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| import streamlit as st | |
| import google.generativeai as genai | |
| import os | |
| # Define a function to check if all sections are filled | |
| def check_all_responses_filled(responses): | |
| return all(responses) and all([all(responses[respondent]) for respondent in respondents]) | |
| # Configure the Google Generative AI API if the API key is available | |
| def configure_genai_api(): | |
| api_key = "AIzaSyDidbVQLrcwKuNEryNTwZCaLGiVQGmi6g0" | |
| if api_key is None: | |
| st.error("API key not found. Please set the GENAI_API_KEY environment variable.") | |
| return None | |
| else: | |
| genai.configure(api_key=api_key) | |
| generation_config = { | |
| "temperature": 0.9, | |
| "top_p": 1, | |
| "top_k": 40, | |
| "max_output_tokens": 2048, | |
| } | |
| safety_settings = [ | |
| {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}, | |
| {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}, | |
| {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}, | |
| {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}, | |
| ] | |
| return genai.GenerativeModel(model_name="gemini-1.0-pro", | |
| generation_config=generation_config, | |
| safety_settings=safety_settings) | |
| # Function to combine responses from all sections | |
| def combine_responses(saved_data): | |
| def extract_strings(data): | |
| if isinstance(data, dict): | |
| return " ".join([extract_strings(value) for value in data.values()]) | |
| elif isinstance(data, list): | |
| return " ".join([extract_strings(item) for item in data]) | |
| elif isinstance(data, str): | |
| return data | |
| else: | |
| return "" | |
| combined_responses = [] | |
| for section, responses in saved_data.items(): | |
| for response in responses.values(): | |
| combined_responses.append(extract_strings(response)) | |
| return " ".join(combined_responses) | |
| def app(): | |
| st.header("Summary of Your Professional Profile") | |
| # Check for environment variable and configure the API | |
| model = configure_genai_api() | |
| if not model: | |
| return | |
| # Display and collect all responses | |
| all_responses = { | |
| 'core_values': st.session_state.get('core_values_responses'), | |
| 'strengths': st.session_state.get('strength_responses'), | |
| 'partner_assessment': st.session_state.get('stories_feedback'), | |
| 'network_feedback': st.session_state.get('network_feedback'), | |
| 'skills': st.session_state.get('core_skills_responses'), | |
| 'priorities': st.session_state.get('priorities_data_saved'), | |
| 'preferences': st.session_state.get('preferences_responses'), | |
| } | |
| # Display all collected responses | |
| for section, responses in all_responses.items(): | |
| if responses: | |
| st.subheader(f"Your {section.replace('_', ' ').title()}:") | |
| if isinstance(responses, dict): | |
| for question, response in responses.items(): | |
| st.text(f"Q: {question}") | |
| st.text(f"A: {response}") | |
| elif isinstance(responses, list): | |
| for response in responses: | |
| st.text(response) | |
| st.write("---") # Separator line | |
| # Check if all sections are completed | |
| all_responses_filled = all(responses is not None for responses in all_responses.values()) | |
| if st.button("Generate My Career Summary") and all_responses_filled: | |
| combined_responses_text = combine_responses(all_responses) | |
| prompt_template = """Make a summary of skills and experience. And future projection of what job a person can do next | |
| Considering all above question responses including values, strengths, weaknesses | |
| Recommend the best next career option this person can do and what upskilling they require | |
| Suggest best certifications, best courses for this person | |
| """ | |
| prompt = prompt_template + combined_responses_text | |
| try: | |
| # Attempt to generate a comprehensive career summary and future projection | |
| response = model.generate_content([prompt]) | |
| if response and hasattr(response, 'parts'): | |
| career_summary = ''.join([part['text'] for part in response.parts]) | |
| st.subheader("Career Summary and Projection") | |
| st.write("Based on all the information you've provided, here's a comprehensive summary and future career projection tailored to you:") | |
| st.info(career_summary) | |
| else: | |
| st.error("The response from the API was not in the expected format.") | |
| except Exception as e: | |
| st.error("An error occurred while generating your career summary. Please try again later.") | |
| st.error(f"Error: {e}") | |
| elif not all_responses_filled: | |
| st.error("Please ensure all sections are completed to receive your comprehensive career summary.") | |
| if __name__ == "__main__": | |
| app() |