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| # mistral.py | |
| import os | |
| import json | |
| import logging | |
| from huggingface_hub import InferenceClient | |
| #from huggingface_hub.utils._errors import BadRequestError | |
| from huggingface_hub import BadRequestError | |
| from dotenv import load_dotenv | |
| from utils.fileTotext import extract_text_based_on_format | |
| import re | |
| from utils.spacy import Parser_from_model | |
| # Load environment variables from .env file | |
| load_dotenv() | |
| # Authenticate with Hugging Face | |
| HFT = os.getenv('HF_TOKEN') | |
| if not HFT: | |
| raise ValueError("Hugging Face token is not set in environment variables.") | |
| client = InferenceClient(model="mistralai/Mistral-Nemo-Instruct-2407", token=HFT) | |
| # Function to clean model output | |
| def Data_Cleaner(text): | |
| pattern = r".*?format:" | |
| result = re.split(pattern, text, maxsplit=1) | |
| if len(result) > 1: | |
| text_after_format = result[1].strip().strip('`').strip('json') | |
| else: | |
| text_after_format = text.strip().strip('`').strip('json') | |
| return text_after_format | |
| # Function to call Mistral and process output | |
| def Model_ProfessionalDetails_Output(resume, client): | |
| system_role = { | |
| "role": "system", | |
| "content": "You are a skilled resume parser. Your task is to extract professional details from resumes in a structured JSON format defined by the User. Ensure accuracy and completeness while maintaining the format provided and if field are missing just return 'not found'." | |
| } | |
| user_prompt = { | |
| "role": "user", | |
| "content": f'''Act as a resume parser for the following text given in text: {resume} | |
| Extract the text in the following output JSON string as: | |
| {{ | |
| "professional": {{ | |
| "technical_skills": "List all technical skills, programming languages, frameworks, and technologies mentioned in the resume, ensuring they are not mixed with other skill types.", | |
| "non_technical_skills": "Identify and list non-technical skills such as leadership, teamwork, and communication skills, ensuring they are not mixed with technical skills.", | |
| "tools": "Enumerate all software tools, platforms, and applications (e.g., Figma, Unity, MS Office, etc.) referenced in the resume, distinctly separate from skills.", | |
| "projects": "Extract the names or titles of all projects mentioned in the resume.", | |
| "projects_experience": "Summarize overall project experiences, providing a brief description of each project as detailed in the resume.", | |
| "experience": "Calculate total professional work experience in years and months based on the resume.", | |
| "companies_worked_at": "List the names of all companies where employment is mentioned in the resume.", | |
| "certifications": "Extract and list all certifications obtained as stated in the resume.", | |
| "roles": "Include the names of all job titles or roles held as indicated in the resume.", | |
| "qualifications": "List educational qualifications (e.g., B.Tech) from the resume. If none are found, return 'No education listed'.", | |
| "courses": "Extract the names of completed courses based on the resume. If none are found, return 'No courses listed'.", | |
| "university": "Identify the name of the university, college, or institute attended, based on the resume. If not found, return 'No university listed'.", | |
| "year_of_graduation": "Extract the year of graduation from the resume. If not found, return 'No year of graduation listed'." | |
| }} | |
| }} | |
| Json Output: | |
| ''' | |
| } | |
| response = "" | |
| for message in client.chat_completion(messages=[system_role, user_prompt], max_tokens=3000, stream=True, temperature=0.35): | |
| response += message.choices[0].delta.content | |
| try: | |
| clean_response = Data_Cleaner(response) | |
| parsed_response = json.loads(clean_response) | |
| except json.JSONDecodeError as e: | |
| logging.error(f"JSON Decode Error: {e}") | |
| return {} | |
| return parsed_response | |
| def Model_PersonalDetails_Output(resume, client): | |
| system_role = { | |
| "role": "system", | |
| "content": "You are a skilled resume parser. Your task is to extract professional details from resumes in a structured JSON format defined by the User. Ensure accuracy and completeness while maintaining the format provided and if field are missing just return 'not found'." | |
| } | |
| user_prompt = { | |
| "role": "user", | |
| "content": f'''Act as a resume parser for the following text given in text: {resume} | |
| Extract the text in the following output JSON string as: | |
| {{ | |
| "personal": {{ | |
| "name": "Extract the full name based on the resume. If not found, return 'No name listed'.", | |
| "contact_number": "Extract the contact number from the resume. If not found, return 'No contact number listed'.", | |
| "email": "Extract the email address from the resume. If not found, return 'No email listed'.", | |
| "Address": "Extract the Address or address from the resume. If not found, return 'No Address listed'.", | |
| "link": "Extract any relevant links (e.g., portfolio, LinkedIn) from the resume. If not found, return 'No link listed'." | |
| }} | |
| }} | |
| output: | |
| ''' | |
| } | |
| # Response | |
| response = "" | |
| for message in client.chat_completion( | |
| messages=[system_role, user_prompt], | |
| max_tokens=3000, | |
| stream=True, | |
| temperature=0.35, | |
| ): | |
| response += message.choices[0].delta.content | |
| # Handle cases where the response might have formatting issues | |
| try: | |
| #print('The Og response:-->',response) | |
| clean_response=Data_Cleaner(response) | |
| #print("After data cleaning",clean_response) | |
| parsed_response = json.loads(clean_response) | |
| except json.JSONDecodeError as e: | |
| print("JSON Decode Error:", e) | |
| print("Raw Response:", response) | |
| return {} | |
| return parsed_response | |
| # # Fallback to SpaCy if Mistral fails | |
| # Add regex pattern for LinkedIn and GitHub links | |
| linkedin_pattern = r"https?://(?:www\.)?linkedin\.com/[\w\-_/]+" | |
| github_pattern = r"https?://(?:www\.)?github\.com/[\w\-_/]+" | |
| email_pattern = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$" | |
| contact_pattern = r"^\+?[\d\s\-()]{7,15}$" | |
| def extract_links(hyperlinks): | |
| linkedin_links = [] | |
| github_links = [] | |
| # Iterate through the hyperlinks and apply regex to find LinkedIn and GitHub links | |
| for link in hyperlinks: | |
| if re.match(linkedin_pattern, link): | |
| linkedin_links.append(link) | |
| elif re.match(github_pattern, link): | |
| github_links.append(link) | |
| return linkedin_links, github_links | |
| def is_valid_email(email): | |
| email_regex = r'^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$' | |
| return re.match(email_regex, email) is not None | |
| def is_valid_contact(contact): | |
| patterns = [ | |
| r'^\+91[\s\.\-\/]?\(?0?\)?[\s\-\.\/]?\d{5}[\s\-\.\/]?\d{5}$', # +91 with optional 0 and separators | |
| r'^\+91[\s\.\-\/]?\d{5}[\s\-\.\/]?\d{5}$', # +91 with 10 digits separated | |
| r'^\d{5}[\s\-\.\/]?\d{5}$', # Local format without country code | |
| r'^\+91[\s\.\-\/]?\d{10}$', # +91 with 10 digits together | |
| r'^\d{10}$', # 10 digits together | |
| r'^\+91[\s\.\-\/]?\(?\d{5}\)?[\s\-\.\/]?\d{5}[\s\-\.\/]?\d{5}$' # +91 with varying separators | |
| r'\+1\s\(\d{3}\)\s\d{3}-\d{4} ', # USA/Canada Intl +1 (XXX) XXX-XXXX | |
| r'\(\d{3}\)\s\d{3}-\d{4} ', # USA/Canada STD (XXX) XXX-XXXX | |
| r'\(\d{3}\)\s\d{3}\s\d{4} ', # USA/Canada (XXX) XXX XXXX | |
| r'\(\d{3}\)\s\d{3}\s\d{3} ', # USA/Canada (XXX) XXX XXX | |
| r'\+1\d{10} ', # +1 XXXXXXXXXX | |
| r'\d{10} ', # XXXXXXXXXX | |
| r'\+44\s\d{4}\s\d{6} ', # UK Intl +44 XXXX XXXXXX | |
| r'\+44\s\d{3}\s\d{3}\s\d{4} ', # UK Intl +44 XXX XXX XXXX | |
| r'0\d{4}\s\d{6} ', # UK STD 0XXXX XXXXXX | |
| r'0\d{3}\s\d{3}\s\d{4} ', # UK STD 0XXX XXX XXXX | |
| r'\+44\d{10} ', # +44 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+61\s\d\s\d{4}\s\d{4} ', # Australia Intl +61 X XXXX XXXX | |
| r'0\d\s\d{4}\s\d{4} ', # Australia STD 0X XXXX XXXX | |
| r'\+61\d{9} ', # +61 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+91\s\d{5}-\d{5} ', # India Intl +91 XXXXX-XXXXX | |
| r'\+91\s\d{4}-\d{6} ', # India Intl +91 XXXX-XXXXXX | |
| r'\+91\s\d{10} ', # India Intl +91 XXXXXXXXXX | |
| r'0\d{2}-\d{7} ', # India STD 0XX-XXXXXXX | |
| r'\+91\d{10} ', # +91 XXXXXXXXXX | |
| r'\+49\s\d{4}\s\d{8} ', # Germany Intl +49 XXXX XXXXXXXX | |
| r'\+49\s\d{3}\s\d{7} ', # Germany Intl +49 XXX XXXXXXX | |
| r'0\d{3}\s\d{8} ', # Germany STD 0XXX XXXXXXXX | |
| r'\+49\d{12} ', # +49 XXXXXXXXXXXX | |
| r'\+49\d{10} ', # +49 XXXXXXXXXX | |
| r'0\d{11} ', # 0XXXXXXXXXXX | |
| r'\+86\s\d{3}\s\d{4}\s\d{4} ', # China Intl +86 XXX XXXX XXXX | |
| r'0\d{3}\s\d{4}\s\d{4} ', # China STD 0XXX XXXX XXXX | |
| r'\+86\d{11} ', # +86 XXXXXXXXXXX | |
| r'\+81\s\d\s\d{4}\s\d{4} ', # Japan Intl +81 X XXXX XXXX | |
| r'\+81\s\d{2}\s\d{4}\s\d{4} ', # Japan Intl +81 XX XXXX XXXX | |
| r'0\d\s\d{4}\s\d{4} ', # Japan STD 0X XXXX XXXX | |
| r'\+81\d{10} ', # +81 XXXXXXXXXX | |
| r'\+81\d{9} ', # +81 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+55\s\d{2}\s\d{5}-\d{4} ', # Brazil Intl +55 XX XXXXX-XXXX | |
| r'\+55\s\d{2}\s\d{4}-\d{4} ', # Brazil Intl +55 XX XXXX-XXXX | |
| r'0\d{2}\s\d{4}\s\d{4} ', # Brazil STD 0XX XXXX XXXX | |
| r'\+55\d{11} ', # +55 XXXXXXXXXXX | |
| r'\+55\d{10} ', # +55 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+33\s\d\s\d{2}\s\d{2}\s\d{2}\s\d{2} ', # France Intl +33 X XX XX XX XX | |
| r'0\d\s\d{2}\s\d{2}\s\d{2}\s\d{2} ', # France STD 0X XX XX XX XX | |
| r'\+33\d{9} ', # +33 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+7\s\d{3}\s\d{3}-\d{2}-\d{2} ', # Russia Intl +7 XXX XXX-XX-XX | |
| r'8\s\d{3}\s\d{3}-\d{2}-\d{2} ', # Russia STD 8 XXX XXX-XX-XX | |
| r'\+7\d{10} ', # +7 XXXXXXXXXX | |
| r'8\d{10} ', # 8 XXXXXXXXXX | |
| r'\+27\s\d{2}\s\d{3}\s\d{4} ', # South Africa Intl +27 XX XXX XXXX | |
| r'0\d{2}\s\d{3}\s\d{4} ', # South Africa STD 0XX XXX XXXX | |
| r'\+27\d{9} ', # +27 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+52\s\d{3}\s\d{3}\s\d{4} ', # Mexico Intl +52 XXX XXX XXXX | |
| r'\+52\s\d{2}\s\d{4}\s\d{4} ', # Mexico Intl +52 XX XXXX XXXX | |
| r'01\s\d{3}\s\d{4} ', # Mexico STD 01 XXX XXXX | |
| r'\+52\d{10} ', # +52 XXXXXXXXXX | |
| r'01\d{7} ', # 01 XXXXXXX | |
| r'\+234\s\d{3}\s\d{3}\s\d{4} ', # Nigeria Intl +234 XXX XXX XXXX | |
| r'0\d{3}\s\d{3}\s\d{4} ', # Nigeria STD 0XXX XXX XXXX | |
| r'\+234\d{10} ', # +234 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+971\s\d\s\d{3}\s\d{4} ', # UAE Intl +971 X XXX XXXX | |
| r'0\d\s\d{3}\s\d{4} ', # UAE STD 0X XXX XXXX | |
| r'\+971\d{8} ', # +971 XXXXXXXX | |
| r'0\d{8} ', # 0XXXXXXXX | |
| r'\+54\s9\s\d{3}\s\d{3}\s\d{4} ', # Argentina Intl +54 9 XXX XXX XXXX | |
| r'\+54\s\d{1}\s\d{4}\s\d{4} ', # Argentina Intl +54 X XXXX XXXX | |
| r'0\d{3}\s\d{4} ', # Argentina STD 0XXX XXXX | |
| r'\+54\d{10} ', # +54 9 XXXXXXXXXX | |
| r'\+54\d{9} ', # +54 XXXXXXXXX | |
| r'0\d{7} ', # 0XXXXXXX | |
| r'\+966\s\d\s\d{3}\s\d{4} ', # Saudi Intl +966 X XXX XXXX | |
| r'0\d\s\d{3}\s\d{4} ', # Saudi STD 0X XXX XXXX | |
| r'\+966\d{8} ', # +966 XXXXXXXX | |
| r'0\d{8} ', # 0XXXXXXXX | |
| r'\+1\d{10} ', # +1 XXXXXXXXXX | |
| r'\+1\s\d{3}\s\d{3}\s\d{4} ', # +1 XXX XXX XXXX | |
| r'\d{5}\s\d{5} ', # XXXXX XXXXX | |
| r'\d{10} ', # XXXXXXXXXX | |
| r'\+44\d{10} ', # +44 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+61\d{9} ', # +61 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+91\d{10} ', # +91 XXXXXXXXXX | |
| r'\+49\d{12} ', # +49 XXXXXXXXXXXX | |
| r'\+49\d{10} ', # +49 XXXXXXXXXX | |
| r'0\d{11} ', # 0XXXXXXXXXXX | |
| r'\+86\d{11} ', # +86 XXXXXXXXXXX | |
| r'\+81\d{10} ', # +81 XXXXXXXXXX | |
| r'\+81\d{9} ', # +81 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+55\d{11} ', # +55 XXXXXXXXXXX | |
| r'\+55\d{10} ', # +55 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+33\d{9} ', # +33 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX | |
| r'\+7\d{10} ', # +7 XXXXXXXXXX | |
| r'8\d{10} ', # 8 XXXXXXXXXX | |
| r'\+27\d{9} ', # +27 XXXXXXXXX | |
| r'0\d{9} ', # 0XXXXXXXXX (South Africa STD) | |
| r'\+52\d{10} ', # +52 XXXXXXXXXX | |
| r'01\d{7} ', # 01 XXXXXXX | |
| r'\+234\d{10} ', # +234 XXXXXXXXXX | |
| r'0\d{10} ', # 0XXXXXXXXXX | |
| r'\+971\d{8} ', # +971 XXXXXXXX | |
| r'0\d{8} ', # 0XXXXXXXX | |
| r'\+54\s9\s\d{10} ', # +54 9 XXXXXXXXXX | |
| r'\+54\d{9} ', # +54 XXXXXXXXX | |
| r'0\d{7} ', # 0XXXXXXX | |
| r'\+966\d{8} ', # +966 XXXXXXXX | |
| r'0\d{8}' # 0XXXXXXXX | |
| ] | |
| # Check if the contact matches any of the patterns | |
| return any(re.match(pattern, contact) for pattern in patterns) is not None | |
| def validate_contact_email(personal_data): | |
| contact = personal_data.get('contact', 'Not found') | |
| email = personal_data.get('email', 'Not found') | |
| valid_contact = is_valid_contact(contact) if contact != 'Not found' else False | |
| valid_email = is_valid_email(email) if email != 'Not found' else False | |
| invalid_contact = 'Invalid contact' if not valid_contact else 'Valid contact' | |
| invalid_email = 'Invalid email' if not valid_email else 'Valid email' | |
| return valid_contact, invalid_contact, valid_email, invalid_email | |
| def process_resume_data(file_path): | |
| resume_text, hyperlinks = extract_text_based_on_format(file_path) | |
| print("Resume converted to text successfully.") | |
| if not resume_text: | |
| return {"error": "Text extraction failed"} | |
| # Extract LinkedIn and GitHub links | |
| linkedin_links, github_links = extract_links(hyperlinks) | |
| # Attempt to use Mistral model for parsing | |
| try: | |
| # Extract personal details using Mistral | |
| per_data = Model_PersonalDetails_Output(resume_text, client) | |
| # Extract professional details using Mistral | |
| pro_data = Model_ProfessionalDetails_Output(resume_text, client) | |
| # Check if per_data and pro_data have been populated correctly | |
| if not per_data: | |
| logging.warning("Mistral personal data extraction failed.") | |
| per_data = {} | |
| if not pro_data: | |
| logging.warning("Mistral professional data extraction failed.") | |
| pro_data = {} | |
| # Combine both personal and professional details into a structured output | |
| result = { | |
| "personal": { | |
| "name": per_data.get('personal', {}).get('name', 'Not found'), | |
| "contact": per_data.get('personal', {}).get('contact_number', 'Not found'), | |
| "email": per_data.get('personal', {}).get('email', 'Not found'), | |
| "location": per_data.get('personal', {}).get('Address', 'Not found'), | |
| "linkedin": linkedin_links, | |
| "github": github_links, | |
| "other_links": hyperlinks # Store remaining links if needed | |
| }, | |
| "professional": { | |
| "technical_skills": pro_data.get('professional', {}).get('technical_skills', 'Not found'), | |
| "non_technical_skills": pro_data.get('professional', {}).get('non_technical_skills', 'Not found'), | |
| "tools": pro_data.get('professional', {}).get('tools', 'Not found'), | |
| "experience": [ | |
| { | |
| "company": pro_data.get('professional', {}).get('companies_worked_at', 'Not found'), | |
| "projects": pro_data.get('professional', {}).get('projects', 'Not found'), | |
| "role": pro_data.get('professional', {}).get('worked_as', 'Not found'), | |
| "years": pro_data.get('professional', {}).get('experience', 'Not found'), | |
| "project_experience": pro_data.get('professional', {}).get('projects_experience', 'Not found') | |
| } | |
| ], | |
| "education": [ | |
| { | |
| "qualification": pro_data.get('professional', {}).get('qualification', 'Not found'), | |
| "university": pro_data.get('professional', {}).get('university', 'Not found'), | |
| "course": pro_data.get('professional', {}).get('course', 'Not found'), | |
| "certificate": pro_data.get('professional', {}).get('certification', 'Not found') | |
| } | |
| ] | |
| } | |
| } | |
| # Validate contact and email | |
| valid_contact, invalid_contact, valid_email, invalid_email = validate_contact_email(result['personal']) | |
| result['personal']['valid_contact'] = valid_contact | |
| result['personal']['invalid_contact'] = invalid_contact | |
| result['personal']['valid_email'] = valid_email | |
| result['personal']['invalid_email'] = invalid_email | |
| # If Mistral produces valid output, return it | |
| if per_data or pro_data: | |
| logging.info("Successfully extracted data using Mistral.") | |
| print("---------Mistral-------") | |
| return result | |
| else: | |
| raise ValueError("Mistral returned no output") | |
| # Handle HuggingFace API or Mistral model errors | |
| except BadRequestError as e: | |
| logging.error(f"HuggingFace API error: {e}. Falling back to SpaCy.") | |
| print(f"HuggingFace API error: {e}. Falling back to SpaCy.") | |
| except Exception as e: | |
| logging.error(f"An error occurred while processing with Mistral: {e}. Falling back to SpaCy.") | |
| print(f"An error occurred while processing with Mistral: {e}. Falling back to SpaCy.") | |
| # Fallback to SpaCy if Mistral fails | |
| logging.warning("Mistral failed, switching to SpaCy.") | |
| print("---------SpaCy-------") | |
| return Parser_from_model(file_path) | |