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from groq import Groq # type: ignore | |
import os | |
# Initialize Groq client with the API key directly | |
api_key = os.getenv("GROQ_API_KEY") | |
# Initialize the Groq client with the retrieved API key | |
client = Groq(api_key=api_key) | |
# Define the template for parsing | |
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." | |
) | |
def parse_with_groq(dom_chunks, parse_description, model="llama3-8b-8192"): | |
parsed_results = [] | |
for i, chunk in enumerate(dom_chunks, start=1): | |
# Prepare the prompt | |
prompt = template.format(dom_content=chunk, parse_description=parse_description) | |
# Send prompt to Groq for processing, specifying the model | |
response = client.chat.completions.create( | |
messages=[ | |
{"role": "user", "content": prompt} | |
], | |
model=model # Specify the model | |
) | |
# Print status and store result | |
print(f"Parsed batch: {i} of {len(dom_chunks)}") | |
parsed_results.append(response.choices[0].message.content) # Access the content | |
return "\n".join(parsed_results) |