Spaces:
Runtime error
Runtime error
File size: 3,405 Bytes
3a16188 f823e77 0e665e7 18aeeba fe1b079 494f37f fe1b079 3a16188 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
import re
import spaces
import gradio as gr
from peft import PeftModel, PeftConfig
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer
model = AutoPeftModelForCausalLM.from_pretrained(
"FlawedLLM/BhashiniLLM", # YOUR MODEL YOU USED FOR TRAINING
load_in_4bit = True,
)
tokenizer = AutoTokenizer.from_pretrained("FlawedLLM/BhashiniLLM")
@spaces.GPU(duration=300)
def chunk_it(input_command):
alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:
{}
### Input:
{}
### Response:
{}"""
inputs = tokenizer(
[
alpaca_prompt.format(
'''
You will receive text input that you need to analyze to perform the following tasks:
transaction: Record the details of an item transaction.
last n days transactions: Retrieve transaction records for a specified time period.
view risk inventory: View inventory items based on a risk category.
view inventory: View inventory details.
new items: Add new items to the inventory.
old items: View old items in inventory.
report generation: Generate various inventory reports.
Required Parameters:
Each task requires specific parameters to execute correctly:
transaction:
ItemName (string)
ItemQt (quantity - integer)
Flow (string: "in" or "out")
ShelfNo (string or integer)
last n days transactions:
ItemName (string)
Duration (integer: number of days, default: 30)
view risk inventory:
RiskType (string: "overstock", "understock", or Null for all risk types)
view inventory:
ItemName (string)
ShelfNo (string or integer)
new items:
ItemName (string)
SellingPrice (number)
CostPrice (number)
old items:
ShelfNo (string or integer)
report generation:
ItemName (string)
Duration (integer: number of days, default: 6)
ReportType (string: "profit", "revenue", "inventory", or Null for all reports)
ALWAYS provide output in a JSON format.''', # instruction
input_command, # input
"", # output - leave this blank for generation!
)
], return_tensors = "pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens = 216, use_cache = True)
tokenizer.batch_decode(outputs)
reply=tokenizer.batch_decode(outputs)
# Regular expression pattern to match content between "### Response:" and "<|end_of_text|>"
pattern = r"### Response:\n(.*?)<\|end_of_text\|>"
# Search for the pattern in the text
match = re.search(pattern, reply[0], re.DOTALL) # re.DOTALL allows '.' to match newlines
reply = match.group(1).strip() # Extract and remove extra whitespace
return reply
iface=gr.Interface(fn=chunk_it,
inputs="text",
outputs="text",
title="Formatter_Pro",
)
iface.launch(inline=False) |