Update app.py

app.py

@@ -11,6 +11,7 @@ description = """You can build with this endpoint using Nexus Raven. The demo is
         You can also use Nexus🐦‍⬛Raven on your laptop & by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/NexusRaven2?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
         Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
 """
+
 raven_pipeline = pipeline(
     "text-generation",
     model="Nexusflow/NexusRaven-V2-13B",
@@ -19,18 +20,13 @@ raven_pipeline = pipeline(
 )
 
 @spaces.GPU
-class DialogueToSpeechConverter:
-    def __init__(self):
-        self.raven_pipeline = raven_pipeline
-
-    def process_text(self, input_text: str) -> str:
-        prompt = f"User Query: {input_text}<human_end>"
-        result = self.raven_pipeline(prompt, max_new_tokens=2048, return_full_text=False, do_sample=False, temperature=0.001)[0]["generated_text"]
-        torch.cuda.empty_cache()
-        return result
+def process_text(input_text: str) -> str:
+    prompt = f"User Query: {input_text}<human_end>"
+    result = raven_pipeline(prompt, max_new_tokens=2048, return_full_text=False, do_sample=False, temperature=0.001)[0]["generated_text"]
+    torch.cuda.empty_cache()
+    return result
 
 def create_interface():
-    converter = DialogueToSpeechConverter()
     with gr.Blocks() as app:
         gr.Markdown(title)
         gr.Markdown(description)
@@ -42,9 +38,8 @@ def create_interface():
     return app
 
 if __name__ == "__main__":
-    converter = DialogueToSpeechConverter()
     demo = gr.Interface(
-        fn=converter.process_text,
+        fn=process_text,
         inputs="text",
         outputs="text",
         examples=[