First Commit

app.py

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+import streamlit as st
+from streamlit_chat import message
+
+from job_description_generator import predict_job_description, get_job_description_conversation
+from job_description_fixer import fix_job_description, get_job_description_fixer_conversation
+
+conversation = get_job_description_conversation()
+if 'conversation' not in st.session_state:
+    st.session_state['conversation'] = conversation
+
+fixer_conversation = get_job_description_fixer_conversation()
+if 'fixer_conversation' not in st.session_state:
+    st.session_state['fixer_conversation'] = fixer_conversation
+
+
+def setup():
+    """
+    Streamlit related setup. This has to be run for each page.
+    """
+    hide_streamlit_style = """
+    
+    <style>
+    #MainMenu {visibility: hidden;}
+    footer {visibility: hidden;}
+    </style>
+    """
+    st.markdown(hide_streamlit_style, unsafe_allow_html=True)
+
+
+def main():
+    '''
+     Main function of the app.
+    '''
+    setup()
+
+    #create a sidebar where you can select your page
+    st.sidebar.title("JobGPT")
+    st.sidebar.markdown("---")
+    #selector
+    page = st.sidebar.selectbox(
+        "Select a page", ["Job Description Generator", "Job Description Fixer"])
+    if page == "Job Description Generator":
+        c1 = st.container()
+        c1.title("JobGPT: A Job Description Generating Chatbot")
+        c1.markdown(
+            "JobGPT is a chatbot that generates job descriptions. This is built just for demo purpose."
+        )
+        input_text = c1.text_input(
+            "Prompt",
+            "Hi, can you please help me generate an unbiased job description?")
+        button = c1.button("Send")
+
+        st.sidebar.markdown("---")
+        st.sidebar.markdown("Click on `new chat` to start a new chat. \
+                History will be cleared and you'll lose access to current chat."
+                           )
+        clear_session = st.sidebar.button("New Chat")
+
+        if clear_session:
+            st.session_state['conversation'] = conversation
+        c1.markdown("---")
+
+        initial_message = "Hello, how can I help you?"
+        message(initial_message)
+
+        if button:
+            messages = []
+            current_message = ""
+            current_is_user = True
+            #clear prompt textbox
+            response = predict_job_description(input_text,
+                                               st.session_state['conversation'])
+            for historical_message in response['history']:
+                if "human" in historical_message.lower():
+                    messages.append([current_message, current_is_user])
+                    current_message = historical_message.replace("Human:", "")
+                    current_is_user = True
+                    # message(historical_message.replace("Human:", ""),
+                    #         is_user=True)
+                elif "JobGPT" in historical_message:
+                    messages.append([current_message, current_is_user])
+                    current_message = historical_message.replace("JobGPT:", "")
+                    current_is_user = False
+                else:
+                    current_message = current_message + "\n" + historical_message
+                # if message_to_send != "":
+                #     message(message_to_send.replace("JobGPT:",
+                #                                     "").replace("Human:", ""),
+                #             is_user=is_user)
+            messages.append([current_message, current_is_user])
+            for message_to_send, is_user in messages:
+                if message_to_send.strip() != "":
+                    message(message_to_send, is_user=is_user)
+            message(input_text, is_user=True)
+            message(response['prediction'], is_user=False)
+    else:
+        c2 = st.container()
+        c2.title("JobGPT: A Job Description Fixing Chatbot")
+        c2.markdown(
+            "JobGPT is a chatbot that fixes job descriptions. This is built just for demo purpose."
+        )
+        input_text = c2.text_area(
+            "Prompt",
+            "Hi, can you please help me fix my job description? It's biased.")
+        button = c2.button("Send")
+
+        st.sidebar.markdown("---")
+        st.sidebar.markdown("Click on `new chat` to start a new chat. \
+                History will be cleared and you'll lose access to current chat."
+                           )
+        clear_session = st.sidebar.button("New Chat")
+
+        if clear_session:
+            st.session_state['fixer_conversation'] = fixer_conversation
+        c2.markdown("---")
+
+        initial_message = "Hello, how can I help you?"
+        message(initial_message)
+
+        if button:
+            messages = []
+            current_message = ""
+            current_is_user = True
+            #clear prompt textbox
+            response = fix_job_description(
+                input_text, st.session_state['fixer_conversation'])
+            for historical_message in response['history']:
+                if "human" in historical_message.lower():
+                    messages.append([current_message, current_is_user])
+                    current_message = historical_message.replace("Human:", "")
+                    current_is_user = True
+                    # message(historical_message.replace("Human:", ""),
+                    #         is_user=True)
+                elif "JobGPT" in historical_message:
+                    messages.append([current_message, current_is_user])
+                    current_message = historical_message.replace("JobGPT:", "")
+                    current_is_user = False
+                else:
+                    current_message = current_message + "\n" + historical_message
+                # if message_to_send != "":
+                #     message(message_to_send.replace("JobGPT:",
+                #                                     "").replace("Human:", ""),
+                #             is_user=is_user)
+            messages.append([current_message, current_is_user])
+            for message_to_send, is_user in messages:
+                if message_to_send.strip() != "":
+                    message(message_to_send, is_user=is_user)
+            message(input_text, is_user=True)
+            message(response['prediction'], is_user=False)
+
+
+main()

job_description_fixer.py

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+import os
+import openai
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+from llm import generate_prompt, generate_conversation, predict
+
+openai_api_key = os.environ['OPENAI_API_KEY']
+openai.api_key = openai_api_key
+
+
+def get_job_description_fixer_conversation():
+    '''
+    Generate a conversation object for job description fixer
+    '''
+    prompt = generate_prompt(
+        input_variables=['history', 'input'],
+        template_file='templates/job_description_fixer.txt')
+    llm = ChatOpenAI(temperature=0, openai_api_key=openai_api_key)
+    memory = ConversationBufferMemory(ai_prefix="JobGPT")
+    conversation = generate_conversation(memory=memory, llm=llm, prompt=prompt)
+    return conversation
+
+
+def fix_job_description(input_text: str, conversation: object):
+    '''
+    predict the next response from the conversation object
+    '''
+    response = predict(input_text=input_text, conversation=conversation)
+    return response

job_description_generator.py

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+import os
+import openai
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+from llm import generate_prompt, generate_conversation, predict
+
+openai_api_key = os.environ['OPENAI_API_KEY']
+openai.api_key = openai_api_key
+
+
+def get_job_description_conversation():
+    '''
+    Generate a conversation object for job description generation
+    '''
+    prompt = generate_prompt(
+        input_variables=['history', 'input'],
+        template_file='templates/job_description_generation.txt')
+    llm = ChatOpenAI(temperature=0, openai_api_key=openai_api_key)
+    memory = ConversationBufferMemory(ai_prefix="JobGPT")
+    conversation = generate_conversation(memory=memory, llm=llm, prompt=prompt)
+    return conversation
+
+
+def predict_job_description(input_text: str, conversation: object):
+    '''
+    Predict the next response from the conversation object
+    '''
+    response = predict(input_text=input_text, conversation=conversation)
+    return response

llm.py

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+from langchain.chains import ConversationChain
+from langchain.prompts import PromptTemplate
+
+
+def generate_prompt(input_variables: list, template_file: str):
+    """
+    Generate a prompt from a template file and a list of input variables
+    """
+    with open(template_file, 'r', encoding='utf-8') as source_file:
+        template = source_file.read()
+    prompt = PromptTemplate(template=template, input_variables=input_variables)
+    return prompt
+
+
+def generate_conversation(memory: object,
+                          llm: object,
+                          prompt: object,
+                          verbose: bool = False):
+    """
+    Generate a conversation from a memory object, a language model object, and a prompt object
+    """
+    conversation = ConversationChain(memory=memory,
+                                     llm=llm,
+                                     prompt=prompt,
+                                     verbose=verbose)
+    return conversation
+
+
+def predict(input_text: str, conversation: object):
+    '''
+    Predict the next response from the conversation object
+    '''
+    response = conversation(input_text)
+    history = response['history']
+    history = history.split('\n')
+    prediction = response['response']
+    return {'history': history, 'prediction': prediction}

requirements.txt

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+langchain==0.0.194
+openai==0.27.8
+streamlit==1.23.1
+streamlit_chat==0.0.2.2

templates/job_description_fixer.txt

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+JobGPT is a chatbot which fixes job posting for executive positions in terms of bias, format etc.
+
+It greets the human and then asks to paste a job posting \
+
+Once it has the job posting, it fixes the job posting using following guidelines \
+Use gender-neutral language: Avoid using gender-specific pronouns (he, she) and job titles (salesman, saleswoman). Instead, opt for inclusive terms such as “they” and “salesperson.” \
+Focus on skills and qualifications: When writing job descriptions, emphasize the skills, qualifications, and experience required for the role, rather than making assumptions about which gender might be more suitable. \
+Remove gender-coded words: Avoid using adjectives that may be associated with a specific gender, such as “aggressive” or “nurturing.” Use neutral descriptors, like “results-driven” or “collaborative.” \
+Closely consider the education requirements listed in the job posting. \
+Express a commitment to equality and diversity. \
+Identify bias in job description in the form of “issue” and “how to fix” \
+
+If the posting is already fixed, it tells the human that it is already fixed. \
+
+The fixed job description includes following sections, well formatted: \
+Job Title \
+Company name \
+About the job \
+    small description \
+    responsibilities \
+    Required qualifications \
+    Benefitial qualifications \
+    Salary : JobGPT estimates salary based on location and title, return a range of numbers \
+Legal writeup \
+
+Finally it tells what changes it made to the job posting \
+
+The following is a friendly conversation between a human and JobGPT. JobGPT provides lots of specific details from its context. Your job is to predict what JobGPT says next.
+
+Current conversation:
+{history}
+Human: {input}
+JobGPT:

templates/job_description_generation.txt

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+JobGPT is a chatbot which generates job description for executive positions 
+
+It greets the human and then ask ONLY one question at a time to get the following information \
+title: \
+industry: \
+location: \
+skills: \
+experience: \
+One it has the above information, generate a job description as follows \
+
+It strictly follows these guidelines: \ 
+Use gender-neutral language: Avoid using gender-specific pronouns (he, she) and job titles (salesman, saleswoman). Instead, opt for inclusive terms such as “they” and “salesperson.” \
+Focus on skills and qualifications: When writing job descriptions, emphasize the skills, qualifications, and experience required for the role, rather than making assumptions about which gender might be more suitable. \
+Remove gender-coded words: Avoid using adjectives that may be associated with a specific gender, such as “aggressive” or “nurturing.” Use neutral descriptors, like “results-driven” or “collaborative.” \
+Closely consider the education requirements listed in the job posting. \
+Express a commitment to equality and diversity. \
+Identify bias in job description in form of “issue” and “how to fix” \
+
+The job description includes following sections, well formatted: \
+Job Title \
+Company name \
+About the job \
+    small description \
+    responsibilities \
+    Required qualifications \
+    Benefitial qualifications \
+    Salary : JobGPT estimates salary based on location and title, return a range of numbers \
+Legal writeup \
+
+The following is a friendly conversation between a human and JobGPT. JobGPT provides lots of specific details from its context. Your job is to predict what JobGPT says next.
+
+Current conversation:
+{history}
+Human: {input}
+JobGPT: