few_shot_prompt_openai.py

from langchain import OpenAI, LLMChain
from langchain import PromptTemplate, FewShotPromptTemplate
from langchain.llms import LlamaCpp
import csv

examples = [
    {"product": "Toothpaste",
     "category": "Health:Dental"},
    {"product": "Toilet Flapper",
     "category": "Home:Maintenance"},
    {"product": "Laptop Stand",
     "category": "Computer:Accessories"},
    {"product": "Pressure Cooker",
     "category": "Kitchen:Appliances"},
    {"product": "T-shirt",
     "category": "Clothing"},
    {"product": "Bananas",
     "category": "Grocery"},
]

example_formatter_template = """
Product: {product}
Category: {category}\n
"""
example_prompt = PromptTemplate(
    input_variables=["product", "category"],
    template=example_formatter_template,
)

few_shot_prompt = FewShotPromptTemplate(
    examples=examples,
    example_prompt=example_prompt,
    prefix="Give the category of every product",
    suffix="Product: {product}\nCategory:",
    input_variables=["product"],
    example_separator="\n\n",
)

llm_chain = LLMChain(
    llm=OpenAI(),
    prompt=few_shot_prompt,
    verbose=False,
)

with open('../../my/finances/amz.csv', 'r') as input_file:
    reader = csv.reader(input_file)
    header = next(reader)
    header.append('Category')
    transformed_data = [header]

    for row in reader:
        print(row[23])
        output = llm_chain.predict(product=row[23])
        row.append(output.lstrip())
        transformed_data.append(row)

with open('output.csv', mode='w', newline='') as output_file:
    writer = csv.writer(output_file)
    writer.writerows(transformed_data)

Example from Category column of output.csv:

Books:Textbooks
Computer:Accessories
Grocery:Cereal
Grocery:Produce
Grocery:Organic Produce
Health:Dental
Electronics:Audio
Electronics:Headphones