rvndbalaji

#Using Keras
model = keras_model_sequential()
model %>%
  layer_dense(units = 3, input_shape = c(5), activation = 'relu') %>%
  layer_dense(units = 2, activation = 'relu') %>%
  layer_dense(units = 1, activation = 'sigmoid')

model %>% compile(
  loss = 'binary_crossentropy',
  optimizer = optimizer_adam(),

rvndbalaji

# Given an incomplete JSON string, extract a subset JSON that is valid
# Obtain the maximum valid portion of this string
# by removing characters one by one from the end and checking the validity

#   By default the incoming json is considered to be an object surrounded by {}
#   Set is_list=True if incoming json is a list surrounded by []

# This method might be inefficient for now since it removes 1 character and validates
# TODO Future optimizaion - 
#   Matching blocks of {} for objects and removing block

rvndbalaji

import base64
import functools
import operator
from typing import *
from typing import Annotated, Any, Dict, List, Sequence

from dto.chat import *
from dto.graph import *
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.tools import BaseTool