| # 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 | |
| # | |
| # client = AzureOpenAI(azure_endpoint = "https://personalityanalysisfinetuning.openai.azure.com/",api_key=os.environ.get("AZURE_OPENAI_KEY"), api_version="2024-02-01") | |
| # | |
| # | |
| # 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 | |
| # } | |
| # } | |
| # } | |
| # ] | |
| # } | |
| # | |
| # # Function to generate a completion using OpenAI API | |
| # # def generate_one_completion(message, temperature): | |
| # # response = client.chat.completions.create( | |
| # # model="personality_gpt4o", | |
| # # temperature=temperature, | |
| # # max_tokens=1000, # Adjust based on desired response length | |
| # # frequency_penalty=0.2, # To avoid repetition | |
| # # presence_penalty=0.2, # To introduce new topics | |
| # # messages= message, | |
| # # stream=False | |
| # # ) | |
| # # | |
| # # return response | |
| # | |
| # import json | |
| # | |
| # def generate_prompt_from_profile(profile, version="TeamSummary"): | |
| # with open('prompts.json') as f: | |
| # prompt_sets = json.load(f)['Prompts'] | |
| # prompt_templates = prompt_sets[version] | |
| # | |
| # try: | |
| # team_members = profile['Team'] | |
| # | |
| # team_member_profiles = [] | |
| # for member in team_members: | |
| # profile = 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) | |
| # | |
| # # Join the team member profiles into a single string | |
| # 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} | |
| # ] | |
| # print(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 validate_json(profile): | |
| # # required_keys = ['Team'] | |
| # # for key in required_keys: | |
| # # if key not in profile: | |
| # # return False, f"Key '{key}' is missing." | |
| # # if not isinstance(profile[key], dict): | |
| # # return False, f"'{key}' should be a dictionary." | |
| # # return True, "JSON structure is valid." | |
| # 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() | |
| # | |
| # # Streamlit app | |
| # st.title('Metaprofiling\'s Career Insight Analyzer Demo') | |
| # | |
| # | |
| # # Check if a profile is selected | |
| # if st.session_state['profile']: | |
| # profile = st.session_state['profile'] | |
| # display_profile_info(profile) # Display the profile information | |
| # | |
| # 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. | |
| # """) | |
| # # Temperature slider | |
| # st.session_state['temperature'] = st.slider("",min_value=0.0, max_value=1.0, value=0.5, step=0.01) | |
| # | |
| # # Allow user to choose from different versions of the prompt | |
| # st.session_state['version'] = st.selectbox("Select Prompt Version", ["TDOS"]) | |
| # # Generate and display prompt | |
| # | |
| # if st.button(f'Analyze Profile ({st.session_state["version"]})'): | |
| # #with st.spinner('Generating completion...'): | |
| # prompt = generate_prompt_from_profile(profile, version=st.session_state['version']) | |
| # | |
| # 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.""" | |
| # | |
| # with st.chat_message("assistant"): | |
| # stream = client.chat.completions.create( | |
| # model="personality_gpt4o", | |
| # temperature=st.session_state['temperature'], | |
| # max_tokens=3000, # Adjust based on desired response length | |
| # frequency_penalty=0.2, # To avoid repetition | |
| # presence_penalty=0.2, # To introduce new topics | |
| # messages= prompt, | |
| # stream=True) | |
| # | |
| # if st.session_state['version'] == "METAEIP": | |
| # st.write(meta_eip_prefix) | |
| # | |
| # response = st.write_stream(stream) | |
| # #st.markdown(response_test_taker) | |
| # | |
| # st.session_state['analysis'] = response | |
| # st.session_state['show_chat'] = True | |
| # st.rerun() | |
| # | |
| # # display the response | |
| # if st.session_state['analysis']: | |
| # st.markdown(st.session_state['analysis']) | |
| # | |
| # else: | |
| # st.write("Please upload a profile JSON file or use the example profile.") | |
| # | |
| # | |
| # # Function to verify credentials and set the session state | |
| # 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") | |
| # | |
| # | |
| # # Login page | |
| # 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) | |
| # | |
| # 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']: | |
| # # Instructions for JSON format | |
| # st.markdown("### JSON File Requirements:") | |
| # st.markdown("1. Must contain Team as top-level keys.") | |
| # st.markdown("2. Both keys should have dictionary values.") | |
| # | |
| # # File uploader | |
| # st.markdown("### Upload a profile JSON file") | |
| # uploaded_file = st.file_uploader("", type=['json']) | |
| # | |
| # if uploaded_file is not None: | |
| # try: | |
| # profile_data = json.load(uploaded_file) | |
| # #valid, message = validate_json(profile_data) | |
| # #if valid: | |
| # st.session_state['profile'] = profile_data | |
| # #else: | |
| # #st.error(message) | |
| # except json.JSONDecodeError: | |
| # st.error("Invalid JSON file. Please upload a valid JSON file.") | |
| # | |
| # # Button to load example profile | |
| # if st.button('Use Example Profile'): | |
| # st.session_state['profile'] = example_profile | |
| # | |
| # # elif uploaded_file is not None: | |
| # # st.session_state['profile'] = json.load(uploaded_file) | |
| # 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.") | |
| # | |
| # | |
| # | |
| # # List of question templates where {} will be replaced with the name | |
| # question_templates = [ | |
| # "What are the main risks associated with {}’s profile?", | |
| # "What are the implications of {}’s profile for working with others?", | |
| # "What conclusions might we draw from his profile about {}’s style of leadership?", | |
| # "Looking specifically at {}'s Red Flags, are there any particular areas of concern?", | |
| # "Based on this profile, is {} better suited as a COO or a CEO?", | |
| # "If speed of execution is important, based on his profile, how likely is {} to be able to achieve this?", | |
| # "How is {} likely to react to business uncertainty and disruption?", | |
| # "Based on his profile, what should a coaching plan designed for {} focus on?" | |
| # ] | |
| # | |
| # # Formatting each question template with the name | |
| # questions_list = [question.format("Test Taker") for question in question_templates] | |
| # | |
| # # Prepare the questions for Markdown display | |
| # questions_markdown = "\n\n".join( | |
| # [f"Q{index + 1}: {question}" for index, question in enumerate(questions_list)]) | |
| # | |
| # # Code to display in the app | |
| # st.sidebar.markdown("### Suggest Questions") | |
| # st.sidebar.markdown(questions_markdown) | |
| # | |
| # # st.sidebar.text_area("Suggested Questions", value=questions.choices[0].message.content, height=200, disabled=True) | |
| # | |
| # 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: | |
| # # with open('prompts.json') as f: | |
| # # prompt_sets = json.load(f)['Prompts'] | |
| # # instruction = prompt_sets['Question'] | |
| # | |
| # | |
| # # instruction = ( | |
| # # "You are a knowledgeable advisor providing insights based on the specific analysis provided earlier. " | |
| # # "Your responses should around 100 words, directly relate to the user's question, drawing on relevant details from the analysis. " | |
| # # "If the user's question does not pertain to the analysis or is beyond the scope of the information provided, " | |
| # # "politely decline to answer, stating that the question is outside the analysis context. Focus on delivering " | |
| # # "concise, accurate, insightful, and relevant information. \n\n" | |
| # # "Question: " + user_input | |
| # # ) | |
| # | |
| # # message = generate_prompt_from_profile(st.session_state['profile']) | |
| # # message.append({"role": "system", "content": st.session_state['analysis']}) | |
| # # message.append({"role": "user", "content": "\n".join(instruction).replace('{{QUESTION}}', user_input)}) | |
| # | |
| # # with st.chat_message("assistant"): | |
| # # stream = client.chat.completions.create( | |
| # # model="personality_gpt4", | |
| # # temperature=st.session_state['temperature'], | |
| # # max_tokens=500, # Adjust based on desired response length | |
| # # frequency_penalty=0.2, # To avoid repetition | |
| # # presence_penalty=0.2, # To introduce new topics | |
| # # messages=message, | |
| # # stream=True | |
| # # ) | |
| # | |
| # chat_prompt_template = create_chat_prompt_template(st.session_state['analysis']) | |
| # response = execute_query(index, chat_prompt_template, user_input) | |
| # | |
| # #response = st.write_stream(stream) | |
| # | |
| # | |
| # # output = generate_one_completion(message,st.session_state['temperature']) | |
| # # | |
| # # #st.sidebar.text_area("Response", value=output.choices[0].message.content, height=200, disabled=True) | |
| # st.sidebar.markdown(response) | |
| # | |
| # # Display the sidebar components based on the state | |
| # 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'] = "" | |
| # | |
| # # Initialize session state for username, password, and authentication | |
| # 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 | |
| # # Show login or main app based on authentication | |
| # if st.session_state['authenticated']: | |
| # main_app() | |
| # else: | |
| # login_page() | |
| 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 | |
| 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", ["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) | |
| if st.button(f'Analyze Profile ({st.session_state["version"]})'): | |
| prompt = generate_prompt_from_profile(profile, selected_members, version=st.session_state['version']) | |
| 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.""" | |
| 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.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?", | |
| "What conclusions might we draw from his profile about {}’s style of leadership?", | |
| "Looking specifically at {}'s Red Flags, are there any particular areas of concern?", | |
| "Based on this profile, is {} better suited as a COO or a CEO?", | |
| "If speed of execution is important, based on his profile, how likely is {} to be able to achieve this?", | |
| "How is {} likely to react to business uncertainty and disruption?", | |
| "Based on his profile, what should a coaching plan designed for {} focus on?" | |
| ] | |
| 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() | |