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| import os | |
| os.environ["OPENAI_API_KEY"] = "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" | |
| import openai | |
| import os | |
| import PyPDF2 | |
| from dotenv import load_dotenv, find_dotenv | |
| _ = load_dotenv(find_dotenv()) | |
| openai.api_key = os.getenv('OPENAI_API_KEY') | |
| def get_completion(prompt, model="gpt-3.5-turbo", temperature=0, max_tokens=500): | |
| messages = [{"role": "user", "content": prompt}] | |
| response = openai.ChatCompletion.create( | |
| model=model, | |
| temperature=temperature, | |
| max_tokens=max_tokens, | |
| messages=messages, | |
| ) | |
| return response.choices[0].message["content"] | |
| def generate_prompt(text, format="text"): | |
| prompt = f"""Play as an AI HR recruiter specialist and extract all the jobs as a list with : | |
| 1. Job Title | |
| 2. Location | |
| 3. Educations as list | |
| 4. Experiences as list | |
| 5. Skills and Competences as list | |
| 6. Functions and Tasks as list | |
| 7. Return the result in {format} format \ | |
| here the text \ | |
| ``` {text}``` | |
| """ | |
| return prompt | |
| import PyPDF2 | |
| def read_pdf(file_path): | |
| pdf_file = open(file_path, 'rb') | |
| pdf_reader = PyPDF2.PdfReader(pdf_file) | |
| text = "" | |
| for page in pdf_reader.pages: | |
| text += page.extract_text() | |
| pdf_file.close() | |
| return text | |
| import PyPDF2 | |
| def summarize(input): | |
| text = read_pdf(input.name) | |
| prompt = generate_prompt(text) | |
| response = get_completion(prompt) | |
| return response | |
| import gradio as gr | |
| gr.close_all() | |
| demo = gr.Interface( | |
| fn=summarize, | |
| inputs=gr.components.File(label="Importez votre document en format PDF ici"), | |
| outputs=gr.components.Textbox(label="Voici le résultat"), | |
| title="Téléchargement de CV\n(version anglaise)", | |
| description="Outil d’importation de CV") | |
| demo.launch() | |
| #++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | |
| #++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | |
| import gradio as gr | |
| def colorize_text(text): | |
| return "<span style='color:red;background-color:orange'>" + text + "</span>" "<span style='color:white;background-color:red'>" + "Experiences" + "</span>" | |
| iface = gr.Interface(fn=colorize_text, inputs="text", outputs="html") | |
| iface.launch() |