Create app.py

app.py

@@ -0,0 +1,73 @@
+import gradio as gr
+import requests
+import importlib
+from bs4 import BeautifulSoup
+from huggingface_hub import InferenceClient
+
+# Import weather script
+weather = importlib.import_module("weather")
+
+# Hugging Face model
+client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
+
+def google_search(query):
+    """Scrape Google search for an answer."""
+    url = f"https://www.google.com/search?q={query}"
+    headers = {"User-Agent": "Mozilla/5.0"}
+    
+    try:
+        response = requests.get(url, headers=headers)
+        soup = BeautifulSoup(response.text, "html.parser")
+        result = soup.find("div", class_="BNeawe iBp4i AP7Wnd")
+        
+        if result:
+            return result.text
+        return "Samahani, siwezi kupata majibu."
+    except Exception:
+        return "Samahani, siwezi kuwasiliana na Google kwa sasa."
+
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    """Chatbot that answers user and fetches real-time info if needed."""
+    
+    # Handle weather requests
+    if "weather" in message.lower() or "hali ya hewa" in message.lower():
+        city = message.split()[-1]  # Last word as city name
+        return weather.get_weather(city)
+
+    # Handle time requests
+    if "time" in message.lower() or "saa ngapi" in message.lower():
+        from datetime import datetime
+        return f"Saa ya sasa ni {datetime.now().strftime('%H:%M:%S')}."
+
+    # Model response
+    messages = [{"role": "system", "content": system_message}]
+    for val in history:
+        if val[0]: messages.append({"role": "user", "content": val[0]})
+        if val[1]: messages.append({"role": "assistant", "content": val[1]})
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+    for message in client.chat_completion(messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p):
+        token = message.choices[0].delta.content
+        response += token
+
+    # If model doesn't know, fetch from Google
+    if "I don't know" in response or response.strip() == "":
+        response = google_search(message)
+    
+    return response
+
+# Gradio UI
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
+    ],
+)
+
+if __name__ == "__main__":
+    demo.launch()
+