Initial Commit

app.py

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+import os
+os.environ["OPENAI_API_KEY"] = "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"
+
+import openai
+import os
+import PyPDF2
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+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="file", outputs="text",title="Experiences And Skills Extraction From PDF file with gpt-3.5-turbo")
+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()

requirement.txt

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+openai==0.27.0
+transformers==4.31.0
+sentencepiece==0.1.99
+PyPDF2==3.0.1
+python-dotenv==1.0.0
+gradio==3.39.0
+torch==2.0.1