add code

app.py

@@ -1,8 +1,51 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+text_generation_model = "cahya/indochat-tiny"
+text_generation = pipeline("text-generation", text_generation_model)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
 
+def get_answer(user_input, decoding_methods, top_k, top_p, temperature, repetition_penalty, penalty_alpha):
+    if decoding_methods == "Beam Search":
+        do_sample = False
+    elif decoding_methods == "Sampling":
+        do_sample = True
+    else:
+        do_sample = False
+    print(user_input, decoding_methods, do_sample, top_k, top_p, temperature, repetition_penalty, penalty_alpha)
+    prompt = f"User: {user_input}\nAssistant: "
+    generated_text = text_generation(f"{prompt}", min_length=50, max_length=200, num_return_sequences=1,
+                                     do_sample=do_sample, top_k=top_k, top_p=top_p, temperature=temperature,
+                                     repetition_penalty=repetition_penalty)#, penalty_alpha=penalty_alpha)
+    answer = generated_text[0]["generated_text"]
+    answer_without_prompt = answer[len(prompt)+1:]
+    return answer_without_prompt
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        gr.Markdown(
+            "## IndoChat")
+    with gr.Row():
+        with gr.Column():
+            user_input = gr.inputs.Textbox(placeholder="",
+                                           label="Ask me something in Indonesian or English",
+                                           default="Bagaimana cara mendidik anak supaya tidak berbohong?")
+            decoding_methods = gr.Dropdown(["Beam Search", "Sampling", "Contrastive Search"])
+            top_k = gr.inputs.Slider(label="Top K: The number of highest probability vocabulary tokens to keep",
+                                     default=40, maximum=50, minimum=1, step=1)
+            top_p = gr.inputs.Slider(label="Top P", default=0.9, step=0.05, minimum=0.1, maximum=1.0)
+            temperature = gr.inputs.Slider(label="Temperature", default=0.5, step=0.05, minimum=0.1, maximum=1.0)
+            repetition_penalty = gr.inputs.Slider(label="Repetition Penalty", default=1.1, step=0.05, minimum=1.0, maximum=2.0)
+            penalty_alpha = gr.inputs.Slider(label="The penalty alpha for contrastive search", default=1.1, step=0.05, minimum=1.0, maximum=2.0)
+            with gr.Row():
+                button_generate_story = gr.Button("Submit")
+        with gr.Column():
+            generated_answer = gr.Textbox()
+    with gr.Row():
+        gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=cahya_indochat)")
+
+    button_generate_story.click(get_answer, inputs=[user_input, decoding_methods, top_k, top_p, temperature,
+                                                    repetition_penalty, penalty_alpha], outputs=[generated_answer])
+
+demo.launch(enable_queue=False)