Create app.py

app.py

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+import gradio as gr
+
+class TafGPT:
+    def generate_response(self, user_input):
+        technology_topics = {
+            "machine learning": "Machine learning is a fascinating field that involves training computers to learn from data and make predictions.",
+            "python programming language": "Python is a versatile programming language known for its simplicity and readability. It's widely used in various domains, including web development and data science.",
+            "web development": "Web development includes designing and building websites. Front-end development focuses on user interfaces, while back-end development handles server-side logic.",
+            "artificial intelligence": "Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence.",
+            "data science": "Data science involves extracting insights and knowledge from structured and unstructured data. It combines expertise in statistics, mathematics, and programming.",
+            "cybersecurity": "Cybersecurity aims to protect computer systems, networks, and data from cyber threats and attacks. It includes measures to ensure the confidentiality, integrity, and availability of information.",
+            "cloud computing": "Cloud computing provides on-demand access to computing resources, such as storage, processing power, and databases, over the internet.",
+        }
+
+        if user_input.lower() in technology_topics:
+            response = f"Taf-gpt: {technology_topics[user_input.lower()]}"
+        else:
+            response = "Taf-gpt: I'm sorry, I'm specialized in technology topics. Feel free to ask me about machine learning, Python programming language, web development, artificial intelligence, data science, cybersecurity, or cloud computing!"
+
+        return f"User: {user_input}\n{Taf-gpt: {response}"
+
+# Create an instance of TafGPT
+taf_gpt = TafGPT()
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=taf_gpt.generate_response,
+    inputs=gr.Textbox(),
+    outputs=gr.Textbox(),
+    live=True,
+    title="Taf-gpt Technology Chatbot",
+    description="Explore technology topics with Taf-gpt! Choose a predefined topic or ask your own questions.",
+    examples=[
+        ["Tell me about machine learning"],
+        ["What is Python programming language?"],
+        ["Web development best practices"],
+        ["What is artificial intelligence?"]
+    ],
+)
+
+# Launch the Gradio interface
+iface.launch()