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decodingdatascience
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Upload 2 files
Browse files- app.py +99 -0
- requirements.txt +6 -0
app.py
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import os
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import requests
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import gradio as gr
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import openai
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Initialize OpenAI client
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openai.api_key = os.getenv("OPENAI_API_KEY1")
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# Define function to get current weather
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def get_current_weather(location, unit='celsius'):
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weather_api_key = os.getenv("WEATHER_API_KEY")
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base_url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={weather_api_key}&units=metric"
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try:
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response = requests.get(base_url, timeout=10) # Increased timeout for the request
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response.raise_for_status() # Check if the request was successful
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data = response.json()
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weather_description = data['weather'][0]['description']
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return {
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"location": location,
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"temperature": data['main']['temp'],
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"weather": weather_description
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}
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except requests.exceptions.Timeout:
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return {"error": "Request timed out. Please try again later."}
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except requests.exceptions.RequestException as e:
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print(f"Request failed: {e}")
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return {"error": str(e)}
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# Function definition and initial message handling
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def weather_chat(user_message):
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messages = []
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messages.append({"role": "user", "content": user_message})
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messages.append({"role": "assistant", "content": "You are a weather bot. Answer only in Celsius. If two cities are asked, provide weather for both."})
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# Sending initial message to OpenAI
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try:
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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temperature=0,
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max_tokens=256,
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0,
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messages=messages,
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functions=[
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{
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {"type": "string", "description": "The city, e.g. San Francisco"},
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"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
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},
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"required": ["location"]
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}
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}
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]
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)
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except Exception as e:
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print(f"OpenAI API call failed: {e}")
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return "Failed to communicate with the OpenAI API. Please try again later."
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# Handling function calls and fetching weather data
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try:
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function_call = response['choices'][0]['message']['function_call']
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arguments = eval(function_call['arguments'])
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weather_data = get_current_weather(arguments['location'])
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if 'error' in weather_data:
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return weather_data['error']
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messages.append({"role": "assistant", "content": None, "function_call": {"name": "get_current_weather", "arguments": str(arguments)}})
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messages.append({"role": "function", "name": "get_current_weather", "content": str(weather_data)})
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# Continue conversation with weather data
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=messages
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)
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return response['choices'][0]['message']['content']
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except Exception as e:
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print(f"Error during processing: {e}")
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return "I'm here to provide weather updates. Please ask me questions related to weather."
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# Define Gradio interface
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iface = gr.Interface(
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fn=weather_chat,
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inputs=gr.Textbox(label="Weather Queries"),
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outputs=gr.Textbox(label="Weather Updates"),
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title="DDS Weather Bot",
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description="Ask me anything about weather!"
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)
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# Launch the Gradio interface
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iface.launch(share=True)
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requirements.txt
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@@ -0,0 +1,6 @@
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requests==2.28.1
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gradio
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openai==0.28
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python-dotenv==1.0.0
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httpx==0.21.1
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httpcore==0.14.7
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