title
self.status = status,
self.is_active = is_active
self.comprehensive_score = comprehensive_score
self.similarity = similarity
self.dataset_name = dataset_name
self.document_name = document_name
self.hit_handling_method = hit_handling_method
self.directly_return_similarity = directly_return_similarity
self.meta = meta
def to_dict(self):
return {
'id': self.id,
'document_id': self.document_id,
'dataset_id': self.dataset_id,
'content': self.content,
'title': self.title,
'status': self.status,
'is_active': self.is_active,
'comprehensive_score': self.comprehensive_score,
'similarity': self.similarity,
'dataset_name': self.dataset_name,
'document_name': self.document_name,
'meta': self.meta,
}
class builder:
def __init__(self):
self.similarity = None
self.paragraph = {}
self.comprehensive_score = None
self.document_name = None
self.dataset_name = None
self.hit_handling_method = None
self.directly_return_similarity = 0.9
self.meta = {}
def add_paragraph(self, paragraph):
if isinstance(paragraph, Paragraph):
self.paragraph = {'id': paragraph.id,
'document_id': paragraph.document_id,
'dataset_id': paragraph.dataset_id,
'content': paragraph.content,
'title': paragraph.title,
'status': paragraph.status,
'is_active': paragraph.is_active,
}
else:
self.paragraph = paragraph
return self
def add_dataset_name(self, dataset_name):
self.dataset_name = dataset_name
return self
def add_document_name(self, document_name):
self.document_name = document_name
return self
def add_hit_handling_method(self, hit_handling_method):
self.hit_handling_method = hit_handling_method
return self
def add_directly_return_similarity(self, directly_return_similarity):
self.directly_return_similarity = directly_return_similarity
return self
def add_comprehensive_score(self, comprehensive_score: float):
self.comprehensive_score = comprehensive_score
return self
def add_similarity(self, similarity: float):
self.similarity = similarity
return self
def add_meta(self, meta: dict):
self.meta = meta
return self
def build(self):
return ParagraphPipelineModel(str(self.paragraph.get('id')), str(self.paragraph.get('document_id')),
str(self.paragraph.get('dataset_id')),
self.paragraph.get('content'), self.paragraph.get('title'),
self.paragraph.get('status'),
self.paragraph.get('is_active'),
self.comprehensive_score, self.similarity, self.dataset_name,
self.document_name, self.hit_handling_method, self.directly_return_similarity,
self.meta)
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class IBaseChatPipelineStep:
def __init__(self):
# 当前步骤上下文,用于存储当前步骤信息
self.context = {}
@abstractmethod
def get_step_serializer(self, manage) -> Type[serializers.Serializer]:
pass
def valid_args(self, manage):
step_serializer_clazz = self.get_step_serializer(manage)
step_serializer = step_serializer_clazz(data=manage.context)
step_serializer.is_valid(raise_exception=True)
self.context['step_args'] = step_serializer.data
def run(self, manage):
"""
:param manage: 步骤管理器
:return: 执行结果
"""
start_time = time.time()
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self.context['start_time'] = start_time
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# 校验参数,
self.valid_args(manage)
self._run(manage)
self.context['run_time'] = time.time() - start_time
def _run(self, manage):
pass
def execute(self, **kwargs):
pass
def get_details(self, manage, **kwargs):
"""
运行详情
:return: 步骤详情
"""
return None