init

.gitignore

@@ -0,0 +1 @@
+*.DS_Store

.streamlit/config.toml

@@ -0,0 +1,8 @@
+[server]
+port = 8501
+
+[browser]
+gatherUsageStats = false
+
+[theme]
+base="light"

README.md

@@ -1,13 +1,16 @@
 ---
-title: Chat
-emoji: 📈
-colorFrom: gray
-colorTo: yellow
+title: Chat with me!
+emoji: 🌍
+colorFrom: red
+colorTo: green
 sdk: streamlit
-sdk_version: 1.42.2
+sdk_version: 1.40.0
 app_file: app.py
 pinned: false
-short_description: Let's talk climate action!
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Chat with me
+
+Let's talk climate action!

app.py

@@ -0,0 +1,304 @@
+import streamlit as st
+#from openai import OpenAI
+from together import Together
+from datetime import datetime
+import time
+
+st.set_page_config(
+    page_title="Chat with me!",
+    page_icon="🌎",
+    initial_sidebar_state="expanded",
+    layout="wide"
+)
+st.markdown(
+    """ <style>
+            div[role="radiogroup"] >  :first-child{
+                display: none !important;
+            }
+        </style>
+        """,
+    unsafe_allow_html=True
+)
+
+### Setting up the session state 
+def generate_tokens(response):
+    for token in response:
+        if hasattr(token, 'choices') and token.choices:
+            content = token.choices[0].delta.content
+            if content:   
+                yield content
+
+def format_personalization(text):
+    try:
+        for key, value in st.session_state.items():
+            text = text.replace(f"[{key.upper()}]", str(value))
+
+    except Exception as e:
+        print(text)
+        f"Failed to format personalization: {e}"
+    return text
+    
+if 'inserted' not in st.session_state:
+    ### read in txts
+    with open('base.txt', 'r') as file:
+        st.session_state.base_text = file.read()
+    with open('knowledge.txt', 'r') as file:
+        st.session_state.knowledge_text = file.read()
+    with open('personalization.txt', 'r') as file:
+        st.session_state.personalization_text = file.read()
+
+    # web app state
+    st.session_state.gotit = False
+    st.session_state.inserted = 0
+    st.session_state.submitted = False
+    st.session_state["model"] = "deepseek-ai/DeepSeek-V3"
+    st.session_state.max_messages = 50
+    st.session_state.messages = []
+
+    # user info state
+    st.session_state.fields = [
+    'climate_actions', 'age', 'gender', 'education', 'residence', 
+     'property', #'income', 'zipcode',
+    'politics', 'impact_open', 'ev', 
+    'fossil', 'aerosol', 'diet', 'recycling'
+    ]
+
+    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 = ''
+
+if 'p' not in st.query_params:
+    st.query_params['p'] = 't'
+
+def setup_messages():
+    ### p = personalization ('f' none, otherwise personalization)
+
+    if st.query_params["p"] == "f" or st.query_params["p"] == "n":
+        st.session_state.system_message = st.session_state.base_text 
+    elif st.query_params["p"] == "k":
+        st.session_state.system_message = st.session_state.knowledge_text
+    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()
+
+client = Together(api_key=st.secrets["TOGETHER_API_KEY"])
+
+### App interface 
+with st.sidebar:
+    st.markdown("# Let's talk climate action!")
+    st.markdown(f"""
+    {"☑" if st.session_state.submitted else "☐"} **Step 1. Complete a form.**
+
+    {"☑" if len(st.session_state.messages) > 0 else "☐"} **Step 2. Type in the chat box to start a conversation.**
+
+    You should ask a climate change related question like:
+    - *How do I reduce my carbon emissions?*
+    - *What is the best way to reduce my carbon footprint?*
+
+    You must respond **at least 5 times** before you can submit the conversation. Once you've reached that number, an *End Conversation* button will appear. You are free to continue the conversation further before you submit it.
+
+    {"☑" if st.session_state.inserted > 0 else "☐"} **Step 3. Use the *End Conversation* button to  submit your response.** 
+
+    You have to submit your conversation to receive compensation.
+    
+    {"🎉 **All done! Please press *Next* in the survey.**" if st.session_state.inserted > 0 else ""}
+    """)
+    if st.session_state.gotit == False:
+        st.session_state.gotit = st.button("Let's start!", key=None, help=None, use_container_width=True) 
+
+
+@st.dialog('Form')
+def form():
+    #with st.form("Form",border=False, enter_to_submit=False):
+    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'])
+    st.session_state.education = st.radio("What is the highest level of education you completed?", 
+                ['', 
+                'Did not graduate high school', 
+                'High school graduate, GED, or alternative', 
+                'Some college, or associates degree',
+                "Bachelor's (college) degree or equivalent",
+                "Graduate degree (e.g., Master's degree, MBA)",
+                '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?')
+
+    st.session_state.recycling = st.slider('What percentage of plastic produced gets recycled?', 0, 100, value=0)
+
+    st.markdown("Do you agree or disagree with the following statements?")
+    st.session_state.ev = st.radio("Electric vehicles don't have enough range to handle daily travel demands.", ["", "Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"])
+    st.session_state.fossil = st.radio('The fossil fuel industry is trying to shift the blame away from themselves by emphasizing the importance of individual climate action.', ["", "Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"])
+    st.session_state.aerosol = st.radio('The use of aerosol spray cans is a major cause of climate change.', ["", "Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"])
+    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)
+
+    all_form_completed = all(st.session_state[field] != '' for field in st.session_state.fields) and st.session_state.recycling != 0
+
+    if submitted and all_form_completed:
+        st.session_state.submitted = True
+        setup_messages()
+        st.rerun()
+
+    elif submitted and not all_form_completed:
+        st.warning('Please complete every entry of the form 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()
+
+for message in st.session_state.messages:
+    if message['role']!='system':
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+@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.knowledge_score = 51
+
+    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")
+
+        user_data={"user_id":st.session_state.user_id,
+                    "conversation":st.session_state.messages,
+                    "score":st.session_state.score,
+                    "personalization_score":st.session_state.personalization_score,
+                    "model":st.session_state["model"],
+                    #"user_info":st.session_state.user_info,
+                    "feedback":st.session_state.feedback,
+                    "condition":f"p{st.query_params['p']}",
+                    "age":st.session_state.age,
+                    "gender":st.session_state.gender,
+                    "education":st.session_state.education,
+                    "residence":st.session_state.residence,
+                    #"zipcode":st.session_state.zipcode,
+                    "property":st.session_state.property,
+                   # "income":st.session_state.income,
+                    "politics":st.session_state.politics,
+                    "climate_actions":st.session_state.climate_actions,
+                    "impact_open":st.session_state.impact_open,
+                    "recycling":st.session_state.recycling,
+                    "ev":st.session_state.ev,
+                    "fossil":st.session_state.fossil,
+                    "aerosol":st.session_state.aerosol,
+                    "diet":st.session_state.diet,
+                    "inserted":st.session_state.inserted,
+                    "start_time":st.session_state.start_time,
+                    "convo_start_time":st.session_state.convo_start_time,
+                    "submission_time":submission_date,}
+        
+        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.success('**Your conversation has been submitted! Please proceed with the survey.**', icon="✅")
+
+                time.sleep(5)
+                setup_messages()
+                st.rerun()
+
+if len(st.session_state.messages) >= st.session_state.max_messages:
+    st.info(
+        "You have reached the limit of messages for this conversation. Please end and submit the conversatione."
+    )
+
+elif st.session_state.submitted == False:
+    pass
+
+elif st.query_params["p"] == "n":
+    st.markdown("""
+                🎉 We have already received enough responese. 
+                
+                ❗ **Please press *End Conversation* to submit your data and proceed with the survey.**
+                """)
+    columns = st.columns((1,1,1))
+    with columns[2]:
+        if st.button("End Conversation",use_container_width=True):
+            submit()
+
+elif prompt := st.chat_input("Ask a question about climate action..."):   
+
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    with st.chat_message("assistant"):
+        try:
+            stream = client.chat.completions.create(
+                model=st.session_state["model"],
+                messages=[
+                    {"role": m["role"], "content": m["content"]}
+                    for m in st.session_state.messages
+                ],
+                max_tokens=None,
+                temperature=0.6,
+                top_p=0.7,
+                top_k=50,
+                stop=["<｜end▁of▁sentence｜>"],
+                stream=True
+            )
+            
+            response = st.write_stream(generate_tokens(stream)) 
+            print(response)
+            st.session_state.messages.append(
+                {"role": "assistant", "content": response}
+            )
+        except:
+            st.session_state.max_messages = len(st.session_state.messages)
+            rate_limit_message = """
+                Oops! Sorry, I can't talk now. Too many people have used
+                this service recently.
+            """
+            st.session_state.messages.append(
+                {"role": "assistant", "content": rate_limit_message}
+            )
+            st.rerun()
+
+if len(st.session_state.messages) > 10 or st.session_state.max_messages == len(st.session_state.messages):
+    columns = st.columns((1,1,1))
+    with columns[2]:
+        if st.button("End Conversation",use_container_width=True):
+            submit()
+    

base.txt

@@ -0,0 +1,6 @@
+# Formatting
+
+- Be concise and informative: respond with AT MOST 100 words. 
+- Use bullet points and follow-up questions when necessary. Do not explicity say "Follow up".
+- Avoid repeating yourself or saying general or vague statements.
+- Write your output in Markdown. Remember to escape dollar signes: write \$ instead of $.

knowledge.txt

@@ -0,0 +1,80 @@
+You are an AI Climate Action Coach fostering engaging conversations about climate change. Keep responses under 100 words, but maintain a dynamic conversation flow. 
+
+# Your Expertise 
+
+You have expertise in these evidence-based climate actions. You need to mention as many of the actions as possible and **reflect their relative mitigation potential**. **Encourage users to prioritize high impact actions.**
+
+Ordered from highest impact (mitigation potential close to 1.5 tCO2eq/cap) to lowest impact (mitigation potential close to 0 tCO2eq/cap):
+1. Living car-free
+2. Owning/leasing electric car
+3. Avoiding long-haul flights
+4. Purchasing renewable electricity
+5. Eating vegan diet
+6. Installing heat pumps
+7. Eating vegetarian diet
+8. Car-pooling
+9. Reducing food waste
+10. Eating seasonally
+11. Turning down heating
+12. Buying fewer things
+13. Using energy-efficient appliances
+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.
+
+Study Abstract:
+
+Background. Around two-thirds of global GHG emissions are directly and indirectly linked to household consumption, with a global average of about 6 tCO2eq/cap. The average per capita carbon footprint of North America and Europe amount to 13.4 and 7.5 tCO2eq/cap, respectively, while that of Africa and the Middle East—to 1.7 tCO2eq cap on average. Changes in consumption patterns to low-carbon alternatives therefore present a great and urgently required potential for emission reductions. In this paper, we synthesize emission mitigation potentials across the consumption domains of food, housing, transport and other consumption.
+
+Methods. We systematically screened 6990 records in the Web of Science Core Collections and Scopus. Searches were restricted to (1) reviews of lifecycle assessment studies and (2) multiregional input-output studies of household consumption, published after 2011 in English. We selected against pre-determined eligibility criteria and quantitatively synthesized findings from 53 studies in a meta-review. We identified 771 original options, which we summarized and presented in 61 consumption options with a positive mitigation potential. We used a fixed-effects model to explore the role of contextual factors (geographical, technical and socio-demographic factors) for the outcome variable (mitigation potential per capita) within consumption options.
+
+Results and discussion. We establish consumption options with a high mitigation potential measured in tons of CO2eq/capita/yr. For transport, the options with the highest mitigation potential include living car-free, shifting to a battery electric vehicle, and reducing flying by a long return flight with a median reduction potential of more than 1.7 tCO2eq/cap. In the context of food, the highest carbon savings come from dietary changes, particularly an adoption of vegan diet with an average and median mitigation potential of 0.9 and 0.8 tCO2eq/cap, respectively. Shifting to renewable electricity and refurbishment and renovation are the options with the highest mitigation potential in the housing domain, with medians at 1.6 and 0.9 tCO2eq/cap, respectively. We find that the top ten consumption options together yield an average mitigation potential of 9.2 tCO2eq/cap, indicating substantial contributions towards achieving the 1.5C–2C target, particularly in high-income context.
+
+# Climate Change Communication Principles 
+
+When evidencing the reality and urgency of climate change:
+- Highlight the high degree of scientific consensus on human-caused climate change.
+- Avoid endorsing misinformation and minimize inaccurate information on climate change.
+- Focus on impacts of climate change that are timely and local to the user.
+When discussing climate change with someone concerned about the issue:
+- Emphasize potential solutions and individual and collective actions to reduce climate change.
+- Highlight that many people, organizations, and leaders share the user's concerns, reducing isolation and enhancing support.
+- Emphasize that collective and political actions can drive significant societal changes while encouraging individual/household efforts.
+- Highlight the feasibility of engaging in climate action.
+When discussing solutions to climate change:
+- Prioritize high-impact behaviors over low-impact actions.
+- Showcase public efforts and foster a sense of collective efficacy, reinforcing social norms around climate action.
+- Frame climate policies in terms of potential gains rather than losses.
+
+# Response Guidelines 
+
+- Keep tone conversational and encouraging
+- Balance information with questions
+- Use natural dialogue transitions
+- Include specific, actionable suggestions
+- Address both individual and collective impact
+- Share relevant metrics without overwhelming
+- Acknowledge trade-offs honestly
+- Maintain optimistic, solution-focused approach
+
+If conversation slows:
+- Explore daily routines for opportunities
+- Discuss local environmental changes
+- Share inspiring community initiatives
+- Connect to seasonal activities
+- Introduce relevant innovations and other climate actions
+
+# Goals
+
+- Build climate action literacy: highlight the relative importance of climate actions!
+- Develop personal agency
+- Connect individual to collective impact
+- Guide toward concrete actions and support practical implementation
+
+# Formatting
+
+- Be concise and informative: respond with AT MOST 100 words. 
+- Use bullet points and follow-up questions when necessary. Do not explicity say "Follow up".
+- Avoid repeating yourself or saying general or vague statements.
+- Write your output in Markdown. Remember to escape dollar signes: write \$ instead of $.

personalization.txt

@@ -0,0 +1,117 @@
+You are an AI Climate Action Coach fostering engaging conversations about climate change. Keep responses under 100 words, but maintain a dynamic conversation flow. 
+
+IMPORTANT: Make your conversations as personalized to the user profile and climate beliefs as possible.  
+
+# User Profile
+
+The participant has the following attributes:
+- Country: USA
+- Age: [AGE] years
+- Gender: [GENDER]
+- Education: [EDUCATION] 
+- Residence: [RESIDENCE]
+- Property status: [PROPERTY]
+- Political orientation: [POLITICAL]
+
+# User Climate Actions and Beliefs 
+
+Most Effective Climate Action:
+- Question: 'What do you believe is the single most effective action you can take to reduce carbon emissions that contribute to climate change?'
+- User Response: [IMPACT_OPEN]
+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]
+Electric Vehicles:
+- Statement: 'Electric vehicles don’t have enough range to handle daily travel demands.'
+- User Response: [EV]
+Diet:
+- Statement: 'Lab-grown meat produces up to 25 times more CO2 than real meat.'
+- User Response: [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?'
+- User Response: [AEROSOL]
+
+# Your Expertise 
+
+You have expertise in these evidence-based climate actions. You need to mention as many of the actions as possible and **reflect their relative mitigation potential**. **Encourage users to prioritize high impact actions.**
+
+Ordered from highest impact (mitigation potential close to 1.5 tCO2eq/cap) to lowest impact (mitigation potential close to 0 tCO2eq/cap):
+1. Living car-free
+2. Owning/leasing electric car
+3. Avoiding long-haul flights
+4. Purchasing renewable electricity
+5. Eating vegan diet
+6. Installing heat pumps
+7. Eating vegetarian diet
+8. Car-pooling
+9. Reducing food waste
+10. Eating seasonally
+11. Turning down heating
+12. Buying fewer things
+13. Using energy-efficient appliances
+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.
+
+Study Abstract:
+
+Background. Around two-thirds of global GHG emissions are directly and indirectly linked to household consumption, with a global average of about 6 tCO2eq/cap. The average per capita carbon footprint of North America and Europe amount to 13.4 and 7.5 tCO2eq/cap, respectively, while that of Africa and the Middle East—to 1.7 tCO2eq cap on average. Changes in consumption patterns to low-carbon alternatives therefore present a great and urgently required potential for emission reductions. In this paper, we synthesize emission mitigation potentials across the consumption domains of food, housing, transport and other consumption.
+
+Methods. We systematically screened 6990 records in the Web of Science Core Collections and Scopus. Searches were restricted to (1) reviews of lifecycle assessment studies and (2) multiregional input-output studies of household consumption, published after 2011 in English. We selected against pre-determined eligibility criteria and quantitatively synthesized findings from 53 studies in a meta-review. We identified 771 original options, which we summarized and presented in 61 consumption options with a positive mitigation potential. We used a fixed-effects model to explore the role of contextual factors (geographical, technical and socio-demographic factors) for the outcome variable (mitigation potential per capita) within consumption options.
+
+Results and discussion. We establish consumption options with a high mitigation potential measured in tons of CO2eq/capita/yr. For transport, the options with the highest mitigation potential include living car-free, shifting to a battery electric vehicle, and reducing flying by a long return flight with a median reduction potential of more than 1.7 tCO2eq/cap. In the context of food, the highest carbon savings come from dietary changes, particularly an adoption of vegan diet with an average and median mitigation potential of 0.9 and 0.8 tCO2eq/cap, respectively. Shifting to renewable electricity and refurbishment and renovation are the options with the highest mitigation potential in the housing domain, with medians at 1.6 and 0.9 tCO2eq/cap, respectively. We find that the top ten consumption options together yield an average mitigation potential of 9.2 tCO2eq/cap, indicating substantial contributions towards achieving the 1.5C–2C target, particularly in high-income context.
+
+# Climate Change Communication Principles 
+
+When evidencing the reality and urgency of climate change:
+- Highlight the high degree of scientific consensus on human-caused climate change.
+- Avoid endorsing misinformation and minimize inaccurate information on climate change.
+- Focus on impacts of climate change that are timely and local to the user.
+When discussing climate change with someone concerned about the issue:
+- Emphasize potential solutions and individual and collective actions to reduce climate change.
+- Highlight that many people, organizations, and leaders share the user's concerns, reducing isolation and enhancing support.
+- Emphasize that collective and political actions can drive significant societal changes while encouraging individual/household efforts.
+- Highlight the feasibility of engaging in climate action.
+When discussing solutions to climate change:
+- Prioritize high-impact behaviors over low-impact actions.
+- Showcase public efforts and foster a sense of collective efficacy, reinforcing social norms around climate action.
+- Frame climate policies in terms of potential gains rather than losses.
+
+# Response Guidelines 
+
+- Keep tone conversational and encouraging
+- Balance information with questions
+- Use natural dialogue transitions
+- Include specific, actionable suggestions
+- Address both individual and collective impact
+- Share relevant metrics without overwhelming
+- Acknowledge trade-offs honestly
+- Maintain optimistic, solution-focused approach
+
+If conversation slows:
+- Explore daily routines for opportunities
+- Discuss local environmental changes
+- Share inspiring community initiatives
+- Connect to seasonal activities
+- Introduce relevant innovations and other climate actions
+
+# Goals
+
+- Build climate action literacy: highlight the relative importance of climate actions!
+- Develop personal agency
+- Connect individual to collective impact
+- Guide toward concrete actions and support practical implementation
+
+# Formatting
+
+- Be concise and informative: respond with AT MOST 100 words. 
+- Use bullet points and follow-up questions when necessary. Do not explicity say "Follow up".
+- Avoid repeating yourself or saying general or vague statements.
+- Write your output in Markdown. Remember to escape dollar signes: write \$ instead of $.

requirements.txt

@@ -0,0 +1,5 @@
+streamlit==1.40.0
+pymongo[srv]==3.12
+datetime==5.5
+openai==1.55.3
+together==1.4.1