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| import gradio as gr | |
| from openai import OpenAI | |
| import json | |
| import os | |
| OPENAI_API_KEY = os.getenv('openai') | |
| org = os.getenv('org') | |
| client = OpenAI(api_key=OPENAI_API_KEY, organization=org) | |
| def getQuestions(job_description: str, no_of_questions: int): | |
| response = client.chat.completions.create( | |
| model="gpt-3.5-turbo-1106", | |
| response_format={"type": "json_object"}, # To ENABLE JSON MODE | |
| messages=[ | |
| {"role": "system", | |
| "content": "You are a helpful assistant designed to output JSON in this format [question-text as key and its value as answer-text]"}, | |
| {"role": "user", | |
| "content": f"Given the job description [{job_description}] create {no_of_questions} " | |
| f"interview questions and their corresponding answers. You need to act like a domain expert and ask relevant questions to the job description only."} | |
| ] | |
| ) | |
| result = response.choices[0].message.content | |
| # Parse the JSON data | |
| parsed_data = json.loads(result) | |
| return parsed_data | |
| iface = gr.Interface( | |
| fn=getQuestions, | |
| inputs=["text", "number"], | |
| outputs="json") | |
| iface.launch(auth=("orblogic", "logicorb")) |