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import os
import logging
from mistralai import Mistral
from model import JobDocument
from .constant import MISTRAL_MODEL
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
class JobProcessor:
def __init__(self, api_key: str = None):
if api_key is None:
# Use the default API key from environment variable
api_key = os.environ.get("MISTRAL_API_KEY")
if not api_key:
raise ValueError("API key for Mistral is not set.")
self.client = Mistral(api_key=api_key)
def get_job_content(self, job_text: str) -> dict:
"""
Process the job description text and return structured content.
Parameters
----------
job_text: str
The job description text.
Returns
-------
dict: A dictionary containing the processed job content.
"""
if not job_text:
raise ValueError("Job description text is empty.")
response = {
"job": {
"description": job_text,
}
}
# Use the OCR model to extract structured data from the job description
logger.info("Processing OCR for job description")
chat_response = self.client.chat.parse(
model=MISTRAL_MODEL,
messages=[
{
"role": "system",
"content": "Extract the job title, responsibilities, requirements, location, and salary range from the job description.",
},
{"role": "user", "content": job_text},
],
response_format=JobDocument,
# max_tokens=256,
temperature=0,
)
response["job"]["annotation"] = chat_response.choices[0].message.content
return response
if __name__ == "__main__":
pass
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