Tobias Weise
579b76ebd5
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Gitea Docker Redeploy / Redploy-App-on-self-via-SSH (push) Successful in 19s
145 lines
2.7 KiB
Python
145 lines
2.7 KiB
Python
import os
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from elasticsearch_dsl import Document, InnerDoc, Nested, Date, Integer, Keyword, Float, Long, Text, connections, Object, Boolean
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class User(Document):
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creation_date = Date()
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email = Keyword()
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password_hash = Text(index=False)
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role = Keyword()
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#salt = Text(index=False)
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#profileImage = Text(index=False)
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#profileImage = Keyword()
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isEmailVerified = Boolean()
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#status = Text()
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#otpExpires = Date()
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#resetPasswordToken = Text(index=False)
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#mailToken = Text(index=False)
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class Index:
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name = 'user'
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settings = {
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"number_of_shards": 1,
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}
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def save(self, ** kwargs):
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return super(User, self).save(**kwargs)
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class Chatbot(Document):
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creation_date = Date()
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name = Text()
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creator_id = Keyword()
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description = Text()
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systemPrompt = Text(index=False)
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#slug = Keyword()
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files = Nested()
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text = Text()
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links = Nested()
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#chatbotImage = Text(index=False)
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sourceCharacters = Integer()
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visibility = Keyword() #public, private, group?
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#status = Keyword()
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temperature = Float()
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llm_model = Keyword()
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class Index:
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name = 'chatbot'
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settings = {
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"number_of_shards": 1,
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}
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def save(self, ** kwargs):
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return super(Chatbot, self).save(**kwargs)
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class Text(Document):
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creation_date = Date()
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creator_id = Keyword()
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text = Text()
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md5 = Keyword()
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class Index:
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name = 'text'
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settings = {
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"number_of_shards": 1,
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}
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def save(self, ** kwargs):
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return super(Text, self).save(**kwargs)
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#======= Query Log ===========
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class Sources(InnerDoc):
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score = Float()
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#sourceFileId = Text()
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sourceType = Text()
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tags = Text()
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#new fields
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sourceFileId = Keyword()
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filename = Keyword()
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url = Keyword()
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txt_id = Keyword()
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page = Integer()
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class QueryLog(Document):
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answer = Text()
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question = Text()
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chatbotid = Keyword()
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durasecs = Float()
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#inCt = Float()
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inToks = Long()
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llm = Text()
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#outCt = Float()
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outToks = Long()
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#queryid = Keyword()
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#rating = Long()
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#reason = Text()
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#reasontags = Text()
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session = Keyword()
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sources = Object(Sources)
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temperature = Float()
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#totalCt = Float()
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timest = Date() #timestamp
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date = Date() #iso date
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class Index:
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name = 'query_log'
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settings = {
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"number_of_shards": 1,
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}
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def save(self, ** kwargs):
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return super(QueryLog, self).save(**kwargs)
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def init_indicies():
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# create the mappings in elasticsearch
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for Index in [QueryLog, Chatbot, User, Text]:
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Index.init()
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