Spaces:
Sleeping
Sleeping
| import logging | |
| import os | |
| from pathlib import Path | |
| from dotenv import load_dotenv | |
| from crewai import Crew | |
| from langchain_groq import ChatGroq | |
| import gradio as gr | |
| from resume import extract_text_from_file | |
| from crew import FormFillingAgents, FormFillingTasks | |
| def build_gradio_app(): | |
| """Builds the Gradio interface for the form-filling app.""" | |
| logging.basicConfig(level=logging.INFO) | |
| # Define input elements | |
| resume_input = gr.File(label="Upload Resume", file_types=[".pdf", ".docx", ".txt"]) | |
| job_desc_input = gr.Textbox(label="Job Description", placeholder="Enter job description here") | |
| questions_input = gr.Textbox(label="Questions", placeholder="Enter questions, separated by commas") | |
| api_key_input = gr.Textbox(label="GROQ API Key", placeholder="Enter your GROQ API Key") | |
| # Define output elements | |
| answers = gr.Textbox(label="Tailored Answer to the Question Based on Your Resume", interactive=False) | |
| # Processing function | |
| def process_inputs(api_key, resume_input, job_desc, questions): | |
| try: | |
| # Debugging | |
| logging.info("Received API Key, Resume, Job Description, and Questions.") | |
| logging.info(f"API Key: {api_key}") | |
| # Save API key to .env file it the user has session active | |
| if api_key: | |
| env_path = Path(__file__).parent / ".env" | |
| with open(env_path, "w") as env_file: | |
| env_file.write(f"GROQ_API_KEY={api_key}") | |
| logging.info("API Key saved to .env file.") | |
| else: | |
| logging.warning("No API Key provided.") | |
| load_dotenv() | |
| # Initialize language model | |
| llm = ChatGroq( | |
| model="groq/llama-3.1-8b-instant", | |
| api_key=os.getenv("GROQ_API_KEY"), | |
| ) | |
| logging.info("Language model initialized successfully.") | |
| # Extract text from resume | |
| resume_text = extract_text_from_file(resume_input) | |
| logging.info("Resume text extracted.") | |
| # Initialize agents and tasks | |
| agents = FormFillingAgents() | |
| analysis_agent = agents.resume_analysis_agent(llm) | |
| qa_agent = agents.question_answering_agent(llm) | |
| tasks = FormFillingTasks() | |
| profile_task = tasks.profile_analysis_task(analysis_agent, resume_text, job_desc) | |
| qa_task = tasks.question_answering_task(qa_agent, questions) | |
| # Run Crew pipeline | |
| crew = Crew( | |
| agents=[analysis_agent, qa_agent], | |
| tasks=[profile_task, qa_task], | |
| verbose=True, | |
| max_rpm=29, | |
| ) | |
| results = crew.kickoff() | |
| logging.info("Pipeline executed successfully.") | |
| return str(results) | |
| except Exception as e: | |
| logging.error(f"Error during processing: {e}") | |
| return f"Error during processing: {str(e)}" | |
| # Gradio interface | |
| interface = gr.Interface( | |
| fn=process_inputs, | |
| inputs=[api_key_input, resume_input, job_desc_input, questions_input], | |
| outputs=[answers], | |
| title="Form Filling Assistant", | |
| description="Upload a resume, provide a job description, input API key, and ask questions to get tailored responses.", | |
| ) | |
| interface.launch() | |
| if __name__ == '__main__': | |
| build_gradio_app() | |