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Create app.py
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app.py
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import gradio as gr
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import requests
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import importlib
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import pytz
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from datetime import datetime
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from bs4 import BeautifulSoup
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from huggingface_hub import InferenceClient
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# Import weather script
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weather = importlib.import_module("weather")
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# Hugging Face model
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client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
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def google_search(query):
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"""Scrape Google search for an answer."""
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url = f"https://www.google.com/search?q={query}"
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headers = {"User-Agent": "Mozilla/5.0"}
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try:
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response = requests.get(url, headers=headers)
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soup = BeautifulSoup(response.text, "html.parser")
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result = soup.find("div", class_="BNeawe iBp4i AP7Wnd")
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if result:
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return result.text
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return "Sorry, I couldn't find an answer."
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except Exception:
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return "I'm unable to fetch data from Google right now."
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def get_time_in_city(city):
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"""Fetch current time for any city using pytz"""
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try:
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timezone = pytz.timezone(pytz.country_timezones['US'][0]) if city.lower() == "new york" else pytz.utc
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now = datetime.now(timezone)
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return f"The current time in {city} is {now.strftime('%H:%M:%S')}."
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except Exception:
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return "I couldn't fetch the time for that city."
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def get_current_date():
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"""Return today's date"""
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return f"Today's date is {datetime.today().strftime('%d %B %Y')}."
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def respond(message, history, system_message, max_tokens, temperature, top_p):
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"""Chatbot that answers user and fetches real-time info if needed."""
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message_lower = message.lower()
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# Time-related questions
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if "what time" in message_lower or "saa ngapi" in message_lower:
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city = message.split()[-1] # Assume last word is city name
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return get_time_in_city(city)
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# Date-related questions
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if "what date" in message_lower or "leo ni tarehe ngapi" in message_lower:
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return get_current_date()
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# Weather-related questions
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if "weather" in message_lower or "hali ya hewa" in message_lower:
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city = message.split()[-1]
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return weather.get_weather(city)
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# General knowledge questions → Try Google if model fails
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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if val[0]: messages.append({"role": "user", "content": val[0]})
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if val[1]: messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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for message in client.chat_completion(messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p):
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token = message.choices[0].delta.content
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response += token
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# If model doesn't know, use Google
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if "I don't know" in response or response.strip() == "":
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response = google_search(message)
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return response
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# Gradio UI
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
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],
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)
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if __name__ == "__main__":
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demo.launch()
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