Upload dpm1.py

dpm1.py

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+# -*- coding: utf-8 -*-
+"""dpm1
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1PJnjffQq5PpvzMoY1aB5uggxb35r11Ut
+"""
+
+#!pip install streamlit
+
+#!pip install transformers
+
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+model_name = "EleutherAI/gpt-neo-1.3B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
+
+def generate_job_posting(position, job_type, skillset, company_name, work_experience, job_location, job_benefits, field, currency, currency_format, package, communication, notice_period, qualifications, responsibility):
+    context = f"{company_name} is hiring a {position} for a {job_type} position in {job_location}. The ideal candidate will have at least {work_experience} years of experience in {field}, and should be proficient in {skillset}. The job responsibility includes:\n- {responsibility}\nWe offer a {package} package in currency format {currency_format}. The successful candidate will be expected to maintain excellent communication with clients and colleagues. The notice period for this role is {notice_period}, and applicants should have the following qualifications: {qualifications}."
+    output = generator(context, max_length=240, do_sample=True, temperature=0.7, num_return_sequences=3)
+    def score_output(output_text):
+        sentences = output_text.split('.')
+        avg_sentence_length = sum(len(s.strip()) for s in sentences) / len(sentences)
+        return 1.0 / avg_sentence_length
+    sorted_outputs = sorted(output, key=lambda x: score_output(x['generated_text']), reverse=True)
+    best_output = sorted_outputs[0]
+    output_text = best_output['generated_text'].replace('- job responsibility', f"\n\n- {responsibility}")
+    paragraphs = output_text.split('\n\n')
+    output_text = '\n\n'.join('\n' + p for p in paragraphs)
+    return output_text
+
+st.title("Job Posting Generator")
+
+position = st.text_input("Enter Position for Job Posting:")
+job_type = st.text_input("Enter Job Type:")
+skillset = st.text_input("Enter Skillset:")
+company_name = st.text_input("Enter Company Name:")
+work_experience = st.text_input("Enter Required Work Experience (in years):")
+job_location = st.text_input("Enter job Location:")
+job_benefits = st.text_input("Enter job benefits:")
+field = st.text_input("Enter job field:")
+currency = st.text_input("Enter Currency:")
+currency_format = st.text_input("Enter Currency Format:")
+package = st.text_input("Enter Package:")
+communication = st.text_input("Enter Communication:")
+notice_period = st.text_input("Enter Notice Period:")
+qualifications = st.text_input("Enter Qualifications:")
+responsibility = st.text_area("Enter Job Responsibility:")
+
+if st.button("Generate Job Posting"):
+    try:
+        output_text = generate_job_posting(position, job_type, skillset, company_name, work_experience, job_location, job_benefits, field, currency, currency_format, package, communication, notice_period, qualifications, responsibility)
+        st.success(output_text)
+    except ValueError as e:
+        st.error(f"Error: {e}")
+    except Exception as e:
+        st.error(f"An error occurred: {e}")