parse.py

from langchain_ollama import OllamaLLM
from langchain_core.prompts import ChatPromptTemplate


template = (
    "You are tasked with extracting specific information from the following text content: {dom_content}. "
    "Please follow these instructions carefully: \n\n"
    "1. **Extract Information:** Only extract the information that directly matches the provided description: {parse_description}. "
    "2. **No Extra Content:** Do not include any additional text, comments, or explanations in your response. "
    "3. **Empty Response:** If no information matches the description, return an empty string ('')."
    "4. **Direct Data Only:** Your output should contain only the data that is explicitly requested, with no other text."
    "5. **Output Format:** If the prompt mentions 'table form' or 'in table', present your response in a table format with clear column headers. Otherwise, provide a plain text response."
)

model = OllamaLLM(model="llama3.2")

def parse_with_ollama(dom_chunks, parse_descript):
    prompt = ChatPromptTemplate.from_template(template)
    chain = prompt | model 

    parsed_result = []

    for i , chunk in enumerate(dom_chunks, start=1):
        response = chain.invoke(
            {"dom_content": chunk,"parse_description": parse_descript}
        )
        print(f"Parsed bach {i} of {len(dom_chunks)} ")
        parsed_result.append(response)

    return "\n".join(parsed_result)