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from .model import InformationExtractedFromABillReceipt as PydanticModel

from langchain.chains import LLMChain
from langchain.chat_models import ChatOpenAI
from langchain.output_parsers import PydanticOutputParser, OutputFixingParser
from langchain.prompts import (
    ChatPromptTemplate,
    HumanMessagePromptTemplate,
    SystemMessagePromptTemplate,
)

model = ChatOpenAI(
    temperature=0,
    n=1,
    model_kwargs= {
        'stop': None,
        'top_p': 1,
        'frequency_penalty': 0,
        'presence_penalty': 0,
    }
)

# Build categorizing chain
system_message_prompt = SystemMessagePromptTemplate.from_template(
    "You are an information extraction engine that outputs details from OCR processed "
    "documents such as date/time/place of departure and arrival. Fields with formats "
    "specified as date, time, or datetime should be ISO 8601 compliant. Fields with "
    "formats specified as date, time, or datetime should be ISO 8601 compliant.\n"
    "{format_instructions}"
)
human_message_prompt = HumanMessagePromptTemplate.from_template("{text}")
chat_prompt = ChatPromptTemplate.from_messages(
    [system_message_prompt, human_message_prompt]
)
output_parser = PydanticOutputParser(pydantic_object=PydanticModel)
fixing_parser = OutputFixingParser.from_llm(llm=model, parser=output_parser)
chain = LLMChain(
    llm=model, prompt=chat_prompt, output_parser=fixing_parser
)

if __name__ == '__main__':
    misformatted_output = '''{
"place_from": "Adarsh Palm Retreat, Bellandur, Bengaluru, Karnataka 560103, India",
"date_from": "08/05/2023",
"time_from": "10:05 AM",
"place_to": "135, Residency Rd, Shanthala Nagar, Ashok Nagar, Bengaluru, Karnataka 560025, India",
"date_to": "08/05/2023",
"time_to": "11:05 AM",
"amount": 474.54
}'''
    formatted_prompt = chain.prompt.format_prompt(
        text='''08/05/2023, 14:56 Gmail - [Personal] Your Wednesday morning trip with Uber
https://mail.google.com/mail/u/0/?ik=9af0dfed43&view=pt&search=all&permthid=thread-f:1764850071084777313&simpl=msg-f:1764850071084777313 1/3
Total ₹474.54
May 3, 2023
We hope you enjoyed your ride
this morning.Thanks for riding, Dhruv
 
 
 
P a y t m
5/3/23 11:06 AMDhruv Kumar <gargdhruv36@gmail.com>
[Personal] Your W ednesday morning trip with Uber
1 message
Uber Receipts <noreply@uber .com> 3 May 2023 at 1 1:06
To: gargdhruv36@gmail.com
    
    
T o t a l ₹ 4 7 4 . 5 4
Trip Charge ₹474.54
Subtotal ₹474.54
Rider Promotion -₹5.27
Fare Adjustment ₹5.27
P a y m e n t s  
₹474.54
A temporary hold of ₹474.54 was placed on your payment method Paytm. This is not a charge
and will be removed. It should disappear from your bank statement shortly. Learn More
Visit the trip page  for more information, including invoices (where available)


08/05/2023, 14:56 Gmail - [Personal] Your Wednesday morning trip with Uber
https://mail.google.com/mail/u/0/?ik=9af0dfed43&view=pt&search=all&permthid=thread-f:1764850071084777313&simpl=msg-f:1764850071084777313 2/3 
License Plate: KA05AM2236You rode with SHANKARA NAGA
5 . 0 0
 R a t i n g
Rate or tip
 
10:05 AM
WMGP+PM2, Adarsh Palm
Retreat, Bellandur, Bengaluru,
Karnataka 560103, India
11:05 AM
135, Residency Rd,
Shanthala Nagar , Ashok
Nagar , Bengaluru, Karnataka
560025, India
Uber Go 15.77 kilometers | 1 h 0 min
Report lost item ›  Contact support›  
My trips ›  The total of ₹474.54 has a GST of ₹38.52 included.
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Download PDF

08/05/2023, 14:56 Gmail - [Personal] Your Wednesday morning trip with Uber
https://mail.google.com/mail/u/0/?ik=9af0dfed43&view=pt&search=all&permthid=thread-f:1764850071084777313&simpl=msg-f:1764850071084777313 3/3
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Privacy
Terms
Uber India Systems Private
Limited
Fares are inclusive of GST. Please download the tax invoice from the trip detail page for a full tax breakdown.


''',
        format_instructions=fixing_parser.get_format_instructions()
    )
    # print("Parsed:", fixing_parser.parse(misformatted_output))
    print("Using fixing parser:", fixing_parser.parse_with_prompt(misformatted_output, formatted_prompt))