Update app.py

app.py

@@ -1,6 +1,17 @@
 import gradio as gr
+from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-python_code = """
+# Hugging Face Inference API Client
+client = InferenceClient("bigscience/bloom")
+
+# Hugging Face Transformers Pipeline for Question Answering
+qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad")
+
+# Code Snippets
+code_snippets = {
+    "fibonacci": {
+        "python": """
 def fib(n):
     if n <= 0:
         return 0
@@ -8,37 +19,57 @@ def fib(n):
         return 1
     else:
         return fib(n-1) + fib(n-2)
-"""
-
-js_code = """
+""",
+        "javascript": """
 function fib(n) {
     if (n <= 0) return 0;
     if (n === 1) return 1;
     return fib(n - 1) + fib(n - 2);
 }
 """
+    }
+}
 
-def chat(message, history):
-    if "python" in message.lower():
-        return "Type Python or JavaScript to see the code.", gr.Code(language="python", value=python_code)
-    elif "javascript" in message.lower():
-        return "Type Python or JavaScript to see the code.", gr.Code(language="javascript", value=js_code)
+# Chatbot Function
+def chatbot(message, history):
+    if "python" in message.lower() and "fibonacci" in message.lower():
+        return "Here is the Fibonacci code in Python:", gr.Code(language="python", value=code_snippets["fibonacci"]["python"])
+    elif "javascript" in message.lower() and "fibonacci" in message.lower():
+        return "Here is the Fibonacci code in JavaScript:", gr.Code(language="javascript", value=code_snippets["fibonacci"]["javascript"])
+    elif "huggingface" in message.lower():
+        # Generate text using the Hugging Face Inference API
+        prompt = "Write a short poem about cybersecurity."
+        response = client.text_generation(prompt, max_length=50)
+        return f"Hugging Face Generated Text: {response['generated_text']}", None
+    elif "question" in message.lower():
+        # Use the QA pipeline to answer a question
+        question = "What is the purpose of cybersecurity?"
+        context = "Cybersecurity involves protecting systems, networks, and programs from digital attacks."
+        result = qa_pipeline(question=question, context=context)
+        return f"Hugging Face QA Answer: {result['answer']}", None
     else:
-        return "Please ask about Python or JavaScript.", None
+        return "Please ask about Python/JavaScript code or Hugging Face functionalities.", None
 
+# Gradio Interface
 with gr.Blocks() as demo:
-    code = gr.Code(render=False)
+    code_output = gr.Code(render=False)
     with gr.Row():
         with gr.Column():
-            gr.Markdown("<center><h1>Write Python or JavaScript</h1></center>")
+            gr.Markdown("<center><h1>Chat About Code or Hugging Face</h1></center>")
             gr.ChatInterface(
-                chat,
-                examples=["Python", "JavaScript"],
-                additional_outputs=[code],
+                chatbot,
+                examples=[
+                    "Python Fibonacci",
+                    "JavaScript Fibonacci",
+                    "HuggingFace: Generate text",
+                    "Ask a question about cybersecurity",
+                ],
+                additional_outputs=[code_output],
                 type="messages"
             )
         with gr.Column():
-            gr.Markdown("<center><h1>Code Artifacts</h1></center>")
-            code.render()
+            gr.Markdown("<center><h1>Code or Model Output</h1></center>")
+            code_output.render()
 
-demo.launch()
+# Launch the Gradio App
+demo.launch()