Update app.py

app.py

@@ -1,8 +1,7 @@
 import streamlit as st
 import openai
 import json
-import os
-from dotenv import load_dotenv
+from fpdf import FPDF
 
 # Load the OpenAI API Key
 api_key = st.text_input('Enter your OpenAI API Key', type="password")
@@ -78,7 +77,6 @@ def save_responses_to_json(username, responses):
         "responses": [{"text": question["text"], "answer": response} for question, response in zip(questions, responses)]
     }
 
-    # Save to UserChoices.json
     with open("UserChoices.json", "w") as json_file:
         json.dump(user_data, json_file, indent=4)
 
@@ -90,10 +88,34 @@ def save_personality_to_output_json(username, mbti_type_classic, mbti_type_llm):
         "mbti_type_llm": mbti_type_llm
     }
 
-    # Save to Output.json
     with open("Output.json", "w") as json_file:
         json.dump(output_data, json_file, indent=4)
 
+# Function to generate PDF report
+def generate_pdf_report(username, mbti_type_classic, mbti_type_llm):
+    pdf = FPDF()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.add_page()
+
+    # Set title
+    pdf.set_font('Arial', 'B', 16)
+    pdf.cell(200, 10, txt="MBTI Personality Report", ln=True, align='C')
+
+    # Add participant information
+    pdf.ln(10)
+    pdf.set_font('Arial', '', 12)
+    pdf.cell(200, 10, txt=f"Participant Name: {username}", ln=True)
+
+    # Add MBTI types
+    pdf.ln(10)
+    pdf.cell(200, 10, txt=f"Your MBTI type based on weighted answers: {mbti_type_classic}", ln=True)
+    pdf.cell(200, 10, txt=f"Your MBTI type according to AI: {mbti_type_llm}", ln=True)
+
+    # Output the PDF
+    pdf_output = "MBTI_Personality_Report.pdf"
+    pdf.output(pdf_output)
+    return pdf_output
+
 # Streamlit component to display the quiz and handle responses
 def show_mbti_quiz():
     st.title('FlexTemp Personality Test')
@@ -120,9 +142,9 @@ def show_mbti_quiz():
                 mbti_type_classic = classic_mbti_weighted(responses)
                 st.write(f"Your MBTI type based on weighted answers: {mbti_type_classic}")
 
-                # You can add LLM-based prediction if needed here (example OpenAI-based model)
+                # LLM-based prediction
+                mbti_type_llm = ""
                 if api_key:
-                    # Run the LLM (GPT-4, for example) model to generate a personality type.
                     prompt = f"""
                     Determine a person's personality type based on their answers to the following Myers-Briggs Type Indicator (MBTI) questions:
                     The person has answered the following questions:
@@ -131,7 +153,7 @@ def show_mbti_quiz():
                     """
                     try:
                         response = openai.ChatCompletion.create(
-                            model="gpt-4o",
+                            model="gpt-4",
                             messages=[{"role": "system", "content": "You are a helpful assistant."},
                                       {"role": "user", "content": prompt}]
                         )
@@ -144,6 +166,17 @@ def show_mbti_quiz():
                 save_responses_to_json(participant_name, responses)
                 save_personality_to_output_json(participant_name, mbti_type_classic, mbti_type_llm)
 
+                # Generate PDF report and offer it as a download
+                pdf_report = generate_pdf_report(participant_name, mbti_type_classic, mbti_type_llm)
+                with open(pdf_report, "rb") as file:
+                    st.download_button(
+                        label="Download Generated Report (PDF)",
+                        data=file,
+                        file_name="MBTI_Personality_Report.pdf",
+                        mime="application/pdf"
+                    )
+
+                # Provide the other download buttons
                 with open("Output.json", "r") as json_file:
                     json_data = json_file.read()
 
@@ -171,8 +204,7 @@ def show_mbti_quiz():
 def main():
     # Add instructions to the sidebar
     with st.sidebar.expander("How This App Works", expanded=False):
-        st.write("""
-            ### FlexTemp Personality Test
+        st.write("""### FlexTemp Personality Test
             This app is designed to help you determine your MBTI personality type based on your answers to a series of questions. The process works as follows:
             1. **Weighted MBTI Scoring**: 
             - Each question corresponds to a trait in the MBTI system. 
@@ -182,11 +214,11 @@ def main():
             - Optionally, you can also get your MBTI type based on the answers using a language model (LLM) like GPT-4. This provides an additional prediction that may offer insights into your personality.
             - The LLM is trained on vast amounts of data and can generate responses based on patterns from psychological research and real-world interactions.
             """)
-    
+
     if api_key:
         show_mbti_quiz()
     else:
         st.info("Please enter your OpenAI API Key to begin the quiz.")
 
 if __name__ == "__main__":
-    main()
+    main()