Create App.py

App.py

@@ -0,0 +1,69 @@
+from transformers import TextIteratorStreamer
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from threading import Thread
+import gradio as gr
+
+class ChatbotService:
+    def __init__(self, model_name="RajuKandasamy/tamillama_tiny_30m"):
+        self.model = AutoModelForCausalLM.from_pretrained(model_name)
+        self.tokenizer = AutoTokenizer.from_pretrained(model_name)
+        self.streamer = None
+
+    def call(self, prompt):
+        self.streamer = TextIteratorStreamer(self.tokenizer, skip_prompt=True, timeout=5)
+        prompt = prompt.replace("<br>", "\n")
+        print(prompt)
+        inputs = self.tokenizer(prompt, return_tensors="pt")
+        print(inputs)
+        kwargs = dict(input_ids=inputs["input_ids"], streamer=self.streamer, max_new_tokens=512, do_sample=True, top_p=0.8, top_k=500, temperature=0.001, repetition_penalty=1.4)
+        thread = Thread(target=self.model.generate, kwargs=kwargs)
+        thread.start()
+        return ""
+
+import gradio as gr
+
+example_questions = [
+    f"""கதை:
+ஒரு காலத்தில் ஒரு பெரிய கோட்டையில் வாழ்ந்த அன்பான மனிதர் ஒருவர் இருந்தார்.""",
+    f"""சுருக்கம்:
+இளவரசனும் அரக்கனும்""",
+    f"""Words: prevent, car, broken
+Features: Dialogue""",
+    f"""சொற்கள்:
+தீர்வு"""
+]
+
+
+chatbot_service = ChatbotService()
+
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot().style(height=400)
+    with gr.Row():
+        msg = gr.Textbox(placeholder="Type your message here...", inputs="text",outputs="text", label="Story Prompt:")
+        run = gr.Button("Run")
+    examples_dropdown = gr.Dropdown(choices=example_questions, label="Select an example prompt")
+    examples_dropdown.change(fn=lambda x: x, inputs=examples_dropdown, outputs=msg)
+
+    clear = gr.Button("Clear")
+
+    def user(question, user_message, history):
+        if history == None:
+            history = []
+        user_message = question
+        return "", history + [[user_message, None]]
+
+    def bot(history):
+        #print("Question: ", history[-1][0])
+        chatbot_service.call(history[-1][0])
+        history[-1][1] = ""
+        for character in chatbot_service.streamer:
+            print(character)
+            history[-1][1] += character
+            yield history
+
+    run.click(user, [msg, chatbot], [msg, chatbot], queue=False).then(bot, chatbot, chatbot)
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+demo.queue()
+demo.launch()