diff --git a/ai_agent_tutorials/ai_aqi_analysis_agent/README.md b/ai_agent_tutorials/ai_aqi_analysis_agent/README.md
new file mode 100644
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+++ b/ai_agent_tutorials/ai_aqi_analysis_agent/README.md
@@ -0,0 +1,81 @@
+# 🌍 AQI Analysis Agent
+
+The AQI Analysis Agent is a powerful air quality monitoring and health recommendation tool powered by Firecrawl and Agno's AI Agent framework. This app helps users make informed decisions about outdoor activities by analyzing real-time air quality data and providing personalized health recommendations.
+
+## Features
+
+- **Multi-Agent System**
+    - **AQI Analyzer**: Fetches and processes real-time air quality data
+    - **Health Recommendation Agent**: Generates personalized health advice
+
+- **Air Quality Metrics**:
+  - Overall Air Quality Index (AQI)
+  - Particulate Matter (PM2.5 and PM10)
+  - Carbon Monoxide (CO) levels
+  - Temperature
+  - Humidity
+  - Wind Speed
+
+- **Comprehensive Analysis**:
+  - Real-time data visualization
+  - Health impact assessment
+  - Activity safety recommendations
+  - Best time suggestions for outdoor activities
+  - Weather condition correlations
+
+- **Interactive Features**:
+  - Location-based analysis
+  - Medical condition considerations
+  - Activity-specific recommendations
+  - Downloadable reports
+  - Example queries for quick testing
+
+## How to Run
+
+Follow these steps to set up and run the application:
+
+1. **Clone the Repository**:
+   ```bash
+   git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+   cd ai_agent_tutorials/ai_aqi_analysis_agent
+   ```
+
+2. **Install the dependencies**:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3. **Set up your API keys**:
+    - Get an OpenAI API key from: https://platform.openai.com/api-keys
+    - Get a Firecrawl API key from: [Firecrawl website](https://www.firecrawl.dev/app/api-keys)
+
+4. **Run the Gradio app**:
+    ```bash
+    python ai_aqi_analysis_agent.py
+    ```
+
+5. **Access the Web Interface**:
+    - The terminal will display two URLs:
+      - Local URL: `http://127.0.0.1:7860` (for local access)
+      - Public URL: `https://xxx-xxx-xxx.gradio.live` (for temporary public access)
+    - Click on either URL to open the web interface in your browser
+
+## Usage
+
+1. Enter your API keys in the API Configuration section
+2. Input location details:
+   - City name
+   - State (optional for Union Territories/US cities)
+   - Country
+3. Provide personal information:
+   - Medical conditions (optional)
+   - Planned outdoor activity
+4. Click "Analyze & Get Recommendations" to receive:
+   - Current air quality data
+   - Health impact analysis
+   - Activity safety recommendations
+5. Try the example queries for quick testing
+
+## Note
+
+The air quality data is fetched using Firecrawl's web scraping capabilities. Due to caching and rate limiting, the data might not always match real-time values on the website. For the most accurate real-time data, consider checking the source website directly.
diff --git a/ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_gradio.py b/ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_gradio.py
new file mode 100644
index 0000000..609d027
--- /dev/null
+++ b/ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_gradio.py
@@ -0,0 +1,272 @@
+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 gradio as gr
+import json
+
+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) -> tuple[Dict[str, float], str]:
+        """Fetch AQI data using Firecrawl"""
+        try:
+            url = self._format_url(country, state, city)
+            info_msg = f"Accessing URL: {url}"
+            
+            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}")
+            
+            return aqi_response.data, info_msg
+            
+        except Exception as e:
+            error_msg = f"Error fetching AQI data: {str(e)}"
+            return {
+                'aqi': 0,
+                'temperature': 0,
+                'humidity': 0,
+                'wind_speed': 0,
+                'pm25': 0,
+                'pm10': 0,
+                'co': 0
+            }, error_msg
+
+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(
+    city: str,
+    state: str,
+    country: str,
+    medical_conditions: str,
+    planned_activity: str,
+    firecrawl_key: str,
+    openai_key: str
+) -> tuple[str, str, str, str]:
+    """Analyze conditions and return AQI data, recommendations, and status messages"""
+    try:
+        # Initialize analyzers
+        aqi_analyzer = AQIAnalyzer(firecrawl_key=firecrawl_key)
+        health_agent = HealthRecommendationAgent(openai_key=openai_key)
+        
+        # Create user input
+        user_input = UserInput(
+            city=city,
+            state=state,
+            country=country,
+            medical_conditions=medical_conditions,
+            planned_activity=planned_activity
+        )
+        
+        # Get AQI data
+        aqi_data, info_msg = aqi_analyzer.fetch_aqi_data(
+            city=user_input.city,
+            state=user_input.state,
+            country=user_input.country
+        )
+        
+        # Format AQI data for display
+        aqi_json = json.dumps({
+            "Air Quality Index (AQI)": aqi_data['aqi'],
+            "PM2.5": f"{aqi_data['pm25']} µg/m³",
+            "PM10": f"{aqi_data['pm10']} µg/m³",
+            "Carbon Monoxide (CO)": f"{aqi_data['co']} ppb",
+            "Temperature": f"{aqi_data['temperature']}°C",
+            "Humidity": f"{aqi_data['humidity']}%",
+            "Wind Speed": f"{aqi_data['wind_speed']} km/h"
+        }, indent=2)
+        
+        # Get recommendations
+        recommendations = health_agent.get_recommendations(aqi_data, user_input)
+        
+        warning_msg = """
+        ⚠️ 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_json, recommendations, info_msg, warning_msg
+        
+    except Exception as e:
+        error_msg = f"Error occurred: {str(e)}"
+        return "", "Analysis failed", error_msg, ""
+
+def create_demo() -> gr.Blocks:
+    """Create and configure the Gradio interface"""
+    with gr.Blocks(title="AQI Analysis Agent") as demo:
+        gr.Markdown(
+            """
+            # 🌍 AQI Analysis Agent
+            Get personalized health recommendations based on air quality conditions.
+            """
+        )
+        
+        # API Configuration
+        with gr.Accordion("API Configuration", open=False):
+            firecrawl_key = gr.Textbox(
+                label="Firecrawl API Key",
+                type="password",
+                placeholder="Enter your Firecrawl API key"
+            )
+            openai_key = gr.Textbox(
+                label="OpenAI API Key",
+                type="password",
+                placeholder="Enter your OpenAI API key"
+            )
+        
+        # Location Details
+        with gr.Row():
+            with gr.Column():
+                city = gr.Textbox(label="City", placeholder="e.g., Mumbai")
+                state = gr.Textbox(
+                    label="State",
+                    placeholder="Leave blank for Union Territories or US cities",
+                    value=""
+                )
+                country = gr.Textbox(label="Country", value="India")
+        
+        # Personal Details
+        with gr.Row():
+            with gr.Column():
+                medical_conditions = gr.Textbox(
+                    label="Medical Conditions (optional)",
+                    placeholder="e.g., asthma, allergies",
+                    lines=2
+                )
+                planned_activity = gr.Textbox(
+                    label="Planned Activity",
+                    placeholder="e.g., morning jog for 2 hours",
+                    lines=2
+                )
+        
+        # Status Messages
+        info_box = gr.Textbox(label="ℹ️ Status", interactive=False)
+        warning_box = gr.Textbox(label="⚠️ Warning", interactive=False)
+        
+        # Output Areas
+        aqi_data_json = gr.JSON(label="📊 Current Air Quality Data")
+        recommendations = gr.Markdown(label="🏥 Health Recommendations")
+        
+        # Analyze Button
+        analyze_btn = gr.Button("🔍 Analyze & Get Recommendations", variant="primary")
+        analyze_btn.click(
+            fn=analyze_conditions,
+            inputs=[
+                city,
+                state,
+                country,
+                medical_conditions,
+                planned_activity,
+                firecrawl_key,
+                openai_key
+            ],
+            outputs=[aqi_data_json, recommendations, info_box, warning_box]
+        )
+        
+        # Examples
+        gr.Examples(
+            examples=[
+                ["Mumbai", "Maharashtra", "India", "asthma", "morning walk for 30 minutes"],
+                ["Delhi", "", "India", "", "outdoor yoga session"],
+                ["New York", "", "United States", "allergies", "afternoon run"],
+                ["Kakinada", "Andhra Pradesh", "India", "none", "Tennis for 2 hours"]
+            ],
+            inputs=[city, state, country, medical_conditions, planned_activity]
+        )
+    
+    return demo
+
+if __name__ == "__main__":
+    demo = create_demo()
+    demo.launch(share=True)
diff --git a/ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_streamlit.py b/ai_agent_tutorials/ai_aqi_analysis_agent/ai_aqi_analysis_agent_streamlit.py
new file mode 100644
index 0000000..b8acaeb
--- /dev/null
+++ b/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()
\ No newline at end of file
diff --git a/ai_agent_tutorials/ai_aqi_analysis_agent/requirements.txt b/ai_agent_tutorials/ai_aqi_analysis_agent/requirements.txt
new file mode 100644
index 0000000..034b309
--- /dev/null
+++ b/ai_agent_tutorials/ai_aqi_analysis_agent/requirements.txt
@@ -0,0 +1,6 @@
+agno
+openai
+firecrawl-py==1.9.0
+gradio==5.9.1
+pydantic
+dataclasses