Update app.py

app.py

@@ -1,11 +1,24 @@
-from transformers import AutoTokenizer, AutoModelForTokenClassification
+import gradio as gr
 from transformers import pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("dslim/bert-base-NER")
-model = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER")
+# Load conversational pipeline
+chat_pipe = pipeline("conversational", model="alpindale/goliath-120b")
 
-nlp = pipeline("ner", model=model, tokenizer=tokenizer)
-example = "My name is Wolfgang and I live in Berlin"
+# Define a function to generate responses
+def generate_response(user_input):
+    # Generate response from the chat pipeline
+    response = chat_pipe(user_input)[0]['generated_responses'][0]
+    return response
 
-ner_results = nlp(example)
-print(ner_results)
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(),
+    outputs=gr.Textbox(),
+    live=True,
+    title="Conversational Chat",
+    description="Chat with the AI model using Gradio!"
+)
+
+# Launch the Gradio interface
+iface.launch()