upd t and m

app.py

@@ -57,20 +57,17 @@ if 'inserted' not in st.session_state:
 
     # user info state
     st.session_state.fields = [
-    'climate_actions', 'age', 'gender', 'education', 'residence', 
-     'property', #'income', 'zipcode',
+    'climate_actions', 'age', 'gender', 'education', 'residence', 'property', 
     'politics', 'impact_open', 'ev', 
-    'fossil', 'aerosol', 'diet', 'recycling'
+    'fossil', 'aerosol', 'diet', 'recycling',
+    'user_id'
     ]
 
     for field in st.session_state.fields:
         st.session_state[field] = ''
 
-    st.session_state.user_id = ''
-
     st.session_state.recycling = 0
 
-
     # timers
     st.session_state.start_time = datetime.now()
     st.session_state.convo_start_time = ''
@@ -79,7 +76,10 @@ if 'p' not in st.query_params:
     st.query_params['p'] = 't'
 
 def setup_messages():
-    ### p = personalization ('f' none, otherwise personalization)
+    # t = personalization 
+    # k = knowledge
+    # f = formatting
+    # n = no chat
 
     if st.query_params["p"] == "f" or st.query_params["p"] == "n":
         st.session_state.system_message = st.session_state.base_text 
@@ -88,7 +88,6 @@ def setup_messages():
     elif st.query_params["p"] == "t":
         st.session_state.system_message = format_personalization(st.session_state.personalization_text)
 
-    print(st.session_state.system_message)
     st.session_state.messages = [{ "role": "system", "content": st.session_state.system_message}]
     st.session_state.convo_start_time = datetime.now()
 
@@ -118,12 +117,14 @@ with st.sidebar:
     {"🎉 **All done! Please press *Next* in the survey.**" if st.session_state.inserted > 0 else ""}
     """)
     if st.session_state.gotit == False:
+        st.markdown("*You can always return to this panel by clicking the arrow on the top left.*")
         st.session_state.gotit = st.button("Let's start!", key=None, help=None, use_container_width=True) 
 
 
 @st.dialog('Form')
 def form():
-    st.markdown("**Please answer every question to proceed.**")
+    st.markdown("**❗ Please answer every question to proceed.**")
+    st.session_state.user_id = st.text_input(label="Enter your Prolific ID", value=st.session_state.user_id)
     st.session_state.age = st.text_input("How old are you in years?")
     st.session_state.gender = st.radio("Do you describe yourself as a man, a woman, or in some other way?", 
                 ['','Man', 'Woman', 'Other'])
@@ -137,12 +138,9 @@ def form():
                 'Doctorate degree (e.g., PhD, MD)'])
     st.session_state.residence = st.radio("What type of a community do you live in?", 
                 ['', 'Urban','Suburban','Rural','Other'])
-    #st.session_state.zipcode = st.text_input("What is your US Zip Code?")
     st.session_state.property = st.radio("Do you own or rent the home in which you live?", 
                 ['', 'Own','Rent','Neither (I live rent-free)',
                 'Other' ])
-    #st.session_state.income = st.radio("What was your total household income before taxes during the past 12 months?",
-      #          ['','Less than \$25,000','\$25,000 to \$49,999','\$50,000 to \$74,999','\$75,000 to \$99,999','\$100,000 to \$149,999','\$150,000 or more'])
     st.session_state.politics = st.radio('What is your political orientation?', ['', 'Extremely liberal', 'Liberal', 'Slightly liberal', 'Moderate', 'Slightly conservative', 'Conservative', 'Extremely conservative'])
     st.session_state.climate_actions = st.text_area('Please describe any actions you are taking to address climate change? Write *None* if you are not taking any.')
     st.session_state.impact_open = st.text_area('What do you believe is the single most effective action you can take to reduce carbon emissions that contribute to climate change?')
@@ -156,26 +154,32 @@ def form():
     st.session_state.diet = st.radio('Lab-grown meat produces up to 25 times more CO2 than real meat.', ["", "Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"])
 
 
-    #st.session_state.user_info = st.text_area(
-    #"Write at least two sentences about yourself. You can write about your job, hobbies, living arrangements or any other information you think might be relevant. **Do not write anything that could identify you, such as your name or address.**",'')
-
     columns_form = st.columns((1,1,1))
     with columns_form[2]:
-        submitted = st.button("Proceed",use_container_width=True)
+        submitted = st.button("Proceed",use_container_width=True, 
+                              help = 'Please answer every question and click *Proceed* to start a conversation.',
+                              disabled = not (all(st.session_state[field] != '' for field in st.session_state.fields) and st.session_state.recycling != 0))
 
-    all_form_completed = all(st.session_state[field] != '' for field in st.session_state.fields) and st.session_state.recycling != 0
+    if submitted:
 
-    if submitted and all_form_completed:
+        user_data = {key: st.session_state[key] for key in st.session_state.fields}
+        user_data["model"] = st.session_state["model"]
+        user_data["condition"] = st.query_params['p']
+        user_data["start_time"] = st.session_state.start_time
+        user_data["inserted"] = st.session_state.inserted
+        user_data["submission_time"] = datetime.now()
+        
+        from pymongo.mongo_client import MongoClient
+        from pymongo.server_api import ServerApi
+        with MongoClient(st.secrets["mongo"],server_api=ServerApi('1')) as client:
+                db = client.chat
+                collection = db.app
+                collection.insert_one(user_data)  
+                st.session_state.inserted += 1
         st.session_state.submitted = True
         setup_messages()
         st.rerun()
 
-    elif submitted and not all_form_completed:
-        st.warning('Please answer every question and click *Proceed* again to start a conversation.')
-    
-
-#st.write(st.session_state.system_message)
-
 if st.session_state.gotit and st.session_state.submitted == False:
     form()
 
@@ -187,31 +191,30 @@ for message in st.session_state.messages:
 @st.dialog('Submit conversation')
 def submit():
     st.markdown("You must answer all questions marked with a ❗ to submit.")
-    st.session_state.user_id = st.text_input(label="❗ Enter your Prolific ID", value=st.session_state.user_id)
     if st.query_params["p"] != "n":
         st.slider('❗ How would you rate the conversation on a scale from *Terrible* to *Perfect*?', 0, 100, format="", key="score", value=50)
         st.slider('❗ How personalized did the conversation feel, on a scale from *Not at all* to *Extremely personalized*?', 0, 100, format="", key="personalization_score", value=50)
         st.slider('❗ How knowledgeable do you feel the chatbot was, on a scale from *Not at all* to *Extremely knowledgeable*?', 0, 100, format="", key="knowledge_score", value=50)
     else:
-        st.session_state.score = 51
-        st.session_state.personalization_score = 51
-        st.session_state.knowledge_score = 51
+        st.session_state.score = 0
+        st.session_state.personalization_score = 0
+        st.session_state.knowledge_score = 0
 
     st.text_area('Any feedback?',key="feedback")
-    if st.button('Submit', key=None, help=None, use_container_width=True, disabled=st.session_state.user_id=="" or st.session_state.score==50 or st.session_state.personalization_score==50):
-        #submission_date = datetime.now() #.strftime("%Y-%m-%d %H:%M:%S")
-
+    if st.button('Submit', key=None, help=None, use_container_width=True, disabled=st.session_state.score==50 or st.session_state.personalization_score==50):
         keys = [
-            "user_id", "messages", "score", "personalization_score", "knowledge_score", "model",
-            "feedback", 
-            "age", "gender", "education", "residence", "property", "politics",
-            "climate_actions", "impact_open", 
-            "recycling", "ev", "fossil", "aerosol", "diet",
-            "inserted", "start_time", "convo_start_time"
-        ]
+                "user_id", "messages", 
+                "score", "personalization_score", "knowledge_score", 
+                "model", "feedback", 
+                "age", "gender", "education", "residence", "property", "politics",
+                "climate_actions", "impact_open", 
+                "recycling", "ev", "fossil", "aerosol", "diet",
+                "inserted", "start_time", 
+                "convo_start_time"
+            ]
 
         user_data = {key: st.session_state[key] for key in keys}
-        user_data["condition"] = f"p{st.query_params['p']}"
+        user_data["condition"] = {st.query_params['p']}
         user_data["submission_time"] = datetime.now()
         
         from pymongo.mongo_client import MongoClient
@@ -224,7 +227,7 @@ def submit():
                 
                 st.success('**Your conversation has been submitted! Please proceed with the survey.**', icon="✅")
 
-                time.sleep(5)
+                time.sleep(10)
                 setup_messages()
                 st.rerun()
 
@@ -238,6 +241,8 @@ elif st.session_state.submitted == False:
 
 elif st.query_params["p"] == "n":
     st.markdown("""
+                You have not been selected to have a conversation with the chatbot.
+
                 ❗ **Please press *End Conversation* to submit your data and proceed with the survey. You have to submit to receive compensation.** 
                 """)
     columns = st.columns((1,1,1))

knowledge.txt

@@ -21,7 +21,7 @@ Ordered from highest impact (mitigation potential close to 1.5 tCO2eq/cap) to lo
 14. Recycling
 
 This knowledge come from a study conducted by Ivanova et al.: 
-Ivanova, D., Barrett, J., Wiedenhofer, D., Macura, B., Callaghan, M., & Creutzig, F. (2020). Quantifying the potential for climate change mitigation of consumption options. Environmental Research Letters, 15(9), 093001.
+Ivanova, D., Barrett, J., Wiedenhofer, D., Macura, B., Callaghan, M., & Creutzig, F. (2020). Quantifying the potential for climate change mitigation of consumption options. Environmental Research Letters, 15(9), 093001. doi.org/10.1088/1748-9326/ab8589
 
 Study Abstract:
 

personalization.txt

@@ -21,6 +21,9 @@ Most Effective Climate Action:
 Current Climate Actions:
 - Question: 'Do you take any actions with the aim of reducing your carbon emissions and reducing your contribution to climate change?'
 - User Response: [CLIMATE_ACTIONS]
+Recycling:
+- Question: 'What percentage of plastic produced gets recycled globally?'
+- User Response: [RECYCLING]%
 Electric Vehicles:
 - Statement: 'Electric vehicles don’t have enough range to handle daily travel demands.'
 - User Response: [EV]
@@ -30,11 +33,8 @@ Diet:
 Fossil Fuel Industry:
 - Statement: 'The fossil fuel industry is trying to shift the blame away from themselves by emphasizing the importance of individual climate action.'
 - User Response: [FOSSIL]
-Recycling:
-- Question: What percentage of plastic produced gets recycled?
-- User Response: [RECYCLING]%
 Aerosols:
-- Question: 'Is the use of aerosol spray cans a major cause of climate change, to the best of your knowledge?'
+- Statement: 'The use of aerosol spray cans is a major cause of climate change.'
 - User Response: [AEROSOL]
 
 # Your Expertise 
@@ -58,7 +58,7 @@ Ordered from highest impact (mitigation potential close to 1.5 tCO2eq/cap) to lo
 14. Recycling
 
 This knowledge come from a study conducted by Ivanova et al.: 
-Ivanova, D., Barrett, J., Wiedenhofer, D., Macura, B., Callaghan, M., & Creutzig, F. (2020). Quantifying the potential for climate change mitigation of consumption options. Environmental Research Letters, 15(9), 093001.
+Ivanova, D., Barrett, J., Wiedenhofer, D., Macura, B., Callaghan, M., & Creutzig, F. (2020). Quantifying the potential for climate change mitigation of consumption options. Environmental Research Letters, 15(9), 093001. doi.org/10.1088/1748-9326/ab8589
 
 Study Abstract: