added streamlit version along with gradio version too

ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_streamlit.py

@@ -0,0 +1,265 @@
+from typing import Dict, Optional
+from dataclasses import dataclass
+from pydantic import BaseModel, Field
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from firecrawl import FirecrawlApp
+import streamlit as st
+
+class AQIResponse(BaseModel):
+    success: bool
+    data: Dict[str, float]
+    status: str
+    expiresAt: str
+
+class ExtractSchema(BaseModel):
+    aqi: float = Field(description="Air Quality Index")
+    temperature: float = Field(description="Temperature in degrees Celsius")
+    humidity: float = Field(description="Humidity percentage")
+    wind_speed: float = Field(description="Wind speed in kilometers per hour")
+    pm25: float = Field(description="Particulate Matter 2.5 micrometers")
+    pm10: float = Field(description="Particulate Matter 10 micrometers")
+    co: float = Field(description="Carbon Monoxide level")
+
+@dataclass
+class UserInput:
+    city: str
+    state: str
+    country: str
+    medical_conditions: Optional[str]
+    planned_activity: str
+
+class AQIAnalyzer:
+    
+    def __init__(self, firecrawl_key: str) -> None:
+        self.firecrawl = FirecrawlApp(api_key=firecrawl_key)
+    
+    def _format_url(self, country: str, state: str, city: str) -> str:
+        """Format URL based on location, handling cases with and without state"""
+        country_clean = country.lower().replace(' ', '-')
+        city_clean = city.lower().replace(' ', '-')
+        
+        if not state or state.lower() == 'none':
+            return f"https://www.aqi.in/dashboard/{country_clean}/{city_clean}"
+        
+        state_clean = state.lower().replace(' ', '-')
+        return f"https://www.aqi.in/dashboard/{country_clean}/{state_clean}/{city_clean}"
+    
+    def fetch_aqi_data(self, city: str, state: str, country: str) -> Dict[str, float]:
+        """Fetch AQI data using Firecrawl"""
+        try:
+            url = self._format_url(country, state, city)
+            st.info(f"Accessing URL: {url}")  # Display URL being accessed
+            
+            response = self.firecrawl.extract(
+                urls=[f"{url}/*"],
+                params={
+                    'prompt': 'Extract the current real-time AQI, temperature, humidity, wind speed, PM2.5, PM10, and CO levels from the page. Also extract the timestamp of the data.',
+                    'schema': ExtractSchema.model_json_schema()
+                }
+            )
+            
+            aqi_response = AQIResponse(**response)
+            if not aqi_response.success:
+                raise ValueError(f"Failed to fetch AQI data: {aqi_response.status}")
+            
+            with st.expander("📦 Raw AQI Data", expanded=True):
+                st.json({
+                    "url_accessed": url,
+                    "timestamp": aqi_response.expiresAt,
+                    "data": aqi_response.data
+                })
+                
+                st.warning("""
+                    ⚠️ Note: The data shown may not match real-time values on the website. 
+                    This could be due to:
+                    - Cached data in Firecrawl
+                    - Rate limiting
+                    - Website updates not being captured
+                    
+                    Consider refreshing or checking the website directly for real-time values.
+                """)
+                
+            return aqi_response.data
+            
+        except Exception as e:
+            st.error(f"Error fetching AQI data: {str(e)}")
+            return {
+                'aqi': 0,
+                'temperature': 0,
+                'humidity': 0,
+                'wind_speed': 0,
+                'pm25': 0,
+                'pm10': 0,
+                'co': 0
+            }
+
+class HealthRecommendationAgent:
+    
+    def __init__(self, openai_key: str) -> None:
+        self.agent = Agent(
+            model=OpenAIChat(
+                id="gpt-4o",
+                name="Health Recommendation Agent",
+                api_key=openai_key
+            )
+        )
+    
+    def get_recommendations(
+        self,
+        aqi_data: Dict[str, float],
+        user_input: UserInput
+    ) -> str:
+        prompt = self._create_prompt(aqi_data, user_input)
+        response = self.agent.run(prompt)
+        return response.content
+    
+    def _create_prompt(self, aqi_data: Dict[str, float], user_input: UserInput) -> str:
+        return f"""
+        Based on the following air quality conditions in {user_input.city}, {user_input.state}, {user_input.country}:
+        - Overall AQI: {aqi_data['aqi']}
+        - PM2.5 Level: {aqi_data['pm25']} µg/m³
+        - PM10 Level: {aqi_data['pm10']} µg/m³
+        - CO Level: {aqi_data['co']} ppb
+        
+        Weather conditions:
+        - Temperature: {aqi_data['temperature']}°C
+        - Humidity: {aqi_data['humidity']}%
+        - Wind Speed: {aqi_data['wind_speed']} km/h
+        
+        User's Context:
+        - Medical Conditions: {user_input.medical_conditions or 'None'}
+        - Planned Activity: {user_input.planned_activity}
+        **Comprehensive Health Recommendations:**
+        1. **Impact of Current Air Quality on Health:**
+        2. **Necessary Safety Precautions for Planned Activity:**
+        3. **Advisability of Planned Activity:**
+        4. **Best Time to Conduct the Activity:**
+        """
+
+def analyze_conditions(
+    user_input: UserInput,
+    api_keys: Dict[str, str]
+) -> str:
+    aqi_analyzer = AQIAnalyzer(firecrawl_key=api_keys['firecrawl'])
+    health_agent = HealthRecommendationAgent(openai_key=api_keys['openai'])
+    
+    aqi_data = aqi_analyzer.fetch_aqi_data(
+        city=user_input.city,
+        state=user_input.state,
+        country=user_input.country
+    )
+    
+    return health_agent.get_recommendations(aqi_data, user_input)
+
+def initialize_session_state():
+    if 'api_keys' not in st.session_state:
+        st.session_state.api_keys = {
+            'firecrawl': '',
+            'openai': ''
+        }
+
+def setup_page():
+    st.set_page_config(
+        page_title="AQI Analysis Agent",
+        page_icon="🌍",
+        layout="wide"
+    )
+    
+    st.title("🌍 AQI Analysis Agent")
+    st.info("Get personalized health recommendations based on air quality conditions.")
+
+def render_sidebar():
+    """Render sidebar with API configuration"""
+    with st.sidebar:
+        st.header("🔑 API Configuration")
+        
+        new_firecrawl_key = st.text_input(
+            "Firecrawl API Key",
+            type="password",
+            value=st.session_state.api_keys['firecrawl'],
+            help="Enter your Firecrawl API key"
+        )
+        new_openai_key = st.text_input(
+            "OpenAI API Key",
+            type="password",
+            value=st.session_state.api_keys['openai'],
+            help="Enter your OpenAI API key"
+        )
+        
+        if (new_firecrawl_key and new_openai_key and
+            (new_firecrawl_key != st.session_state.api_keys['firecrawl'] or 
+             new_openai_key != st.session_state.api_keys['openai'])):
+            st.session_state.api_keys.update({
+                'firecrawl': new_firecrawl_key,
+                'openai': new_openai_key
+            })
+            st.success("✅ API keys updated!")
+
+def render_main_content():
+    st.header("📍 Location Details")
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        city = st.text_input("City", placeholder="e.g., Mumbai")
+        state = st.text_input("State", placeholder="If it's a Union Territory or a city in the US, leave it blank")
+        country = st.text_input("Country", value="India", placeholder="United States")
+    
+    with col2:
+        st.header("👤 Personal Details")
+        medical_conditions = st.text_area(
+            "Medical Conditions (optional)",
+            placeholder="e.g., asthma, allergies"
+        )
+        planned_activity = st.text_area(
+            "Planned Activity",
+            placeholder="e.g., morning jog for 2 hours"
+        )
+    
+    return UserInput(
+        city=city,
+        state=state,
+        country=country,
+        medical_conditions=medical_conditions,
+        planned_activity=planned_activity
+    )
+
+def main():
+    """Main application entry point"""
+    initialize_session_state()
+    setup_page()
+    render_sidebar()
+    user_input = render_main_content()
+    
+    result = None
+    
+    if st.button("🔍 Analyze & Get Recommendations"):
+        if not all([user_input.city, user_input.planned_activity]):
+            st.error("Please fill in all required fields (state and medical conditions are optional)")
+        elif not all(st.session_state.api_keys.values()):
+            st.error("Please provide both API keys in the sidebar")
+        else:
+            try:
+                with st.spinner("🔄 Analyzing conditions..."):
+                    result = analyze_conditions(
+                        user_input=user_input,
+                        api_keys=st.session_state.api_keys
+                    )
+                    st.success("✅ Analysis completed!")
+            
+            except Exception as e:
+                st.error(f"❌ Error: {str(e)}")
+
+    if result:
+        st.markdown("### 📦 Recommendations")
+        st.markdown(result)
+        
+        st.download_button(
+            "💾 Download Recommendations",
+            data=result,
+            file_name=f"aqi_recommendations_{user_input.city}_{user_input.state}.txt",
+            mime="text/plain"
+        )
+
+if __name__ == "__main__":
+    main()