import streamlit as st import os import json from openai import AzureOpenAI from model import invoke, create_models, configure_settings, load_documents_and_create_index, \ create_chat_prompt_template, execute_query meta_eip_prefix = """# META: Entrepreneurial and Intrapreneurial Potential\nMETA evaluates five traits essential for entrepreneurial success: Vision, Ideation, Opportunism, Drive, and Resilience. It also measures four ‘Red Flags’ or derailers common to the entrepreneurial personality.""" client = AzureOpenAI(azure_endpoint="https://personalityanalysisfinetuning.openai.azure.com/", api_key=os.environ.get("AZURE_OPENAI_KEY"), api_version="2024-02-01") # Example profile (as before) example_profile = { "Team": [ {"name": "JAMES ARTHUR", "main_profile": {"VISION": {"score": 76}, "IDEATION": {"score": 73}, "OPPORTUNISM": {"score": 78}, "DRIVE": {"score": 80}, "RESILIENCE": {"score": 75}}, "red_flag": {"HUBRIS": {"score": 80}, "MERCURIAL": {"score": 28}, "DOMINANT": {"score": 70}, "MACHIAVELLIAN": {"score": 50}}}, {"name": "LOUSIE HART", "main_profile": {"VISION": {"score": 55}, "IDEATION": {"score": 60}, "OPPORTUNISM": {"score": 65}, "DRIVE": {"score": 70}, "RESILIENCE": {"score": 72}}, "red_flag": {"HUBRIS": {"score": 55}, "MERCURIAL": {"score": 25}, "DOMINANT": {"score": 67}, "MACHIAVELLIAN": {"score": 30}}}, {"name": "SIMONE LEVY", "main_profile": {"VISION": {"score": 30}, "IDEATION": {"score": 45}, "OPPORTUNISM": {"score": 20}, "DRIVE": {"score": 50}, "RESILIENCE": {"score": 32}}, "red_flag": {"HUBRIS": {"score": 20}, "MERCURIAL": {"score": 15}, "DOMINANT": {"score": 18}, "MACHIAVELLIAN": {"score": 25}}}, {"name": "Uri Lef", "main_profile": {"VISION": {"score": 70}, "IDEATION": {"score": 68}, "OPPORTUNISM": {"score": 73}, "DRIVE": {"score": 65}, "RESILIENCE": {"score": 30}}, "red_flag": {"HUBRIS": {"score": 55}, "MERCURIAL": {"score": 72}, "DOMINANT": {"score": 68}, "MACHIAVELLIAN": {"score": 50}}} ] } def verify_credentials(): if st.session_state['username'] == os.getenv("username_app") and st.session_state['password'] == os.getenv("password_app"): st.session_state['authenticated'] = True else: st.error("Invalid username or password") def login_page(): st.title("Welcome to Metaprofiling's Career Insight Analyzer Demo") st.write("This application provides in-depth analysis and insights into professional profiles. Please log in to continue.") # Description and Instructions st.markdown(""" ## How to Use This Application - Enter your username and password in the sidebar. - Click on 'Login' to access the application. - Once logged in, you will be able to upload and analyze professional profiles. """) st.sidebar.write("Login:") username = st.sidebar.text_input("Username")#, key='username') password = st.sidebar.text_input("Password", type="password")#, key='password') st.session_state['username'] = username st.session_state['password'] = password st.sidebar.button("Login", on_click=verify_credentials) # Update generate_prompt_from_profile to take selected team members def generate_prompt_from_profile(profile, selected_members, version="TeamSummary"): with open('prompts.json') as f: prompt_sets = json.load(f)['Prompts'] prompt_templates = prompt_sets[version] try: team_member_profiles = [] for member in profile['Team']: if member['name'] in selected_members: profile_str = (f"{member['name']}: Main Profile - VISION: {member['main_profile']['VISION']['score']}, " f"IDEATION: {member['main_profile']['IDEATION']['score']}, " f"OPPORTUNISM: {member['main_profile']['OPPORTUNISM']['score']}, " f"DRIVE: {member['main_profile']['DRIVE']['score']}, " f"RESILIENCE: {member['main_profile']['RESILIENCE']['score']}. " f"Red Flags - HUBRIS: {member['red_flag']['HUBRIS']['score']}, " f"MERCURIAL: {member['red_flag']['MERCURIAL']['score']}, " f"DOMINANT: {member['red_flag']['DOMINANT']['score']}, " f"MACHIAVELLIAN: {member['red_flag']['MACHIAVELLIAN']['score']}.") team_member_profiles.append(profile_str) team_member_profiles_str = "\n".join(team_member_profiles) prompt = "\n".join(prompt_templates).replace("{{TEAM_MEMBERS}}", team_member_profiles_str) print(prompt) except KeyError as e: return [{"role": "system", "content": f"Error processing profile data: missing {str(e)}"}] message = [ {"role": "system", "content": prompt_sets["System"][0]}, {"role": "user", "content": prompt} ] return message def display_profile_info(profile): st.markdown("### Profile Information:") team_members = profile["Team"] for member in team_members: st.sidebar.markdown(f"#### {member['name']}") main_profile = member["main_profile"] red_flag = member["red_flag"] st.sidebar.markdown("### Main Profile:") st.sidebar.markdown("\n".join([f"- **{attribute}**: {details['score']}" for attribute, details in main_profile.items()])) st.sidebar.markdown("### Red Flags:") st.sidebar.markdown("\n".join([f"- **{attribute}**: {details['score']}" for attribute, details in red_flag.items()])) def logout(): st.session_state['authenticated'] = False st.session_state['profile'] = None st.session_state['show_chat'] = None st.session_state['analysis'] = None st.rerun() def main_app(): sidebar_components() if st.button('Logout'): logout() st.title("Metaprofiling's Career Insight Analyzer Demo") if st.session_state['profile']: profile = st.session_state['profile'] display_profile_info(profile) st.markdown(""" ### Generation Temperature Adjust the 'Generation Temperature' to control the creativity of the AI responses. - A *lower temperature* (closer to 0.0) generates more predictable, conservative responses. - A *higher temperature* (closer to 1.0) generates more creative, diverse responses. """) st.session_state['temperature'] = st.slider("", min_value=0.0, max_value=1.0, value=0.5, step=0.01) st.session_state['version'] = st.selectbox("Select Prompt Version", ["METAEIP","TDOS"]) # Add a multiselect for team member selection # team_member_names = [member['name'] for member in profile['Team']] # selected_members = st.multiselect("Select Team Members to Include in the Analysis", team_member_names, default=team_member_names) team_member_names = [member['name'] for member in profile['Team']] if st.session_state['version'] == "METAEIP": selected_members = st.selectbox("Select Team Member to Include in the Analysis", team_member_names) selected_members = [selected_members] else: selected_members = st.multiselect("Select Team Members to Include in the Analysis", team_member_names, default=team_member_names) if st.button(f'Analyze Profile ({st.session_state["version"]})'): prompt = generate_prompt_from_profile(profile, selected_members, version=st.session_state['version']) with st.chat_message("assistant"): stream = client.chat.completions.create( model="personality_gpt4o", temperature=st.session_state['temperature'], max_tokens=3000, frequency_penalty=0.2, presence_penalty=0.2, messages=prompt, stream=True ) if st.session_state['version'] == "METAEIP": st.write(meta_eip_prefix) response = st.write_stream(stream) st.session_state['analysis'] = response st.session_state['show_chat'] = True st.rerun() if st.session_state['analysis']: st.write(meta_eip_prefix) st.markdown(st.session_state['analysis']) else: st.write("Please upload a profile JSON file or use the example profile.") def sidebar_components(): with st.sidebar: if st.button('Reset'): st.session_state['profile'] = None st.session_state['show_chat'] = None st.session_state['analysis'] = None st.rerun() if not st.session_state['show_chat']: st.markdown("### JSON File Requirements:") st.markdown("1. Must contain Team as top-level keys.") st.markdown("2. Both keys should have dictionary values.") uploaded_file = st.file_uploader("", type=['json']) if uploaded_file is not None: try: profile_data = json.load(uploaded_file) st.session_state['profile'] = profile_data except json.JSONDecodeError: st.error("Invalid JSON file. Please upload a valid JSON file.") if st.button('Use Example Profile'): st.session_state['profile'] = example_profile else: st.sidebar.title("Chat with Our Career Advisor") st.sidebar.markdown("Hello, we hope you learned something about yourself in this report. This chat is here so you can ask any questions you have about your report! It’s also a great tool to get ideas about how you can use the information in your report for your personal development and achieving your current goals.") question_templates = [ "What are the main risks associated with {}’s profile?", "What are the implications of {}’s profile for working with others?" ] questions_list = [question.format("Test Taker") for question in question_templates] questions_markdown = "\n\n".join([f"Q{index + 1}: {question}" for index, question in enumerate(questions_list)]) st.sidebar.markdown("### Suggest Questions") st.sidebar.markdown(questions_markdown) user_input = st.sidebar.text_input("Ask a question about the profile analysis:") llm, embed_model = create_models() configure_settings(llm, embed_model) index = load_documents_and_create_index() if st.sidebar.button('Submit'): if user_input: chat_prompt_template = create_chat_prompt_template(st.session_state['analysis']) response = execute_query(index, chat_prompt_template, user_input) st.sidebar.markdown(response) if 'show_chat' not in st.session_state: st.session_state['show_chat'] = None if 'profile' not in st.session_state: st.session_state['profile'] = None if 'analysis' not in st.session_state: st.session_state['analysis'] = None if 'temperature' not in st.session_state: st.session_state['temperature'] = 0 if 'version' not in st.session_state: st.session_state['version'] = "" if 'username' not in st.session_state: st.session_state['username'] = '' if 'password' not in st.session_state: st.session_state['password'] = '' if 'authenticated' not in st.session_state: st.session_state['authenticated'] = False if st.session_state['authenticated']: main_app() else: login_page()