Update app.py

app.py

@@ -1,25 +1,17 @@
+
 import gradio as gr
 from gradio_client import Client
 
-
-
-system_message = "\nYou are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."
-temperature = 0.9
-top_p = 0.6
-repetition_penalty = 1.2
-
 title = "Llama2 70B Chatbot"
+
 description = """
 This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta, a Llama 2 model with 70B parameters fine-tuned for chat instructions. 
-It relies on 2 models:
-1. [Whisper-large-v2](https://huggingface.co/spaces/sanchit-gandhi/whisper-large-v2) as an ASR model, to transcribe recorded audio to text. It is called through a [gradio client](https://www.gradio.app/docs/client).
-2. [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) as the chat model, the actual chat model. It is also called through a [gradio client](https://www.gradio.app/docs/client).
 | Model | Llama2 | Llama2-hf | Llama2-chat | Llama2-chat-hf |
 |---|---|---|---|---|
 | 70B | [Link](https://huggingface.co/meta-llama/Llama-2-70b) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-hf) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) |
-
 """
 css = """.toast-wrap { display: none !important } """
+
 examples=[
     ['Hello there! How are you doing?'],
     ['Can you explain to me briefly what is Python programming language?'],
@@ -28,96 +20,39 @@ examples=[
     ["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
     ]
 
-whisper_client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
-text_client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
+
 
 
 def transcribe(wav_path):
+    whisper_client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
     
     return whisper_client.predict(
 				wav_path,	# str (filepath or URL to file) in 'inputs' Audio component
 				"transcribe",	# str in 'Task' Radio component
 				api_name="/predict"
-)
-    
-
-# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
-
-
-def add_text(history, text):
-    history = [] if history is None else history
-    history = history + [(text, None)]
-    return history, gr.update(value="", interactive=False)
-
-
-def add_file(history, file):
-    history = [] if history is None else history
-    text = transcribe(
-        file
     )
-    
-    history = history + [(text, None)]
-    return history
-
 
 
-def bot(history, system_prompt=""):    
-    history = [] if history is None else history
-
-    if system_prompt == "":
-        system_prompt = system_message
-        
-    history[-1][1] = ""
-    for character in text_client.submit(
-                    history,
-                    system_prompt,
-                    temperature,
-                    4096,
-                    temperature,
-                    repetition_penalty,
-                    api_name="/chat_1"
-    ):
-        history[-1][1] = character
-        yield history  
-
+# Stream text
+def predict(message, chatbot, system_prompt="", temperature=0.9, max_new_tokens=4096):
+    
+    client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
+    return client.predict(transcribe(message),	# str in 'Message' Textbox component
+            system_prompt,	# str in 'Optional system prompt' Textbox component
+			temperature,	# int | float (numeric value between 0.0 and 1.0)
+			max_new_tokens,	# int | float (numeric value between 0 and 4096)
+			0.3,	# int | float (numeric value between 0.0 and 1)
+			1,	# int | float (numeric value between 1.0 and 2.0)
+			api_name="/chat_1")
     
 
 
-with gr.Blocks(title=title,theme=gr.themes.Base(),description = description) as demo:
-    
-    
-    chatbot = gr.Chatbot(
-        [],
-        elem_id="chatbot",
-        bubble_full_width=False,
-    )
 
-    with gr.Row():
-        txt = gr.Textbox(
-            scale=3,
-            show_label=False,
-            placeholder="Enter text and press enter, or speak to your microphone",
-            container=False,
-        )
-        txt_btn = gr.Button(value="Submit text",scale=1)
-        btn = gr.Audio(source="microphone", type="filepath", scale=4)
-    
-    # with gr.Row():
-    #     Ex = gr.Examples(examples, [txt_btn], [chatbot],fn =add_text )
-        
-    clear_btn = gr.ClearButton([chatbot])
-    
-    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt]).then(
-        bot, chatbot, chatbot
-    )
-    
-    txt_msg.then(lambda: gr.update(interactive=True), None, [txt])
-    
-    file_msg = btn.stop_recording(add_file, [chatbot, btn], [chatbot]).then(
-        bot, chatbot, chatbot
-    )
-    
 
+# Gradio Demo 
+with gr.Blocks(theme=gr.themes.Base()) as demo:
+    gr.DuplicateButton()
+    gr.ChatInterface(predict, title=title, inputs="audio", description=description, css=css, examples=examples) 
     
-demo.queue()
-demo.launch(debug=True)
+        
+demo.queue().launch(debug=True)