changed it to mental health crisis agent
This commit is contained in:
Madhu
parent
1062536f4a
commit
e07ab78a35
1 changed files with 165 additions and 116 deletions
|
|
@ -18,10 +18,10 @@ os.environ["AUTOGEN_USE_DOCKER"] = "0"
|
|||
# Initialize session state
|
||||
if 'output' not in st.session_state:
|
||||
st.session_state.output = {
|
||||
'climate': '',
|
||||
'urban': '',
|
||||
'economic': '',
|
||||
'community': ''
|
||||
'psychology': '',
|
||||
'resources': '',
|
||||
'action': '',
|
||||
'followup': ''
|
||||
}
|
||||
|
||||
# Sidebar for API key input
|
||||
|
|
@ -32,28 +32,63 @@ st.sidebar.title("AgentOps API Key")
|
|||
agentops_key = st.sidebar.text_input("Enter your AgentOps API Key", type="password", value="4e725ba8-b57e-49b5-809a-4eeef18d92ed")
|
||||
|
||||
# Main app UI
|
||||
st.title("🌍 Climate Impact Response Planner")
|
||||
st.title("🧠 Mental Health Crisis Navigator")
|
||||
|
||||
# Add agent information below title
|
||||
st.info("""
|
||||
**Meet Your Climate Planning Team:**
|
||||
**Meet Your Mental Health Support Team:**
|
||||
|
||||
🌡️ **Climate Analysis Agent** - Analyzes climate data and risk projections
|
||||
🏙️ **Urban Planning Agent** - Develops infrastructure and zoning strategies
|
||||
💰 **Economic Impact Agent** - Assesses financial implications
|
||||
👥 **Community Engagement Agent** - Plans public involvement and behavior change
|
||||
🧠 **Psychology Agent** - Analyzes emotional state and psychological needs
|
||||
📋 **Resource Agent** - Identifies relevant support services and professionals
|
||||
🎯 **Action Agent** - Creates immediate step-by-step action plans
|
||||
🔄 **Follow-up Agent** - Designs ongoing support and prevention strategies
|
||||
""")
|
||||
|
||||
# User input
|
||||
st.subheader("City Information")
|
||||
city_name = st.text_input("Enter City Name", "")
|
||||
city_description = st.text_area("Brief description of the city (population, geography, main industries, etc.)", "")
|
||||
# User inputs
|
||||
st.subheader("Personal Information")
|
||||
col1, col2 = st.columns(2)
|
||||
|
||||
with col1:
|
||||
mental_state = st.text_area("How have you been feeling recently?",
|
||||
placeholder="Describe your emotional state, thoughts, or concerns...")
|
||||
sleep_pattern = st.select_slider(
|
||||
"Sleep Pattern (hours per night)",
|
||||
options=[f"{i}" for i in range(0, 13)],
|
||||
value="7"
|
||||
)
|
||||
|
||||
with col2:
|
||||
stress_level = st.slider("Current Stress Level (1-10)", 1, 10, 5)
|
||||
support_system = st.multiselect(
|
||||
"Current Support System",
|
||||
["Family", "Friends", "Therapist", "Support Groups", "None"]
|
||||
)
|
||||
|
||||
# Additional context
|
||||
recent_changes = st.text_area(
|
||||
"Any significant life changes or events recently?",
|
||||
placeholder="Job changes, relationships, losses, etc..."
|
||||
)
|
||||
|
||||
current_symptoms = st.multiselect(
|
||||
"Current Symptoms",
|
||||
["Anxiety", "Depression", "Insomnia", "Fatigue", "Loss of Interest",
|
||||
"Difficulty Concentrating", "Changes in Appetite", "Social Withdrawal",
|
||||
"Mood Swings", "Physical Discomfort"]
|
||||
)
|
||||
|
||||
# Emergency notice
|
||||
st.warning("""
|
||||
⚠️ **Important**: If you're having thoughts of self-harm or experiencing a severe crisis,
|
||||
please immediately contact emergency services or crisis hotlines:
|
||||
- National Crisis Hotline: 988
|
||||
- Emergency: 911
|
||||
""")
|
||||
|
||||
@contextmanager
|
||||
def agentops_session(api_key: str, tags: list):
|
||||
"""Context manager for AgentOps sessions"""
|
||||
try:
|
||||
# Initialize new session
|
||||
agentops.init(
|
||||
api_key=api_key,
|
||||
tags=tags,
|
||||
|
|
@ -62,28 +97,84 @@ def agentops_session(api_key: str, tags: list):
|
|||
)
|
||||
yield
|
||||
finally:
|
||||
# Always ensure session is ended
|
||||
try:
|
||||
agentops.end_session("Success")
|
||||
except Exception as e:
|
||||
print(f"Failed to end AgentOps session: {e}")
|
||||
|
||||
# Button to start the agent collaboration
|
||||
if st.button("Generate Climate Response Plan"):
|
||||
if st.button("Get Support Plan"):
|
||||
if not api_key:
|
||||
st.error("Please enter your OpenAI API key.")
|
||||
else:
|
||||
with st.spinner('🤖 AI Agents are collaborating on your climate response plan...'):
|
||||
with agentops_session(api_key=agentops_key, tags=["aqi_agent"]):
|
||||
with st.spinner('🤖 AI Agents are analyzing your situation...'):
|
||||
with agentops_session(api_key=agentops_key, tags=["mental_health_navigator"]):
|
||||
try:
|
||||
task = f"""
|
||||
Create a comprehensive climate impact response plan for:
|
||||
City: {city_name}
|
||||
Description: {city_description}
|
||||
Create a comprehensive mental health support plan based on:
|
||||
|
||||
Consider all aspects of climate adaptation including environmental, infrastructural, economic, and social factors.
|
||||
Emotional State: {mental_state}
|
||||
Sleep: {sleep_pattern} hours per night
|
||||
Stress Level: {stress_level}/10
|
||||
Support System: {', '.join(support_system) if support_system else 'None reported'}
|
||||
Recent Changes: {recent_changes}
|
||||
Current Symptoms: {', '.join(current_symptoms) if current_symptoms else 'None reported'}
|
||||
"""
|
||||
|
||||
system_messages = {
|
||||
"psychology_agent": """
|
||||
You are an experienced mental health professional speaking directly to the user. Your task is to:
|
||||
1. Analyze their emotional state and psychological symptoms with empathy
|
||||
2. Help them understand potential mental health concerns
|
||||
3. Assess their risk levels and urgency
|
||||
4. Suggest therapeutic approaches that would work for them
|
||||
5. Help them understand how their life changes and stressors are affecting them
|
||||
6. Provide supportive psychological insights
|
||||
|
||||
Always use "you" and "your" when addressing the user. Maintain a warm, supportive, and non-judgmental tone.
|
||||
Example: "Based on what you've shared about your sleep patterns..." instead of "The individual's sleep patterns..."
|
||||
""",
|
||||
|
||||
"resource_agent": """
|
||||
You are a mental health resource coordinator speaking directly to the user. Your task is to:
|
||||
1. Connect you with appropriate mental health services
|
||||
2. Suggest support groups or communities that would benefit you
|
||||
3. Recommend professional care options for your situation
|
||||
4. Provide crisis resources when needed
|
||||
5. Consider what resources would be most accessible for you
|
||||
6. Share specific contact information for your local resources
|
||||
|
||||
Always address the user directly using "you" and "your". Focus on practical, accessible resources.
|
||||
Example: "Given your current situation, these resources might help..." instead of "The following resources are recommended..."
|
||||
""",
|
||||
|
||||
"action_agent": """
|
||||
You are a crisis intervention specialist speaking directly to the user. Your task is to:
|
||||
1. Help you develop immediate coping strategies
|
||||
2. Work with you to create a daily wellness routine
|
||||
3. Teach you stress management techniques
|
||||
4. Guide you in improving your sleep habits
|
||||
5. Help you make healthy lifestyle adjustments
|
||||
6. Create an emergency response plan with you if needed
|
||||
|
||||
Use "you" and "your" when providing guidance. Give clear, actionable steps.
|
||||
Example: "Here are steps you can take right now..." instead of "The following steps are recommended..."
|
||||
""",
|
||||
|
||||
"followup_agent": """
|
||||
You are a mental health recovery planner speaking directly to the user. Your task is to:
|
||||
1. Help you develop long-term support strategies
|
||||
2. Create a progress monitoring plan that works for you
|
||||
3. Work with you on relapse prevention strategies
|
||||
4. Plan how to engage your support system
|
||||
5. Guide you through lifestyle modifications
|
||||
6. Set up maintenance and check-in schedules with you
|
||||
|
||||
Always use "you" and "your" in your recommendations. Focus on sustainable, long-term solutions.
|
||||
Example: "To maintain your progress, you might want to..." instead of "The following maintenance plan is suggested..."
|
||||
"""
|
||||
}
|
||||
|
||||
# Then modify the agent configurations
|
||||
llm_config = {
|
||||
"config_list": [{"model": "gpt-4o", "api_key": api_key}]
|
||||
|
|
@ -91,78 +182,36 @@ if st.button("Generate Climate Response Plan"):
|
|||
|
||||
# Context management for agent communication
|
||||
context_variables = {
|
||||
"climate": None,
|
||||
"urban": None,
|
||||
"economic": None,
|
||||
"community": None,
|
||||
"psychology": None,
|
||||
"resources": None,
|
||||
"action": None,
|
||||
"followup": None,
|
||||
}
|
||||
|
||||
# Update functions for each agent
|
||||
def update_climate_overview(climate_summary: str, context_variables: dict) -> SwarmResult:
|
||||
def update_psychology_overview(psychology_summary: str, context_variables: dict) -> SwarmResult:
|
||||
"""Keep the summary as short as possible."""
|
||||
context_variables["climate"] = climate_summary
|
||||
st.sidebar.success('Climate Analysis: ' + climate_summary)
|
||||
return SwarmResult(agent="urban_agent", context_variables=context_variables)
|
||||
context_variables["psychology"] = psychology_summary
|
||||
st.sidebar.success('Psychology Analysis: ' + psychology_summary)
|
||||
return SwarmResult(agent="resource_agent", context_variables=context_variables)
|
||||
|
||||
def update_urban_overview(urban_summary: str, context_variables: dict) -> SwarmResult:
|
||||
def update_resource_overview(resource_summary: str, context_variables: dict) -> SwarmResult:
|
||||
"""Keep the summary as short as possible."""
|
||||
context_variables["urban"] = urban_summary
|
||||
st.sidebar.success('Urban Planning: ' + urban_summary)
|
||||
return SwarmResult(agent="economic_agent", context_variables=context_variables)
|
||||
context_variables["resources"] = resource_summary
|
||||
st.sidebar.success('Resource Identification: ' + resource_summary)
|
||||
return SwarmResult(agent="action_agent", context_variables=context_variables)
|
||||
|
||||
def update_economic_overview(economic_summary: str, context_variables: dict) -> SwarmResult:
|
||||
def update_action_overview(action_summary: str, context_variables: dict) -> SwarmResult:
|
||||
"""Keep the summary as short as possible."""
|
||||
context_variables["economic"] = economic_summary
|
||||
st.sidebar.success('Economic Impact: ' + economic_summary)
|
||||
return SwarmResult(agent="community_agent", context_variables=context_variables)
|
||||
context_variables["action"] = action_summary
|
||||
st.sidebar.success('Action Plan: ' + action_summary)
|
||||
return SwarmResult(agent="followup_agent", context_variables=context_variables)
|
||||
|
||||
def update_community_overview(community_summary: str, context_variables: dict) -> SwarmResult:
|
||||
def update_followup_overview(followup_summary: str, context_variables: dict) -> SwarmResult:
|
||||
"""Keep the summary as short as possible."""
|
||||
context_variables["community"] = community_summary
|
||||
st.sidebar.success('Community Engagement: ' + community_summary)
|
||||
return SwarmResult(agent="climate_agent", context_variables=context_variables)
|
||||
|
||||
system_messages = {
|
||||
"climate_agent": """
|
||||
You are an expert climate scientist and risk analyst. Your task is to:
|
||||
1. Analyze historical climate data and future projections for the specified city
|
||||
2. Identify key climate risks (flooding, heat waves, storms, etc.)
|
||||
3. Assess vulnerability of different city areas and systems
|
||||
4. Prioritize climate threats based on likelihood and impact
|
||||
5. Recommend key areas for climate resilience focus
|
||||
6. Provide specific climate scenarios the city should prepare for
|
||||
""",
|
||||
|
||||
"urban_agent": """
|
||||
You are an experienced urban planner specializing in climate adaptation. Your task is to:
|
||||
1. Design infrastructure modifications for climate resilience
|
||||
2. Develop zoning recommendations for risk reduction
|
||||
3. Plan green infrastructure and nature-based solutions
|
||||
4. Identify critical infrastructure vulnerabilities
|
||||
5. Create phased implementation strategies
|
||||
6. Consider both immediate and long-term adaptation needs
|
||||
""",
|
||||
|
||||
"economic_agent": """
|
||||
You are a climate economics and finance specialist. Your task is to:
|
||||
1. Calculate potential economic impacts of climate risks
|
||||
2. Identify funding sources for adaptation projects
|
||||
3. Analyze cost-benefit ratios of proposed solutions
|
||||
4. Assess impacts on local industries and businesses
|
||||
5. Develop economic incentives for climate adaptation
|
||||
6. Create budget allocation recommendations
|
||||
""",
|
||||
|
||||
"community_agent": """
|
||||
You are a community engagement and behavior change expert. Your task is to:
|
||||
1. Design public communication strategies
|
||||
2. Plan community involvement in adaptation efforts
|
||||
3. Develop education and awareness programs
|
||||
4. Create behavior change initiatives
|
||||
5. Plan vulnerable population support systems
|
||||
6. Design feedback and monitoring systems
|
||||
"""
|
||||
}
|
||||
context_variables["followup"] = followup_summary
|
||||
st.sidebar.success('Follow-up Strategy: ' + followup_summary)
|
||||
return SwarmResult(agent="psychology_agent", context_variables=context_variables)
|
||||
|
||||
def update_system_message_func(agent: SwarmAgent, messages) -> str:
|
||||
""""""
|
||||
|
|
@ -196,42 +245,42 @@ if st.button("Generate Climate Response Plan"):
|
|||
state_update = UPDATE_SYSTEM_MESSAGE(update_system_message_func)
|
||||
|
||||
# Define agents with proper code execution config
|
||||
climate_agent = SwarmAgent(
|
||||
"climate_agent",
|
||||
psychology_agent = SwarmAgent(
|
||||
"psychology_agent",
|
||||
llm_config=llm_config,
|
||||
functions=update_climate_overview,
|
||||
functions=update_psychology_overview,
|
||||
update_agent_state_before_reply=[state_update]
|
||||
)
|
||||
|
||||
urban_agent = SwarmAgent(
|
||||
"urban_agent",
|
||||
resource_agent = SwarmAgent(
|
||||
"resource_agent",
|
||||
llm_config=llm_config,
|
||||
functions=update_urban_overview,
|
||||
functions=update_resource_overview,
|
||||
update_agent_state_before_reply=[state_update]
|
||||
)
|
||||
|
||||
economic_agent = SwarmAgent(
|
||||
"economic_agent",
|
||||
action_agent = SwarmAgent(
|
||||
"action_agent",
|
||||
llm_config=llm_config,
|
||||
functions=update_economic_overview,
|
||||
functions=update_action_overview,
|
||||
update_agent_state_before_reply=[state_update]
|
||||
)
|
||||
|
||||
community_agent = SwarmAgent(
|
||||
name="community_agent",
|
||||
followup_agent = SwarmAgent(
|
||||
name="followup_agent",
|
||||
llm_config=llm_config,
|
||||
functions=update_community_overview,
|
||||
functions=update_followup_overview,
|
||||
update_agent_state_before_reply=[state_update]
|
||||
)
|
||||
|
||||
climate_agent.register_hand_off(AFTER_WORK(urban_agent))
|
||||
urban_agent.register_hand_off(AFTER_WORK(economic_agent))
|
||||
economic_agent.register_hand_off(AFTER_WORK(community_agent))
|
||||
community_agent.register_hand_off(AFTER_WORK(climate_agent))
|
||||
psychology_agent.register_hand_off(AFTER_WORK(resource_agent))
|
||||
resource_agent.register_hand_off(AFTER_WORK(action_agent))
|
||||
action_agent.register_hand_off(AFTER_WORK(followup_agent))
|
||||
followup_agent.register_hand_off(AFTER_WORK(psychology_agent))
|
||||
|
||||
result, _, _ = initiate_swarm_chat(
|
||||
initial_agent=climate_agent,
|
||||
agents=[climate_agent, urban_agent, economic_agent, community_agent],
|
||||
initial_agent=psychology_agent,
|
||||
agents=[psychology_agent, resource_agent, action_agent, followup_agent],
|
||||
user_agent=None,
|
||||
messages=task,
|
||||
max_rounds=13,
|
||||
|
|
@ -239,27 +288,27 @@ if st.button("Generate Climate Response Plan"):
|
|||
|
||||
# Update session state with the individual responses
|
||||
st.session_state.output = {
|
||||
'climate': result.chat_history[-4]['content'],
|
||||
'urban': result.chat_history[-3]['content'],
|
||||
'economic': result.chat_history[-2]['content'],
|
||||
'community': result.chat_history[-1]['content']
|
||||
'psychology': result.chat_history[-4]['content'],
|
||||
'resources': result.chat_history[-3]['content'],
|
||||
'action': result.chat_history[-2]['content'],
|
||||
'followup': result.chat_history[-1]['content']
|
||||
}
|
||||
|
||||
# Display success message after completion
|
||||
st.success('✨ Climate response plan generated successfully!')
|
||||
st.success('✨ Mental health support plan generated successfully!')
|
||||
|
||||
# Display the individual outputs in expanders
|
||||
with st.expander("Climate Analysis"):
|
||||
st.markdown(st.session_state.output['climate'])
|
||||
with st.expander("Psychology Analysis"):
|
||||
st.markdown(st.session_state.output['psychology'])
|
||||
|
||||
with st.expander("Urban Planning"):
|
||||
st.markdown(st.session_state.output['urban'])
|
||||
with st.expander("Resource Identification"):
|
||||
st.markdown(st.session_state.output['resources'])
|
||||
|
||||
with st.expander("Economic Impact"):
|
||||
st.markdown(st.session_state.output['economic'])
|
||||
with st.expander("Action Plan"):
|
||||
st.markdown(st.session_state.output['action'])
|
||||
|
||||
with st.expander("Community Engagement"):
|
||||
st.markdown(st.session_state.output['community'])
|
||||
with st.expander("Follow-up Strategy"):
|
||||
st.markdown(st.session_state.output['followup'])
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"An error occurred: {str(e)}")
|
||||
|
|
|
|||
Loading…
Reference in a new issue