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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+weather_bot.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,259 @@
+# -*- coding: utf-8 -*-
+import gradio as gr
+import os
+import requests
+import openai
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Initialize OpenAI client your openai key
+openai.api_key = os.getenv('OPENAI_API_KEY')
+
+
+def get_current_weather(location, unit='celsius'):
+    weather_api_key = userdata.get('WEATHER_API_KEY')
+    base_url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={weather_api_key}&units=metric"
+    response = requests.get(base_url)
+    data = response.json()
+
+    weather_description = data['weather'][0]['description']
+    return {
+        "location": location,
+        "temperature": data['main']['temp'],
+        "weather": weather_description
+    }
+
+#print(get_current_weather("fremont"))
+
+# format is referred from opeai Function Chat->Tools->Add->Function->get_weather()
+functions = [
+    {
+        "name": "get_current_weather",
+        "description": "Get the current weather in a given location",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "The city, e.g. San Francisco"
+                },
+                "unit": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"]
+                }
+            },
+            "required": ["location"]
+        }
+    }
+]
+
+functions
+
+#Function Definition and Initial Message Handling
+def weather_chat(user_message):
+    messages=[]
+    messages.append({"role": "user", "content": user_message})
+    messages.append({"role": "assistant", "content": "You are a weather bot . Answer only in Celsius and answer only related to weather related questions. If user asks other than weather then politely decline it"})
+
+        # Sending Initial Message to OpenAI
+    response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            temperature = 0,
+            max_tokens=256,
+            top_p=0.2,
+            frequency_penalty=0,
+            presence_penalty=0,
+            messages=messages,
+            functions=functions
+        )
+    #print(f'response1 is : {response}')
+
+    #Handling Function Calls and Fetching Weather Data
+    try:
+        function_call = response['choices'][0]['message']['function_call']
+        #print(f'function_call : {function_call}')
+        # Extract function name and arguments
+        arguments = eval(function_call['arguments']) # we are passing locatioon in arguments. this line of code is taking the string representation of the arguments returned by the OpenAI API and converting it into a usable Python dictionary, which you then use to call your get_current_weather function.
+        #print(f'arguments : {arguments}')
+        # Fetch weather data using the extracted arguments
+        weather_data = get_current_weather(arguments['location'])
+
+        # Append the function call and weather data to the messages
+        messages.append({"role": "assistant", "content": None, "function_call": {"name": "get_current_weather", "arguments": str(arguments)}})
+        messages.append({"role": "function", "name": "get_current_weather", "content": str(weather_data)})
+
+        #print(f'message : {messages}')
+#magic of llm
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=messages
+        )
+        #print(f'response2 : {response}')
+        return response['choices'][0]['message']['content']
+    except Exception as e:
+        return "I'm here to provide weather updates. Please ask me questions related to weather."
+
+#import gradio as gr
+# Define Gradio interface
+# iface = gr.Interface(
+    # fn=weather_chat,
+    # inputs=gr.Textbox(label="Weather Queries"),
+    # outputs=gr.Textbox(label="Weather Updates", lines=5),
+    # title = "Weather Bot",
+    # description = "Ask me anything about weather!"
+# )
+
+# Launch the Gradio interface
+#iface.launch(share="True")
+
+# To create a customized Gradio Interference, following is the prompt.
+# import gradio as gr
+# # Define Gradio interface
+# iface = gr.Interface(
+#     fn=weather_chat,
+#     inputs=gr.Textbox(label="Weather Queries"),
+#     outputs=gr.Textbox(label="Weather Updates", lines=5),
+#     title = "Weather Bot",
+#     description = "Ask me anything about weather!"
+# )
+
+# # Launch the Gradio interface
+# iface.launch(share="True")
+
+# make the above gradio app more professional, use blocks and add 2 columns format, give option for famous cities in a drop down or give a option of manually submitting the city, also add the logo
+# https://github.com/Decoding-Data-Science/airesidency/blob/main/dds_logo.jpg
+
+# List of famous cities for the dropdown
+FAMOUS_CITIES = [
+    "New York", "London", "Tokyo", "Paris", "Dubai",
+    "Singapore", "Hong Kong", "Sydney", "Mumbai", "Toronto",
+    "Los Angeles", "Chicago", "San Francisco", "Berlin", "Madrid",
+    "Rome", "Barcelona", "Amsterdam", "Bangkok", "Seoul",
+    "Shanghai", "Beijing", "Istanbul", "Moscow", "Mexico City"
+]
+
+def process_weather_query(city_dropdown, custom_city, query):
+    """
+    Process weather query based on city selection and custom input
+    """
+    # Determine which city to use
+    city = custom_city.strip() if custom_city.strip() else city_dropdown
+
+    # Combine city with query if query exists
+    if query.strip():
+        full_query = f"{query} in {city}"
+    else:
+        full_query = f"What's the weather in {city}?"
+
+    # Call your weather_chat function
+    response = weather_chat(full_query)
+    return response
+
+# Create the Gradio Blocks interface
+with gr.Blocks(theme=gr.themes.Soft(), title="Weather Bot") as iface:
+
+    # Header with logo
+    with gr.Row():
+        gr.Image(
+            "https://github.com/Decoding-Data-Science/airesidency/blob/main/dds_logo.jpg?raw=true",
+            label=None,
+            show_label=False,
+            height=100,
+            width=200,
+            show_download_button=False,
+            container=False
+        )
+
+    # Title and description
+    gr.Markdown(
+        """
+        # 🌤️ Weather Bot
+        ### Get real-time weather information for any city around the world
+        """
+    )
+
+    # Main content with two columns
+    with gr.Row():
+        # Left Column - Input Section
+        with gr.Column(scale=1):
+            gr.Markdown("### 📍 Select or Enter City")
+
+            city_dropdown = gr.Dropdown(
+                choices=FAMOUS_CITIES,
+                value="New York",
+                label="Choose from Popular Cities",
+                info="Select a city from the dropdown"
+            )
+
+            gr.Markdown("**OR**")
+
+            custom_city = gr.Textbox(
+                label="Enter Custom City",
+                placeholder="Type any city name...",
+                info="Leave empty to use the dropdown selection"
+            )
+
+            query_input = gr.Textbox(
+                label="Additional Query (Optional)",
+                placeholder="e.g., temperature, forecast, humidity...",
+                lines=2,
+                info="Ask specific weather questions"
+            )
+
+            with gr.Row():
+                submit_btn = gr.Button("Get Weather 🌍", variant="primary", size="lg")
+                clear_btn = gr.Button("Clear 🔄", variant="secondary")
+
+        # Right Column - Output Section
+        with gr.Column(scale=1):
+            gr.Markdown("### 🌡️ Weather Information")
+
+            output = gr.Textbox(
+                label="Weather Updates",
+                lines=12,
+                placeholder="Weather information will appear here...",
+                show_copy_button=True
+            )
+
+    # Example queries
+    gr.Markdown("### 💡 Example Queries")
+    gr.Examples(
+        examples=[
+            ["London", "", "What's the current temperature?"],
+            ["", "Seattle", "Will it rain today?"],
+            ["Tokyo", "", "7-day forecast"],
+            ["", "Mumbai", "humidity levels"],
+            ["Paris", "", ""]
+        ],
+        inputs=[city_dropdown, custom_city, query_input],
+        label="Try these examples"
+    )
+
+    # Event handlers
+    submit_btn.click(
+        fn=process_weather_query,
+        inputs=[city_dropdown, custom_city, query_input],
+        outputs=output
+    )
+
+    clear_btn.click(
+        fn=lambda: ("New York", "", "", ""),
+        inputs=None,
+        outputs=[city_dropdown, custom_city, query_input, output]
+    )
+
+    # Footer
+    gr.Markdown(
+        """
+        ---
+        <p style='text-align: center; color: #666;'>
+        Powered by AI | Built with Gradio
+        </p>
+        """
+    )
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch(share=True)

requirements.txt

@@ -0,0 +1,3 @@
+gradio==3.38.0
+openai==0.28
+python-dotenv