Parse with Additional Prompts

Parsing prompts allow you to guide our parsing model in the same way you would instruct an LLM.

These prompts can be useful for improving the parser's performance on complex document layouts, extracting data in a specific format, or transforming the document in other ways.

In this example, we showcase how providing addtiaional instructions (prompts) to LlamaParse can be used to shape the way an LLM parses information from unstructured documents. Using a McDonald's Receipt, we show how to ignore parts of the document and only parse the price of each order and the final amount to be paid.

Setup

First, we setup our environment and connect to LlamaCloud:

!pip install llama-cloud-services

import os
from getpass import getpass 

os.environ["LLAMA_CLOUD_API_KEY"] = getpass("Llama Cloud API Key: ")

Parse Receipt With No Instructions

For this example, we're using the following McDonald's receipt. Download it and save it with the name mcdonalds_receipt.png:

We start off by intilizing LlamaParse, with no instructions:

from llama_cloud_services import LlamaParse

parser = LlamaParse(
    parse_mode="parse_page_with_agent",
    model="openai-gpt-4-1-mini",
    high_res_ocr=True,
    outlined_table_extraction=True,
    output_tables_as_HTML=True,
)

The results we get are the following:

vanilla_result = await parser.aparse("mcdonalds_receipt.png")
print(vanilla_result.pages[0].md)

Started parsing the file under job_id fa0c25a4-999f-439a-81a2-54f024ce2809

# McDonald's Receipt

> Rate us HIGHLY SATISFIED and  
> Receive ONE FREE ITEM  
> Purchase any sandwich and receive an item of equal or lesser value  
> Go to www.mcdvoice.com within 7 days and tell us about your visit.  
> Validation Code:  
> Expires 30 days after receipt date.  
> Valid at participating US McDonald's.  
> Survey Code:  
> 31278-01121-21018-20481-00081-0  

## McDonald's Restaurant #31278  
2378 PINE RD NW  
RICE, MN 56367-9740  
TEL# 320 393 4600  

| KS# 1           | 12/08/2022 08:48 PM |  
|-----------------|---------------------|  
| Side1           | Order 12            |  

| Item                     | Price |  
|--------------------------|-------|  
| 1 Happy Meal 6 Pc        | 4.89  |  
| - 1 Creamy Ranch Cup     |       |  
| - 1 Extra Kids Fry       |       |  
| - 1 Wreck It Ralph 2     |       |  
| - 1 S Coke               |       |  
| 1 Snack Oreo McFlurry    | 2.69  |  

| Subtotal                 | 7.58  |  
| Tax                      | 0.52  |  
| Take-Out Total           | 8.10  |  

| Cash Tendered            | 10.00 |  
| Change                   | 1.90  |  

> McDonalds Restaurant Rice  
> ***NOW ACCEPTING APPLICATIONS***  
> text to #36453  
> apply31278  

Parse Receipt With Instructions

Now let's have a look at the way we can change the output by providing an additional prompt:

parsing_instruction = """The provided document is a McDonald's receipt. Provide ONLY each line item (item name and price) and the final amount to be paid."""

parser = LlamaParse(
    parse_mode="parse_page_with_agent",
    model="openai-gpt-4-1-mini",
    high_res_ocr=True,
    outlined_table_extraction=True,
    output_tables_as_HTML=True,
    # Inject the parsing instruction into the user prompt
    user_prompt=parsing_instruction,
)

result_with_prompt = await parser.aparse("mcdonalds_receipt.png")

print(result_with_prompt.pages[0].md)

Which results in:

Started parsing the file under job_id 4c6a6443-0590-4384-b84d-65e4455f5e48

* Happy Meal 6 Pc 4.89
* Snack Oreo McFlurry 2.69

Take-Out Total 8.10

Setup​

Parse Receipt With No Instructions​

Parse Receipt With Instructions​

Setup

Parse Receipt With No Instructions

Parse Receipt With Instructions