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| from langchain_community.document_loaders import PyPDFLoader | |
| from huggingface_hub import InferenceClient | |
| import requests | |
| import openai | |
| from openai import OpenAI | |
| from utils.constants import system_prompt | |
| def pdf_loader(file): | |
| loader = PyPDFLoader(file) | |
| cv_data = "" | |
| for page in loader.lazy_load(): | |
| cv_data += page.page_content | |
| # print(cv_data) | |
| return cv_data | |
| class PitchPerfect: | |
| def __init__(self, model, model_family, token, system_prompt = system_prompt): | |
| self.system_prompt = system_prompt | |
| self.model = model | |
| if model_family == "gpt": | |
| self.client = OpenAI(api_key = token) | |
| self.check_openai_token() | |
| elif model_family == "together": | |
| self.client = InferenceClient(provider = "together", api_key = token) | |
| self.check_hf_token(token) | |
| else: | |
| self.client = InferenceClient(provider="hf-inference", api_key = token) | |
| self.check_hf_token(token) | |
| def check_openai_token(self): | |
| try: | |
| self.client.models.list() | |
| except openai.AuthenticationError: | |
| print("❌ Invalid API key.") | |
| self.client = "INVALID" | |
| self.error = "❌ Invalid API key." | |
| except Exception as e: | |
| print(f"❌ An error occurred: {e}") | |
| self.client = "INVALID" | |
| self.error = "❌ An error occurred: {e}" | |
| def check_hf_token(self, token): | |
| headers = {"Authorization": f"Bearer {token}"} | |
| try: | |
| response = requests.get("https://huggingface.co/api/whoami-v2", headers=headers) | |
| if response.status_code == 200: | |
| user_info = response.json() | |
| print(f"✅ Token is valid. Logged in as: {user_info.get('name', 'Unknown User')}") | |
| elif response.status_code == 401: | |
| print("❌ Invalid Hugging Face token.") | |
| self.client = "INVALID" | |
| self.error = "❌ Invalid HF Token." | |
| elif response.status_code == 403: | |
| print("❌ Token does not have the necessary permissions.") | |
| self.client = "INVALID" | |
| self.error = "❌ Token does not have the necessary permissions." | |
| else: | |
| print(f"❌ Unexpected error: {response.status_code} - {response.text}") | |
| self.client = "INVALID" | |
| self.error = f"❌ Unexpected error: {response.status_code} - {response.text}" | |
| except Exception as e: | |
| print(f"❌ An unexpected error occurred: {e}") | |
| self.client = "INVALID" | |
| self.error = f"❌ An unexpected error occurred: {e}" | |
| # def check_api_key(self): | |
| # try: | |
| # # Make a simple request to test the API key | |
| # self.client.models.list() | |
| # print("✅ API key is valid.") | |
| # except openai.APIConnectionError: | |
| # print("❌ Network error. Please check your connection.") | |
| # except openai.AuthenticationError: | |
| # print("❌ Invalid API key.") | |
| # except Exception as e: | |
| # print(f"❌ An error occurred: {e}") | |
| def prepare_user_prompt(self, job_title, company, job_desc, cv_data, word_limit): | |
| user_prompt = ( | |
| f"Job Title: {job_title}\n" | |
| f"Company Name: {company}\n" | |
| f"Job Description: {job_desc}\n\n" | |
| f"CV Data: {cv_data}\n\n" | |
| f""" | |
| Instructions: | |
| Based on the job description and the CV Data, write a concise cover letter in under {word_limit} words, following this format and structure and using a positive and humble tone. | |
| Include in Your Cover Letter: | |
| Start with: "Hi [hiring manager's name]," | |
| Introduce yourself as a graduate from [name of your university], looking for a role as a [Job Title]. Add 2 lines of brief introduction of my profile. | |
| Begin a new paragraph with: "Here are reasons that make me a great fit for the role:". | |
| List at least 4 reasons based on the requirements from the job description, where these should be in the order that are in the job description. Explain how my skills align with the role's requirements (Include impactful numbers and results from my CV to show alignment) | |
| Conclude with: "Please find my CV attached below. I look forward to hearing from you." | |
| End with: "Best wishes, [Your Name]" | |
| Example Cover Letter: | |
| Hi [Hiring Manager's Name], | |
| I am a recent MSc Management graduate from [University Name], looking for a role as a [Job Title]. | |
| Here are the reasons that make me a great fit for the role: | |
| [First reason, based on experience or passion related to the job. Include the quantifiable impact I made] | |
| [Second reason, highlighting skills or achievements. Include the quantifiable impact I made] | |
| [Third reason, highlighting skills or achievements. Include the quantifiable impact I made] | |
| [Fourth reason, highlighting skills or achievements. Include the quantifiable impact I made] | |
| Please find my CV attached below. I look forward to hearing from you. | |
| Best wishes, | |
| [Your Name] | |
| """ | |
| ) | |
| return user_prompt | |
| def generate_cover_letter(self, job_title, company, job_desc, cv_data, word_limit = 400, temp = 0.7, top_p = 0.9): | |
| user_prompt = self.prepare_user_prompt(job_title, company, job_desc, cv_data, word_limit) | |
| messages = [ | |
| {"role" : "system", "content" : self.system_prompt}, | |
| {"role" : "user", "content" : user_prompt} | |
| ] | |
| response = self.client.chat.completions.create( | |
| model = self.model, | |
| messages = messages, | |
| temperature = temp, | |
| top_p = top_p | |
| ) | |
| cover_letter = response.choices[0].message.content | |
| if "<think>" in cover_letter: | |
| reason = cover_letter.split("</think>")[0].replace("<think>","") | |
| cover_letter = cover_letter.split("</think>")[1] | |
| else: | |
| reason = "This model doesn't offer reasoning." | |
| return cover_letter, reason | |